Seasonal Occurrence and Ecological Risk Assessment of Polycyclic Aromatic Hydrocarbons in sediments and water of Left-Bank canals of Indus River, Pakistan

Seasonal Occurrence and Ecological Risk Assessment of Polycyclic Aromatic Hydrocarbons in sediments and water of Left-Bank canals of Indus River, Pakistan | 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 Seasonal Occurrence and Ecological Risk Assessment of Polycyclic Aromatic Hydrocarbons in sediments and water of Left-Bank canals of Indus River, Pakistan Mohammed Hammad Sidiqui, Uzma Imran, Kaleemullah Shaikh, Shoaib Ahmed, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3984144/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Nov, 2024 Read the published version in Environmental Monitoring and Assessment → Version 1 posted 7 You are reading this latest preprint version Abstract Kotri Barrage Left Bank Canals, i.e., Akram Pinyari, and Phuleli Wah, pass through Hyderabad Sindh, Pakistan. These canals are utilized for industrial, domestic, and agricultural purposes. These canals are badly affected by anthropogenic activities, which are major sources of organic content, especially PAHs. The present study aimed to investigate the presence, distribution, source, and ecological risk assessment of sixteen ∑ 16 polycyclic aromatic hydrocarbons (PAHs) in water and sediments of Left-bank canals of River Indus-Pakistan in both pre & post monsoon seasons. From each canal 3 water and 2 sediment samples were collected in pre-monsoon and post-monsoon seasons. After collection of sample EPA liquid-liquid extraction were used for the extraction of samples then GC-chromatography was used to investigate the concentration of PAHs. The cumulative concentrations of ∑ 16 PAHs in the pre-monsoon season ranged between 22.26–836.46 ng/l and 26.95–49560 ng/g in water and sediments respectively. The total concentration of water and sediments in the post-monsoon season ranged between 76.51-5663.1 ng/L and 2976.70 -15238.33 ng/g respectively. The Principal Component Analysis (PCA) revealed that industrial and domestic wastewater discharge, solid waste burning, heavy vehicular exhaust, biomass combustion, and petroleum residues are the primary sources of PAH contamination. The toxic equivalent factor (TEF) depicted that Benzo(a)Pyrene and Banzo(a,h)anthracene are the contributing PAHs with higher carcinogenic exposure equivalent in both water and sediments. The left-bank canals of River Indus are highly contaminated with PAHs, thus posing a severe health issue to humans and aquatic life. Polycyclic aromatic hydrocarbons Principal Component Analysis left bank canals Indus River water and sediment samples Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Water pollution with toxic organic chemicals, specifically those characterized as carcinogenic, is one of the major threats we all are facing around the globe. Surface water is most often utilized for drinking and agricultural purposes. If contaminated with these pollutants might affect aquatic and human life (Adekunle et al. 2020 ; Škrbić et al. 2021 ). Polycyclic aromatic hydrocarbons (PAHs) are essential hazardous chemicals with compressed structures of 2 or more aromatic rings have variable toxicity and carcinogenic properties (Lv et al. 2014 ; Abdel-shafy and Mansour 2016 ). Due to their toxic impacts on flora and fauna, the United States Environmental Protection Agencies (USEPA) listed them as priority organic contaminants (Aziz et al. 2014b ; Liu et al. 2020 ). Exposure to PAHs might damage DNA and genotoxicity in humans (Igwe and Ukaogo 2015 ; Varjani et al. 2017 ). US-EPA highlighted sixteen different PAHs in the priority list based on their toxicity which includes Naphthalene (Nap) acenaphthene (Ac), anthracene (An), acehnaphthylene (AcPhth), chrysene (Chr), benzo(k)fluoranthene (BkF), benzo[a]anthracene (BaP), benzo(ghi)perylene (BgP), pyrene (Pyr), fluoranthene (Flour), fluorine (Fluo), indeno (1,2,3–c, d) pyrene (Ind), phenanthrene (Phen) (Keith 2015 ). These chemicals enter the ecosystem through natural (prairie fire, volcanoes, and forest fire) and anthropogenic sources. Anthropogenic sources include industrial and domestic wastewater discharge, solid waste disposal, agricultural runoff, oil spills, automobile emission, coal, and wood-burning (Aziz et al. 2014c ). Moreover, PAHs may enter the aquatic environment through atmospheric fallout such as precipitation or dry deposition (Duodu et al. 2017 ). It has been reported that 10 to 80 percent of polycyclic aromatic hydrocarbons contribute to ocean pollution from atmospheric fallout (Farooq et al. 2011b ; Ishