Current and Historic Levels of Persistent (PAHs, PCBs) and Emerging Pollutant (Nano- microplastics or NMPs) Body-Burdens in Oysters and Fish from an Urban-Industrialized Subtropical Estuary (Galveston Bay, TX, USA)

Current and Historic Levels of Persistent (PAHs, PCBs) and Emerging Pollutant (Nano- microplastics or NMPs) Body-Burdens in Oysters and Fish from an Urban-Industrialized Subtropical Estuary (Galveston Bay, TX, USA) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Current and Historic Levels of Persistent (PAHs, PCBs) and Emerging Pollutant (Nano- microplastics or NMPs) Body-Burdens in Oysters and Fish from an Urban-Industrialized Subtropical Estuary (Galveston Bay, TX, USA) Asif Mortuza, Bryan Gahn, Marcus Wharton, R. J. David Wells, Lene H. Petersen, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9509872/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Galveston Bay is a highly urban‑industrialized system that drains the Houston metropolitan area and serves as a major hub for maritime transport and energy production. In this study, we compared the current and historic levels of persistent (PAHs, PCBs) and emerging pollutants (Nano-microplastics or NMPs) in biota (oysters, fish) sampled from Galveston Bay. Specifically, the concentrations of 14 EPA priority PAHs, 28 PCBs (including 11 dioxin-like PCBs), and 12 commonly used NMPs (700 nm − 5 mm) were measured in gill/mantle tissue of eastern oysters ( Crassostrea virginica ), and in the muscle and livers of Gafftopsail catfish ( Bagre marinus ), red drum ( Sciaenops ocellatus ), and spotted seatrout ( Cynoscion nebulosus ). GCMS was used for PAHs and PCBs quantification, and Py-GCMS/MS with lipid correction was used to quantify the NMPs. Overall, NMPs exhibited the highest body-burdens across all biota, ranging from two to four-orders of magnitude higher than PAHs and PCBs. Oysters also accumulated the highest concentrations of all pollutants relative to fish muscle (PAHs ≤ 2.4x, PCBs ≤ 19.2x, NMPs ≤ 278x higher). Source ratio analysis indicated mixed petrogenic and pyrogenic PAHs origins in Galveston Bay. Estimated human intake of NMPs was ≤ 443.90 mg NMP/kg body weight/year from the consumption of fish, and ≤ 309.98 mg NMP/kg body weight/year from oysters. A comparison of past and present body‑burden data showed that current PAH and PCB levels remain within previously reported ranges, while the relatively recent adoption of Py‑GCMS/MS enables the first quantified measurements of NMPs in Galveston Bay fish and demonstrates the method’s effectiveness for environmental monitoring. subtropical estuary shellfish fish microplastics body-burdens persistent pollutants Figures Figure 1 Figure 2 Figure 3 1. Introduction Coastal zones are among the most densely inhabited regions on Earth, with almost half of the global population residing within 100 km of coastlines (Cosby et al., 2024). As a consequence, approximately 49% of marine ecosystems are already impacted by anthropogenic stressors (Gaw et al., 2014). These pressures highlight the need for robust pollutant monitoring and marine risk assessment frameworks to safeguard and manage estuarine and coastal environments, which serve as invaluable ecological and economic resources. Galveston Bay represents a relevant model system, as it is the largest estuary in Texas and the 7th largest in the continental United States (Fig. 1 ) (GBEP, 2025). The urban-industrialized estuary has an area of 1544 km 2 , an average depth of 2.1 m, and water residence time of ~ 40 days (Solis & Powell, 1999; Rayson et al., 2016; Wetz et al., 2025). The bay also receives major industrial, agricultural, and municipal pollution discharges from Houston (fourth most populous city in the U.S.) and its surrounding areas (Melosi & Pratt, 2007; Wilson et al., 2008; Leonard, 2018). Freshwater inflows are dominated by the San Jacinto and Trinity rivers that carry urban and agricultural effluents (Newell et al., 1994). Galveston Bay connects the northwestern Gulf of Mexico with the Houston shipping channel and is a major shipping and transportation hub for oil tankers and other energy infrastructure related traffic (GBF, 2025). The industrial transformation of the Galveston Bay area began with the discovery of the Spindletop oil field near Beaumont, TX in 1901 (ref). This in turn spurred petroleum exploration and subsequent discovery of the Goose Creek oil field in 1903 and subsequent establishment of oil refineries in Texas City, Baytown and Pasadena on the shores around Galveston Bay by 1908 (Pomeroy Jr, 2020; Sibley, 2020; Young, 2020). The region became a wartime manufacturing hub during the 1930s − 1940s, which was also facilitated by the expansion of the Houston Ship Channel (Cutler, 2020). By the 1960s, the Texas Gulf coast dominated national petrochemical production, processing over 80% of butadiene, 70% of ethylene, and 66% of benzene through more than 200 production plants and with investments exceeding $ 5 billion (TSHA, 1995). In Galveston Bay, there were an estimated 275 oil spills per year with an average spill of ≤ 100 gallons recorded between 1998 and 2014 (Rowe et al., 2020). On March 22, 2014, a collision between two vessels released approximately 6.4 × 105 L (169,070 gallons) of RMG‑380 marine fuel oil into Galveston Bay. (Williams et al., 2017). From March 17–20, 2019, an explosion at the International Terminals Company facility in Deer Park, Texas, released roughly 696,990 gallons of oil‑contaminated wastewater and an additional 1.5 million gallons of flame‑retardant chemicals into the bay (Rice, 2019; An Han et al., 2020). The fire was soon followed by a barge collision and spill of gasoline in upper Galveston Bay on May 10, 2019 (NOAA, 2019). The barge spill released an estimated ~ 378,000 gallons of gasoline into the bay (Trevizo, 2019). These events led to the partial closure of the waterways in the area, leading to an estimated economic loss of $ 0.5 – $ 1 billion (Leinfelder & Blum, 2019; Trevizo, 2019). A barge collision on May 15th, 2024 with the Pelican Island bridge in Galveston (TX) made the national news and reported the release of ~ 2,000 gallons of environmentally toxic vacuum gas oil (VGO) into Galveston (Lozano et al., 2024). In addition to the burgeoning petroleum industry, the Texas coast has also transformed into a major plastics production hub beginning in the mid‑20th century (TSHA, 1995). In 2018, ExxonMobil began operations at its Baytown Chemical & Refining Complex near Galveston Bay, producing ethylene feedstock for the Mont Belvieu polyethylene plant, one of the world’s largest with an annual capacity of around 2.3 million tons (ExxonMobil, 2018). This wave of petrochemical expansion included dozens of plastics facilities built or expanded along the Texas Gulf Coast between 2012 and 2024, many supported by billions in public tax incentives (Patel, 2024b). However, this industrial growth has brought significant plastic pollution, notably pellet (“nurdle”) spills (Tunnell et al., 2020). Monitoring in the 2020s revealed microplastics are ubiquitous across Galveston Bay and its tributaries, documenting high microplastic loads in surface water and sediments, totaling an estimated 20 trillion pieces suspended in the upper 0.3 m of the Bay at any time (Oakley et al., 2024). This issue is compounded by the proximity of Houston, whose dense population and urban sprawl contribute anthropogenic plastic waste through stormwater runoff, litter, and wastewater discharge into the bay (NOAA, 2025). In 2019, a $ 50 million penalty was imposed on Formosa Plastics following a lawsuit alleging the company discharged billions of pellets into the nearby Lavaca Bay (EPA, 2012; Conkle, 2018; Baddour, 2024); while not directly impacting Galveston Bay, this case underscores the broader regional problem. At beaches across the Gulf Coast, microplastics, including nurdles, fibers, fragments, and films continue to wash ashore, accumulating in marine habitats and being ingested by oysters, fish, and birds (Grace et al., 2022; Celis-Hernandez et al., 2023; Wontor et al., 2023). In this study, we assessed persistent (PAHs and PCBs) and emerging nano-microplastics (NMPs) pollutant body-burdens in fish and oysters from Galveston Bay. We compared our findings to historical data for PAHs and PCBs reported in Galveston Bay (biota, surface waters, and sediments). This is the first study to report NMPs body-burdens in the fish from Galveston Bay using a novel pyrolysis gas chromatography and mass spectrometry (Py-GCMS/MS) (Gahn et al., 2025). We hypothesize that the current levels of these persistent and emerging pollutants will be higher than historic levels due to continued industrialization and expansion of urbanization in the area (Comptroller, 2024). Beyond quantifying tissue concentrations, we also inferred probable PAH sources by evaluating ratios of diagnostic low‑ versus high‑molecular‑weight PAHs (Budzinski et al., 1997; Yunker et al., 2002; Tobiszewski & Namieśnik, 2012). Finally, annual plastic intake from seafood for an adult human was estimated using NMP concentrations measured in the muscle of fish and oyster gill/mantle tissues. 2. Methods 2.1. Sample collection and preparation Biota collected from Galveston Bay are eastern oysters ( Crassostrea virginica , Gmelin, 1791), gafftopsail catfish ( Bagre marinus , Mitchill, 1815), red drum ( Sciaenops ocellatus , Linnaeus, 1776), and spotted seatrout ( Cynoscion nebulosus , Cuvier, 1830). All biological specimens were generously provided by the Texas Parks and Wildlife Department (TPWD) as part of their routine annual wildlife monitoring surveys in Galveston Bay. Collections took place opportunistically during the spring and fall of 2021 and 2022. There were no major oil spills during this period. A random stratified sampling approach was employed to choose representative sites across the bay (Fig. 1 ). Sampling at shoreline locations utilized 18.3-meter bag seines, while open-water sites were sampled using 6.1-meter bay trawls. All organisms collected met or exceeded the TPWD’s minimum legal size limits for recreational and commercial harvest for eastern oysters (12.7–20.3 cm), gafftopsail catfish (> 35.6 cm), red drum (> 50.8 cm), and spotted seatrout (> 38.1 cm) (TPWD, 2024). All oysters and fish were weighed, and their total length (TL) and fork length (FL) (fish only) measured ( Supplemental Table 1 ). After capture, specimens were kept on ice and then stored frozen at − 20°C at the Dickinson Marine Laboratory (TX). Subsequently, all samples were transferred to − 20°C storage at Texas A&M University at Galveston. Prior to tissue dissection, samples were thawed on ice. From each fish, approximately 5–10 grams of skinless muscle (fillet) or liver tissue were excised, and from oysters, about 1–2 grams of mantle and gill tissue were collected. The isolated tissues were then stored separately at − 20°C until analytical processing. For chemical analysis, approximately 0.5 g of frozen tissue was freeze-dried at -40 o C for 24 hours at 0.20 mBar pressure using a LABCONCO freeze dryer. The lyophilized tissue was then ground into a fine powder with a mortar and pestle. 2.2 PAHs and PCBs quantification The analytical method used to quantify PAHs and PCBs in oysters and fish has previously been published (Cullen et al., 2019). Briefly, an accelerated solvent extraction (ASE) system (Dionex ASE 350) was used to extract PAHs and PCBs from ~ 0.5 g of freeze-dried muscle or liver tissue using 1:1 dichloromethane (DCM) and hexane as solvents. Samples were loaded into 34 mL ASE cells (Thermofisher Scientific, Cat# 068099), packed with Ottawa sand (Spectrum, Cat # S1010) above and below each sample and spiked with 10 µL of deuterated internal standards (B[a]P-d12 and PCB65-d5). Blanks consisting of Ottawa sand (Sigma‑Aldrich, Cat# 274739) only were similarly spiked with internal standards. Extraction conditions were 100°C, 1500 psi, with 5 min preheat and heat times, followed by a 4 min static phase, and 300 sec purge time, completing two static cycles (60% flush rate) per sample. Extracts were collected in ASE collection vials (Dionex, Cat # 048781), evaporated under N₂, reconstituted in 1 mL DCM, and transferred to 5 mL test tubes. Lipids were removed by solid phase extraction using Captiva lipid solid phase extraction (SPE) cartridges (Agilent Technologies, Cat # 5190 − 1002) conditioned with 1 mL of DCM. The eluate was dried under N 2 , reconstituted into 0.2 mL acetonitrile, frozen at -20°C to further precipitate lipids and debris, and 0.1 mL of clear supernatant was collected, dried under N 2 and reconstituted in 0.1 mL DCM, and transferred to a 0.1 mL glass insert (Wheaton, Cat # 225260) for analysis via GCMS. EPA priority pollutant PAHs (14 congeners) and toxic (28 dioxin like and non-dioxin like) PCBs were quantified using a Hewlett Packard HP 6890 GC coupled with an Agilent 5973 Mass Selective Detector. The PAHs included acenaphthene (ACE), fluorene (FLU), anthracene (ANT), phenanthrene (PHE), fluoranthene (FLT), chrysene (CHR), pyrene (PYR), benzo[a]anthracene (BaA), benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), dibenz[a,h]anthracene (DahA), benzo[g,h,i]perylene (BghiP), and indeno[1,2,3-cd]pyrene (IcdP). The 28 PCB congeners included PCBs 1, 18, 33, 52, 77, 81, 95, 101, 105, 114, 118, 123, 126, 128, 138, 149, 153, 156, 157, 167, 169, 170, 171, 177, 180, 183, 187, and 189 (per IUPAC numbering). Samples were injected in splitless mode (2 µL) into an Agilent DB-5MS column, with helium as carrier gas at 1.0 mL/min. GC oven temperatures started at 40°C, ramped to 180°C at 20°C/min, then to 300°C at 5°C/min, holding for 10 min (total runtime 40 min). The MS was operated in electron impact mode (70 eV, 230°C source temperature) using selected ion monitoring. Quantification was based on an 11-point calibration curve (10–0.01 µg/mL), with detection limits set to the lowest standard giving a signal-to-noise ratio > 5:1 ( Supplemental Table 5 ). Body-burden concentrations were reported as ng/g dry weight (ng/g DW). Sample quality assurance included blank extractions for background correction and standard addition for select analytes. For every ten samples, two blanks (comprising Ottawa sand and internal standard) and one spiked sample (comprising muscle/liver with standard addition PAH and PCB) were analyzed. Recovery averages were 74.07 ± 0.44% for BaA, 46.01 ± 9.24% for PYR, 69.07 ± 3.88% for PCB 18, and 68.50 ± 5.83% for PCB 101. 2.3 Source assessment of PAHs High molecular weight (HMW) PAHs (> four aromatic rings) are generally produced by high-temperature combustion (400–700°C) and are primarily of pyrogenic origin, while low molecular weight (LMW) PAHs (< four aromatic rings) are formed during lower-temperature combustion (100–300°C) and are predominantly petrogenic (Budzinski et al., 1997; Wolska et al., 2012). Diagnostic ratios such as ∑LMW/∑HMW, ∑COMB (i.e., all ∑HMW PAHs)/∑PAHs (∑LMW+∑HMW PAHs), FLT/(FLT + PYR), ANT/(ANT + PHE), BaA/(BaA + CHR), IcdP/(IcdP+BghiP), BaP/BghiP, and PHE/ANT were used to identify dominant sources of PAH (petrogenic or pyrogenic). The interpretation of the ratios are outlined in Tobiszewski and Namieśnik (2012). 2.4 Nano-microplastics (NMPs) quantification The analysis of NMPs was performed according to Gahn et al. (2025). An enzyme solution was prepared to digest freeze-dried tissue for NMP extraction following the methods detailed by von Friesen et al. (2019). Six grams of porcine pancreatic enzyme (Pez, Sigma-Aldrich, Cat # P7545) was dissolved in 100 mL of tris buffer (Sigma-Aldrich, Cat # T2694) and filtered through 2.8 µm and 0.7 µm glass fiber filters (Sigma-Aldrich, Cat # WHA1825025, WHA1823047) to remove plastic contamination. Dried tissue (~ 0.02 g) was treated with 1 mL of Pez/Tris solution (pH 8) in glass vials, shaken at 40°C for 24 hours using a benchtop orbital shaker and filtered onto cleaned 0.7 µm glass filters. Filters were dried at 38°C for 24 hours, then cut and packed into stainless-steel pyrolysis cups (Frontier Eco‑Cup LF, 80 µL, Frontier Labs, USA). Each cup was loaded with the internal standard, poly-4-fluorostyrene (PFS, obtained from PSS, Germany), followed by a layer of calcium carbonate (CaCO₃, ACS grade, J.T. Baker, USA) and capped with a quartz wool plug (Thermo Scientific, USA, Cat. no. 20411). The prepared samples were subsequently analyzed using pyrolysis-GC/MS/MS. The plastics identified included, polymethyl methacrylate (PMMA), polypropylene (PP), polyvinyl chloride (PVC), polyamide (PA), polycarbonate (PC), nylon 6,6 (N66), polyethylene (PE), polyethylene terephthalate (PET), acrylonitrile butadiene styrene (ABS), polyurethane (PUR), styrene‑butadiene rubber (SBR), and polystyrene (PS). The method used to quantify NMPs in the fish tissue has previously been published in detail (Gahn et al., 2025). Briefly, a Frontier Laboratories Auto-shot sampler pyrolyzer, paired with an Agilent 8890 gas chromatograph and an Agilent 7010B triple quadrupole mass spectrometer (Py-GC/MS-MS) was used to quantify NMPs. Tissue pyrolysis was conducted at 600°C, volatilizing microplastics, which were separated using an Ultra Alloy + -5 Capillary Column (30 m length x 0.25 mm I.D. x 0.25 µm film, Frontier Labs, Japan). The GC injector operated with a 50:1 split ratio with a split flow of 40 mL/min at 300°C. A septum purge flow of 20 mL/min was maintained. Helium served as the carrier gas at 2.25 mL/min, while nitrogen was used as the collision gas at 1.5 mL/min. Chromatographic separation followed a temperature program beginning at 35°C (held for 0.25 min), ramping at 20°C/min to a final temperature of 310°C (held for 3 min), yielding a total run time of 17 minutes. The mass spectrometer was configured with a source temperature of 230°C, quadrupole temperature of 150°C, auxiliary temperature of 280°C, and a solvent delay of 5 minutes. Plastic quantification relied on the multiple reaction monitoring of distinctive mass ions, against a five-point calibration curve (1500–150 µg), with all standards loaded onto GF/F filters and processed identically to the samples. Given current concerns of lipid interference for major plastics (A. Monikh et al., 2025), we implemented a stringent QA/QC protocol to minimize false positives, including a rigorous correction procedure as outlined in Gahn et al. (2025). Briefly, a triglyceride lipid mixture (Sigma, CAS# 17810) was used to build a 5-point calibration curve (0.25–1.25 mg) encompassing lipid weight typically observed for our sample types. This was used to relate lipid mass to apparent plastic concentration, enabling calculation of a correction factor that was subtracted from each sample’s NMP quantification. Lipid weight per sample was determined by extracting ~ 0.5 g of freeze‑dried tissue using ASE with DCM:hexane and quantifying lipids gravimetrically by weighing collection vials before and after N₂ evaporation. The limit of detection (LOD) was calculated using signal/noise ≥ 3. Quality controls per 10 samples included two blanks, two recovery controls, and one replicate. Blanks measured background contamination (and were subtracted from sample responses), recoveries assessed plastic standard recovery, and replicates checked reproducibility. Recovery for select plastics were 115 ± 0.15% for PP, 93 ± 0.08% for N66, and 113 ± 0.05% for PE. 2.5 Average Daily Intake of NMPs The Daily Intake (DI) of seafood (g/kg body weight/day) was calculated as follows: $$\:DI=\frac{{DC}_{shellfish\:or\:fish}}{BW}\:\:\:\left(1\right)$$ $$\:ADI={C}_{Plastics}*\:DI\:\:\:\left(2\right)$$ First, seafood daily intake (DI) was calculated by dividing the estimated daily consumption (DC, 30 g/day) of fish or shellfish by the average adult human body weight (BW, 70 kg), as recommended by the Texas Department of State Health Services (DSHS, 2011). Secondly, the Average Daily Intake (ADI) of NMPs (mg/kg/day) was estimated by multiplying the DI by the plastic concentration (C plastics ) in fish muscle or oyster gill/mantle, originally measured in µg/g dry weight (DW). These concentrations were converted to wet weight (WW) using species-specific correction factors accounting for water loss during freeze-drying (e.g., if a 6 g oyster was dried to 1g, the DW concentration was divided by 6 to get WW concentration). Finally, the ADI values were scaled to estimate annual plastic intake per person per year by multiplying the daily intake rate by 365 days. 2.6 Historic levels of PAHs, PCBs, and NMPs in Galveston Bay A targeted literature search was conducted using Google Scholar and PubMed by combining the keywords: PAH, PCB, microplastics; with the geographic terms: Galveston Bay, Gulf of Mexico; and environmental matrices: air, water, sediment, oyster, fish muscle, fish liver. Additional search terms included concentration, body burden, historic, and related descriptors. Both acronyms (i.e. PAH, PCB) and full chemical names (i.e. polycyclic aromatic hydrocarbons, polychlorinated biphenyls) were used in various combinations to capture a broad range of studies. The relevant publications were downloaded without date restriction, including early reports dating back to 1965. From these sources, data on pollutant levels were extracted from tables, charts, and figures wherever reported in each source. The retrieved values were compiled into a unified Excel spreadsheet, and the concentration units converted to ng/g for PAHs and PCBs, and µg/g for microplastics, wherever possible. For water concentrations, we assumed the density of water to be 1 g/mL, therefore allowing the conversion of ng/L to ng/g water. Wet-weight (WW) contaminant concentrations in fish muscle were converted to dry weight (DW) using a 4:1 ratio, reflecting an expected moisture content of ~ 75% (Bigler & Greene, 1993; Cresson et al., 2017). Fish liver tissue, which typically contains 83–85% moisture, necessitated the use of 6:1 WW-to-DW correction factor (Bigler & Greene, 1993). Oyster soft tissue concentrations were converted using the 6:1 WW-to-DW ratio, based on a reported 82% mean moisture content (Mo & Neilson, 1994). Reported organism body weights were also recorded when available. The final datasets comprised 204 concentration entries from 70 unique studies spanning from 1965–2021 for PAHs and PCBs, and from 2000–2023 for NMPs. The fully annotated spreadsheet is provided with sources to allow replication and secondary analyses by other authors ( Supplemental Tables 2, 3, 4 ). The ‘past’ datasets were presented alongside those measured in the current study. 2.7 Statistical analysis ArcGIS Pro (v3.0) was used to map the biota sampling sites across Galveston Bay (ESRI, 2025). Statistical analyses were conducted using base R (v4.1.3) along with the tidyr and ggplot2 packages for data organization and visualization (R, 2025). Statistical significance was determined at α ≤ 0.05. Data normality was assessed using the Shapiro-Wilk test, followed by Levene’s test to evaluate homogeneity of variances. For pairwise comparisons (i.e., pollutant concentration between tissue), either a parametric t-test or a non-parametric Mann-Whitney U test was applied, depending on data distribution. When analyzing datasets involving a main effects variable, one-way ANOVA (parametric) or Kruskal-Wallis test (non-parametric) was used, with Tukey’s or Dunn’s post hoc tests, respectively, for pairwise group comparisons of body burden of pollutants between species. For analysis including both a main effect and a covariate, a two-way ANOVA was conducted followed by Tukey’s post hoc test (i.e., contaminant body burden across species and tissue type). 3. Results 3.1. Morphometric parameters All fish and oysters collected for the present study were adults with the exception of red drum, which were categorized as juveniles ( Table S1 ). We found animal size to not be a determinant for pollutant bioaccumulation as a spearman-rank correlational analysis conducted between morphometric parameters and the pollutant body-burdens showed no significant correlations (data not shown). 3.2. PAHs body-burdens in biota from Galveston Bay as reported in this study Total PAHs in the gill/mantle tissue of oysters (608.51 ± 15.72 ng/g DW) and muscle of seatrout (605.30 ± 19.08 ng/g DW) were significantly higher (both 2.4x) than red drum (252.06 ± 6.44 ng/g DW) (Fig. 2 (a) , Table 1 (a) ). However, total hepatic PAH levels showed red drum (3,995.90 ± 182.84 ng/g DW) to have the highest (~ 2.5x; statistically significant) hepatic PAH levels compared to catfish (1,644.72 ± 61.99 ng/g DW), and seatrout (1,651.56 ± 76.38 ng/g DW) (Fig. 2 (a) , Table 2 (a) ). Overall, the total PAHs in livers as compared to muscle samples were 3x higher in seatrout, 5x higher in catfish and 16x higher in red drum (p < 0.05). The analysis of PAHs congeners in muscle of fish and gill/mantle of oysters showed the proportion of ACE and PHE to be higher (20–35%) as compared to the rest of PAHs (Table 1 (a), Supplemental Fig. 1(a)) . In red drum muscle, BkF comprised up to 25% of all PAHs. Whereas, in red drum and spotted seatrout muscle, and gill/mantle of oysters, FLU was also predominant at 10–15%. In the livers of all fish, FLU dominated at up to 50% (Table 2 (a), Supplemental Fig. 1(b)) . There was also a higher proportion of ACE in catfish only, which was responsible for ~ 25% of all the PAHs detected in catfish livers collected from Galveston Bay. Finally, there was a higher proportion of BaP in seatrout (up to 25%) and IcdP in red drum (up to 50%) in livers. Table 1 Muscle concentration of PAH, PCB and NMP congeners found in biota collected from Galveston Bay. Levels are reported in ng/g tissue dry weight (DW) for PAHs, PCBs; and in µg/g dry weight (DW) for NMPs (mean ± standard error). Significant differences are denoted using letters. Levels below the limit of detection are represented by “- “. (a) PAHs (ng/g DW) Oyster (n = 9) Catfish (n = 8) Red drum (n = 9) Seatrout (n = 8) Low molecular weight (LMW) ACE 197.64 ± 38.98 95.64 ± 15.25 66.13 ± 17.37 249.71 ± 99.04 FLU 103.39 ± 37.99 13.46 ± 4.18 27.98 ± 9.04 63.21 ± 21.87 PHE 117.09 ± 10.45 118.04 ± 22.46 54.85 ± 7.82 151.56 ± 34.01 ANT 6.76 ± 3.72 8.05 ± 2.12 2.97 ± 0.96 11.20 ± 2.14 High molecular weight (HMW) FLT - 13.84 ± 3.68 2.42 ± 2.42 2.58 ± 1.64 PYR 7.18 ± 2.95 18.81 ± 2.55 6.57 ± 2.61 8.90 ± 6.02 BaA 15.70 ± 4.14 4.90 ± 1.93 5.98 ± 2.21 8.89 ± 2.09 CHR 15.61 ± 3.39 2.31 ± 0.88 2.47 ± 0.79 12.19 ± 3.30 BbF 1.17 ± 0.86 15.82 ± 7.10 0.38 ± 0.38 7.73 ± 2.90 BkF 31.08 ± 13.46 27.60 ± 8.50 60.15 ± 6.91 44.80 ± 11.25 BaP 16.07 ± 5.08 2.93 ± 1.80 3.67 ± 1.20 9.17 ± 2.90 IcdP 6.54 ± 2.27 1.93 ± 0.94 1.01 ± 1.01 5.48 ± 2.12 DahA 76.79 ± 46.07 2.32 ± 2.32 13.44 ± 1.82 19.03 ± 9.46 BghiP 13.48 ± 3.33 3.05 ± 1.50 4.050 ± 1.53 10.84 ± 2.83 ΣPAHs 608.51 ± 15.72 a 328.70 ± 9.73 a,b 252.06 ± 6.44 b 605.30 ± 19.08 a (b) PCBs (ng/g DW) Oyster (n = 9) Catfish (n = 8) Red drum (n = 9) Seatrout (n = 8) Non-ortho (dioxin like) PCB 77 53.60 ± 37.42 - 0.46 ± 0.46 0.56 ± 0.56 PCB 81 10.93 ± 4.22 - - 2.83 ± 1.48 PCB 126 0.03 ± 0.03 - 0.77 ± 0.77 3.98 ± 1.60 PCB 169 8.39 ± 4.25 - 0.57 ± 0.57 1.68 ± 1.21 Mono-ortho (dioxin like) PCB 105 0.49 ± 0.49 2.01 ± 1.01 2.63 ± 1.97 5.88 ± 3.84 PCB 114 - - 1.13 ± 1.13 3.14 ± 1.47 PCB 118 2.50 ± 1.35 8.50 ± 4.10 - 2.78 ± 1.40 PCB 123 0.45 ± 0.45 - - 2.97 ± 1.23 PCB 156 - - - 0.95 ± 0.95 PCB 167 4.15 ± 3.24 2.94 ± 1.44 0.55 ± 0.55 38.00 ± 23.25 PCB 189 - - - 0.49 ± 0.49 Non-dioxin like PCB 1 - - - - PCB 18 43.00 ± 8.66 0.80 ± 0.80 0.43 ± 0.43 5.98 ± 2.18 PCB 33 9.18 ± 3.18 - 0.92 ± 0.61 0.55 ± 0.55 PCB 52 2.79 ± 1.43 14.14 ± 2.92 7.45 ± 1.04 13.48 ± 2.22 PCB 95 0.50 ± 0.50 0.85 ± 0.85 - 0.71 ± 0.71 PCB 101 1.32 ± 0.91 14.22 ± 5.37 - 1.36 ± 0.92 PCB 128 148.39 ± 39.20 6.89 ± 2.72 - 93.13 ± 51.85 PCB 138 - 47.66 ± 18.04 - 3.16 ± 2.35 PCB 149 - 9.10 ± 3.76 - 0.82 ± 0.82 PCB 153 - 36.60 ± 13.92 - 1.37 ± 0.92 PCB 157 - 0.64 ± 0.64 - 0.97 ± 0.97 PCB 170 0.84 ± 0.84 9.31 ± 4.72 - 1.62 ± 1.14 PCB 171 - 1.80 ± 1.18 - - PCB 177 - - - 0.84 ± 0.84 PCB 180 - 27.32 ± 11.48 - - PCB 183 - 7.58 ± 2.85 - 1.43 ± 0.95 PCB 187 - 18.92 ± 7.26 - - ΣPCBs 286.56 ± 5.65 a 209.29 ± 2.28 a 14.90 ± 0.28 b 188.69 ± 3.48 a (c) NMPs (µg/g DW) Oyster (n = 10) Catfish (n = 9) Red drum (n = 10) Seatrout (n = 10) PMMA - - - - PP 7,057.07 ± 5261.07 - - 2,146.60 ± 1,148.99 PVC - - - - PA - 6.19 ± 2.33 43.16 ± 9.30 10.22 ± 3.56 PC - - - - N66 3,208.69 ± 1,100.72 277.54 ± 151.39 - 5,783.76 ± 2,395.55 PE 1,441.13 ± 599.85 - - 5,122.73 ± 2809.69 PET - - - - ABS - - - - PUR - - - - SBR 281.66 ± 157.69 - - - PS - - - - ΣNMPs 11,988.55 ± 6,392.18 a 283.74 ± 150.56 b 43.16 ± 9.30 b 13,063.30 ± 6,225.16 a 3.3. Overview of historic PAHs levels in Galveston Bay The long-term trends of PAHs concentrations (Fig. 3 (a)) reported across various environmental matrices (from the literature) reveal levels in surface waters (2010–2017) to be the lowest, with a median concentration of 47 ng/L or 0.047 ng/g (min-max range, 25–9,520 ng/L or 0.025–9.52 ng/g). Sediment PAHs concentrations (1968–2017) exhibited a median concentration of 174 ng/g DW (min/max of 19.8–3,608 ng/g DW) and were significantly higher than those measured in water. In contrast to surface waters, higher concentrations of PAHs were observed in biota (Fig. 3 (a) ). For example, fish muscle (2010–2021) and fish liver (2018–2021) showed median concentrations of 252.06 ng/g DW (67.36–4,600 ng/g DW) and 1800 ng/g DW (500–13,200 ng/g DW), respectively. The median concentration of PAHs in fish liver was significantly higher than those in fish muscle (7x), sediment (10x), and water (39x). Fish muscle PAHs concentrations were also significantly higher than that in water (5x). Finally, oyster body burdens (1971–2021) were in between fish muscle and liver, with a median of 608.51 ng/g DW (230.50–4857.50 ng/g DW) and were significantly higher than both sediment (3.5x) and water (13x). 3.4. PCBs body-burdens in biota from Galveston Bay as reported in this study The sum of total PCBs in oysters (286.56 ± 5.65 ng/g DW), while slightly higher, were within the same order of magnitude and not statistically different from catfish muscle (209.29 ± 2.28 ng/g DW) and seatrout muscle (188.69 ± 3.48 ng/g DW). In contrast, red drum muscle exhibited the lowest sum of total PCBs levels at 14.90 ± 0.28 ng/g DW amongst the biota (Fig. 2 (b) , Table 1 (b) ). No significant differences across biota were observed for the liver body-burdens of PCBs in fish Fig. 2 (b) , Table 2 (b) ). The highest hepatic sum of total PCBs was measured in seatrout (2,161.75 ± 33.19 ng/g DW) followed by catfish (1,349.75 ± 25.31 ng/g DW) and red drum (630.13 ± 12.25 ng/g DW) (Table 2 (b) ). Overall, the total PCB levels were 6x higher in catfish, 11x higher in red drum and 42x higher in red drum liver vs. muscle (significantly different). The analysis of PCBs congeners in muscle samples revealed PCB 52 was the most prominent in red drum (75% of total PCBs) and spotted seatrout (30% of total PCBs) (Table 1 (b), Supplemental Fig. 2 (a) ). In contrast, PCB 128 was the most prominent congener in oysters (~ 50% of total PCBs) and seatrout (~ 25% of total PCBs). In catfish, PCBs 138 and 153 dominated (22% and 18% respectively of total PCBs). In the liver samples, PCB 126 was the most prominent congener in catfish (50% of total PCBs), red drum (38% of total PCBs) and seatrout (up to 25% of total PCBs). Whereas PCB 128 mainly dominated in seatrout (25% of total PCBs) (Table 2 (b), Supplemental Fig. 2 (b)) . Table 2 Liver concentrations of (a) PAHs, (b) PCBs, and (c) NMPs congeners found in biota collected from Galveston Bay. Levels are reported in ng/g tissue dry weight (DW) for PAHs, PCBs; and in µg/g dry weight (DW) for NMPs (mean ± standard error). Significant differences are denoted using letters. Levels below the limit of detection are represented by “- “. (a) PAHs (ng/g DW) Catfish (n = 10) Red drum (n = 10) Seatrout (n = 7) Low molecular weight (LMW) ACE 539.44 ± 105.93 - - FLU 762.82 ± 130.88 1,421.37 ± 371.30 1,046.07 ± 447.25 PHE 59.21 ± 13.89 109.91 ± 39.70 181.86 ± 40.46 ANT 31.87 ± 8.41 153.28 ± 58.70 71.45 ± 27.62 High molecular weight (HMW) FLT 10.53 ± 4.89 9.95 ± 9.95 - PYR 7.90 ± 3.95 - - BaA 13.38 ± 5.31 - - CHR 12.31 ± 4.83 - - BbF 1.12 ± 1.12 - - BkF 0.34 ± 0.34 - - BaP 66.81 ± 19.81 27.98 ± 27.98 352.18 ± 92.37 IcdP 52.28 ± 15.77 2,273.41 ± 733.34 - DahA - - - BghiP 86.71 ± 23.90 - - ΣPAHs 1,644.72 ± 61.99 a 3,995.90 ± 182.84 b 1,651.56 ± 76.38 a (b) PCBs (ng/g DW) Catfish (n = 10) Red drum (n = 10) Seatrout (n = 7) Non-ortho (dioxin like) PCB 77 - - - PCB 81 - - - PCB 126 694.48 ± 241.28 333.89 ± 130.25 570.41 ± 188.08 PCB 169 - 7.72 ± 7.72 56.87 ± 56.87 Mono-ortho (dioxin like) PCB 105 45.36 ± 26.14 54.78 ± 40.61 - PCB 114 193.78 ± 100.43 4.79 ± 3.23 - PCB 118 7.86 ± 6.01 - 107.85 ± 49.93 PCB 123 7.53 ± 6.49 - 86.48 ± 40.84 PCB 156 1.49 ± 1.43 61.68 ± 30.54 - PCB 167 43.40 ± 26.68 1.65 ± 1.65 367.89 ± 139.12 PCB 189 - - 0.27 ± 0.27 Non-dioxin like PCB 1 43.43 ± 10.65 - - PCB 18 12.85 ± 10.22 90.11 ± 45.37 97.16 ± 77.30 PCB 33 - - - PCB 52 8.15 ± 5.45 18.10 ± 8.89 - PCB 95 - 16.84 ± 13.03 - PCB 101 6.61 ± 6.61 - - PCB 128 131.96 ± 62.57 15.81 ± 15.81 706.33 ± 267.99 PCB 138 54.09 ± 23.54 - 83.33 ± 57.58 PCB 149 7.72 ± 3.92 - 10.29 ± 7.95 PCB 153 38.21 ± 25.58 - 23.53 ± 22.74 PCB 157 - 6.63 ± 6.22 4.06 ± 3.38 PCB 170 0.73 ± 0.73 14.52 ± 8.71 7.82 ± 7.82 PCB 171 - - 2.46 ± 2.46 PCB 177 - 2.58 ± 2.58 - PCB 180 33.12 ± 19.72 - 20.30 ± 16.91 PCB 183 8.36 ± 6.19 1.01 ± 1.01 16.71 ± 9.62 PCB 187 10.62 ± 6.67 - - ΣPCBs 1,349.75 ± 25.31 630.13 ± 12.25 2,161.75 ± 33.19 (c) NMPs (µg/g DW) Catfish (n = 10) Red drum (n = 6) Seatrout (n = 7) PMMA - - - PP - - - PVC - - - PA 50.51 ± 19.24 34.75 ± 22.62 - PC - - - N66 3,950.07 ± 1099.60 1,824.10 ± 1123.69 - PE - - - PET - - - ABS 57.15 ± 13.45 - - PUR 37.87 ± 1.22 - - SBR 3,975.20 ± 304.19 432.49 ± 145.47 - PS - - - ΣNMPs 8,070.80 ± 970.99 a 2,291.35 ± 1268.41 b - 3.5. Overview of historic PCBs levels in Galveston Bay A literature review of PCBs concentrations in Galveston Bay revealed levels in surface waters (2002–2018) to be the lowest (compared to the matrices reported), with a median concentration of 2.2 ng/L or 0.0022 ng/g (min – max of 0.1–16.1 ng/L or 0.0001–0.0161 ng/g). For example, the reported PCBs concentrations in sediments (1972–2018) exhibited a median concentration of 26.0 ng/g DW (2.73–17,000 ng/g DW) and were significantly higher than those in water. As observed for PAHs in biota, PCBs levels were also higher in fish and oysters than in surface waters and sediments (Fig. 3 (b) ). Fish muscle (1989–2021) and fish liver (2018–2021) showed median concentrations of 344.00 ng/g DW (14.90–10,000 ng/g DW) and 2,032.02 ng/g DW (392.76–21,600 ng/g DW), respectively. The concentrations of PCBs in fish livers were significantly higher than fish muscle (6x), oysters (7x), sediments (78x), and surface waters (924,000x). PCBs in the muscle tissue of fish were also significantly higher than those in sediments (13x) and surface waters (156,000x). Finally, oyster body-burdens (1987–2021) had a median concentration of 288.43 ng/g DW (41.55–588.50 ng/g DW) and were significantly higher than in sediments (11x) and surface waters (131,000x). 3.6. NMPs body-burdens in biota from Galveston Bay as reported in this study The sum of total NMPs in the gill/mantle tissue of oysters (11,988.55 ± 6,392.18 µg/g DW) was significantly higher than the muscle in fish, at levels 42x higher than catfish (283.74 ± 150.56 µg/g DW), and 279x higher than red drum (43.16 ± 9.30 µg/g DW) (Fig. 2 (c) , Table 1 (c) ). For NMPs body-burdens in fish livers, catfish (8,070.80 ± 970.99 µg/g DW) had significantly higher levels (4x) of NMPs as compared to red drum (2,291.35 ± 1,268.41 µg/g DW). In muscle tissue, there was a prevalence of PA comprising of 23–45% of the sum of total NMPs in catfish and seatrout, and up to 88% in red drum. N66 was the second most abundant NMP (30–55% sum of total NMPs) in oysters, catfish and seatrouts (Table 1 (c), Supplemental Fig. 3 (a)) . Lower profiles of PE (13% in oyster, 19% in seatrout), PP (up to 31% in oyster), and SBR (up to 19% in oyster) were also detected. In contrast, in liver tissues of fish only N66 (39% in catfish and 37% in red drum) and SBR (57% in catfish and 39% in red drum) were prominently detected (Table 2 (c), Supplemental Fig. 3 (b)). The analysis of NMPs in the livers of catfish was not possible due to insufficient tissue biomass after PAH-PCB analysis. 3.7. Overview of historic NMPs levels in Galveston Bay Given the recent development of NMPs quantification using mass spectrometry methods (such as Py-GCMS/MS), our review of environmental datasets begins from ≥ 2000 and only included studies using Py-GCMS (Fig. 3 (c) ). Our review showed that surface waters contained the lowest NMP concentrations, with a median of 0.001 µg/g (or 0.001 µg/mL of water; min - max of 0.00014–0.010 µg/g). Sediments had the second lowest NMP concentrations, with a median of 0.16 µg/g DW (min-max of 0.01–8.76 µg/g DW), approximately two orders of magnitude higher than the levels quantified in surface waters. In contrast, the analysis of biota from the bay showed fish muscle to contain a median of 818.44 µg/g DW (min-max of 43.16–13,063.30 µg/g DW), roughly three orders of magnitude higher than sediment and six orders of magnitude greater than water; these differences were statistically significant. Fish liver had a median NMP concentration of 7,303.75 µg/g DW (min-max of 2,291.40–18,166.10 µg/g DW), ~9x higher than fish muscle. Oyster body burdens were the highest overall, with a median of 10,457.14 µg/g DW (min-max of 8,925.70–11,988.55 µg/g DW). 4. Discussion 4.1. PAHs body-burdens in biota from Galveston Bay as measured in this study Eastern oysters exhibited higher total PAH body burdens, approximately 2× those of seatrout, 2× those of catfish, and 2.5× those of red drum (Fig. 2 (a) , Table 1 (a) ). Elevated PAHs concentrations in shellfish compared to finfish observed in this study are consistent with previous reports. For example, Rowe et al. (2020), documented significantly higher concentrations of sum of total PAHs in oysters (203 ± 68 ng/g WW) in comparison to spotted seatrout (14 ± 8 ng/g WW) sampled from Galveston Bay. This disparity likely stems from oysters’ filter-feeding behavior, the lipophilic nature of PAHs, and the comparatively limited metabolic capacity of invertebrates to process and eliminate these contaminants. Oysters are capable of filtering approximately 25–50 gallons of water daily (Ehrich & Harris, 2015; NOAA, 2020), increasing their potential exposure to pollutants such as PAHs (Fisher et al., 2000; Bustamante et al., 2012; Trevisan et al., 2017; Wang et al., 2020). Furthermore, invertebrates generally exhibit lower biotransformation efficiencies than fish, making them less effective at metabolizing and excreting pollutants (Neff et al., 1976; Vidal-Liñán et al., 2016; Honda & Suzuki, 2020). Consequently, oysters tend to accumulate greater PAH burdens and may serve as sentinel organisms for assessing contaminant exposure in marine ecosystems. In contrast to the muscle tissue in fish, their livers exhibited total PAH levels that were 3x (seatrout) to 16x (red drum) higher than in muscle (Fig. 2 (a) , Table 2 (a) ). This result likely reflects the lipophilicity of PAHs (Sverdrup et al., 2002) and the elevated lipid content in fish liver relative to muscle tissue (Ando et al., 1993; Arrington et al., 2006). In our study, gravimetric analysis revealed liver lipid levels to be ~4x higher than muscle in catfish, 11x higher in seatrout, and 12x higher in red drum (data not shown). Given the high hydrophobicity of PAHs (i.e., Log Kow = 3.37–6.75) and strong affinity for lipids (Choi et al., 2010), PAHs tend to accumulate more readily in lipid-rich tissues such as the liver. For instance, Blacktip and Bonnethead sharks in the Gulf of Mexico exhibited approximately double the PAHs body burden in liver (2,120 ± 106 and 2,200 ± 219 ng/g, respectively) compared to muscle tissue (1,150 ± 75.70 and 1,080 ± 44.20 ng/g, respectively) (Cullen et al., 2019). 4.2. PAHs congener profiles and likely sources in biota In the gill/mantle of oysters and in fish muscle, LMW PAHs such as ACE and PHE made up 20–35% of the total PAHs, with FLU also being prominent in red drum, seatrout, and oysters (10–15%) (Table 1 (a), Supplemental Fig. 1 (a) ). In fish livers, a similar trend was reflected, where FLU contributed ~ 50% across species. ACE was particularly elevated in catfish liver, accounting for 25% of total PAHs (Table 2 (a), Supplemental Fig. 1 (b) ). LMW PAHs consist of less than four aromatic rings, combust between 100–300°C, and are typically petrogenic in origin (Budzinski et al., 1997). They are mainly associated with petroleum, crude oil and refined petroleum products such as gasoline, kerosine, diesel, lubricating oils etc. (Wolska et al., 2012). The prominence of the LMW PAHs in the bay could be indicative of its petrogenic pollution sources (Table 3 ). Specifically, the presence of crude oil processing facilities around Galveston Bay may contribute to this result (HARC, 2014; Rice, 2019; Trevizo, 2019). Similarly, in Sabine Lake (90 miles east of Houston) biota (red drum and seatrout), the profiles of LMW PAHs such as ACE, PHE and FLU were also found to be prominent (Hernout et al., 2020). In the findings of Williams et al. (2017), after the Texas city oil spill, surface water samples collected from Galveston Bay showed a higher profile of PHE concentration, relative to other PAHs, underscoring the role of petrogenic pollution in LMW PAH contribution. In contrast, BkF, a HMW PAH, made up to 25% of total PAHs in red drum muscles (Table 1 (a), Supplemental Fig. 1 (a) ). The liver samples showed distinct HMW PAH profiles: BaP reached up to 25% in seatrout, while IcdP dominated red drum (up to 50%) (Table 2 (a), Supplemental. Figure 1 (b) ). IcdP was also found to be relatively higher in proportion to other PAHs in Sabine Lake fish in a previous study (Hernout et al., 2020). HMW PAHs have four or more aromatic rings, combust between 400–700°C and are known to be pyrogenic (Wolska et al., 2012). Pyrogenic sources of PAHs are mainly associated with incomplete combustion of organic matter such as coal, wood, petroleum and garbage (Wolska et al., 2012). Bacosa et al. (2020) noted the prevalence of HMW PAHs in Galveston Bay after Hurricane Harvey (such as BaP, IcdP, BghiP) and concluded their sources to be predominantly combustion related. Together, this data illustrates the mixed sources (petrogenic and pyrogenic) of PAHs in Galveston Bay. Table 3 Source-diagnostic assessment of PAHs in oyster and fish tissues (muscle and liver) based on established LMW/HMW ratio criteria. Thresholds indicating pyrogenic origin follow Tobiszewski & Namieśnik (2012); values marked with * denote ratios consistent with predominantly pyrogenic inputs. Diagnostic Ratios Pyrogenic* if Oyster Catfish Muscle Red drum Muscle Seatrout Muscle Catfish Liver Red drum Liver Seatrout Liver ∑LMW/∑HMW 0.4 0.00 0.46* - 1.00* - - - ANT/(ANT + PHE) > 0.1 0.03 0.08 0.08 0.07 0.34* 0.72* 0.36* BaA/(BaA + CHR) > 0.2 0.53* 0.70* 0.60* 0.50* 0.60* - - IcdP/(IcdP+BghiP) > 0.2 0.34* - 0.00 0.34* 0.41* 1.00* - PHE/ANT < 10 29.03 12.31 12.22 13.78 1.90* 0.39* 1.79* Pyrogenic* 29% 33% 17% 43% 67% 60% 50% Petrogenic 71% 67% 83% 57% 33% 40% 50% Diagnostic PAH source ratio analysis is a widely used tool for identifying contaminant sources in environmental samples (Blumer, 1976; Simoneit, 1985; Lipiatou & Saliot, 1991; Yunker et al., 1996; Budzinski et al., 1997; Yunker et al., 1999). Our analysis indicated petrogenic sources of PAHs to predominate in Galveston Bay (Table 3 ). Of the ratios calculated, 71% indicated petrogenic dominance in oysters, 67% in catfish muscle, 83% in red drum muscle, and 57% in seatrout muscle. However, liver tissues showed a varied pattern, with catfish liver and red drum liver indicating pyrogenic dominance (67% and 60% respectively). While seatrout liver exhibited equal contributions (50% petrogenic and pyrogenic source) across the ratios calculated (Table 3 ). Averaged across all tissues, petrogenic PAHs constituted 57% and pyrogenic sources 43%, underscoring a mixed signature, with an overall petrogenic dominance. In a study looking at the PAH profiles of fish in Sabine Lake (also hub of petroleum refineries), a prevalence of LMW PAHs was also observed, alluding to the prevalence of petrogenic exposure (Hernout et al., 2020). This is expected given the Texas Gulf Coast's extensive oil production, historical spills, and barge collisions (HARC, 2014; Rice, 2019; Trevizo, 2019). Recent events such as the Texas City “Y” spill (2014), which released approximately 168,000 gallons of intermediate fuel oil, the ITC Deer Park fire (2019), which resulted in the release of nearly 19.7 million gallons of petrochemical products, as well as a barge collision in Pelican island bridge (Galveston; 2,000 gallons of toxic vacuum gas oil was spilt) (Rice, 2019; Edwards et al., 2021; Cohen, 2024). The Gulf of Mexico has also endured catastrophic spills like Deepwater Horizon in 2010, which released 4.9 million barrels of oil, leading to documented influx of LMW PAHs (Ramseur, 2010; Liu et al., 2012; Murawski et al., 2014; Snyder et al., 2015; Beyer et al., 2016; Romero et al., 2021). The ongoing Taylor Energy oil spill, active since 2004, continuously discharges oil into the waters of the northwestern Gulf (Warren et al., 2014; Fears, 2018). The greater Houston area also experiences significant air pollution from the intense combustion of petroleum products, stemming from both large-scale industrial operations and extensive vehicle traffic. Petrochemical complexes along the Houston Ship Channel, including ExxonMobil’s Baytown refinery, LyondellBasell’s Channelview plant, and Chevron Phillips’ Cedar Bayou facility, are major emitters of volatile organic compounds (VOCs), particulates, and polycyclic aromatic hydrocarbons (PAHs) through processes like flaring, process vents, and heat-generation units (EPA, 2021; Patel, 2024a; Ward, 2024). Houston's urban sprawl and vehicular traffic contribute to high rankings in vehicle miles traveled nationally, leading to a continuous stream of exhaust (McGaughey et al., 2004; Qiao et al., 2005; TxDOT, 2025). Maritime traffic and port activities further exacerbate this issue, as the combustion of heavy fuel oil in ocean-going vessels and emissions from cargo handling equipment contribute additional PAH-laden particulates (Williams et al., 2009; Schulze et al., 2018). These combined sources of petroleum combustion are reflected in the PAH diagnostic ratios observed in environmental samples, indicating inputs from the complete and incomplete combustion of fossil fuels. 4.3. Historic PAHs levels in Galveston Bay An analysis of historical data on PAH concentrations in Galveston Bay reveals a persistent level of contamination and distinct accumulation pattern (surface water < sediment < fish muscle < oyster < fish liver) across environmental matrices (Fig. 3 (a), Supplemental Table 2 ). The concentration of PAHs in surface water was found to be the lowest, spanning across several orders of magnitude, ranging from 25 ng/L in 2014 (Williams et al., 2017) to a peak of 1,714,000 ng/g in oil-contaminated water the same year from Galveston Bay following the Texas city “Y” spill (Yin et al., 2015) which released approximately 168,000 gallons of intermediate fuel oil directly into Galveston Bay (Stephens, 1997; DARRP, 2014). PAHs levels measured in 2012 ranged from 800 − 18,230 ng/L (Rowe et al., 2020), while measurements in 2017 ranged from 25–175 ng/L (Bacosa et al., 2020). Such variable ranges for PAHs concentrations in the surface waters of Galveston Bay reflect episodic pollution events, indicating water concentrations to be reflective of anthropogenic disturbances (Du et al., 2019). Sediment core samples from Galveston Bay reveal PAHs to be 3 orders of magnitude higher than water, with reported values of 479 − 250 ng/g between 1968–1975 (Presley et al., 1998), and 220–320 ng/g between 1981 and 2001 (Santschi et al., 2001). Additional findings by Jackson et al. (1998) show values ranging from 24 ng/g (in 1991) to 202 ng/g in 1989, while concentrations in the late 1990s ranged from 52 to 724 ng/g (Willett et al., 1997; Presley et al., 1998). More recent data include values of 468.40 ng/g to 89.20 ng/g from 2002 to 2017 (Harmon et al., 2003; Camargo et al., 2021). Despite such variability, sediments are an effective reservoir for PAHs accumulation (Du & Jing, 2018; Usanase et al., 2021). Hydrophobic compounds such as PAHs and PCBs preferentially partition from the water column and adsorb to suspended particulate matter, which eventually settles and becomes incorporated into the sediment (Guo et al., 2009; Sun et al., 2017; Khadhar et al., 2018; Combi et al., 2020). Sediments thus serve as a long-term reservoir or "sink," reflecting cumulative contaminant loads over months to years (Brion & Pelletier, 2005; Bouloubassi et al., 2006; Chiaia-Hernández et al., 2022). The concentrations of PAHs in biota samples (fish and oysters) were found to be 1.45x – 10 7 x higher than both water and sediment. This increased partitioning into biota is indicative of bioaccumulation. Specifically, lipophilic contaminants readily bioaccumulate into lipid-rich biological compartments (such as hepatic tissue) (Nácher-Mestre et al., 2010; Torres et al., 2012; Gan et al., 2021). The data from fish tissues illustrate this accumulation pathway. Fish muscle concentrations were 4 orders of magnitude higher than typical PAH levels in surface waters and only 1.5x higher than sediment (Fig. 3 (a), Supplemental Table 2 ). Bioaccumulation in fish livers is even more pronounced at ~7x higher than in muscle. This demonstrates progressive accumulation from surface waters > sediments > biota (Monod & Vindimian, 1991; Barber et al., 2006; Topić Popović et al., 2023). Oysters, as sessile filter-feeders, appear to bioaccumulate higher concentrations of PAHs compared to fish muscle (2.4x higher), sediment (3.5x higher) and water (10 7 x higher), which could be explained by their filter feeding strategy (Fisher et al., 2000; Bustamante et al., 2012; Trevisan et al., 2017; Wang et al., 2020). Previously published studies show a range of high values in oysters, from 488–9,227 ng/g DW in 2001 (Qian et al., 2001), 203 ± 68 ng/g WW in 2012 (Rowe et al., 2020), and 608.51 ± 15.72 ng/g DW in 2019 (this study). Together, these findings highlight oysters’ chronic exposure to PAHs, with levels remaining consistently elevated over the decades. This makes oysters highly effective bioindicators for PAHs in the environment (Sericano et al., 1990; Vaezzadeh et al., 2019). When placed within a broader regional context, PAHs concentrations in Galveston Bay are within range of neighboring bays. For example, the historic sediment concentration of PAHs in Galveston Bay range of 19.8–479 ng/g which is comparable to an average of 11.5 ng/g from Matagorda Bay (Geiselbrecht Allison et al., 1998) and 140 ng/g in sediments from the Mississippi river delta (Wade et al., 2008). In Matagorda Bay, PAHs body-burdens in fish muscle tissue were 124.40 ± 3.00 ng/g DW in gafftopsail catfish, 198.91 ± 7.94 ng/g DW in red drum, and 196.40 ± 3.26 ng/g DW in spotted seatrout (Mortuza et al., 2025). These body-burdens are 2–3x lower than their counterparts in Galveston Bay (as reported in this study). The PAH concentrations in fish livers from Galveston Bay (red drum: 3,995.90 ± 182.84 ng/g DW; seatrout: 1,651.56 ± 76.38 ng/g DW) were broadly comparable to those from Matagorda Bay (red drum: 2,817.79 ± 1,200.68 ng/g DW; seatrout: 2,812.69 ± 1,683.88 ng/g DW). In Sabine Lake, liver PAH concentrations reported in 2020 ranged from 500 ng/g in gafftopsail catfish to 1,800 ng/g in gar ( Atractosteus spatula ) (Hernout et al., 2020), again aligning with the elevated hepatic burdens observed in Galveston. The analysis of PAHs in sharks from the northwestern Gulf of Mexico showed muscle PAHs concentrations to be 1,080–1,330 ng/g WW and liver concentrations up to 2,200 ng/g WW (2x higher than muscle) (Cullen et al., 2019). Similarly, the PAHs body-burdens in oysters from Galveston Bay range from 203–608.51 ng/g (Rowe et al., 2020) which is similar to 230.50 ± 7.87 ng/g DW collected from Matagorda Bay in 2021(Mortuza et al., 2025), reinforcing that Galveston Bay values, fall well within the regional scale of accumulation. Compared with levels globally, the PAHs levels in Galveston Bay surface waters are moderately high. For example, the PAHs surface water levels reported by Bacosa et al. (2020) in Galveston Bay (18.95–167.35 ng/L), are within range of levels observed various U.S. coastal systems, such as Chesapeake Bay (Virginia) (20–65.7 ng/L) (Gustafson & Dickhut, 1997), Murrells Inlet (South Carolina) (7–79 ng/L) (Ngabe et al., 2000), and North Inlet (South Carolina) ( ≤ 63 ng/L) (Ngabe et al., 2000). And is also within range of values measured elsewhere, such as in Chabahar Bay (Oman) ( ≤ 60 ng/L) (Agah et al., 2017), and the Gulf of Gabes (Tunisia) (3.53–53.73 ng/L) (Fourati et al., 2018). However, the PAH levels reported in Galveston Bay are orders of magnitude lower than those reported in heavily industrialized Asian regions such as the Jiulong River Estuary (Fujian Province, China) (6,960 − 26,920 ng/L) (Maskaoui et al., 2002), and in Daya Bay (Guangdong Province, China) (4,228 − 29,325 ng/L) (Zhou & Maskaoui, 2003). Taken together, this distinct elevation in Galveston Bay concentrations relative to other U.S. locations highlights the influence of regional urbanization and industrial activities along the Houston Ship Channel and surrounding watershed, though still falling short of the higher PAH burdens documented in some Asian coastal industrial zones. 4.4. PCBs body-burdens in biota from Galveston Bay as determined in this study PCBs body-burdens in the gill/mantle tissue of oysters (286.56 ± 5.65 ng/g DW) was ~ 1.4x – 19x higher than the levels measured in fish muscle (Fig. 2 (b) , Table 1 (b) ). However, the levels of PCBs were the highest in fish livers, exhibiting concentrations ~6x − 42x higher than in muscle (Fig. 2 (b) , Table 2 (b) ). Such higher accumulation in the liver is a likely reflection of the lipophilicity of PCBs (Log Kow = 4.43–5.02) (Safe & Hutzinger, 1984; Ballschmiter et al., 2005; Bourez et al., 2013), and the over 4x − 12x higher lipid content of livers relative to muscle for the fish analyzed in this study (Ando et al., 1993; Arrington et al., 2006). Analogous trends have been reported in the Gulf of Mexico, where Blacktip, and Bonnethead sharks were shown to have double the hepatic PCB body-burdens compared to muscle (Cullen et al., 2019). Similarly, fish (gafftopsail catfish, red drum, spotted seatrout) collected from Matagorda Bay were shown to have 11x − 15x higher concentrations of PCBs in livers in comparison to muscle (Mortuza et al., 2025), demonstrating the propensity of lipophilic PCBs in accumulating in lipid rich liver. PCBs are entirely anthropogenic in origin (Delzell et al., 1994), and although banned in the 1970s, they persist in the environment and are classified as persistent pollutants (Boyle & Highland, 1979). Dioxin-like PCBs (DL-PCBs) have chlorine atoms at the para (opposite sides of the benzene ring) position and two or more at meta (one carbon away from the para) positions, and thus share toxic coplanar (flat, planar) structures with 2,3,7,8-tetrachlorodibenzo-p-dioxin (Safe et al., 1985). There were twelve such structural PCB congeners monitored in our study (ATSDR, 2023), and included non-ortho (no adjacent chlorine) PCBs 77, 81, 126, and 169; and mono-ortho (one adjacent chlorine) PCBs 105, 114, 118, 123, 156, 167, and 189 (Giesy & Kannan, 1998). A higher chlorination of the biphenyl rings of PCBs tend to correspond with lower environmental degradation and increased persistence (Delzell et al., 1994). The PCBs profiles of liver samples in fish from Galveston Bay biota (Table 2 (b), Supplemental Fig. 2 (b) ) showed the DL-PCB, PCB 126, to be the most prominent congener in catfish (50% sum of total PCBs), red drum (38% sum of total PCBs) and seatrout ( ≤ 25% sum of total PCBs). The prevalence of PCB 126 in Galveston Bay could be of concern due to its dioxin-like structure and thus its toxicity. PCBs are lipophilic and tend to bioaccumulate in organisms (Hawker & Connell, 1988; Beyer & Biziuk, 2009), leading to biomagnification through the food chain (Walters et al., 2011). This poses toxicity risks to aquatic species and can expose humans to dioxin-like compounds via seafood (Perelló et al., 2015). PCBs have contributed to population declines in bald eagles ( Haliaeetus leucocephalus ) due to contaminated finfish consumption causing thinning of eggshells (Bowerman et al., 1995). And are also linked to reduced cetacean populations (endocrine disruption) (Hall et al., 2018). In humans, they’re associated with endocrine disruption, including immunological, metabolic, and neurological disorders through seafood consumption with higher levels in historically contaminated areas (Birnbaum, 1994; Crinnion, 2011). Among the NDL-PCBs congeners, PCB 52 was prominent in red drum muscle ( ≤ 75% sum of total PCBs) and in seatrout ( ≤ 30% sum of total PCBs) (Table 1 (b), Supplemental Fig. 2 (a) ). PCB 128 was prominent in oysters ( ≤ 50% sum of total) and in seatrout ( ≤ 25% sum of total). In catfish from Galveston Bay, there were high proportions of PCB 138 and 153 ( ≤ 20% sum of total PCBs). Lastly, a prominent signature of PCB 128 in seatrout liver ( ≤ 25% sum of total) was also detected. Anaerobic microbial degradation of highly chlorinated PCBs remove chlorine atoms from the meta and para positions, producing lower-chlorinated ortho-substituted congeners like PCBs 18, 52, and 128 (Tiedje et al., 1993; Abramowicz, 1995). Their presence in samples may reflect the prominence of such microbial processes. Similarly, PCBs 128 and 153 were found to be prominent in the muscle tissue of juvenile sharks sampled from the northwestern Gulf of Mexico (Cullen et al., 2019). While in fish sampled from Sabine Lake (TX/LA border), PCB 18 was found to be the most prominent congener in muscle tissue (Hernout et al., 2020). Persistent DL and NDL-PCB contamination may be driven by legacy industrial activity and sediment resuspension facilitated by tidal forces, shipping, and dredging (Yeager et al., 2007). 4.5. Historic PCB levels in Galveston Bay The historical record of PCBs in Galveston Bay reveals persistent contamination and bioaccumulation. Despite a ban on PCBs production in the U.S. in 1979 (Safe et al., 1985), and the natural flushing (tidal exchange, freshwater inflow) of the bay system (Rayson et al., 2016), there has been no significant long-term decrease in PCBs levels in sediment. Early measurements from the 1960s reveal sediment levels to range from ~ 10–100 ng/g in the bay (Presley et al., 1998; Mahler & Van Metre, 2003) (Fig. 3 (b), Supplemental Table 3 ). These levels have remained relatively consistent through the 1980s and 1990s, with values ranging from ~ 5–100 ng/g (Jackson et al., 1998; Santschi et al., 2001). And more recently, sediment concentrations have remained ~ < 100 ng/g sediment (Mahler & Van Metre, 2003; Rifai & Palachek, 2007; Lakshmanan et al., 2010). The overall lack of a significant decline in PCBs indicates their stable sequestration into sediments (Lake et al., 1990; Lang et al., 2018). For legacy pollutants like PCBs, this could imply that historically contaminated sediments acts as a long-term reservoir, potentially making them chronically bioavailable due to intermittent reconstitution (i.e., by storms, dredging, etc.) (Horzempa & Di Toro, 1983; Yeager et al., 2007; Lang et al., 2018). A major historical contributor of PCBs into the bay was the Champion Paper Mill, which in the 1960s disposed of PCB laden paper sludge in unlined pits along the San Jacinto River (Iyer et al., 2016; Govindarajan et al., 2023). These disposal sites are designated as Superfund sites and are of continuous cause for concern due to the persistent release of PCBs, dioxins, and furans into the bay through leaching and mobilization of pollutants through sediment disturbance and hydrological processes (Tucker, 2012; Iyer et al., 2016). Industrial runoff from facilities along the Houston Ship Channel and adjoining waterways further exacerbates this contamination, as do inflows from rivers such as the San Jacinto and Trinity, which carry sediments and pollutants into the bay (Rifai & Palachek, 2007). Regular dredging operations within the ship channel and intense maritime traffic also resuspend PCB contaminated sediments, facilitating their redistribution into the water column and uptake by biota (Yeager et al., 2010; Howell, 2012). This may explain why, in part, values have not declined in the biota despite the ban on these materials over more than 40 years. In contrast to sediments, the reported water concentrations are 4 orders of magnitude lower than those measured in the sediment, and 5–6 orders lower than biota PCB burdens (oyster, fish muscle and liver) (Fig. 3 (b) ). This vast difference, underscores the potent lipophilic nature of these compounds and their propensity to partition out of the water and accumulate in organic-rich matrices (Porte & Albaigés, 1994; Borgå et al., 2005; Walters et al., 2011). From 2002 to 2015, reported concentrations in surface water remain within a range spanning from ~ 1–30 ng/L ( Supplemental Table 3) , with no clear change in overall trends. For example, the survey of surface waters from 2002–2003, measured levels ranging from ~ 1–13 ng/L (Rifai & Palachek, 2007; Howell et al., 2008). In subsequent years (i.e., 2005–2009), the overall PCBs levels in surface waters range from 1–30 ng/L (Lakshmanan et al., 2010; Howell et al., 2011; Balasubramani et al., 2014). A more recent survey in 2015, indicated surface water levels to remain within the same order of magnitude at 1.60 ± 0.28 ng/L (Howell & Rifai, 2015). These data reinforce the observation that, despite spatial variability, PCB concentrations in surface waters have remained low and relatively stable over time in comparison to sediment and biota. In fish muscle, studies quantifying PCBs body-burdens (from 1989–2013), report levels to range from 14.90–6,384.00 ng/g DW. For example, in tidewater silverside (1,040 ± 76 ng/g DW) and sheepshead minnow (2,160 ± 306 ng/g DW) from 1989 (King, 1989), alongside similarly elevated concentrations in Gulf killifish (1,800 ± 240 ng/g DW), Gulf menhaden (880 ± 144 ng/g DW), and striped mullet (280 ± 40 ng/g DW) from the same study. Data from 2002–2003 show 327.20 ng/g DW and 416.80 ng/g DW in estuarine fish (Rifai & Palachek, 2007), while catfish sampled in 2003 exhibited a striking range of 16.52–6,384 ng/g DW (Howell et al., 2008). Subsequent studies from 2008 reported 548 ± 432 ng/g DW in catfish and 1,140 ± 1212 ng/g DW in seatrout and Atlantic croaker (Lakshmanan et al., 2010), followed by concentration levels of 408 ± 264 ng/g DW in gafftopsail catfish, 84 ± 44 ng/g DW in red drum, and 208 ± 132 ng/g DW in spotted seatrout from 2011 (Worth, 2013). Most recently, this study found 209.29 ± 2.28 ng/g DW in gafftopsail catfish, 14.90 ± 0.28 ng/g DW in red drum, and 188.69 ± 3.48 ng/g DW in spotted seatrout collected in 2019, further reinforcing the consistent elevation of PCB concentrations in fish muscle relative to environmental matrices. These levels are substantially higher than any recorded sediment concentrations, indicating biomagnification (Porte & Albaigés, 1994; Borgå et al., 2005). This process is further evidenced in the liver, which generally concentrates PCBs to even higher levels. For instance, the median concentration of PCBs in fish liver across various species from literature (Fig. 3 (b), Supplemental Table 3 ) was found to be 6x higher than fish muscle (significantly different). Specifically in Galveston Bay fish data from this study alone, liver PCBs concentrations were approximately 7x higher in gafftopsail catfish, 42x higher in red drum, and 11x higher in spotted seatrout compared to muscle tissue. Similarly, in previously published PCBs body burdens data from Matagorda Bay, liver concentrations exceeded muscle by roughly 15x in gafftopsail catfish, 13x in red drum, and 11x in spotted seatrout (Mortuza et al., 2025). Previously reported PCBs concentrations in sharks from the northern Gulf of Mexico show a similar disparity in liver vs muscle, with levels 13x higher in the livers of bull sharks vs. muscle, 5x higher in blacktip sharks, and 4x higher in bonnethead sharks (Cullen et al., 2019). Therefore the review of these datasets demonstrates the overall greater accumulation of PCBs into aquatic biota vs. environmental matrices (such as surface waters and sediments) (Monod & Vindimian, 1991; Barber et al., 2006; Topić Popović et al., 2023). Furthermore, our data shows oysters to be effective indicators of PCBs and PAHs exposures. As filter feeders, they continuously process water and suspended particles, integrating contaminant exposure over time (Fisher et al., 2000; Bustamante et al., 2012; Wontor et al., 2023). Our analysis of historical data (1992–2019) shows oysters body-burdens to range from 77–1,100 ng/g DW (286.56 ± 5.65 ng/g DW reported in this study) (Sericano et al., 1992; Sericano et al., 1994). Moreover, these values are comparable to those reported in the wider Gulf of Mexico (62–79 ng/g DW) and in an adjacent bay, Matagorda Bay (290.29 ± 4.49 ng/g DW) (Sericano et al., 1990; Mortuza et al., 2025). This indicates that Galveston Bay reflects a broader regional trend in PCBs exposure among filter-feeding bivalves. These concentrations are higher than those in sediment (11x) and water (fiver order of magnitude), highlighting their role in accumulating PCBs from their environment and making them a valuable sentinel species for monitoring the bioavailability of persistent organic pollutants in the Galveston Bay ecosystem (Sericano et al., 1990; Sericano et al., 1992; Jackson et al., 1998). Galveston Bay exhibits similar PCB concentrations in sediment among Gulf of Mexico coastal sites, with a reported value of 1.10 ng/g (Giam & Chan, 1978), on par with Nueces Estuary (1.50 ng/g) (Giam & Chan, 1978). Apalachicola Bay (FL) (3 ng/g) (Livingston et al., 1978), and Apalachicola River (1 ng/g) (Elder & Mattraw Jr, 1984). This is notably lower than the Mississippi Delta (LA), which shows a an elevated concentration of 18.70 ng/g of PCB in sediment, over 17 times higher, suggesting a legacy of industrial discharge or riverine input from the Mississippi River system (Giam & Chan, 1978; Presley et al., 1998; Santschi et al., 2001). These differences may reflect variations in watershed industrialization, hydrodynamics, and sedimentation rates (Du et al., 2019). On a global context, the PCBs concentrations in Galveston Bay position it as a moderate-to-heavily impacted site. Water concentrations of PCBs range from 0.12 to 2.61 ng/L, while sediment concentrations span 0.47 to 1418 ng/g (Howell et al., 2008). These values place Galveston Bay among many U.S. coastal systems in terms PCB contamination in surface water, including San Diego Bay (0.024–0.419 ng/L) (Zeng et al., 2002), Baltimore Harbor (0.10–1.52 ng/L) (Bamford et al., 2002), Palos Verdes Peninsula (0.06–1.14 ng/L) (Zeng et al., 1999), and Lake Michigan (0.34–1.74 ng/L) (Pearson et al., 1996), indicating its similar industrial legacy. However, water concentrations in Galveston Bay are lower than those reported in more legacy and current industrial sites such as New York Harbor (6.70–9.40 ng/L) (Totten et al., 2001) and the Delaware River (1.20–6.50 ng/L) (Rowe et al., 2007). A similar story is portrayed in Galveston Bay sediment burdens of PCB (up to 1418 ng/g) (Howell et al., 2008) which is much higher than the reported sediment burdens in Bahrain coastal region (0.18–7.41 ng/g) (De Mora et al., 2005), Salton Sea Lake (116–304 ng/g) (Sapozhnikova et al., 2004) and Rio de la Plata estuary, Argentina (0.04–98.50 ng/g) (Colombo et al., 2005), Busan Bay, Korea (5.71–199 ng/g) (Hong et al., 2005), and Singapore’s southwestern coast (1.40–329.60 ng/g) (Wurl & Obbard, 2005), reinforcing its status as a high-contamination zone. However, Galveston bay remains below the higher sediment burdens documented in Chesapeake Bay (8–2150 ng/g) (Ashley & Baker, 1999) and Narragansett Bay (20.80–1760 ng/g) (Hartmann et al., 2004) and Venice Lagoon, Italy (2–2049 ng/g) (Frignani et al., 2001), where legacy industrial inputs and hydrodynamic trapping may have driven persistent contamination, underscoring Galveston Bay as a moderate to heavily impacted site in terms of PCB contamination. 4.6. NMPs body-burdens in biota from Galveston Bay as determined in this study This study is the first to use Py-GCMS/MS to quantify NMPs in fish from Galveston Bay. Previously, oysters showed significantly higher NMPs body-burdens (11,988.55 ± 6,392.18 µg/g DW) than catfish (283.74 ± 150.56 µg/g DW) and red drum (43.16 ± 9.30 µg/g DW) muscle (Fig. 2 (c) , Table 1 (c) ). This elevated accumulation in oysters likely reflects their filter-feeding nature, accumulating higher level of pollutants over time (Ehrich & Harris, 2015; NOAA, 2020). Ribeiro et al. (2021) quantified NMPs body-burdens in oysters ( Saccostrea glomerata ) of up to 39,000 µg/g, which is ~3x higher than those reported in our study for oysters from Galveston Bay. In comparison to fish muscle, MPs body-burdens were markedly greater in fish livers, at ~ 29x higher in catfish (vs. catfish muscle) and ~ 53x higher in red drum (vs. red drum muscle). The higher levels of NMPs in livers is a likely reflection of the liver’s dense vascularization and its central role in removing xenobiotics from the body (Wisse et al., 1985; Wood, 2014; Zhao et al., 2014; Ozougwu, 2017). Controlled laboratory studies show a preferential bioaccumulation of NMPs in the hepatic tissue of fish vs. other tissues. For example, early juvenile European seabass ( Dicentrarchus labrax ) exposed to a mixture of environmental microplastics sized 0.45–3 µm for 3 to 5 days exhibited size-dependent accumulation, with liver concentrations approximately 4x higher than those in the gut and 3x higher than in the gills. While goldfish ( Carassius auratus ) exposed to 44 nm polystyrene nanoplastics at 100 µg/L for 30 days, accumulated ~ 14x higher concentration in the liver than in muscle (Brandts et al., 2022), underscoring the higher bioaccumulation of NMPs in the liver. 4.7. NMP profiles and average human daily intake Among the various types of plastics quantified, Nylon-66 (N66) emerged as one of the most prevalent polymers in muscle (32–55% of total NMP) and liver (37–39% of total NMP) from fish (Table 1 (c), Supplemental Fig. 3 (a) ). Known for its durability and resistance to abrasion, N66 is primarily used in textiles such as carpets, clothing, and upholstery as well as ropes, cords, fishing nets, and toothbrush bristles (Stafford et al., 1986; Zhang et al., 2010; Shakiba et al., 2021). Recreational and commercial fishing in the area as well as laundry wastewater can be major contributors to N66 pollution in the bay (Saturno, 2020; Vassilenko et al., 2021; Le et al., 2022). Polyamide (PA) also exhibited a prominent abundance in red drum (89% of total NMPs) and seatrout (20% of total NMPs) muscle. Known for its strength, flexibility, and resistance to heat and chemicals, PA is widely used in consumer goods such as kitchen utensils, sportswear, and luggage, as well as in industrial applications including automotive components, electrical connectors, and machine parts (Wesołowski & Płachta, 2016; Kondo et al., 2022; Kohutiar et al., 2025). Polyethylene (PE) comprised ~ 13% of the total detected NMPs in oysters and 19% in seatrout muscle ( Supplemental Fig. 3 (a) ). Due to its flexibility, PE is extensively utilized in packaging materials, plastic bags, pellets (nurdles), plastic wraps, bottles, and containers as well as in medical items, pipes, and fittings (Duffy Jr, 1949; Savas et al., 2016; Ronca, 2017). Polypropylene (PP) represented 31% of total NMPs identified in oysters and 6% of NMPs in seatrout muscle from Galveston Bay. Widely adopted in packaging (e.g., bottles, tubs), automotive parts (bumpers, battery housings), and textile-based goods (diapers, filtration fabrics), it is also common in household items like furniture and reusable containers (Guidetti et al., 1996; Maddah, 2016; Hossain et al., 2024). The recurring detection of PE and PP in aquatic organisms agrees with findings from Ribeiro et al. (2020) in Australia, where PE was the most abundant NMP (< 2,400 µg/g WW tissue), and PP was also detected at lower concentrations (< 60 µg/g WW tissue). Additionally, Lim et al. (2022) reported that globally, fibrous microplastics dominate in the food ingested by fish (70% of all plastics), with PE accounting for a significant fraction (16% of the total fiber). Unsurprisingly, consumer single use plastics such as PE and PP are prominently featured due to their use and abundance, especially in urban areas (McDermott, 2016). Lastly, Styrene-Butadiene Rubber (SBR) was also prominently detected in oysters (17% of total NMPs) as well as in catfish livers (56% of total NMPs) and red drum livers (43% of total NMPs). SBR is a synthetic polymer prized for its abrasion resistance and flexibility, and is thus most commonly used in automobile tires, which account for a major share of its global use (Henderson, 1987; Dhanorkar et al., 2021). It is also widely used in shoe soles, conveyor belts, seals, and gaskets (Henderson, 1987; Miller et al., 1994). Tire wear from the Houston urban sprawl and its accompanying traffic are likely contributors of SBR into Galveston Bay (Wik & Dave, 2009; Li et al., 2023; Nelson, 2024). Together, our analysis indicates widespread plastic pollution and exposure of biota from Galveston Bay. Table 4 Estimated Average Daily Intake (ADI) of NMPs in adults (mg NMPs/Kg of body weight/day), reported by species with corresponding minimum and maximum intake values. Each ADI estimate was further converted to an annual intake to characterize likely yearly NMP exposure. Oysters ADI (min - max) (mg NMPs/Kg body weight/day) Yearly Intake (min - max) (mg NMPs/Kg body weight/year) 0.85 (0.01–4.80) 309.98 (4.45–1752.60) Catfish 0.03 (0–0.12) 9.64 (0–42.58) Red drum 0 (0–0.01) 1.47 (0–2.69) Seatrout 1.22 (0–4.83) 443.90 (0.01–1763.93) Finally, the Average Daily Intakes (ADIs) of NMPs in humans through seafood consumption was estimated to be 443.90 mg NMPs/kg adult human body weight/year from seatrout, 309.98 mg NMPs/kg adult human body weight/year from oysters, and 1.47 mg NMPs/kg adult human body weight/year from the consumption of red drum muscle (Table 4 ). This amounts to the consumption of 0.103 g of plastics from the consumption of red drums and 21 and 31 g of plastics from the consumption of oyster and seatrout per year, respectively. For reference, an average plastic credit card weighs 6g. These consumption values are comparatively modest next to prior estimates suggesting humans ingest up to < 5 g of microplastics weekly (or < 260 g annually) (Senathirajah et al., 2021). However, our findings are consistent with those reported by Ribeiro et al. (2021), who report the concentration of seafood collected from Brisbane River estuary in Australia. Using Py-GCMS, they quantified 100 µg/g of plastics in oysters and 2,850 µg/g in sardines. Applying a similar ADI calculation, this yields a projected yearly intake of 1.1 to 31.2 g of plastic a year from oyster and sardine respectively, which is comparable to our estimates for Galveston Bay. In humans, Py-GCMS was used to detect NMPs at 1.60 ± 0.49 µg/mL in blood (Leslie et al., 2022) and 3–36 µg/g in human feces (Zhang et al., 2021). In human brain’s frontal cortex, microplastic concentrations ranging from 3,345–4,917 µg/g WW have been detected (Nihart et al., 2025), indicative of higher bioaccumulation in the brain in comparison to blood and feces. Human brain NMP concentration exceeded that in oyster tissue and seatrout muscle by ~ 1.7× (Nihart et al., 2025), which could be indicative of biomagnification, although further evidence is required. While we can estimate the ADI of plastics from seafood, the toxicological effects of NMPs are still an ongoing area of inquiry. A meta-analysis by Liu et al. (2023) explored the toxic effects of plastics on biological endpoints in rodent models. Out of 1,762 biological endpoints reviewed, 53% showed the disruption on lipid metabolism, oxidative stress, reproduction, and glucose metabolism. The ADI calculated for the consumption of oysters and fish in our study (i.e., 0.28 mg/day – 84 mg/day) could be compared to doses tested in multiple murine models reported in the literature. For example, male adult mice exposed to fluorescent and pristine polystyrene microplastics (PS MPs, 5 µm and 20 µm) at 0.01–0.50 mg/day for up to 28 days exhibited hepatic and renal accumulation, disturbances in energy and lipid metabolism, oxidative stress, and reduced acetylcholinesterase activity (Deng et al., 2017). Similarly, male C57BL/6J mice receiving 0.5 mg/day of 0.5 µm PS MPs for four weeks showed pronounced immune modulation, with up‑regulation of pro‑inflammatory cytokines and down‑regulation of anti‑inflammatory mediators via NF‑κB pathway activation (Zhao et al., 2021). Adverse reproductive effects have also been reported at comparable daily intakes. For example, male and female C57BL/6 mice exposed to pristine PS MPs (5.0–5.9 µm) at 0.1 mg/day for 30–44 days accumulated particles in gonads, with reduced ovary size, follicle number, altered reproductive hormones, and decreased pregnancy rates (Wei et al., 2022). Female mice gavage fed with MPs (0.79 µm) at 30 mg/kg/day for 35 days, corresponding to a per‑animal daily mass within our range, and showed multi‑organ accumulation, oxidative stress in oocytes, and reproductive toxicity (Liu et al., 2022). Comparable doses have also elicited gastrointestinal and hepatic effects. In C57BL/6 male mice fed polyethylene (PE) MPs (10–150 µm) at 2–200 µg/g feed for five weeks developed gut microbiota dysbiosis, intestinal inflammation, and altered T‑cell subsets (Li et al., 2020). Male mice exposed to PE MPs (100 nm) at 600 µg/day for 15 days exhibited altered liver function parameters (Abdel-Zaher et al., 2023), while ingestion of PE microbeads (36 µm and 116 µm) at 100 µg/g feed for 6–9 weeks exacerbated hepatic fibrogenesis (Djouina et al., 2023). Taken together, these studies demonstrate that daily microplastic intakes in the hundreds of micrograms to low‑milligram range are sufficient to induce measurable biological effects in mice across multiple organ systems. 4.8. Historic NMPs levels in Galveston Bay Given the relatively recent concern and awareness for NMPs pollution in the aquatic environment (Burns & Boxall, 2018; Garcia-Vazquez & Garcia-Ael, 2021), there is an overall paucity of environmental data in Galveston Bay from before 2019. What little exists is count based microplastic data that is not comparable to our analytical concentration-based approach using Py-GCMS/MS. Therefore, our analysis of NMPs trends commences from 2019 and onwards to compare different environmental matrices such as water, sediment, fish muscle, fish liver, and oysters (Fig. 3 (c) , Supplemental Table 4 ). The concentrations of NMPs in surface waters was found to be the lowest, ranging from 0.82–19.8 µg/L (Gahn et al., 2025). In contrast, recent sediment core samples from Galveston Bay reveal NMPs concentrations to be two orders of magnitude higher than in the surface waters. Data from 2021–2024 showed a range of concentration from 0.01 to 8.76 µg/g (Summers et al., 2024). Sediments are the ultimate sink for NMPs as they can sequester into sediments (from water) with marine snow (particles falling from the upper ocean to the deep sea) (Wu et al., 2025), and become incorporated into the sediment (Sun et al., 2021; Martin et al., 2022). As a result, sediments may serve as a long-term reservoir or "sink” for plastics (Martin et al., 2020; Martin et al., 2022). Plastics have been reported to form geological formations recently named, “plastiglomerate” or “plastistone” (plastic and pre-existing rock/ sand lithified together), which have been discovered globally (De-la-Torre et al., 2022; Rakib et al., 2023; Wang & Hou, 2023). This new geological formation has been proposed to mark the beginning of a new era, the “Plasticene” (Rangel-Buitrago et al., 2022). The deposition of NMPs via marine snow may also make them more bioavailable to marine bivalves (Porter et al., 2018). Similarly, fish have also been reported to accumulate NMPs (Ribeiro et al., 2020; Ribeiro et al., 2021; Mortuza et al., 2025). Together, ocean biota may bioaccumulate NMPs over their lifetime, providing a long-term mechanism for accumulation. The quantification of NMPs in fish muscle has revealed concentrations that are six orders of magnitude higher than those measured in surface waters and three orders of magnitude higher than sediments (Fig. 3 (c) , Supplemental Table 4 ). This trend is evident across multiple species in Galveston Bay. Fish muscle body-burdens of NMPs varied widely across species, ranging from a minimum of ~ 640 µg/g dry weight (DW) in juvenile trout to a maximum of 2,410.20 µg/g DW in clupeids (e.g., menhaden, shads), with mullet showing intermediate levels of up to 1,732.92 µg/g DW (our unpublished data). While more recent data from 2021 revealed striking interspecies differences: red drum exhibited the lowest concentrations (43.16 ± 9.30 µg/g DW), whereas spotted seatrout showed significantly higher bioaccumulation (13,063.30 ± 6,225.16 µg/g DW) of NMPs. Similar trends were observed in Matagorda Bay (an adjacent estuary to Galveston Bay), where gafftopsail catfish and spotted seatrout had elevated levels (1,636.97 ± 786.63 and 966.71 ± 206.69 µg/g DW, respectively), contrasting with lower concentrations in red drum (355.42 ± 183.75 µg/g DW) (Mortuza et al., 2025). These findings suggest species-specific uptake and retention mechanisms, potentially influenced by trophic level, feeding behavior, and habitat use (Wootton et al., 2021; da Costa et al., 2023). The accumulation within fish is even more pronounced in the liver, demonstrating a progressive accumulation from the environment into muscle tissue and subsequent sequestration and concentration in the liver (possibly due to dense vascularization) (Wisse et al., 1985; Wood, 2014; Ozougwu, 2017). In Galveston Bay, gafftopsail catfish and red drum exhibited liver concentrations approximately 28x and 53x higher than their respective muscle tissue (this study). In Matagorda Bay, red drum showed a similar pattern with liver levels about 51x higher than muscle and 7x higher in spotted seatrout (Mortuza et al., 2025). These differences highlight increased bioaccumulation in the liver. Oysters, as sessile filter-feeders, exhibit greater bioaccumulation of NMPs compared to fish muscle (13x lower), sediment (four orders of magnitude lower) and water (seven orders of magnitude lower), which could be explained by their filter feeding strategy (Ribeiro et al., 2019; NOAA, 2020). While oyster have been documented to ingest particles preferentially (Newell & Jordan, 1983; Shumway et al., 1985), smaller polystyrene microplastic beads (6–45 µm) have been demonstrated to be taken up by oysters, with 88 − 68% ingestion from the water (Dunphy et al., 2006; Ward et al., 2019). In Galveston Bay, oyster tissue body burden of NMPs were found to be 11,988.55 ± 6392.18 µg/g DW (this study), while those from Matagorda Bay measured slightly lower at 8,925.72 ± 2608.77 µg/g DW (Mortuza et al., 2025). These levels were significantly higher than those measured in the muscle tissues of fish from each respective bay. Together, these findings highlight oysters’ chronic exposure to NMP from water and sediment as sources due to their sessile filter feeding nature. This makes oysters effective bioindicators, as their tissues provide a long-term measure of NMP bioavailability from the environment (Bendell et al., 2020; Savoca et al., 2024). At present, we are unable to compare the analytical concentrations quantified using Py-GCMS/MS with other studies that rely on microscopy to count microplastics particles in environmental matrices (i.e., as particles/m² or particles/kg). Previous studies have reported an average of 61.08 ± 34.61 particles m⁻² of plastic in sediments along the Gulf of Mexico, based on samples collected from the Port of Florida to Alligator Point, FL (Beckwith & Fuentes, 2018). Along the Mexican coastline of the Gulf, reported abundances ranged from 31.70 to 545.80 particles/m² (Alvarez-Zeferino et al., 2020). Substantially higher concentrations of 696–1,392 particles/m² have been reported in sediments sampled from Campeche Bay, southern GOM (Ramirez et al., 2019). In terms of particles per mass sediment, concentrations of < 60 to 300 particles/kg have been reported in sediments along the Gulf of Mexico (Yu et al., 2018). The Tecolutla estuary on Veracruz coast of Mexico has reported levels of 121 ± 115 particles/kg (Sánchez-Hernández et al., 2021), and southern Gulf sites typically exhibit 1.30–95.20 particles/kg (Osten et al., 2023). These values illustrate that US GOM concentrations fall within the regional scale of accumulation of plastics. On a global scale, the plastic abundance in GOM sediments can be classified as moderate. Overall, an average of 61.08 ± 34.61 particles/m² have been reported across GOM sediments (Beckwith & Fuentes, 2018). Globally, GOM concentrations fall below the accumulations documented in high-impact regions such as Hawaii (1,327–45,554 particles/m²) (McDermid & McMullen, 2004), the Great Lakes (North American) (43,157 ± 115,519 particles/m²) (Eriksen et al., 2013), and South Korea’s high-tidal coastal zones (56–285,673 particles/m²) (Kim et al., 2015). Particles per mass-based comparisons of plastic concentration further reinforce this pattern. Sediment concentrations of plastics in the southern U.S. coast of the GOM range from < 60 to 300 particles/kg (Yu et al., 2018), which are in range with values from the Gulf of Mannar (India) (1–89 particles/kg) (Vidyasakar et al., 2018), and Melbourne (Port Phillip Bay, Australia) (4.50–172.70 particles/kg) (Su et al., 2020). These values are also comparable to those reported in the United Arab Emirates (91.70–233.30 particles/kg) (Al Hammadi et al., 2022) and Xiamen, China (76–333 particles/kg) (Tang et al., 2018), but remain well below those documented in heavily industrialized coastal areas such as Maowei Sea, China (520–940 particles/kg) (Li et al., 2019) and Laizhou Bay (56.60–855.40 particles/kg) (Sun et al., 2021). These regional differences likely reflect varying extents of urbanization and industrial activities, with overall levels along the GOM and falling below those documented in some Asian coastal industrial zones. 5. Conclusions This study provides a current and historic assessment of body burdens for both legacy (PAHs, PCBs) and emerging (NMPs) pollutants in shellfish and fish collected from Galveston Bay (TX). Oysters consistently exhibited elevated levels of PAHs, PCBs and NMPs relative to fish muscle, likely due to their filter-feeding activity. Within fish tissues, contaminant concentrations were markedly higher in liver than muscle, this is likely due to the greater lipid content of the liver (promoting PAHs and PCBs bioaccumulation) and dense vascularization (likely promoting NMPs bioaccumulation). PAH congener profiles indicate inputs from both petrogenic and pyrogenic sources in Galveston Bay, reflecting the urban and industrial petrochemical activities in the region. PCB congener analysis revealed a predominance of dioxin-like compounds, particularly PCB-126 in fish tissue. For the NMPs polymers, N66, PA, PE, PP, and SBR were the most frequently detected across the sampled biota, also reflecting the urban and industrial activities in Galveston Bay and the Houston metro area. When integrated with historic datasets, PAHs and PCBs show no discernible decline from historic levels, highlighting the importance of ongoing monitoring efforts. In contrast, historical baselines for NMPs are sparse, complicating efforts to assess trends. Thus, future monitoring should also prioritize NMPs along with legacy persistent pollutants (PAHs, PCBs) to inform risk assessment and mitigation strategies. Declarations Acknowledgements The authors thank the Matagorda Bay Mitigation Trust (Grant #013) for supporting this research, awarded to David Hala, Karl Kaiser, Robert J. David Wells, Antonietta Quigg, and Lene H. Petersen. Additional support was provided by the Texas Comptroller of Public Accounts (Grant #CMD 19‑6799CS to Robert J. David Wells) and the U.S. Army Corps of Engineers (Grant #ERDC BAA 21‑0045A to Karl Kaiser). We also acknowledge the field and laboratory assistance provided by team members and students who contributed to sample processing and data organization. Funding This work was supported by the Matagorda Bay Mitigation Trust (Grant #013), the Texas Comptroller of Public Accounts (Grant #CMD 19‑6799CS), and the U.S. Army Corps of Engineers (Grant #ERDC BAA 21‑0045A). Authors’ Contributions Asif Mortuza : Investigation, methodology, data analysis, software, writing—original draft, writing—review and editing. Michael Bryan Gahn : Methodology, data analysis, software, writing—review and editing. Marcus Wharton : Methodology, software. Robert J. David Wells : Resources, funding acquisition, supervision, writing—review and editing. Lene H. Petersen : Conceptualization, resources, funding acquisition, supervision. Antonietta Quigg : Supervision, resources, funding acquisition, writing—review and editing. Karl Kaiser : Methodology, software, resources, supervision, funding acquisition, writing—review and editing. David Hala : Supervision, funding acquisition, conceptualization, methodology, software, data analysis, writing—original draft, writing—review and editing. Ethical Approval Ethical approval was not required for this study. All fish and oyster samples were collected from Galveston Bay in accordance with Texas Parks and Wildlife (TPWD) regulations using a valid fishing license. No live vertebrates were subjected to laboratory experimentation. Consent to Participate All authors provided consent to participate in the research and preparation of this manuscript. Consent to Publish All authors provided consent for publication of this manuscript. Competing Interests The authors declare that they have no competing interests. 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Distribution of polycyclic aromatic hydrocarbon (PAH) residues in several tissues of edible fishes from the largest freshwater lake in China, Poyang Lake, and associated human health risk assessment. Ecotoxicol Environ Saf, 104 , 323–331. https://doi.org/10.1016/j.ecoenv.2014.01.037 Zhou, J., & Maskaoui, K. (2003). Distribution of polycyclic aromatic hydrocarbons in water and surface sediments from Daya Bay, China. Environmental Pollution, 121 (2), 269–281. Additional Declarations No competing interests reported. Supplementary Files SupplementalGalvestonbiota.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9509872","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":633255466,"identity":"6c312662-fb83-450b-880b-5f14cba2ba79","order_by":0,"name":"Asif Mortuza","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYNACAxs5KIuZKPWMDQwVacY8JGo5czixh2gtuu29zx/8bGNO389+Ok2CocI6sYGQFrMzxw0be9vYcnt4crdJMJxJJ0LLjTTGBt42ntweBqAWxrbDxGlp/Nsmkc7D/xao5R+RWpp5zhgk8EiAbGkgRsuZY4yzZSoSDHtuvN1skXAs3ZiwluNtDB/fGPyXZ+/P3XjjQ421LEEtqCCBNOWjYBSMglEwCnABAOuQPtaCC1K4AAAAAElFTkSuQmCC","orcid":"","institution":"Texas A\u0026M University at Galveston","correspondingAuthor":true,"prefix":"","firstName":"Asif","middleName":"","lastName":"Mortuza","suffix":""},{"id":633255467,"identity":"248b6b9c-5ac5-4320-b680-fe5753d1895f","order_by":1,"name":"Bryan Gahn","email":"","orcid":"","institution":"Texas A\u0026M University at Galveston","correspondingAuthor":false,"prefix":"","firstName":"Bryan","middleName":"","lastName":"Gahn","suffix":""},{"id":633255469,"identity":"d888ea78-0ff9-4779-9b68-be19d68e2701","order_by":2,"name":"Marcus Wharton","email":"","orcid":"","institution":"Texas A\u0026M University","correspondingAuthor":false,"prefix":"","firstName":"Marcus","middleName":"","lastName":"Wharton","suffix":""},{"id":633255471,"identity":"74253f8d-fa22-44e1-b790-27b7b1ac18fe","order_by":3,"name":"R. J. David Wells","email":"","orcid":"","institution":"Texas A\u0026M University at Galveston","correspondingAuthor":false,"prefix":"","firstName":"R.","middleName":"J. David","lastName":"Wells","suffix":""},{"id":633255472,"identity":"74720450-dc90-4335-b965-fbf9e01dc90f","order_by":4,"name":"Lene H. Petersen","email":"","orcid":"","institution":"Texas A\u0026M University at Galveston","correspondingAuthor":false,"prefix":"","firstName":"Lene","middleName":"H.","lastName":"Petersen","suffix":""},{"id":633255477,"identity":"933a1841-d1f9-4ec3-be12-c793c49ad151","order_by":5,"name":"Antonietta Quigg","email":"","orcid":"","institution":"Texas A\u0026M University at Galveston","correspondingAuthor":false,"prefix":"","firstName":"Antonietta","middleName":"","lastName":"Quigg","suffix":""},{"id":633255489,"identity":"96508267-fb9b-4ecf-a23e-404711cfbe17","order_by":6,"name":"Karl Kaiser","email":"","orcid":"","institution":"Texas A\u0026M University at Galveston","correspondingAuthor":false,"prefix":"","firstName":"Karl","middleName":"","lastName":"Kaiser","suffix":""},{"id":633255490,"identity":"b698a8da-6807-4284-a53d-92f6a485d858","order_by":7,"name":"David Hala","email":"","orcid":"","institution":"Texas A\u0026M University at Galveston","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Hala","suffix":""}],"badges":[],"createdAt":"2026-04-23 18:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9509872/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9509872/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108492685,"identity":"82caef01-d210-4c3e-b033-18a346545cab","added_by":"auto","created_at":"2026-05-05 09:58:19","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":246526,"visible":true,"origin":"","legend":"\u003cp\u003eMap of Galveston Bay in the Texas coast of Gulf of Mexico showing fish and oyster sampling locations.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9509872/v1/b5d37ecb251d91d5df3327a3.jpeg"},{"id":108492570,"identity":"ae1401d6-4b14-4659-87fa-5e587b2deffe","added_by":"auto","created_at":"2026-05-05 09:58:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99360,"visible":true,"origin":"","legend":"\u003cp\u003eBox and whiskers plot showing the total (a) PAHs, (b) PCBs (ng/g DW); and (c) NMPs concentrations (µg/g DW) in gill/mantle of oysters and fish muscle (red) or fish livers (green) collected from Galveston Bay.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9509872/v1/8af00412b1f65d435ac50ba5.png"},{"id":108379905,"identity":"25f8e956-8bbb-4cc7-b5f6-e1c90bfc6db5","added_by":"auto","created_at":"2026-05-04 04:32:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":159197,"visible":true,"origin":"","legend":"\u003cp\u003eBox and whiskers plot showing the total concentrations of (a) PAHs, (b) PCBs (ng/g DW), and (c) NMPs (µg/g DW) in water, sediment, fish muscle, fish liver and in oysters sampled from Galveston Bay (as previously reported in the published literature and listed in Supplementary Tables 2, 3, and 4). The blue triangles represents the median concentrations reported in this study.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9509872/v1/a5cb326ce14696b0ee8bd118.png"},{"id":108821860,"identity":"6030f59e-d4b5-4e17-9a77-b748655a2099","added_by":"auto","created_at":"2026-05-08 16:46:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1611872,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9509872/v1/9176515b-d471-4621-a454-62b2d06c227d.pdf"},{"id":108379902,"identity":"ab50df4b-b799-4732-a019-a4eb2b273458","added_by":"auto","created_at":"2026-05-04 04:32:54","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":641407,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalGalvestonbiota.docx","url":"https://assets-eu.researchsquare.com/files/rs-9509872/v1/9791169a8fe203d63960b8ed.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Current and Historic Levels of Persistent (PAHs, PCBs) and Emerging Pollutant (Nano- microplastics or NMPs) Body-Burdens in Oysters and Fish from an Urban-Industrialized Subtropical Estuary (Galveston Bay, TX, USA)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCoastal zones are among the most densely inhabited regions on Earth, with almost half of the global population residing within 100 km of coastlines (Cosby et al., 2024). As a consequence, approximately 49% of marine ecosystems are already impacted by anthropogenic stressors (Gaw et al., 2014). These pressures highlight the need for robust pollutant monitoring and marine risk assessment frameworks to safeguard and manage estuarine and coastal environments, which serve as invaluable ecological and economic resources. Galveston Bay represents a relevant model system, as it is the largest estuary in Texas and the 7th largest in the continental United States (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (GBEP, 2025). The urban-industrialized estuary has an area of 1544 km\u003csup\u003e2\u003c/sup\u003e, an average depth of 2.1 m, and water residence time of ~\u0026thinsp;40 days (Solis \u0026amp; Powell, 1999; Rayson et al., 2016; Wetz et al., 2025). The bay also receives major industrial, agricultural, and municipal pollution discharges from Houston (fourth most populous city in the U.S.) and its surrounding areas (Melosi \u0026amp; Pratt, 2007; Wilson et al., 2008; Leonard, 2018). Freshwater inflows are dominated by the San Jacinto and Trinity rivers that carry urban and agricultural effluents (Newell et al., 1994). Galveston Bay connects the northwestern Gulf of Mexico with the Houston shipping channel and is a major shipping and transportation hub for oil tankers and other energy infrastructure related traffic (GBF, 2025).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe industrial transformation of the Galveston Bay area began with the discovery of the Spindletop oil field near Beaumont, TX in 1901 (ref). This in turn spurred petroleum exploration and subsequent discovery of the Goose Creek oil field in 1903 and subsequent establishment of oil refineries in Texas City, Baytown and Pasadena on the shores around Galveston Bay by 1908 (Pomeroy Jr, 2020; Sibley, 2020; Young, 2020). The region became a wartime manufacturing hub during the 1930s \u0026minus;\u0026thinsp;1940s, which was also facilitated by the expansion of the Houston Ship Channel (Cutler, 2020). By the 1960s, the Texas Gulf coast dominated national petrochemical production, processing over 80% of butadiene, 70% of ethylene, and 66% of benzene through more than 200 production plants and with investments exceeding \u003cspan\u003e$\u003c/span\u003e5\u0026nbsp;billion (TSHA, 1995). In Galveston Bay, there were an estimated 275 oil spills per year with an average spill of \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;100 gallons recorded between 1998 and 2014 (Rowe et al., 2020). On March 22, 2014, a collision between two vessels released approximately 6.4 \u0026times; 105 L (169,070 gallons) of RMG‑380 marine fuel oil into Galveston Bay. (Williams et al., 2017). From March 17\u0026ndash;20, 2019, an explosion at the International Terminals Company facility in Deer Park, Texas, released roughly 696,990 gallons of oil‑contaminated wastewater and an additional 1.5\u0026nbsp;million gallons of flame‑retardant chemicals into the bay (Rice, 2019; An Han et al., 2020). The fire was soon followed by a barge collision and spill of gasoline in upper Galveston Bay on May 10, 2019 (NOAA, 2019). The barge spill released an estimated\u0026thinsp;~\u0026thinsp;378,000 gallons of gasoline into the bay (Trevizo, 2019). These events led to the partial closure of the waterways in the area, leading to an estimated economic loss of \u003cspan\u003e$\u003c/span\u003e0.5 \u0026ndash; \u003cspan\u003e$\u003c/span\u003e1\u0026nbsp;billion (Leinfelder \u0026amp; Blum, 2019; Trevizo, 2019). A barge collision on May 15th, 2024 with the Pelican Island bridge in Galveston (TX) made the national news and reported the release of ~\u0026thinsp;2,000 gallons of environmentally toxic vacuum gas oil (VGO) into Galveston (Lozano et al., 2024).\u003c/p\u003e \u003cp\u003eIn addition to the burgeoning petroleum industry, the Texas coast has also transformed into a major plastics production hub beginning in the mid‑20th century (TSHA, 1995). In 2018, ExxonMobil began operations at its Baytown Chemical \u0026amp; Refining Complex near Galveston Bay, producing ethylene feedstock for the Mont Belvieu polyethylene plant, one of the world\u0026rsquo;s largest with an annual capacity of around 2.3\u0026nbsp;million tons (ExxonMobil, 2018). This wave of petrochemical expansion included dozens of plastics facilities built or expanded along the Texas Gulf Coast between 2012 and 2024, many supported by billions in public tax incentives (Patel, 2024b). However, this industrial growth has brought significant plastic pollution, notably pellet (\u0026ldquo;nurdle\u0026rdquo;) spills (Tunnell et al., 2020). Monitoring in the 2020s revealed microplastics are ubiquitous across Galveston Bay and its tributaries, documenting high microplastic loads in surface water and sediments, totaling an estimated 20 trillion pieces suspended in the upper 0.3 m of the Bay at any time (Oakley et al., 2024). This issue is compounded by the proximity of Houston, whose dense population and urban sprawl contribute anthropogenic plastic waste through stormwater runoff, litter, and wastewater discharge into the bay (NOAA, 2025). In 2019, a \u003cspan\u003e$\u003c/span\u003e50\u0026nbsp;million penalty was imposed on Formosa Plastics following a lawsuit alleging the company discharged billions of pellets into the nearby Lavaca Bay (EPA, 2012; Conkle, 2018; Baddour, 2024); while not directly impacting Galveston Bay, this case underscores the broader regional problem. At beaches across the Gulf Coast, microplastics, including nurdles, fibers, fragments, and films continue to wash ashore, accumulating in marine habitats and being ingested by oysters, fish, and birds (Grace et al., 2022; Celis-Hernandez et al., 2023; Wontor et al., 2023).\u003c/p\u003e \u003cp\u003eIn this study, we assessed persistent (PAHs and PCBs) and emerging nano-microplastics (NMPs) pollutant body-burdens in fish and oysters from Galveston Bay. We compared our findings to historical data for PAHs and PCBs reported in Galveston Bay (biota, surface waters, and sediments). This is the first study to report NMPs body-burdens in the fish from Galveston Bay using a novel pyrolysis gas chromatography and mass spectrometry (Py-GCMS/MS) (Gahn et al., 2025). We hypothesize that the current levels of these persistent and emerging pollutants will be higher than historic levels due to continued industrialization and expansion of urbanization in the area (Comptroller, 2024). Beyond quantifying tissue concentrations, we also inferred probable PAH sources by evaluating ratios of diagnostic low‑ versus high‑molecular‑weight PAHs (Budzinski et al., 1997; Yunker et al., 2002; Tobiszewski \u0026amp; Namieśnik, 2012). Finally, annual plastic intake from seafood for an adult human was estimated using NMP concentrations measured in the muscle of fish and oyster gill/mantle tissues.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Sample collection and preparation\u003c/h2\u003e \u003cp\u003eBiota collected from Galveston Bay are eastern oysters (\u003cem\u003eCrassostrea virginica\u003c/em\u003e, Gmelin, 1791), gafftopsail catfish (\u003cem\u003eBagre marinus\u003c/em\u003e, Mitchill, 1815), red drum (\u003cem\u003eSciaenops ocellatus\u003c/em\u003e, Linnaeus, 1776), and spotted seatrout (\u003cem\u003eCynoscion nebulosus\u003c/em\u003e, Cuvier, 1830). All biological specimens were generously provided by the Texas Parks and Wildlife Department (TPWD) as part of their routine annual wildlife monitoring surveys in Galveston Bay. Collections took place opportunistically during the spring and fall of 2021 and 2022. There were no major oil spills during this period. A random stratified sampling approach was employed to choose representative sites across the bay (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Sampling at shoreline locations utilized 18.3-meter bag seines, while open-water sites were sampled using 6.1-meter bay trawls. All organisms collected met or exceeded the TPWD\u0026rsquo;s minimum legal size limits for recreational and commercial harvest for eastern oysters (12.7\u0026ndash;20.3 cm), gafftopsail catfish (\u0026gt;\u0026thinsp;35.6 cm), red drum (\u0026gt;\u0026thinsp;50.8 cm), and spotted seatrout (\u0026gt;\u0026thinsp;38.1 cm) (TPWD, 2024). All oysters and fish were weighed, and their total length (TL) and fork length (FL) (fish only) measured (\u003cb\u003eSupplemental Table\u0026nbsp;1\u003c/b\u003e). After capture, specimens were kept on ice and then stored frozen at \u0026minus;\u0026thinsp;20\u0026deg;C at the Dickinson Marine Laboratory (TX). Subsequently, all samples were transferred to \u0026minus;\u0026thinsp;20\u0026deg;C storage at Texas A\u0026amp;M University at Galveston. Prior to tissue dissection, samples were thawed on ice. From each fish, approximately 5\u0026ndash;10 grams of skinless muscle (fillet) or liver tissue were excised, and from oysters, about 1\u0026ndash;2 grams of mantle and gill tissue were collected. The isolated tissues were then stored separately at \u0026minus;\u0026thinsp;20\u0026deg;C until analytical processing. For chemical analysis, approximately 0.5 g of frozen tissue was freeze-dried at -40\u003csup\u003eo\u003c/sup\u003eC for 24 hours at 0.20 mBar pressure using a LABCONCO freeze dryer. The lyophilized tissue was then ground into a fine powder with a mortar and pestle.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 PAHs and PCBs quantification\u003c/h2\u003e \u003cp\u003eThe analytical method used to quantify PAHs and PCBs in oysters and fish has previously been published (Cullen et al., 2019). Briefly, an accelerated solvent extraction (ASE) system (Dionex ASE 350) was used to extract PAHs and PCBs from ~\u0026thinsp;0.5 g of freeze-dried muscle or liver tissue using 1:1 dichloromethane (DCM) and hexane as solvents. Samples were loaded into 34 mL ASE cells (Thermofisher Scientific, Cat# 068099), packed with Ottawa sand (Spectrum, Cat # S1010) above and below each sample and spiked with 10 \u0026micro;L of deuterated internal standards (B[a]P-d12 and PCB65-d5). Blanks consisting of Ottawa sand (Sigma‑Aldrich, Cat# 274739) only were similarly spiked with internal standards. Extraction conditions were 100\u0026deg;C, 1500 psi, with 5 min preheat and heat times, followed by a 4 min static phase, and 300 sec purge time, completing two static cycles (60% flush rate) per sample. Extracts were collected in ASE collection vials (Dionex, Cat # 048781), evaporated under N₂, reconstituted in 1 mL DCM, and transferred to 5 mL test tubes. Lipids were removed by solid phase extraction using Captiva lipid solid phase extraction (SPE) cartridges (Agilent Technologies, Cat # 5190\u0026thinsp;\u0026minus;\u0026thinsp;1002) conditioned with 1 mL of DCM. The eluate was dried under N\u003csub\u003e2\u003c/sub\u003e, reconstituted into 0.2 mL acetonitrile, frozen at -20\u0026deg;C to further precipitate lipids and debris, and 0.1 mL of clear supernatant was collected, dried under N\u003csub\u003e2\u003c/sub\u003e and reconstituted in 0.1 mL DCM, and transferred to a 0.1 mL glass insert (Wheaton, Cat # 225260) for analysis via GCMS.\u003c/p\u003e \u003cp\u003eEPA priority pollutant PAHs (14 congeners) and toxic (28 dioxin like and non-dioxin like) PCBs were quantified using a Hewlett Packard HP 6890 GC coupled with an Agilent 5973 Mass Selective Detector. The PAHs included acenaphthene (ACE), fluorene (FLU), anthracene (ANT), phenanthrene (PHE), fluoranthene (FLT), chrysene (CHR), pyrene (PYR), benzo[a]anthracene (BaA), benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), dibenz[a,h]anthracene (DahA), benzo[g,h,i]perylene (BghiP), and indeno[1,2,3-cd]pyrene (IcdP). The 28 PCB congeners included PCBs 1, 18, 33, 52, 77, 81, 95, 101, 105, 114, 118, 123, 126, 128, 138, 149, 153, 156, 157, 167, 169, 170, 171, 177, 180, 183, 187, and 189 (per IUPAC numbering). Samples were injected in splitless mode (2 \u0026micro;L) into an Agilent DB-5MS column, with helium as carrier gas at 1.0 mL/min. GC oven temperatures started at 40\u0026deg;C, ramped to 180\u0026deg;C at 20\u0026deg;C/min, then to 300\u0026deg;C at 5\u0026deg;C/min, holding for 10 min (total runtime 40 min). The MS was operated in electron impact mode (70 eV, 230\u0026deg;C source temperature) using selected ion monitoring. Quantification was based on an 11-point calibration curve (10\u0026ndash;0.01 \u0026micro;g/mL), with detection limits set to the lowest standard giving a signal-to-noise ratio\u0026thinsp;\u0026gt;\u0026thinsp;5:1 (\u003cb\u003eSupplemental Table\u0026nbsp;5\u003c/b\u003e). Body-burden concentrations were reported as ng/g dry weight (ng/g DW). Sample quality assurance included blank extractions for background correction and standard addition for select analytes. For every ten samples, two blanks (comprising Ottawa sand and internal standard) and one spiked sample (comprising muscle/liver with standard addition PAH and PCB) were analyzed. Recovery averages were 74.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44% for BaA, 46.01\u0026thinsp;\u0026plusmn;\u0026thinsp;9.24% for PYR, 69.07\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88% for PCB 18, and 68.50\u0026thinsp;\u0026plusmn;\u0026thinsp;5.83% for PCB 101.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Source assessment of PAHs\u003c/h2\u003e \u003cp\u003eHigh molecular weight (HMW) PAHs (\u0026gt;\u0026thinsp;four aromatic rings) are generally produced by high-temperature combustion (400\u0026ndash;700\u0026deg;C) and are primarily of pyrogenic origin, while low molecular weight (LMW) PAHs (\u0026lt;\u0026thinsp;four aromatic rings) are formed during lower-temperature combustion (100\u0026ndash;300\u0026deg;C) and are predominantly petrogenic (Budzinski et al., 1997; Wolska et al., 2012). Diagnostic ratios such as \u0026sum;LMW/\u0026sum;HMW, \u0026sum;COMB (i.e., all \u0026sum;HMW PAHs)/\u0026sum;PAHs (\u0026sum;LMW+\u0026sum;HMW PAHs), FLT/(FLT\u0026thinsp;+\u0026thinsp;PYR), ANT/(ANT\u0026thinsp;+\u0026thinsp;PHE), BaA/(BaA\u0026thinsp;+\u0026thinsp;CHR), IcdP/(IcdP+BghiP), BaP/BghiP, and PHE/ANT were used to identify dominant sources of PAH (petrogenic or pyrogenic). The interpretation of the ratios are outlined in Tobiszewski and Namieśnik (2012).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Nano-microplastics (NMPs) quantification\u003c/h2\u003e \u003cp\u003eThe analysis of NMPs was performed according to Gahn et al. (2025). An enzyme solution was prepared to digest freeze-dried tissue for NMP extraction following the methods detailed by von Friesen et al. (2019). Six grams of porcine pancreatic enzyme (Pez, Sigma-Aldrich, Cat # P7545) was dissolved in 100 mL of tris buffer (Sigma-Aldrich, Cat # T2694) and filtered through 2.8 \u0026micro;m and 0.7 \u0026micro;m glass fiber filters (Sigma-Aldrich, Cat # WHA1825025, WHA1823047) to remove plastic contamination. Dried tissue (~\u0026thinsp;0.02 g) was treated with 1 mL of Pez/Tris solution (pH 8) in glass vials, shaken at 40\u0026deg;C for 24 hours using a benchtop orbital shaker and filtered onto cleaned 0.7 \u0026micro;m glass filters. Filters were dried at 38\u0026deg;C for 24 hours, then cut and packed into stainless-steel pyrolysis cups (Frontier Eco‑Cup LF, 80 \u0026micro;L, Frontier Labs, USA). Each cup was loaded with the internal standard, poly-4-fluorostyrene (PFS, obtained from PSS, Germany), followed by a layer of calcium carbonate (CaCO₃, ACS grade, J.T. Baker, USA) and capped with a quartz wool plug (Thermo Scientific, USA, Cat. no. 20411). The prepared samples were subsequently analyzed using pyrolysis-GC/MS/MS.\u003c/p\u003e \u003cp\u003eThe plastics identified included, polymethyl methacrylate (PMMA), polypropylene (PP), polyvinyl chloride (PVC), polyamide (PA), polycarbonate (PC), nylon 6,6 (N66), polyethylene (PE), polyethylene terephthalate (PET), acrylonitrile butadiene styrene (ABS), polyurethane (PUR), styrene‑butadiene rubber (SBR), and polystyrene (PS). The method used to quantify NMPs in the fish tissue has previously been published in detail (Gahn et al., 2025). Briefly, a Frontier Laboratories Auto-shot sampler pyrolyzer, paired with an Agilent 8890 gas chromatograph and an Agilent 7010B triple quadrupole mass spectrometer (Py-GC/MS-MS) was used to quantify NMPs. Tissue pyrolysis was conducted at 600\u0026deg;C, volatilizing microplastics, which were separated using an Ultra Alloy\u003csup\u003e+\u003c/sup\u003e-5 Capillary Column (30 m length x 0.25 mm I.D. x 0.25 \u0026micro;m film, Frontier Labs, Japan). The GC injector operated with a 50:1 split ratio with a split flow of 40 mL/min at 300\u0026deg;C. A septum purge flow of 20 mL/min was maintained. Helium served as the carrier gas at 2.25 mL/min, while nitrogen was used as the collision gas at 1.5 mL/min. Chromatographic separation followed a temperature program beginning at 35\u0026deg;C (held for 0.25 min), ramping at 20\u0026deg;C/min to a final temperature of 310\u0026deg;C (held for 3 min), yielding a total run time of 17 minutes. The mass spectrometer was configured with a source temperature of 230\u0026deg;C, quadrupole temperature of 150\u0026deg;C, auxiliary temperature of 280\u0026deg;C, and a solvent delay of 5 minutes.\u003c/p\u003e \u003cp\u003ePlastic quantification relied on the multiple reaction monitoring of distinctive mass ions, against a five-point calibration curve (1500\u0026ndash;150 \u0026micro;g), with all standards loaded onto GF/F filters and processed identically to the samples. Given current concerns of lipid interference for major plastics (A. Monikh et al., 2025), we implemented a stringent QA/QC protocol to minimize false positives, including a rigorous correction procedure as outlined in Gahn et al. (2025). Briefly, a triglyceride lipid mixture (Sigma, CAS# 17810) was used to build a 5-point calibration curve (0.25\u0026ndash;1.25 mg) encompassing lipid weight typically observed for our sample types. This was used to relate lipid mass to apparent plastic concentration, enabling calculation of a correction factor that was subtracted from each sample\u0026rsquo;s NMP quantification. Lipid weight per sample was determined by extracting\u0026thinsp;~\u0026thinsp;0.5 g of freeze‑dried tissue using ASE with DCM:hexane and quantifying lipids gravimetrically by weighing collection vials before and after N₂ evaporation. The limit of detection (LOD) was calculated using signal/noise\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;3. Quality controls per 10 samples included two blanks, two recovery controls, and one replicate. Blanks measured background contamination (and were subtracted from sample responses), recoveries assessed plastic standard recovery, and replicates checked reproducibility. Recovery for select plastics were 115\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15% for PP, 93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08% for N66, and 113\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05% for PE.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Average Daily Intake of NMPs\u003c/h2\u003e \u003cp\u003eThe Daily Intake (DI) of seafood (g/kg body weight/day) was calculated as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:DI=\\frac{{DC}_{shellfish\\:or\\:fish}}{BW}\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:ADI={C}_{Plastics}*\\:DI\\:\\:\\:\\left(2\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eFirst, seafood daily intake (DI) was calculated by dividing the estimated daily consumption (DC, 30 g/day) of fish or shellfish by the average adult human body weight (BW, 70 kg), as recommended by the Texas Department of State Health Services (DSHS, 2011). Secondly, the Average Daily Intake (ADI) of NMPs (mg/kg/day) was estimated by multiplying the DI by the plastic concentration (C\u003csub\u003eplastics\u003c/sub\u003e) in fish muscle or oyster gill/mantle, originally measured in \u0026micro;g/g dry weight (DW). These concentrations were converted to wet weight (WW) using species-specific correction factors accounting for water loss during freeze-drying (e.g., if a 6 g oyster was dried to 1g, the DW concentration was divided by 6 to get WW concentration). Finally, the ADI values were scaled to estimate annual plastic intake per person per year by multiplying the daily intake rate by 365 days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Historic levels of PAHs, PCBs, and NMPs in Galveston Bay\u003c/h2\u003e \u003cp\u003eA targeted literature search was conducted using Google Scholar and PubMed by combining the keywords: PAH, PCB, microplastics; with the geographic terms: Galveston Bay, Gulf of Mexico; and environmental matrices: air, water, sediment, oyster, fish muscle, fish liver. Additional search terms included concentration, body burden, historic, and related descriptors. Both acronyms (i.e. PAH, PCB) and full chemical names (i.e. polycyclic aromatic hydrocarbons, polychlorinated biphenyls) were used in various combinations to capture a broad range of studies. The relevant publications were downloaded without date restriction, including early reports dating back to 1965. From these sources, data on pollutant levels were extracted from tables, charts, and figures wherever reported in each source. The retrieved values were compiled into a unified Excel spreadsheet, and the concentration units converted to ng/g for PAHs and PCBs, and \u0026micro;g/g for microplastics, wherever possible. For water concentrations, we assumed the density of water to be 1 g/mL, therefore allowing the conversion of ng/L to ng/g water. Wet-weight (WW) contaminant concentrations in fish muscle were converted to dry weight (DW) using a 4:1 ratio, reflecting an expected moisture content of ~\u0026thinsp;75% (Bigler \u0026amp; Greene, 1993; Cresson et al., 2017). Fish liver tissue, which typically contains 83\u0026ndash;85% moisture, necessitated the use of 6:1 WW-to-DW correction factor (Bigler \u0026amp; Greene, 1993). Oyster soft tissue concentrations were converted using the 6:1 WW-to-DW ratio, based on a reported 82% mean moisture content (Mo \u0026amp; Neilson, 1994). Reported organism body weights were also recorded when available. The final datasets comprised 204 concentration entries from 70 unique studies spanning from 1965\u0026ndash;2021 for PAHs and PCBs, and from 2000\u0026ndash;2023 for NMPs. The fully annotated spreadsheet is provided with sources to allow replication and secondary analyses by other authors (\u003cb\u003eSupplemental Tables\u0026nbsp;2, 3, 4\u003c/b\u003e). The \u0026lsquo;past\u0026rsquo; datasets were presented alongside those measured in the current study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Statistical analysis\u003c/h2\u003e \u003cp\u003eArcGIS Pro (v3.0) was used to map the biota sampling sites across Galveston Bay (ESRI, 2025). Statistical analyses were conducted using base R (v4.1.3) along with the \u003cem\u003etidyr\u003c/em\u003e and \u003cem\u003eggplot2\u003c/em\u003e packages for data organization and visualization (R, 2025). Statistical significance was determined at α\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;0.05. Data normality was assessed using the Shapiro-Wilk test, followed by Levene\u0026rsquo;s test to evaluate homogeneity of variances. For pairwise comparisons (i.e., pollutant concentration between tissue), either a parametric t-test or a non-parametric Mann-Whitney U test was applied, depending on data distribution. When analyzing datasets involving a main effects variable, one-way ANOVA (parametric) or Kruskal-Wallis test (non-parametric) was used, with Tukey\u0026rsquo;s or Dunn\u0026rsquo;s post hoc tests, respectively, for pairwise group comparisons of body burden of pollutants between species. For analysis including both a main effect and a covariate, a two-way ANOVA was conducted followed by Tukey\u0026rsquo;s post hoc test (i.e., contaminant body burden across species and tissue type).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Morphometric parameters\u003c/h2\u003e \u003cp\u003eAll fish and oysters collected for the present study were adults with the exception of red drum, which were categorized as juveniles (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). We found animal size to not be a determinant for pollutant bioaccumulation as a spearman-rank correlational analysis conducted between morphometric parameters and the pollutant body-burdens showed no significant correlations (data not shown).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2. PAHs body-burdens in biota from Galveston Bay as reported in this study\u003c/h2\u003e \u003cp\u003eTotal PAHs in the gill/mantle tissue of oysters (608.51\u0026thinsp;\u0026plusmn;\u0026thinsp;15.72 ng/g DW) and muscle of seatrout (605.30\u0026thinsp;\u0026plusmn;\u0026thinsp;19.08 ng/g DW) were significantly higher (both 2.4x) than red drum (252.06\u0026thinsp;\u0026plusmn;\u0026thinsp;6.44 ng/g DW) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e). However, total hepatic PAH levels showed red drum (3,995.90\u0026thinsp;\u0026plusmn;\u0026thinsp;182.84 ng/g DW) to have the highest (~\u0026thinsp;2.5x; statistically significant) hepatic PAH levels compared to catfish (1,644.72\u0026thinsp;\u0026plusmn;\u0026thinsp;61.99 ng/g DW), and seatrout (1,651.56\u0026thinsp;\u0026plusmn;\u0026thinsp;76.38 ng/g DW) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e). Overall, the total PAHs in livers as compared to muscle samples were 3x higher in seatrout, 5x higher in catfish and 16x higher in red drum (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThe analysis of PAHs congeners in muscle of fish and gill/mantle of oysters showed the proportion of ACE and PHE to be higher (20\u0026ndash;35%) as compared to the rest of PAHs (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(a), Supplemental Fig.\u0026nbsp;1(a))\u003c/b\u003e. In red drum muscle, BkF comprised up to 25% of all PAHs. Whereas, in red drum and spotted seatrout muscle, and gill/mantle of oysters, FLU was also predominant at 10\u0026ndash;15%. In the livers of all fish, FLU dominated at up to 50% (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a), Supplemental Fig.\u0026nbsp;1(b))\u003c/b\u003e. There was also a higher proportion of ACE in catfish only, which was responsible for ~\u0026thinsp;25% of all the PAHs detected in catfish livers collected from Galveston Bay. Finally, there was a higher proportion of BaP in seatrout (up to 25%) and IcdP in red drum (up to 50%) in livers.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMuscle concentration of PAH, PCB and NMP congeners found in biota collected from Galveston Bay. Levels are reported in ng/g tissue dry weight (DW) for PAHs, PCBs; and in \u0026micro;g/g dry weight (DW) for NMPs (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error). Significant differences are denoted using letters. Levels below the limit of detection are represented by \u0026ldquo;- \u0026ldquo;.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(a) PAHs (ng/g DW)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOyster (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCatfish (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRed drum (n\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSeatrout (n\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow molecular weight (LMW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197.64\u0026thinsp;\u0026plusmn;\u0026thinsp;38.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.64\u0026thinsp;\u0026plusmn;\u0026thinsp;15.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.13\u0026thinsp;\u0026plusmn;\u0026thinsp;17.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e249.71\u0026thinsp;\u0026plusmn;\u0026thinsp;99.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103.39\u0026thinsp;\u0026plusmn;\u0026thinsp;37.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.46\u0026thinsp;\u0026plusmn;\u0026thinsp;4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.98\u0026thinsp;\u0026plusmn;\u0026thinsp;9.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63.21\u0026thinsp;\u0026plusmn;\u0026thinsp;21.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117.09\u0026thinsp;\u0026plusmn;\u0026thinsp;10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118.04\u0026thinsp;\u0026plusmn;\u0026thinsp;22.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.85\u0026thinsp;\u0026plusmn;\u0026thinsp;7.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e151.56\u0026thinsp;\u0026plusmn;\u0026thinsp;34.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.76\u0026thinsp;\u0026plusmn;\u0026thinsp;3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.05\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.20\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh molecular weight (HMW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.84\u0026thinsp;\u0026plusmn;\u0026thinsp;3.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.42\u0026thinsp;\u0026plusmn;\u0026thinsp;2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePYR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.18\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.81\u0026thinsp;\u0026plusmn;\u0026thinsp;2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.90\u0026thinsp;\u0026plusmn;\u0026thinsp;6.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.70\u0026thinsp;\u0026plusmn;\u0026thinsp;4.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.90\u0026thinsp;\u0026plusmn;\u0026thinsp;1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.98\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.89\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.61\u0026thinsp;\u0026plusmn;\u0026thinsp;3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBbF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.82\u0026thinsp;\u0026plusmn;\u0026thinsp;7.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBkF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.08\u0026thinsp;\u0026plusmn;\u0026thinsp;13.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.60\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.15\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.80\u0026thinsp;\u0026plusmn;\u0026thinsp;11.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.07\u0026thinsp;\u0026plusmn;\u0026thinsp;5.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.17\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIcdP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.54\u0026thinsp;\u0026plusmn;\u0026thinsp;2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDahA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.79\u0026thinsp;\u0026plusmn;\u0026thinsp;46.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.03\u0026thinsp;\u0026plusmn;\u0026thinsp;9.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBghiP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.48\u0026thinsp;\u0026plusmn;\u0026thinsp;3.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.050\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.84\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΣPAHs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e608.51\u0026thinsp;\u0026plusmn;\u0026thinsp;15.72\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e328.70\u0026thinsp;\u0026plusmn;\u0026thinsp;9.73\u003c/b\u003e\u003csup\u003e\u003cb\u003ea,b\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e252.06\u0026thinsp;\u0026plusmn;\u0026thinsp;6.44\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e605.30\u0026thinsp;\u0026plusmn;\u0026thinsp;19.08\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(b) PCBs (ng/g DW)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOyster (n\u0026thinsp;=\u0026thinsp;9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCatfish (n\u0026thinsp;=\u0026thinsp;8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRed drum (n\u0026thinsp;=\u0026thinsp;9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eSeatrout (n\u0026thinsp;=\u0026thinsp;8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-ortho\u003c/p\u003e \u003cp\u003e(dioxin like)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53.60\u0026thinsp;\u0026plusmn;\u0026thinsp;37.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.93\u0026thinsp;\u0026plusmn;\u0026thinsp;4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.39\u0026thinsp;\u0026plusmn;\u0026thinsp;4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMono-ortho\u003c/p\u003e \u003cp\u003e(dioxin like)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.88\u0026thinsp;\u0026plusmn;\u0026thinsp;3.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.50\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.15\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.00\u0026thinsp;\u0026plusmn;\u0026thinsp;23.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-dioxin like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.00\u0026thinsp;\u0026plusmn;\u0026thinsp;8.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.98\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.14\u0026thinsp;\u0026plusmn;\u0026thinsp;2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.22\u0026thinsp;\u0026plusmn;\u0026thinsp;5.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148.39\u0026thinsp;\u0026plusmn;\u0026thinsp;39.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.89\u0026thinsp;\u0026plusmn;\u0026thinsp;2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.13\u0026thinsp;\u0026plusmn;\u0026thinsp;51.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.66\u0026thinsp;\u0026plusmn;\u0026thinsp;18.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.60\u0026thinsp;\u0026plusmn;\u0026thinsp;13.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.31\u0026thinsp;\u0026plusmn;\u0026thinsp;4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.32\u0026thinsp;\u0026plusmn;\u0026thinsp;11.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.92\u0026thinsp;\u0026plusmn;\u0026thinsp;7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΣPCBs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e286.56\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e209.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e188.69\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(c) NMPs (\u0026micro;g/g DW)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOyster (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eCatfish (n\u0026thinsp;=\u0026thinsp;9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eRed drum (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eSeatrout (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,057.07\u0026thinsp;\u0026plusmn;\u0026thinsp;5261.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,146.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1,148.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.19\u0026thinsp;\u0026plusmn;\u0026thinsp;2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.22\u0026thinsp;\u0026plusmn;\u0026thinsp;3.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,208.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1,100.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e277.54\u0026thinsp;\u0026plusmn;\u0026thinsp;151.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,783.76\u0026thinsp;\u0026plusmn;\u0026thinsp;2,395.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,441.13\u0026thinsp;\u0026plusmn;\u0026thinsp;599.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,122.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2809.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e281.66\u0026thinsp;\u0026plusmn;\u0026thinsp;157.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΣNMPs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11,988.55\u0026thinsp;\u0026plusmn;\u0026thinsp;6,392.18\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e283.74\u0026thinsp;\u0026plusmn;\u0026thinsp;150.56\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e43.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.30\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e13,063.30\u0026thinsp;\u0026plusmn;\u0026thinsp;6,225.16\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Overview of historic PAHs levels in Galveston Bay\u003c/h2\u003e \u003cp\u003eThe long-term trends of PAHs concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(a))\u003c/b\u003e reported across various environmental matrices (from the literature) reveal levels in surface waters (2010\u0026ndash;2017) to be the lowest, with a median concentration of 47 ng/L or 0.047 ng/g (min-max range, 25\u0026ndash;9,520 ng/L or 0.025\u0026ndash;9.52 ng/g). Sediment PAHs concentrations (1968\u0026ndash;2017) exhibited a median concentration of 174 ng/g DW (min/max of 19.8\u0026ndash;3,608 ng/g DW) and were significantly higher than those measured in water. In contrast to surface waters, higher concentrations of PAHs were observed in biota (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e). For example, fish muscle (2010\u0026ndash;2021) and fish liver (2018\u0026ndash;2021) showed median concentrations of 252.06 ng/g DW (67.36\u0026ndash;4,600 ng/g DW) and 1800 ng/g DW (500\u0026ndash;13,200 ng/g DW), respectively. The median concentration of PAHs in fish liver was significantly higher than those in fish muscle (7x), sediment (10x), and water (39x). Fish muscle PAHs concentrations were also significantly higher than that in water (5x). Finally, oyster body burdens (1971\u0026ndash;2021) were in between fish muscle and liver, with a median of 608.51 ng/g DW (230.50\u0026ndash;4857.50 ng/g DW) and were significantly higher than both sediment (3.5x) and water (13x).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4. PCBs body-burdens in biota from Galveston Bay as reported in this study\u003c/h2\u003e \u003cp\u003eThe sum of total PCBs in oysters (286.56\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65 ng/g DW), while slightly higher, were within the same order of magnitude and not statistically different from catfish muscle (209.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28 ng/g DW) and seatrout muscle (188.69\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48 ng/g DW). In contrast, red drum muscle exhibited the lowest sum of total PCBs levels at 14.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28 ng/g DW amongst the biota (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). No significant differences across biota were observed for the liver body-burdens of PCBs in fish Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). The highest hepatic sum of total PCBs was measured in seatrout (2,161.75\u0026thinsp;\u0026plusmn;\u0026thinsp;33.19 ng/g DW) followed by catfish (1,349.75\u0026thinsp;\u0026plusmn;\u0026thinsp;25.31 ng/g DW) and red drum (630.13\u0026thinsp;\u0026plusmn;\u0026thinsp;12.25 ng/g DW) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). Overall, the total PCB levels were 6x higher in catfish, 11x higher in red drum and 42x higher in red drum liver vs. muscle (significantly different).\u003c/p\u003e \u003cp\u003eThe analysis of PCBs congeners in muscle samples revealed PCB 52 was the most prominent in red drum (75% of total PCBs) and spotted seatrout (30% of total PCBs) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(b), Supplemental Fig.\u0026nbsp;2 (a)\u003c/b\u003e). In contrast, PCB 128 was the most prominent congener in oysters (~\u0026thinsp;50% of total PCBs) and seatrout (~\u0026thinsp;25% of total PCBs). In catfish, PCBs 138 and 153 dominated (22% and 18% respectively of total PCBs). In the liver samples, PCB 126 was the most prominent congener in catfish (50% of total PCBs), red drum (38% of total PCBs) and seatrout (up to 25% of total PCBs). Whereas PCB 128 mainly dominated in seatrout (25% of total PCBs) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b), Supplemental Fig.\u0026nbsp;2 (b))\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLiver concentrations of (a) PAHs, (b) PCBs, and (c) NMPs congeners found in biota collected from Galveston Bay. Levels are reported in ng/g tissue dry weight (DW) for PAHs, PCBs; and in \u0026micro;g/g dry weight (DW) for NMPs (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error). Significant differences are denoted using letters. Levels below the limit of detection are represented by \u0026ldquo;- \u0026ldquo;.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e(a) PAHs (ng/g DW)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatfish (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRed drum (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeatrout (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow molecular weight (LMW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e539.44\u0026thinsp;\u0026plusmn;\u0026thinsp;105.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e762.82\u0026thinsp;\u0026plusmn;\u0026thinsp;130.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,421.37\u0026thinsp;\u0026plusmn;\u0026thinsp;371.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,046.07\u0026thinsp;\u0026plusmn;\u0026thinsp;447.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.21\u0026thinsp;\u0026plusmn;\u0026thinsp;13.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109.91\u0026thinsp;\u0026plusmn;\u0026thinsp;39.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e181.86\u0026thinsp;\u0026plusmn;\u0026thinsp;40.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.87\u0026thinsp;\u0026plusmn;\u0026thinsp;8.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153.28\u0026thinsp;\u0026plusmn;\u0026thinsp;58.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.45\u0026thinsp;\u0026plusmn;\u0026thinsp;27.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh molecular weight (HMW)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.95\u0026thinsp;\u0026plusmn;\u0026thinsp;9.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePYR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.38\u0026thinsp;\u0026plusmn;\u0026thinsp;5.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.31\u0026thinsp;\u0026plusmn;\u0026thinsp;4.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBbF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBkF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.81\u0026thinsp;\u0026plusmn;\u0026thinsp;19.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.98\u0026thinsp;\u0026plusmn;\u0026thinsp;27.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e352.18\u0026thinsp;\u0026plusmn;\u0026thinsp;92.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIcdP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.28\u0026thinsp;\u0026plusmn;\u0026thinsp;15.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,273.41\u0026thinsp;\u0026plusmn;\u0026thinsp;733.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDahA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBghiP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.71\u0026thinsp;\u0026plusmn;\u0026thinsp;23.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΣPAHs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1,644.72\u0026thinsp;\u0026plusmn;\u0026thinsp;61.99\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3,995.90\u0026thinsp;\u0026plusmn;\u0026thinsp;182.84\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1,651.56\u0026thinsp;\u0026plusmn;\u0026thinsp;76.38\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(b) PCBs (ng/g DW)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCatfish (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRed drum (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSeatrout (n\u0026thinsp;=\u0026thinsp;7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-ortho\u003c/p\u003e \u003cp\u003e(dioxin like)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e694.48\u0026thinsp;\u0026plusmn;\u0026thinsp;241.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e333.89\u0026thinsp;\u0026plusmn;\u0026thinsp;130.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e570.41\u0026thinsp;\u0026plusmn;\u0026thinsp;188.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.72\u0026thinsp;\u0026plusmn;\u0026thinsp;7.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.87\u0026thinsp;\u0026plusmn;\u0026thinsp;56.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMono-ortho\u003c/p\u003e \u003cp\u003e(dioxin like)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.36\u0026thinsp;\u0026plusmn;\u0026thinsp;26.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.78\u0026thinsp;\u0026plusmn;\u0026thinsp;40.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e193.78\u0026thinsp;\u0026plusmn;\u0026thinsp;100.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.79\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.86\u0026thinsp;\u0026plusmn;\u0026thinsp;6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107.85\u0026thinsp;\u0026plusmn;\u0026thinsp;49.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.53\u0026thinsp;\u0026plusmn;\u0026thinsp;6.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.48\u0026thinsp;\u0026plusmn;\u0026thinsp;40.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.68\u0026thinsp;\u0026plusmn;\u0026thinsp;30.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.40\u0026thinsp;\u0026plusmn;\u0026thinsp;26.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e367.89\u0026thinsp;\u0026plusmn;\u0026thinsp;139.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-dioxin like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.43\u0026thinsp;\u0026plusmn;\u0026thinsp;10.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e 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colname=\"c1\"\u003e \u003cp\u003ePCB 52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.15\u0026thinsp;\u0026plusmn;\u0026thinsp;5.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.10\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.84\u0026thinsp;\u0026plusmn;\u0026thinsp;13.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 101\u003c/p\u003e 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align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.52\u0026thinsp;\u0026plusmn;\u0026thinsp;8.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.82\u0026thinsp;\u0026plusmn;\u0026thinsp;7.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.46\u0026thinsp;\u0026plusmn;\u0026thinsp;2.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.58\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.12\u0026thinsp;\u0026plusmn;\u0026thinsp;19.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.30\u0026thinsp;\u0026plusmn;\u0026thinsp;16.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.36\u0026thinsp;\u0026plusmn;\u0026thinsp;6.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.71\u0026thinsp;\u0026plusmn;\u0026thinsp;9.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCB 187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.62\u0026thinsp;\u0026plusmn;\u0026thinsp;6.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΣPCBs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1,349.75\u0026thinsp;\u0026plusmn;\u0026thinsp;25.31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e630.13\u0026thinsp;\u0026plusmn;\u0026thinsp;12.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2,161.75\u0026thinsp;\u0026plusmn;\u0026thinsp;33.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e(c) NMPs (\u0026micro;g/g DW)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eCatfish (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRed drum (n\u0026thinsp;=\u0026thinsp;6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSeatrout (n\u0026thinsp;=\u0026thinsp;7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePMMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.51\u0026thinsp;\u0026plusmn;\u0026thinsp;19.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.75\u0026thinsp;\u0026plusmn;\u0026thinsp;22.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,950.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1099.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,824.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1123.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57.15\u0026thinsp;\u0026plusmn;\u0026thinsp;13.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,975.20\u0026thinsp;\u0026plusmn;\u0026thinsp;304.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e432.49\u0026thinsp;\u0026plusmn;\u0026thinsp;145.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eΣNMPs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8,070.80\u0026thinsp;\u0026plusmn;\u0026thinsp;970.99\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2,291.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1268.41\u003c/b\u003e\u003csup\u003e\u003cb\u003eb\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Overview of historic PCBs levels in Galveston Bay\u003c/h2\u003e \u003cp\u003eA literature review of PCBs concentrations in Galveston Bay revealed levels in surface waters (2002\u0026ndash;2018) to be the lowest (compared to the matrices reported), with a median concentration of 2.2 ng/L or 0.0022 ng/g (min \u0026ndash; max of 0.1\u0026ndash;16.1 ng/L or 0.0001\u0026ndash;0.0161 ng/g). For example, the reported PCBs concentrations in sediments (1972\u0026ndash;2018) exhibited a median concentration of 26.0 ng/g DW (2.73\u0026ndash;17,000 ng/g DW) and were significantly higher than those in water. As observed for PAHs in biota, PCBs levels were also higher in fish and oysters than in surface waters and sediments (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). Fish muscle (1989\u0026ndash;2021) and fish liver (2018\u0026ndash;2021) showed median concentrations of 344.00 ng/g DW (14.90\u0026ndash;10,000 ng/g DW) and 2,032.02 ng/g DW (392.76\u0026ndash;21,600 ng/g DW), respectively. The concentrations of PCBs in fish livers were significantly higher than fish muscle (6x), oysters (7x), sediments (78x), and surface waters (924,000x). PCBs in the muscle tissue of fish were also significantly higher than those in sediments (13x) and surface waters (156,000x). Finally, oyster body-burdens (1987\u0026ndash;2021) had a median concentration of 288.43 ng/g DW (41.55\u0026ndash;588.50 ng/g DW) and were significantly higher than in sediments (11x) and surface waters (131,000x).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.6. NMPs body-burdens in biota from Galveston Bay as reported in this study\u003c/h2\u003e \u003cp\u003eThe sum of total NMPs in the gill/mantle tissue of oysters (11,988.55\u0026thinsp;\u0026plusmn;\u0026thinsp;6,392.18 \u0026micro;g/g DW) was significantly higher than the muscle in fish, at levels 42x higher than catfish (283.74\u0026thinsp;\u0026plusmn;\u0026thinsp;150.56 \u0026micro;g/g DW), and 279x higher than red drum (43.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.30 \u0026micro;g/g DW) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e). For NMPs body-burdens in fish livers, catfish (8,070.80\u0026thinsp;\u0026plusmn;\u0026thinsp;970.99 \u0026micro;g/g DW) had significantly higher levels (4x) of NMPs as compared to red drum (2,291.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1,268.41 \u0026micro;g/g DW).\u003c/p\u003e \u003cp\u003eIn muscle tissue, there was a prevalence of PA comprising of 23\u0026ndash;45% of the sum of total NMPs in catfish and seatrout, and up to 88% in red drum. N66 was the second most abundant NMP (30\u0026ndash;55% sum of total NMPs) in oysters, catfish and seatrouts (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(c), Supplemental Fig.\u0026nbsp;3 (a))\u003c/b\u003e. Lower profiles of PE (13% in oyster, 19% in seatrout), PP (up to 31% in oyster), and SBR (up to 19% in oyster) were also detected. In contrast, in liver tissues of fish only N66 (39% in catfish and 37% in red drum) and SBR (57% in catfish and 39% in red drum) were prominently detected (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(c), Supplemental Fig.\u0026nbsp;3 (b)).\u003c/b\u003e The analysis of NMPs in the livers of catfish was not possible due to insufficient tissue biomass after PAH-PCB analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.7. Overview of historic NMPs levels in Galveston Bay\u003c/h2\u003e \u003cp\u003eGiven the recent development of NMPs quantification using mass spectrometry methods (such as Py-GCMS/MS), our review of environmental datasets begins from \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;2000 and only included studies using Py-GCMS (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e). Our review showed that surface waters contained the lowest NMP concentrations, with a median of 0.001 \u0026micro;g/g (or 0.001 \u0026micro;g/mL of water; min - max of 0.00014\u0026ndash;0.010 \u0026micro;g/g). Sediments had the second lowest NMP concentrations, with a median of 0.16 \u0026micro;g/g DW (min-max of 0.01\u0026ndash;8.76 \u0026micro;g/g DW), approximately two orders of magnitude higher than the levels quantified in surface waters. In contrast, the analysis of biota from the bay showed fish muscle to contain a median of 818.44 \u0026micro;g/g DW (min-max of 43.16\u0026ndash;13,063.30 \u0026micro;g/g DW), roughly three orders of magnitude higher than sediment and six orders of magnitude greater than water; these differences were statistically significant. Fish liver had a median NMP concentration of 7,303.75 \u0026micro;g/g DW (min-max of 2,291.40\u0026ndash;18,166.10 \u0026micro;g/g DW), ~9x higher than fish muscle. Oyster body burdens were the highest overall, with a median of 10,457.14 \u0026micro;g/g DW (min-max of 8,925.70\u0026ndash;11,988.55 \u0026micro;g/g DW).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.1. PAHs body-burdens in biota from Galveston Bay as measured in this study\u003c/h2\u003e \u003cp\u003eEastern oysters exhibited higher total PAH body burdens, approximately 2\u0026times; those of seatrout, 2\u0026times; those of catfish, and 2.5\u0026times; those of red drum (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e). Elevated PAHs concentrations in shellfish compared to finfish observed in this study are consistent with previous reports. For example, Rowe et al. (2020), documented significantly higher concentrations of sum of total PAHs in oysters (203\u0026thinsp;\u0026plusmn;\u0026thinsp;68 ng/g WW) in comparison to spotted seatrout (14\u0026thinsp;\u0026plusmn;\u0026thinsp;8 ng/g WW) sampled from Galveston Bay. This disparity likely stems from oysters\u0026rsquo; filter-feeding behavior, the lipophilic nature of PAHs, and the comparatively limited metabolic capacity of invertebrates to process and eliminate these contaminants. Oysters are capable of filtering approximately 25\u0026ndash;50 gallons of water daily (Ehrich \u0026amp; Harris, 2015; NOAA, 2020), increasing their potential exposure to pollutants such as PAHs (Fisher et al., 2000; Bustamante et al., 2012; Trevisan et al., 2017; Wang et al., 2020). Furthermore, invertebrates generally exhibit lower biotransformation efficiencies than fish, making them less effective at metabolizing and excreting pollutants (Neff et al., 1976; Vidal-Li\u0026ntilde;\u0026aacute;n et al., 2016; Honda \u0026amp; Suzuki, 2020). Consequently, oysters tend to accumulate greater PAH burdens and may serve as sentinel organisms for assessing contaminant exposure in marine ecosystems.\u003c/p\u003e \u003cp\u003eIn contrast to the muscle tissue in fish, their livers exhibited total PAH levels that were 3x (seatrout) to 16x (red drum) higher than in muscle (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a)\u003c/b\u003e). This result likely reflects the lipophilicity of PAHs (Sverdrup et al., 2002) and the elevated lipid content in fish liver relative to muscle tissue (Ando et al., 1993; Arrington et al., 2006). In our study, gravimetric analysis revealed liver lipid levels to be ~4x higher than muscle in catfish, 11x higher in seatrout, and 12x higher in red drum (data not shown). Given the high hydrophobicity of PAHs (i.e., Log Kow\u0026thinsp;=\u0026thinsp;3.37\u0026ndash;6.75) and strong affinity for lipids (Choi et al., 2010), PAHs tend to accumulate more readily in lipid-rich tissues such as the liver. For instance, Blacktip and Bonnethead sharks in the Gulf of Mexico exhibited approximately double the PAHs body burden in liver (2,120\u0026thinsp;\u0026plusmn;\u0026thinsp;106 and 2,200\u0026thinsp;\u0026plusmn;\u0026thinsp;219 ng/g, respectively) compared to muscle tissue (1,150\u0026thinsp;\u0026plusmn;\u0026thinsp;75.70 and 1,080\u0026thinsp;\u0026plusmn;\u0026thinsp;44.20 ng/g, respectively) (Cullen et al., 2019).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.2. PAHs congener profiles and likely sources in biota\u003c/h2\u003e \u003cp\u003eIn the gill/mantle of oysters and in fish muscle, LMW PAHs such as ACE and PHE made up 20\u0026ndash;35% of the total PAHs, with FLU also being prominent in red drum, seatrout, and oysters (10\u0026ndash;15%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(a), Supplemental Fig.\u0026nbsp;1 (a)\u003c/b\u003e). In fish livers, a similar trend was reflected, where FLU contributed\u0026thinsp;~\u0026thinsp;50% across species. ACE was particularly elevated in catfish liver, accounting for 25% of total PAHs (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a), Supplemental Fig.\u0026nbsp;1 (b)\u003c/b\u003e). LMW PAHs consist of less than four aromatic rings, combust between 100\u0026ndash;300\u0026deg;C, and are typically petrogenic in origin (Budzinski et al., 1997). They are mainly associated with petroleum, crude oil and refined petroleum products such as gasoline, kerosine, diesel, lubricating oils etc. (Wolska et al., 2012). The prominence of the LMW PAHs in the bay could be indicative of its petrogenic pollution sources (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Specifically, the presence of crude oil processing facilities around Galveston Bay may contribute to this result (HARC, 2014; Rice, 2019; Trevizo, 2019). Similarly, in Sabine Lake (90 miles east of Houston) biota (red drum and seatrout), the profiles of LMW PAHs such as ACE, PHE and FLU were also found to be prominent (Hernout et al., 2020). In the findings of Williams et al. (2017), after the Texas city oil spill, surface water samples collected from Galveston Bay showed a higher profile of PHE concentration, relative to other PAHs, underscoring the role of petrogenic pollution in LMW PAH contribution. In contrast, BkF, a HMW PAH, made up to 25% of total PAHs in red drum muscles (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(a), Supplemental Fig.\u0026nbsp;1 (a)\u003c/b\u003e). The liver samples showed distinct HMW PAH profiles: BaP reached up to 25% in seatrout, while IcdP dominated red drum (up to 50%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(a), Supplemental.\u003c/b\u003e Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). IcdP was also found to be relatively higher in proportion to other PAHs in Sabine Lake fish in a previous study (Hernout et al., 2020). HMW PAHs have four or more aromatic rings, combust between 400\u0026ndash;700\u0026deg;C and are known to be pyrogenic (Wolska et al., 2012). Pyrogenic sources of PAHs are mainly associated with incomplete combustion of organic matter such as coal, wood, petroleum and garbage (Wolska et al., 2012). Bacosa et al. (2020) noted the prevalence of HMW PAHs in Galveston Bay after Hurricane Harvey (such as BaP, IcdP, BghiP) and concluded their sources to be predominantly combustion related. Together, this data illustrates the mixed sources (petrogenic and pyrogenic) of PAHs in Galveston Bay.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSource-diagnostic assessment of PAHs in oyster and fish tissues (muscle and liver) based on established LMW/HMW ratio criteria. Thresholds indicating pyrogenic origin follow Tobiszewski \u0026amp; Namieśnik (2012); values marked with * denote ratios consistent with predominantly pyrogenic inputs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnostic Ratios\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePyrogenic* if\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOyster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCatfish Muscle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRed drum Muscle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSeatrout Muscle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCatfish Liver\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRed drum Liver\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSeatrout Liver\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum;LMW/\u0026sum;HMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum;COMB/\u0026sum;PAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e~\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLT/(FLT\u0026thinsp;+\u0026thinsp;PYR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eANT/(ANT\u0026thinsp;+\u0026thinsp;PHE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.34*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.72*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.36*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaA/(BaA\u0026thinsp;+\u0026thinsp;CHR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.53*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIcdP/(IcdP+BghiP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.34*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.41*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.00*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHE/ANT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.90*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.39*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.79*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePyrogenic*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e67%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e60%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePetrogenic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e71%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e67%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e83%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e57%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDiagnostic PAH source ratio analysis is a widely used tool for identifying contaminant sources in environmental samples (Blumer, 1976; Simoneit, 1985; Lipiatou \u0026amp; Saliot, 1991; Yunker et al., 1996; Budzinski et al., 1997; Yunker et al., 1999). Our analysis indicated petrogenic sources of PAHs to predominate in Galveston Bay (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Of the ratios calculated, 71% indicated petrogenic dominance in oysters, 67% in catfish muscle, 83% in red drum muscle, and 57% in seatrout muscle. However, liver tissues showed a varied pattern, with catfish liver and red drum liver indicating pyrogenic dominance (67% and 60% respectively). While seatrout liver exhibited equal contributions (50% petrogenic and pyrogenic source) across the ratios calculated (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Averaged across all tissues, petrogenic PAHs constituted 57% and pyrogenic sources 43%, underscoring a mixed signature, with an overall petrogenic dominance. In a study looking at the PAH profiles of fish in Sabine Lake (also hub of petroleum refineries), a prevalence of LMW PAHs was also observed, alluding to the prevalence of petrogenic exposure (Hernout et al., 2020). This is expected given the Texas Gulf Coast's extensive oil production, historical spills, and barge collisions (HARC, 2014; Rice, 2019; Trevizo, 2019). Recent events such as the Texas City \u0026ldquo;Y\u0026rdquo; spill (2014), which released approximately 168,000 gallons of intermediate fuel oil, the ITC Deer Park fire (2019), which resulted in the release of nearly 19.7\u0026nbsp;million gallons of petrochemical products, as well as a barge collision in Pelican island bridge (Galveston; 2,000 gallons of toxic vacuum gas oil was spilt) (Rice, 2019; Edwards et al., 2021; Cohen, 2024). The Gulf of Mexico has also endured catastrophic spills like Deepwater Horizon in 2010, which released 4.9\u0026nbsp;million barrels of oil, leading to documented influx of LMW PAHs (Ramseur, 2010; Liu et al., 2012; Murawski et al., 2014; Snyder et al., 2015; Beyer et al., 2016; Romero et al., 2021). The ongoing Taylor Energy oil spill, active since 2004, continuously discharges oil into the waters of the northwestern Gulf (Warren et al., 2014; Fears, 2018).\u003c/p\u003e \u003cp\u003eThe greater Houston area also experiences significant air pollution from the intense combustion of petroleum products, stemming from both large-scale industrial operations and extensive vehicle traffic. Petrochemical complexes along the Houston Ship Channel, including ExxonMobil\u0026rsquo;s Baytown refinery, LyondellBasell\u0026rsquo;s Channelview plant, and Chevron Phillips\u0026rsquo; Cedar Bayou facility, are major emitters of volatile organic compounds (VOCs), particulates, and polycyclic aromatic hydrocarbons (PAHs) through processes like flaring, process vents, and heat-generation units (EPA, 2021; Patel, 2024a; Ward, 2024). Houston's urban sprawl and vehicular traffic contribute to high rankings in vehicle miles traveled nationally, leading to a continuous stream of exhaust (McGaughey et al., 2004; Qiao et al., 2005; TxDOT, 2025). Maritime traffic and port activities further exacerbate this issue, as the combustion of heavy fuel oil in ocean-going vessels and emissions from cargo handling equipment contribute additional PAH-laden particulates (Williams et al., 2009; Schulze et al., 2018). These combined sources of petroleum combustion are reflected in the PAH diagnostic ratios observed in environmental samples, indicating inputs from the complete and incomplete combustion of fossil fuels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Historic PAHs levels in Galveston Bay\u003c/h2\u003e \u003cp\u003eAn analysis of historical data on PAH concentrations in Galveston Bay reveals a persistent level of contamination and distinct accumulation pattern (surface water\u0026thinsp;\u0026lt;\u0026thinsp;sediment\u0026thinsp;\u0026lt;\u0026thinsp;fish muscle\u0026thinsp;\u0026lt;\u0026thinsp;oyster\u0026thinsp;\u0026lt;\u0026thinsp;fish liver) across environmental matrices (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(a), Supplemental Table\u0026nbsp;2\u003c/b\u003e). The concentration of PAHs in surface water was found to be the lowest, spanning across several orders of magnitude, ranging from 25 ng/L in 2014 (Williams et al., 2017) to a peak of 1,714,000 ng/g in oil-contaminated water the same year from Galveston Bay following the Texas city \u0026ldquo;Y\u0026rdquo; spill (Yin et al., 2015) which released approximately 168,000 gallons of intermediate fuel oil directly into Galveston Bay (Stephens, 1997; DARRP, 2014). PAHs levels measured in 2012 ranged from 800\u0026thinsp;\u0026minus;\u0026thinsp;18,230 ng/L (Rowe et al., 2020), while measurements in 2017 ranged from 25\u0026ndash;175 ng/L (Bacosa et al., 2020). Such variable ranges for PAHs concentrations in the surface waters of Galveston Bay reflect episodic pollution events, indicating water concentrations to be reflective of anthropogenic disturbances (Du et al., 2019).\u003c/p\u003e \u003cp\u003eSediment core samples from Galveston Bay reveal PAHs to be 3 orders of magnitude higher than water, with reported values of 479\u0026thinsp;\u0026minus;\u0026thinsp;250 ng/g between 1968\u0026ndash;1975 (Presley et al., 1998), and 220\u0026ndash;320 ng/g between 1981 and 2001 (Santschi et al., 2001). Additional findings by Jackson et al. (1998) show values ranging from 24 ng/g (in 1991) to 202 ng/g in 1989, while concentrations in the late 1990s ranged from 52 to 724 ng/g (Willett et al., 1997; Presley et al., 1998). More recent data include values of 468.40 ng/g to 89.20 ng/g from 2002 to 2017 (Harmon et al., 2003; Camargo et al., 2021). Despite such variability, sediments are an effective reservoir for PAHs accumulation (Du \u0026amp; Jing, 2018; Usanase et al., 2021). Hydrophobic compounds such as PAHs and PCBs preferentially partition from the water column and adsorb to suspended particulate matter, which eventually settles and becomes incorporated into the sediment (Guo et al., 2009; Sun et al., 2017; Khadhar et al., 2018; Combi et al., 2020). Sediments thus serve as a long-term reservoir or \"sink,\" reflecting cumulative contaminant loads over months to years (Brion \u0026amp; Pelletier, 2005; Bouloubassi et al., 2006; Chiaia-Hern\u0026aacute;ndez et al., 2022).\u003c/p\u003e \u003cp\u003eThe concentrations of PAHs in biota samples (fish and oysters) were found to be 1.45x \u0026ndash; 10\u003csup\u003e7\u003c/sup\u003ex higher than both water and sediment. This increased partitioning into biota is indicative of bioaccumulation. Specifically, lipophilic contaminants readily bioaccumulate into lipid-rich biological compartments (such as hepatic tissue) (N\u0026aacute;cher-Mestre et al., 2010; Torres et al., 2012; Gan et al., 2021). The data from fish tissues illustrate this accumulation pathway. Fish muscle concentrations were 4 orders of magnitude higher than typical PAH levels in surface waters and only 1.5x higher than sediment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(a), Supplemental Table\u0026nbsp;2\u003c/b\u003e). Bioaccumulation in fish livers is even more pronounced at ~7x higher than in muscle. This demonstrates progressive accumulation from surface waters\u0026thinsp;\u0026gt;\u0026thinsp;sediments\u0026thinsp;\u0026gt;\u0026thinsp;biota (Monod \u0026amp; Vindimian, 1991; Barber et al., 2006; Topić Popović et al., 2023). Oysters, as sessile filter-feeders, appear to bioaccumulate higher concentrations of PAHs compared to fish muscle (2.4x higher), sediment (3.5x higher) and water (10\u003csup\u003e7\u003c/sup\u003ex higher), which could be explained by their filter feeding strategy (Fisher et al., 2000; Bustamante et al., 2012; Trevisan et al., 2017; Wang et al., 2020). Previously published studies show a range of high values in oysters, from 488\u0026ndash;9,227 ng/g DW in 2001 (Qian et al., 2001), 203\u0026thinsp;\u0026plusmn;\u0026thinsp;68 ng/g WW in 2012 (Rowe et al., 2020), and 608.51\u0026thinsp;\u0026plusmn;\u0026thinsp;15.72 ng/g DW in 2019 (this study). Together, these findings highlight oysters\u0026rsquo; chronic exposure to PAHs, with levels remaining consistently elevated over the decades. This makes oysters highly effective bioindicators for PAHs in the environment (Sericano et al., 1990; Vaezzadeh et al., 2019).\u003c/p\u003e \u003cp\u003eWhen placed within a broader regional context, PAHs concentrations in Galveston Bay are within range of neighboring bays. For example, the historic sediment concentration of PAHs in Galveston Bay range of 19.8\u0026ndash;479 ng/g which is comparable to an average of 11.5 ng/g from Matagorda Bay (Geiselbrecht Allison et al., 1998) and 140 ng/g in sediments from the Mississippi river delta (Wade et al., 2008). In Matagorda Bay, PAHs body-burdens in fish muscle tissue were 124.40\u0026thinsp;\u0026plusmn;\u0026thinsp;3.00 ng/g DW in gafftopsail catfish, 198.91\u0026thinsp;\u0026plusmn;\u0026thinsp;7.94 ng/g DW in red drum, and 196.40\u0026thinsp;\u0026plusmn;\u0026thinsp;3.26 ng/g DW in spotted seatrout (Mortuza et al., 2025). These body-burdens are 2\u0026ndash;3x lower than their counterparts in Galveston Bay (as reported in this study). The PAH concentrations in fish livers from Galveston Bay (red drum: 3,995.90\u0026thinsp;\u0026plusmn;\u0026thinsp;182.84 ng/g DW; seatrout: 1,651.56\u0026thinsp;\u0026plusmn;\u0026thinsp;76.38 ng/g DW) were broadly comparable to those from Matagorda Bay (red drum: 2,817.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1,200.68 ng/g DW; seatrout: 2,812.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1,683.88 ng/g DW). In Sabine Lake, liver PAH concentrations reported in 2020 ranged from 500 ng/g in gafftopsail catfish to 1,800 ng/g in gar (\u003cem\u003eAtractosteus spatula\u003c/em\u003e) (Hernout et al., 2020), again aligning with the elevated hepatic burdens observed in Galveston. The analysis of PAHs in sharks from the northwestern Gulf of Mexico showed muscle PAHs concentrations to be 1,080\u0026ndash;1,330 ng/g WW and liver concentrations up to 2,200 ng/g WW (2x higher than muscle) (Cullen et al., 2019). Similarly, the PAHs body-burdens in oysters from Galveston Bay range from 203\u0026ndash;608.51 ng/g (Rowe et al., 2020) which is similar to 230.50\u0026thinsp;\u0026plusmn;\u0026thinsp;7.87 ng/g DW collected from Matagorda Bay in 2021(Mortuza et al., 2025), reinforcing that Galveston Bay values, fall well within the regional scale of accumulation.\u003c/p\u003e \u003cp\u003eCompared with levels globally, the PAHs levels in Galveston Bay surface waters are moderately high. For example, the PAHs surface water levels reported by Bacosa et al. (2020) in Galveston Bay (18.95\u0026ndash;167.35 ng/L), are within range of levels observed various U.S. coastal systems, such as Chesapeake Bay (Virginia) (20\u0026ndash;65.7 ng/L) (Gustafson \u0026amp; Dickhut, 1997), Murrells Inlet (South Carolina) (7\u0026ndash;79 ng/L) (Ngabe et al., 2000), and North Inlet (South Carolina) (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;63 ng/L) (Ngabe et al., 2000). And is also within range of values measured elsewhere, such as in Chabahar Bay (Oman) (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;60 ng/L) (Agah et al., 2017), and the Gulf of Gabes (Tunisia) (3.53\u0026ndash;53.73 ng/L) (Fourati et al., 2018). However, the PAH levels reported in Galveston Bay are orders of magnitude lower than those reported in heavily industrialized Asian regions such as the Jiulong River Estuary (Fujian Province, China) (6,960\u0026thinsp;\u0026minus;\u0026thinsp;26,920 ng/L) (Maskaoui et al., 2002), and in Daya Bay (Guangdong Province, China) (4,228\u0026thinsp;\u0026minus;\u0026thinsp;29,325 ng/L) (Zhou \u0026amp; Maskaoui, 2003). Taken together, this distinct elevation in Galveston Bay concentrations relative to other U.S. locations highlights the influence of regional urbanization and industrial activities along the Houston Ship Channel and surrounding watershed, though still falling short of the higher PAH burdens documented in some Asian coastal industrial zones.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.4. PCBs body-burdens in biota from Galveston Bay as determined in this study\u003c/h2\u003e \u003cp\u003ePCBs body-burdens in the gill/mantle tissue of oysters (286.56\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65 ng/g DW) was ~\u0026thinsp;1.4x \u0026ndash; 19x higher than the levels measured in fish muscle (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). However, the levels of PCBs were the highest in fish livers, exhibiting concentrations ~6x \u0026minus;\u0026thinsp;42x higher than in muscle (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(b)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). Such higher accumulation in the liver is a likely reflection of the lipophilicity of PCBs (Log Kow\u0026thinsp;=\u0026thinsp;4.43\u0026ndash;5.02) (Safe \u0026amp; Hutzinger, 1984; Ballschmiter et al., 2005; Bourez et al., 2013), and the over 4x \u0026minus;\u0026thinsp;12x higher lipid content of livers relative to muscle for the fish analyzed in this study (Ando et al., 1993; Arrington et al., 2006). Analogous trends have been reported in the Gulf of Mexico, where Blacktip, and Bonnethead sharks were shown to have double the hepatic PCB body-burdens compared to muscle (Cullen et al., 2019). Similarly, fish (gafftopsail catfish, red drum, spotted seatrout) collected from Matagorda Bay were shown to have 11x \u0026minus;\u0026thinsp;15x higher concentrations of PCBs in livers in comparison to muscle (Mortuza et al., 2025), demonstrating the propensity of lipophilic PCBs in accumulating in lipid rich liver.\u003c/p\u003e \u003cp\u003ePCBs are entirely anthropogenic in origin (Delzell et al., 1994), and although banned in the 1970s, they persist in the environment and are classified as persistent pollutants (Boyle \u0026amp; Highland, 1979). Dioxin-like PCBs (DL-PCBs) have chlorine atoms at the para (opposite sides of the benzene ring) position and two or more at meta (one carbon away from the para) positions, and thus share toxic coplanar (flat, planar) structures with 2,3,7,8-tetrachlorodibenzo-p-dioxin (Safe et al., 1985). There were twelve such structural PCB congeners monitored in our study (ATSDR, 2023), and included non-ortho (no adjacent chlorine) PCBs 77, 81, 126, and 169; and mono-ortho (one adjacent chlorine) PCBs 105, 114, 118, 123, 156, 167, and 189 (Giesy \u0026amp; Kannan, 1998). A higher chlorination of the biphenyl rings of PCBs tend to correspond with lower environmental degradation and increased persistence (Delzell et al., 1994). The PCBs profiles of liver samples in fish from Galveston Bay biota (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(b), Supplemental Fig.\u0026nbsp;2 (b)\u003c/b\u003e) showed the DL-PCB, PCB 126, to be the most prominent congener in catfish (50% sum of total PCBs), red drum (38% sum of total PCBs) and seatrout (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;25% sum of total PCBs). The prevalence of PCB 126 in Galveston Bay could be of concern due to its dioxin-like structure and thus its toxicity. PCBs are lipophilic and tend to bioaccumulate in organisms (Hawker \u0026amp; Connell, 1988; Beyer \u0026amp; Biziuk, 2009), leading to biomagnification through the food chain (Walters et al., 2011). This poses toxicity risks to aquatic species and can expose humans to dioxin-like compounds via seafood (Perell\u0026oacute; et al., 2015). PCBs have contributed to population declines in bald eagles (\u003cem\u003eHaliaeetus leucocephalus\u003c/em\u003e) due to contaminated finfish consumption causing thinning of eggshells (Bowerman et al., 1995). And are also linked to reduced cetacean populations (endocrine disruption) (Hall et al., 2018). In humans, they\u0026rsquo;re associated with endocrine disruption, including immunological, metabolic, and neurological disorders through seafood consumption with higher levels in historically contaminated areas (Birnbaum, 1994; Crinnion, 2011).\u003c/p\u003e \u003cp\u003eAmong the NDL-PCBs congeners, PCB 52 was prominent in red drum muscle (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;75% sum of total PCBs) and in seatrout (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;30% sum of total PCBs) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(b), Supplemental Fig.\u0026nbsp;2 (a)\u003c/b\u003e). PCB 128 was prominent in oysters (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;50% sum of total) and in seatrout (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;25% sum of total). In catfish from Galveston Bay, there were high proportions of PCB 138 and 153 (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;20% sum of total PCBs). Lastly, a prominent signature of PCB 128 in seatrout liver (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;25% sum of total) was also detected. Anaerobic microbial degradation of highly chlorinated PCBs remove chlorine atoms from the \u003cem\u003emeta\u003c/em\u003e and \u003cem\u003epara\u003c/em\u003e positions, producing lower-chlorinated ortho-substituted congeners like PCBs 18, 52, and 128 (Tiedje et al., 1993; Abramowicz, 1995). Their presence in samples may reflect the prominence of such microbial processes. Similarly, PCBs 128 and 153 were found to be prominent in the muscle tissue of juvenile sharks sampled from the northwestern Gulf of Mexico (Cullen et al., 2019). While in fish sampled from Sabine Lake (TX/LA border), PCB 18 was found to be the most prominent congener in muscle tissue (Hernout et al., 2020). Persistent DL and NDL-PCB contamination may be driven by legacy industrial activity and sediment resuspension facilitated by tidal forces, shipping, and dredging (Yeager et al., 2007).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.5. Historic PCB levels in Galveston Bay\u003c/h2\u003e \u003cp\u003eThe historical record of PCBs in Galveston Bay reveals persistent contamination and bioaccumulation. Despite a ban on PCBs production in the U.S. in 1979 (Safe et al., 1985), and the natural flushing (tidal exchange, freshwater inflow) of the bay system (Rayson et al., 2016), there has been no significant long-term decrease in PCBs levels in sediment. Early measurements from the 1960s reveal sediment levels to range from ~\u0026thinsp;10\u0026ndash;100 ng/g in the bay (Presley et al., 1998; Mahler \u0026amp; Van Metre, 2003) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(b), Supplemental Table\u0026nbsp;3\u003c/b\u003e). These levels have remained relatively consistent through the 1980s and 1990s, with values ranging from ~\u0026thinsp;5\u0026ndash;100 ng/g (Jackson et al., 1998; Santschi et al., 2001). And more recently, sediment concentrations have remained\u0026thinsp;~\u0026thinsp;\u0026lt;\u0026thinsp;100 ng/g sediment (Mahler \u0026amp; Van Metre, 2003; Rifai \u0026amp; Palachek, 2007; Lakshmanan et al., 2010).\u003c/p\u003e \u003cp\u003eThe overall lack of a significant decline in PCBs indicates their stable sequestration into sediments (Lake et al., 1990; Lang et al., 2018). For legacy pollutants like PCBs, this could imply that historically contaminated sediments acts as a long-term reservoir, potentially making them chronically bioavailable due to intermittent reconstitution (i.e., by storms, dredging, etc.) (Horzempa \u0026amp; Di Toro, 1983; Yeager et al., 2007; Lang et al., 2018). A major historical contributor of PCBs into the bay was the Champion Paper Mill, which in the 1960s disposed of PCB laden paper sludge in unlined pits along the San Jacinto River (Iyer et al., 2016; Govindarajan et al., 2023). These disposal sites are designated as Superfund sites and are of continuous cause for concern due to the persistent release of PCBs, dioxins, and furans into the bay through leaching and mobilization of pollutants through sediment disturbance and hydrological processes (Tucker, 2012; Iyer et al., 2016). Industrial runoff from facilities along the Houston Ship Channel and adjoining waterways further exacerbates this contamination, as do inflows from rivers such as the San Jacinto and Trinity, which carry sediments and pollutants into the bay (Rifai \u0026amp; Palachek, 2007). Regular dredging operations within the ship channel and intense maritime traffic also resuspend PCB contaminated sediments, facilitating their redistribution into the water column and uptake by biota (Yeager et al., 2010; Howell, 2012). This may explain why, in part, values have not declined in the biota despite the ban on these materials over more than 40 years.\u003c/p\u003e \u003cp\u003eIn contrast to sediments, the reported water concentrations are 4 orders of magnitude lower than those measured in the sediment, and 5\u0026ndash;6 orders lower than biota PCB burdens (oyster, fish muscle and liver) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(b)\u003c/b\u003e). This vast difference, underscores the potent lipophilic nature of these compounds and their propensity to partition out of the water and accumulate in organic-rich matrices (Porte \u0026amp; Albaig\u0026eacute;s, 1994; Borg\u0026aring; et al., 2005; Walters et al., 2011). From 2002 to 2015, reported concentrations in surface water remain within a range spanning from ~\u0026thinsp;1\u0026ndash;30 ng/L (\u003cb\u003eSupplemental Table\u0026nbsp;3)\u003c/b\u003e, with no clear change in overall trends. For example, the survey of surface waters from 2002\u0026ndash;2003, measured levels ranging from ~\u0026thinsp;1\u0026ndash;13 ng/L (Rifai \u0026amp; Palachek, 2007; Howell et al., 2008). In subsequent years (i.e., 2005\u0026ndash;2009), the overall PCBs levels in surface waters range from 1\u0026ndash;30 ng/L (Lakshmanan et al., 2010; Howell et al., 2011; Balasubramani et al., 2014). A more recent survey in 2015, indicated surface water levels to remain within the same order of magnitude at 1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28 ng/L (Howell \u0026amp; Rifai, 2015). These data reinforce the observation that, despite spatial variability, PCB concentrations in surface waters have remained low and relatively stable over time in comparison to sediment and biota.\u003c/p\u003e \u003cp\u003eIn fish muscle, studies quantifying PCBs body-burdens (from 1989\u0026ndash;2013), report levels to range from 14.90\u0026ndash;6,384.00 ng/g DW. For example, in tidewater silverside (1,040\u0026thinsp;\u0026plusmn;\u0026thinsp;76 ng/g DW) and sheepshead minnow (2,160\u0026thinsp;\u0026plusmn;\u0026thinsp;306 ng/g DW) from 1989 (King, 1989), alongside similarly elevated concentrations in Gulf killifish (1,800\u0026thinsp;\u0026plusmn;\u0026thinsp;240 ng/g DW), Gulf menhaden (880\u0026thinsp;\u0026plusmn;\u0026thinsp;144 ng/g DW), and striped mullet (280\u0026thinsp;\u0026plusmn;\u0026thinsp;40 ng/g DW) from the same study. Data from 2002\u0026ndash;2003 show 327.20 ng/g DW and 416.80 ng/g DW in estuarine fish (Rifai \u0026amp; Palachek, 2007), while catfish sampled in 2003 exhibited a striking range of 16.52\u0026ndash;6,384 ng/g DW (Howell et al., 2008). Subsequent studies from 2008 reported 548\u0026thinsp;\u0026plusmn;\u0026thinsp;432 ng/g DW in catfish and 1,140\u0026thinsp;\u0026plusmn;\u0026thinsp;1212 ng/g DW in seatrout and Atlantic croaker (Lakshmanan et al., 2010), followed by concentration levels of 408\u0026thinsp;\u0026plusmn;\u0026thinsp;264 ng/g DW in gafftopsail catfish, 84\u0026thinsp;\u0026plusmn;\u0026thinsp;44 ng/g DW in red drum, and 208\u0026thinsp;\u0026plusmn;\u0026thinsp;132 ng/g DW in spotted seatrout from 2011 (Worth, 2013). Most recently, this study found 209.29\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28 ng/g DW in gafftopsail catfish, 14.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28 ng/g DW in red drum, and 188.69\u0026thinsp;\u0026plusmn;\u0026thinsp;3.48 ng/g DW in spotted seatrout collected in 2019, further reinforcing the consistent elevation of PCB concentrations in fish muscle relative to environmental matrices. These levels are substantially higher than any recorded sediment concentrations, indicating biomagnification (Porte \u0026amp; Albaig\u0026eacute;s, 1994; Borg\u0026aring; et al., 2005). This process is further evidenced in the liver, which generally concentrates PCBs to even higher levels. For instance, the median concentration of PCBs in fish liver across various species from literature (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(b), Supplemental Table\u0026nbsp;3\u003c/b\u003e) was found to be 6x higher than fish muscle (significantly different). Specifically in Galveston Bay fish data from this study alone, liver PCBs concentrations were approximately 7x higher in gafftopsail catfish, 42x higher in red drum, and 11x higher in spotted seatrout compared to muscle tissue. Similarly, in previously published PCBs body burdens data from Matagorda Bay, liver concentrations exceeded muscle by roughly 15x in gafftopsail catfish, 13x in red drum, and 11x in spotted seatrout (Mortuza et al., 2025). Previously reported PCBs concentrations in sharks from the northern Gulf of Mexico show a similar disparity in liver vs muscle, with levels 13x higher in the livers of bull sharks vs. muscle, 5x higher in blacktip sharks, and 4x higher in bonnethead sharks (Cullen et al., 2019). Therefore the review of these datasets demonstrates the overall greater accumulation of PCBs into aquatic biota vs. environmental matrices (such as surface waters and sediments) (Monod \u0026amp; Vindimian, 1991; Barber et al., 2006; Topić Popović et al., 2023).\u003c/p\u003e \u003cp\u003eFurthermore, our data shows oysters to be effective indicators of PCBs and PAHs exposures. As filter feeders, they continuously process water and suspended particles, integrating contaminant exposure over time (Fisher et al., 2000; Bustamante et al., 2012; Wontor et al., 2023). Our analysis of historical data (1992\u0026ndash;2019) shows oysters body-burdens to range from 77\u0026ndash;1,100 ng/g DW (286.56\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65 ng/g DW reported in this study) (Sericano et al., 1992; Sericano et al., 1994). Moreover, these values are comparable to those reported in the wider Gulf of Mexico (62\u0026ndash;79 ng/g DW) and in an adjacent bay, Matagorda Bay (290.29\u0026thinsp;\u0026plusmn;\u0026thinsp;4.49 ng/g DW) (Sericano et al., 1990; Mortuza et al., 2025). This indicates that Galveston Bay reflects a broader regional trend in PCBs exposure among filter-feeding bivalves. These concentrations are higher than those in sediment (11x) and water (fiver order of magnitude), highlighting their role in accumulating PCBs from their environment and making them a valuable sentinel species for monitoring the bioavailability of persistent organic pollutants in the Galveston Bay ecosystem (Sericano et al., 1990; Sericano et al., 1992; Jackson et al., 1998).\u003c/p\u003e \u003cp\u003eGalveston Bay exhibits similar PCB concentrations in sediment among Gulf of Mexico coastal sites, with a reported value of 1.10 ng/g (Giam \u0026amp; Chan, 1978), on par with Nueces Estuary (1.50 ng/g) (Giam \u0026amp; Chan, 1978). Apalachicola Bay (FL) (3 ng/g) (Livingston et al., 1978), and Apalachicola River (1 ng/g) (Elder \u0026amp; Mattraw Jr, 1984). This is notably lower than the Mississippi Delta (LA), which shows a an elevated concentration of 18.70 ng/g of PCB in sediment, over 17 times higher, suggesting a legacy of industrial discharge or riverine input from the Mississippi River system (Giam \u0026amp; Chan, 1978; Presley et al., 1998; Santschi et al., 2001). These differences may reflect variations in watershed industrialization, hydrodynamics, and sedimentation rates (Du et al., 2019).\u003c/p\u003e \u003cp\u003eOn a global context, the PCBs concentrations in Galveston Bay position it as a moderate-to-heavily impacted site. Water concentrations of PCBs range from 0.12 to 2.61 ng/L, while sediment concentrations span 0.47 to 1418 ng/g (Howell et al., 2008). These values place Galveston Bay among many U.S. coastal systems in terms PCB contamination in surface water, including San Diego Bay (0.024\u0026ndash;0.419 ng/L) (Zeng et al., 2002), Baltimore Harbor (0.10\u0026ndash;1.52 ng/L) (Bamford et al., 2002), Palos Verdes Peninsula (0.06\u0026ndash;1.14 ng/L) (Zeng et al., 1999), and Lake Michigan (0.34\u0026ndash;1.74 ng/L) (Pearson et al., 1996), indicating its similar industrial legacy. However, water concentrations in Galveston Bay are lower than those reported in more legacy and current industrial sites such as New York Harbor (6.70\u0026ndash;9.40 ng/L) (Totten et al., 2001) and the Delaware River (1.20\u0026ndash;6.50 ng/L) (Rowe et al., 2007). A similar story is portrayed in Galveston Bay sediment burdens of PCB (up to 1418 ng/g) (Howell et al., 2008) which is much higher than the reported sediment burdens in Bahrain coastal region (0.18\u0026ndash;7.41 ng/g) (De Mora et al., 2005), Salton Sea Lake (116\u0026ndash;304 ng/g) (Sapozhnikova et al., 2004) and Rio de la Plata estuary, Argentina (0.04\u0026ndash;98.50 ng/g) (Colombo et al., 2005), Busan Bay, Korea (5.71\u0026ndash;199 ng/g) (Hong et al., 2005), and Singapore\u0026rsquo;s southwestern coast (1.40\u0026ndash;329.60 ng/g) (Wurl \u0026amp; Obbard, 2005), reinforcing its status as a high-contamination zone. However, Galveston bay remains below the higher sediment burdens documented in Chesapeake Bay (8\u0026ndash;2150 ng/g) (Ashley \u0026amp; Baker, 1999) and Narragansett Bay (20.80\u0026ndash;1760 ng/g) (Hartmann et al., 2004) and Venice Lagoon, Italy (2\u0026ndash;2049 ng/g) (Frignani et al., 2001), where legacy industrial inputs and hydrodynamic trapping may have driven persistent contamination, underscoring Galveston Bay as a moderate to heavily impacted site in terms of PCB contamination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.6. NMPs body-burdens in biota from Galveston Bay as determined in this study\u003c/h2\u003e \u003cp\u003eThis study is the first to use Py-GCMS/MS to quantify NMPs in fish from Galveston Bay. Previously, oysters showed significantly higher NMPs body-burdens (11,988.55\u0026thinsp;\u0026plusmn;\u0026thinsp;6,392.18 \u0026micro;g/g DW) than catfish (283.74\u0026thinsp;\u0026plusmn;\u0026thinsp;150.56 \u0026micro;g/g DW) and red drum (43.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.30 \u0026micro;g/g DW) muscle (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e). This elevated accumulation in oysters likely reflects their filter-feeding nature, accumulating higher level of pollutants over time (Ehrich \u0026amp; Harris, 2015; NOAA, 2020). Ribeiro et al. (2021) quantified NMPs body-burdens in oysters (\u003cem\u003eSaccostrea glomerata\u003c/em\u003e) of up to 39,000 \u0026micro;g/g, which is ~3x higher than those reported in our study for oysters from Galveston Bay.\u003c/p\u003e \u003cp\u003eIn comparison to fish muscle, MPs body-burdens were markedly greater in fish livers, at ~\u0026thinsp;29x higher in catfish (vs. catfish muscle) and ~\u0026thinsp;53x higher in red drum (vs. red drum muscle). The higher levels of NMPs in livers is a likely reflection of the liver\u0026rsquo;s dense vascularization and its central role in removing xenobiotics from the body (Wisse et al., 1985; Wood, 2014; Zhao et al., 2014; Ozougwu, 2017). Controlled laboratory studies show a preferential bioaccumulation of NMPs in the hepatic tissue of fish vs. other tissues. For example, early juvenile European seabass (\u003cem\u003eDicentrarchus labrax\u003c/em\u003e) exposed to a mixture of environmental microplastics sized 0.45\u0026ndash;3 \u0026micro;m for 3 to 5 days exhibited size-dependent accumulation, with liver concentrations approximately 4x higher than those in the gut and 3x higher than in the gills. While goldfish (\u003cem\u003eCarassius auratus\u003c/em\u003e) exposed to 44 nm polystyrene nanoplastics at 100 \u0026micro;g/L for 30 days, accumulated ~\u0026thinsp;14x higher concentration in the liver than in muscle (Brandts et al., 2022), underscoring the higher bioaccumulation of NMPs in the liver.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.7. NMP profiles and average human daily intake\u003c/h2\u003e \u003cp\u003eAmong the various types of plastics quantified, Nylon-66 (N66) emerged as one of the most prevalent polymers in muscle (32\u0026ndash;55% of total NMP) and liver (37\u0026ndash;39% of total NMP) from fish (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(c), Supplemental Fig.\u0026nbsp;3 (a)\u003c/b\u003e). Known for its durability and resistance to abrasion, N66 is primarily used in textiles such as carpets, clothing, and upholstery as well as ropes, cords, fishing nets, and toothbrush bristles (Stafford et al., 1986; Zhang et al., 2010; Shakiba et al., 2021). Recreational and commercial fishing in the area as well as laundry wastewater can be major contributors to N66 pollution in the bay (Saturno, 2020; Vassilenko et al., 2021; Le et al., 2022). Polyamide (PA) also exhibited a prominent abundance in red drum (89% of total NMPs) and seatrout (20% of total NMPs) muscle. Known for its strength, flexibility, and resistance to heat and chemicals, PA is widely used in consumer goods such as kitchen utensils, sportswear, and luggage, as well as in industrial applications including automotive components, electrical connectors, and machine parts (Wesołowski \u0026amp; Płachta, 2016; Kondo et al., 2022; Kohutiar et al., 2025). Polyethylene (PE) comprised\u0026thinsp;~\u0026thinsp;13% of the total detected NMPs in oysters and 19% in seatrout muscle (\u003cb\u003eSupplemental Fig.\u0026nbsp;3 (a)\u003c/b\u003e). Due to its flexibility, PE is extensively utilized in packaging materials, plastic bags, pellets (nurdles), plastic wraps, bottles, and containers as well as in medical items, pipes, and fittings (Duffy Jr, 1949; Savas et al., 2016; Ronca, 2017). Polypropylene (PP) represented 31% of total NMPs identified in oysters and 6% of NMPs in seatrout muscle from Galveston Bay. Widely adopted in packaging (e.g., bottles, tubs), automotive parts (bumpers, battery housings), and textile-based goods (diapers, filtration fabrics), it is also common in household items like furniture and reusable containers (Guidetti et al., 1996; Maddah, 2016; Hossain et al., 2024). The recurring detection of PE and PP in aquatic organisms agrees with findings from Ribeiro et al. (2020) in Australia, where PE was the most abundant NMP (\u0026lt;\u0026thinsp;2,400 \u0026micro;g/g WW tissue), and PP was also detected at lower concentrations (\u0026lt;\u0026thinsp;60 \u0026micro;g/g WW tissue). Additionally, Lim et al. (2022) reported that globally, fibrous microplastics dominate in the food ingested by fish (70% of all plastics), with PE accounting for a significant fraction (16% of the total fiber). Unsurprisingly, consumer single use plastics such as PE and PP are prominently featured due to their use and abundance, especially in urban areas (McDermott, 2016). Lastly, Styrene-Butadiene Rubber (SBR) was also prominently detected in oysters (17% of total NMPs) as well as in catfish livers (56% of total NMPs) and red drum livers (43% of total NMPs). SBR is a synthetic polymer prized for its abrasion resistance and flexibility, and is thus most commonly used in automobile tires, which account for a major share of its global use (Henderson, 1987; Dhanorkar et al., 2021). It is also widely used in shoe soles, conveyor belts, seals, and gaskets (Henderson, 1987; Miller et al., 1994). Tire wear from the Houston urban sprawl and its accompanying traffic are likely contributors of SBR into Galveston Bay (Wik \u0026amp; Dave, 2009; Li et al., 2023; Nelson, 2024). Together, our analysis indicates widespread plastic pollution and exposure of biota from Galveston Bay.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimated Average Daily Intake (ADI) of NMPs in adults (mg NMPs/Kg of body weight/day), reported by species with corresponding minimum and maximum intake values. Each ADI estimate was further converted to an annual intake to characterize likely yearly NMP exposure.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOysters\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eADI (min - max)\u003c/p\u003e \u003cp\u003e(mg NMPs/Kg body weight/day)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYearly Intake (min - max)\u003c/p\u003e \u003cp\u003e(mg NMPs/Kg body weight/year)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85 (0.01\u0026ndash;4.80)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309.98 (4.45\u0026ndash;1752.60)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCatfish\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03 (0\u0026ndash;0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.64 (0\u0026ndash;42.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRed drum\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0\u0026ndash;0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.47 (0\u0026ndash;2.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeatrout\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22 (0\u0026ndash;4.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e443.90 (0.01\u0026ndash;1763.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFinally, the Average Daily Intakes (ADIs) of NMPs in humans through seafood consumption was estimated to be 443.90 mg NMPs/kg adult human body weight/year from seatrout, 309.98 mg NMPs/kg adult human body weight/year from oysters, and 1.47 mg NMPs/kg adult human body weight/year from the consumption of red drum muscle (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This amounts to the consumption of 0.103 g of plastics from the consumption of red drums and 21 and 31 g of plastics from the consumption of oyster and seatrout per year, respectively. For reference, an average plastic credit card weighs 6g. These consumption values are comparatively modest next to prior estimates suggesting humans ingest up to \u0026lt;\u0026thinsp;5 g of microplastics weekly (or \u0026lt;\u0026thinsp;260 g annually) (Senathirajah et al., 2021). However, our findings are consistent with those reported by Ribeiro et al. (2021), who report the concentration of seafood collected from Brisbane River estuary in Australia. Using Py-GCMS, they quantified 100 \u0026micro;g/g of plastics in oysters and 2,850 \u0026micro;g/g in sardines. Applying a similar ADI calculation, this yields a projected yearly intake of 1.1 to 31.2 g of plastic a year from oyster and sardine respectively, which is comparable to our estimates for Galveston Bay.\u003c/p\u003e \u003cp\u003eIn humans, Py-GCMS was used to detect NMPs at 1.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49 \u0026micro;g/mL in blood (Leslie et al., 2022) and 3\u0026ndash;36 \u0026micro;g/g in human feces (Zhang et al., 2021). In human brain\u0026rsquo;s frontal cortex, microplastic concentrations ranging from 3,345\u0026ndash;4,917 \u0026micro;g/g WW have been detected (Nihart et al., 2025), indicative of higher bioaccumulation in the brain in comparison to blood and feces. Human brain NMP concentration exceeded that in oyster tissue and seatrout muscle by ~\u0026thinsp;1.7\u0026times; (Nihart et al., 2025), which could be indicative of biomagnification, although further evidence is required. While we can estimate the ADI of plastics from seafood, the toxicological effects of NMPs are still an ongoing area of inquiry. A meta-analysis by Liu et al. (2023) explored the toxic effects of plastics on biological endpoints in rodent models. Out of 1,762 biological endpoints reviewed, 53% showed the disruption on lipid metabolism, oxidative stress, reproduction, and glucose metabolism. The ADI calculated for the consumption of oysters and fish in our study (i.e., 0.28 mg/day \u0026ndash; 84 mg/day) could be compared to doses tested in multiple murine models reported in the literature. For example, male adult mice exposed to fluorescent and pristine polystyrene microplastics (PS MPs, 5 \u0026micro;m and 20 \u0026micro;m) at 0.01\u0026ndash;0.50 mg/day for up to 28 days exhibited hepatic and renal accumulation, disturbances in energy and lipid metabolism, oxidative stress, and reduced acetylcholinesterase activity (Deng et al., 2017). Similarly, male C57BL/6J mice receiving 0.5 mg/day of 0.5 \u0026micro;m PS MPs for four weeks showed pronounced immune modulation, with up‑regulation of pro‑inflammatory cytokines and down‑regulation of anti‑inflammatory mediators via NF‑κB pathway activation (Zhao et al., 2021). Adverse reproductive effects have also been reported at comparable daily intakes. For example, male and female C57BL/6 mice exposed to pristine PS MPs (5.0\u0026ndash;5.9 \u0026micro;m) at 0.1 mg/day for 30\u0026ndash;44 days accumulated particles in gonads, with reduced ovary size, follicle number, altered reproductive hormones, and decreased pregnancy rates (Wei et al., 2022). Female mice gavage fed with MPs (0.79 \u0026micro;m) at 30 mg/kg/day for 35 days, corresponding to a per‑animal daily mass within our range, and showed multi‑organ accumulation, oxidative stress in oocytes, and reproductive toxicity (Liu et al., 2022). Comparable doses have also elicited gastrointestinal and hepatic effects. In C57BL/6 male mice fed polyethylene (PE) MPs (10\u0026ndash;150 \u0026micro;m) at 2\u0026ndash;200 \u0026micro;g/g feed for five weeks developed gut microbiota dysbiosis, intestinal inflammation, and altered T‑cell subsets (Li et al., 2020). Male mice exposed to PE MPs (100 nm) at 600 \u0026micro;g/day for 15 days exhibited altered liver function parameters (Abdel-Zaher et al., 2023), while ingestion of PE microbeads (36 \u0026micro;m and 116 \u0026micro;m) at 100 \u0026micro;g/g feed for 6\u0026ndash;9 weeks exacerbated hepatic fibrogenesis (Djouina et al., 2023). Taken together, these studies demonstrate that daily microplastic intakes in the hundreds of micrograms to low‑milligram range are sufficient to induce measurable biological effects in mice across multiple organ systems.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.8. Historic NMPs levels in Galveston Bay\u003c/h2\u003e \u003cp\u003eGiven the relatively recent concern and awareness for NMPs pollution in the aquatic environment (Burns \u0026amp; Boxall, 2018; Garcia-Vazquez \u0026amp; Garcia-Ael, 2021), there is an overall paucity of environmental data in Galveston Bay from before 2019. What little exists is count based microplastic data that is not comparable to our analytical concentration-based approach using Py-GCMS/MS. Therefore, our analysis of NMPs trends commences from 2019 and onwards to compare different environmental matrices such as water, sediment, fish muscle, fish liver, and oysters (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e, \u003cb\u003eSupplemental Table\u0026nbsp;4\u003c/b\u003e). The concentrations of NMPs in surface waters was found to be the lowest, ranging from 0.82\u0026ndash;19.8 \u0026micro;g/L (Gahn et al., 2025). In contrast, recent sediment core samples from Galveston Bay reveal NMPs concentrations to be two orders of magnitude higher than in the surface waters. Data from 2021\u0026ndash;2024 showed a range of concentration from 0.01 to 8.76 \u0026micro;g/g (Summers et al., 2024). Sediments are the ultimate sink for NMPs as they can sequester into sediments (from water) with marine snow (particles falling from the upper ocean to the deep sea) (Wu et al., 2025), and become incorporated into the sediment (Sun et al., 2021; Martin et al., 2022). As a result, sediments may serve as a long-term reservoir or \"sink\u0026rdquo; for plastics (Martin et al., 2020; Martin et al., 2022). Plastics have been reported to form geological formations recently named, \u0026ldquo;plastiglomerate\u0026rdquo; or \u0026ldquo;plastistone\u0026rdquo; (plastic and pre-existing rock/ sand lithified together), which have been discovered globally (De-la-Torre et al., 2022; Rakib et al., 2023; Wang \u0026amp; Hou, 2023). This new geological formation has been proposed to mark the beginning of a new era, the \u0026ldquo;Plasticene\u0026rdquo; (Rangel-Buitrago et al., 2022). The deposition of NMPs via marine snow may also make them more bioavailable to marine bivalves (Porter et al., 2018). Similarly, fish have also been reported to accumulate NMPs (Ribeiro et al., 2020; Ribeiro et al., 2021; Mortuza et al., 2025). Together, ocean biota may bioaccumulate NMPs over their lifetime, providing a long-term mechanism for accumulation.\u003c/p\u003e \u003cp\u003eThe quantification of NMPs in fish muscle has revealed concentrations that are six orders of magnitude higher than those measured in surface waters and three orders of magnitude higher than sediments (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003e(c)\u003c/b\u003e, \u003cb\u003eSupplemental Table\u0026nbsp;4\u003c/b\u003e). This trend is evident across multiple species in Galveston Bay. Fish muscle body-burdens of NMPs varied widely across species, ranging from a minimum of ~\u0026thinsp;640 \u0026micro;g/g dry weight (DW) in juvenile trout to a maximum of 2,410.20 \u0026micro;g/g DW in clupeids (e.g., menhaden, shads), with mullet showing intermediate levels of up to 1,732.92 \u0026micro;g/g DW (our unpublished data). While more recent data from 2021 revealed striking interspecies differences: red drum exhibited the lowest concentrations (43.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.30 \u0026micro;g/g DW), whereas spotted seatrout showed significantly higher bioaccumulation (13,063.30\u0026thinsp;\u0026plusmn;\u0026thinsp;6,225.16 \u0026micro;g/g DW) of NMPs. Similar trends were observed in Matagorda Bay (an adjacent estuary to Galveston Bay), where gafftopsail catfish and spotted seatrout had elevated levels (1,636.97\u0026thinsp;\u0026plusmn;\u0026thinsp;786.63 and 966.71\u0026thinsp;\u0026plusmn;\u0026thinsp;206.69 \u0026micro;g/g DW, respectively), contrasting with lower concentrations in red drum (355.42\u0026thinsp;\u0026plusmn;\u0026thinsp;183.75 \u0026micro;g/g DW) (Mortuza et al., 2025). These findings suggest species-specific uptake and retention mechanisms, potentially influenced by trophic level, feeding behavior, and habitat use (Wootton et al., 2021; da Costa et al., 2023). The accumulation within fish is even more pronounced in the liver, demonstrating a progressive accumulation from the environment into muscle tissue and subsequent sequestration and concentration in the liver (possibly due to dense vascularization) (Wisse et al., 1985; Wood, 2014; Ozougwu, 2017). In Galveston Bay, gafftopsail catfish and red drum exhibited liver concentrations approximately 28x and 53x higher than their respective muscle tissue (this study). In Matagorda Bay, red drum showed a similar pattern with liver levels about 51x higher than muscle and 7x higher in spotted seatrout (Mortuza et al., 2025). These differences highlight increased bioaccumulation in the liver.\u003c/p\u003e \u003cp\u003eOysters, as sessile filter-feeders, exhibit greater bioaccumulation of NMPs compared to fish muscle (13x lower), sediment (four orders of magnitude lower) and water (seven orders of magnitude lower), which could be explained by their filter feeding strategy (Ribeiro et al., 2019; NOAA, 2020). While oyster have been documented to ingest particles preferentially (Newell \u0026amp; Jordan, 1983; Shumway et al., 1985), smaller polystyrene microplastic beads (6\u0026ndash;45 \u0026micro;m) have been demonstrated to be taken up by oysters, with 88\u0026thinsp;\u0026minus;\u0026thinsp;68% ingestion from the water (Dunphy et al., 2006; Ward et al., 2019). In Galveston Bay, oyster tissue body burden of NMPs were found to be 11,988.55\u0026thinsp;\u0026plusmn;\u0026thinsp;6392.18 \u0026micro;g/g DW (this study), while those from Matagorda Bay measured slightly lower at 8,925.72\u0026thinsp;\u0026plusmn;\u0026thinsp;2608.77 \u0026micro;g/g DW (Mortuza et al., 2025). These levels were significantly higher than those measured in the muscle tissues of fish from each respective bay. Together, these findings highlight oysters\u0026rsquo; chronic exposure to NMP from water and sediment as sources due to their sessile filter feeding nature. This makes oysters effective bioindicators, as their tissues provide a long-term measure of NMP bioavailability from the environment (Bendell et al., 2020; Savoca et al., 2024).\u003c/p\u003e \u003cp\u003eAt present, we are unable to compare the analytical concentrations quantified using Py-GCMS/MS with other studies that rely on microscopy to count microplastics particles in environmental matrices (i.e., as particles/m\u0026sup2; or particles/kg). Previous studies have reported an average of 61.08\u0026thinsp;\u0026plusmn;\u0026thinsp;34.61 particles m⁻\u0026sup2; of plastic in sediments along the Gulf of Mexico, based on samples collected from the Port of Florida to Alligator Point, FL (Beckwith \u0026amp; Fuentes, 2018). Along the Mexican coastline of the Gulf, reported abundances ranged from 31.70 to 545.80 particles/m\u0026sup2; (Alvarez-Zeferino et al., 2020). Substantially higher concentrations of 696\u0026ndash;1,392 particles/m\u0026sup2; have been reported in sediments sampled from Campeche Bay, southern GOM (Ramirez et al., 2019). In terms of particles per mass sediment, concentrations of \u0026lt;\u0026thinsp;60 to 300 particles/kg have been reported in sediments along the Gulf of Mexico (Yu et al., 2018). The Tecolutla estuary on Veracruz coast of Mexico has reported levels of 121\u0026thinsp;\u0026plusmn;\u0026thinsp;115 particles/kg (S\u0026aacute;nchez-Hern\u0026aacute;ndez et al., 2021), and southern Gulf sites typically exhibit 1.30\u0026ndash;95.20 particles/kg (Osten et al., 2023). These values illustrate that US GOM concentrations fall within the regional scale of accumulation of plastics.\u003c/p\u003e \u003cp\u003eOn a global scale, the plastic abundance in GOM sediments can be classified as moderate. Overall, an average of 61.08\u0026thinsp;\u0026plusmn;\u0026thinsp;34.61 particles/m\u0026sup2; have been reported across GOM sediments (Beckwith \u0026amp; Fuentes, 2018). Globally, GOM concentrations fall below the accumulations documented in high-impact regions such as Hawaii (1,327\u0026ndash;45,554 particles/m\u0026sup2;) (McDermid \u0026amp; McMullen, 2004), the Great Lakes (North American) (43,157\u0026thinsp;\u0026plusmn;\u0026thinsp;115,519 particles/m\u0026sup2;) (Eriksen et al., 2013), and South Korea\u0026rsquo;s high-tidal coastal zones (56\u0026ndash;285,673 particles/m\u0026sup2;) (Kim et al., 2015). Particles per mass-based comparisons of plastic concentration further reinforce this pattern. Sediment concentrations of plastics in the southern U.S. coast of the GOM range from \u0026lt;\u0026thinsp;60 to 300 particles/kg (Yu et al., 2018), which are in range with values from the Gulf of Mannar (India) (1\u0026ndash;89 particles/kg) (Vidyasakar et al., 2018), and Melbourne (Port Phillip Bay, Australia) (4.50\u0026ndash;172.70 particles/kg) (Su et al., 2020). These values are also comparable to those reported in the United Arab Emirates (91.70\u0026ndash;233.30 particles/kg) (Al Hammadi et al., 2022) and Xiamen, China (76\u0026ndash;333 particles/kg) (Tang et al., 2018), but remain well below those documented in heavily industrialized coastal areas such as Maowei Sea, China (520\u0026ndash;940 particles/kg) (Li et al., 2019) and Laizhou Bay (56.60\u0026ndash;855.40 particles/kg) (Sun et al., 2021). These regional differences likely reflect varying extents of urbanization and industrial activities, with overall levels along the GOM and falling below those documented in some Asian coastal industrial zones.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study provides a current and historic assessment of body burdens for both legacy (PAHs, PCBs) and emerging (NMPs) pollutants in shellfish and fish collected from Galveston Bay (TX). Oysters consistently exhibited elevated levels of PAHs, PCBs and NMPs relative to fish muscle, likely due to their filter-feeding activity. Within fish tissues, contaminant concentrations were markedly higher in liver than muscle, this is likely due to the greater lipid content of the liver (promoting PAHs and PCBs bioaccumulation) and dense vascularization (likely promoting NMPs bioaccumulation). PAH congener profiles indicate inputs from both petrogenic and pyrogenic sources in Galveston Bay, reflecting the urban and industrial petrochemical activities in the region. PCB congener analysis revealed a predominance of dioxin-like compounds, particularly PCB-126 in fish tissue. For the NMPs polymers, N66, PA, PE, PP, and SBR were the most frequently detected across the sampled biota, also reflecting the urban and industrial activities in Galveston Bay and the Houston metro area. When integrated with historic datasets, PAHs and PCBs show no discernible decline from historic levels, highlighting the importance of ongoing monitoring efforts. In contrast, historical baselines for NMPs are sparse, complicating efforts to assess trends. Thus, future monitoring should also prioritize NMPs along with legacy persistent pollutants (PAHs, PCBs) to inform risk assessment and mitigation strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Matagorda Bay Mitigation Trust (Grant #013) for supporting this research, awarded to David Hala, Karl Kaiser, Robert J. David Wells, Antonietta Quigg, and Lene H. Petersen. Additional support was provided by the Texas Comptroller of Public Accounts (Grant #CMD 19‑6799CS to Robert J. David Wells) and the U.S. Army Corps of Engineers (Grant #ERDC BAA 21‑0045A to Karl Kaiser). We also acknowledge the field and laboratory assistance provided by team members and students who contributed to sample processing and data organization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Matagorda Bay Mitigation Trust (Grant #013), the Texas Comptroller of Public Accounts (Grant #CMD 19‑6799CS), and the U.S. Army Corps of Engineers (Grant #ERDC BAA 21‑0045A).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eAsif Mortuza\u003c/strong\u003e: Investigation, methodology, data analysis, software, writing\u0026mdash;original draft, writing\u0026mdash;review and editing. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMichael Bryan Gahn\u003c/strong\u003e: Methodology, data analysis, software, writing\u0026mdash;review and editing. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eMarcus Wharton\u003c/strong\u003e: Methodology, software. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eRobert J. David Wells\u003c/strong\u003e: Resources, funding acquisition, supervision, writing\u0026mdash;review and editing. \u0026nbsp;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eLene H. Petersen\u003c/strong\u003e: Conceptualization, resources, funding acquisition, supervision. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eAntonietta Quigg\u003c/strong\u003e: Supervision, resources, funding acquisition, writing\u0026mdash;review and editing. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eKarl Kaiser\u003c/strong\u003e: Methodology, software, resources, supervision, funding acquisition, writing\u0026mdash;review and editing. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eDavid Hala\u003c/strong\u003e: Supervision, funding acquisition, conceptualization, methodology, software, data analysis, writing\u0026mdash;original draft, writing\u0026mdash;review and editing.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was not required for this study. All fish and oyster samples were collected from Galveston Bay in accordance with Texas Parks and Wildlife (TPWD) regulations using a valid fishing license. No live vertebrates were subjected to laboratory experimentation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors provided consent to participate in the research and preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors provided consent for publication of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are provided in the supplementary materials. Additional datasets are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eA. Monikh, F., Materić, D., Valsami-Jones, E., Grossart, H.-P., Altmann, K., Holzinger, R., Lynch, I., Stubenrauch, J., \u0026amp; Peijnenburg, W. (2025). Challenges in studying microplastics in human brain. \u003cem\u003eNature medicine\u003c/em\u003e, 1\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdel-Zaher, S., Mohamed, M. S., \u0026amp; Sayed, A. E.-D. H. (2023). Hemotoxic effects of polyethylene microplastics on mice. \u003cem\u003eFrontiers in Physiology, 14\u003c/em\u003e, 1072797.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbramowicz, D. A. (1995). 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Distribution of polycyclic aromatic hydrocarbons in water and surface sediments from Daya Bay, China. \u003cem\u003eEnvironmental Pollution, 121\u003c/em\u003e(2), 269\u0026ndash;281.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"subtropical estuary, shellfish, fish, microplastics, body-burdens, persistent pollutants","lastPublishedDoi":"10.21203/rs.3.rs-9509872/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9509872/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGalveston Bay is a highly urban‑industrialized system that drains the Houston metropolitan area and serves as a major hub for maritime transport and energy production. In this study, we compared the current and historic levels of persistent (PAHs, PCBs) and emerging pollutants (Nano-microplastics or NMPs) in biota (oysters, fish) sampled from Galveston Bay. Specifically, the concentrations of 14 EPA priority PAHs, 28 PCBs (including 11 dioxin-like PCBs), and 12 commonly used NMPs (700 nm\u0026thinsp;\u0026minus;\u0026thinsp;5 mm) were measured in gill/mantle tissue of eastern oysters (\u003cem\u003eCrassostrea virginica\u003c/em\u003e), and in the muscle and livers of Gafftopsail catfish (\u003cem\u003eBagre marinus\u003c/em\u003e), red drum (\u003cem\u003eSciaenops ocellatus\u003c/em\u003e), and spotted seatrout (\u003cem\u003eCynoscion nebulosus\u003c/em\u003e). GCMS was used for PAHs and PCBs quantification, and Py-GCMS/MS with lipid correction was used to quantify the NMPs. Overall, NMPs exhibited the highest body-burdens across all biota, ranging from two to four-orders of magnitude higher than PAHs and PCBs. Oysters also accumulated the highest concentrations of all pollutants relative to fish muscle (PAHs\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;2.4x, PCBs\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;19.2x, NMPs \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;278x higher). Source ratio analysis indicated mixed petrogenic and pyrogenic PAHs origins in Galveston Bay. Estimated human intake of NMPs was \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;443.90 mg NMP/kg body weight/year from the consumption of fish, and \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;309.98 mg NMP/kg body weight/year from oysters. A comparison of past and present body‑burden data showed that current PAH and PCB levels remain within previously reported ranges, while the relatively recent adoption of Py‑GCMS/MS enables the first quantified measurements of NMPs in Galveston Bay fish and demonstrates the method\u0026rsquo;s effectiveness for environmental monitoring.\u003c/p\u003e","manuscriptTitle":"Current and Historic Levels of Persistent (PAHs, PCBs) and Emerging Pollutant (Nano- microplastics or NMPs) Body-Burdens in Oysters and Fish from an Urban-Industrialized Subtropical Estuary (Galveston Bay, TX, USA)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 04:32:50","doi":"10.21203/rs.3.rs-9509872/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1b16656b-1eb1-4c92-b8fd-780dd6ba9242","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-08T14:25:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-02T07:43:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-02T07:43:44+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T16:20:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 04:32:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9509872","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9509872","identity":"rs-9509872","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}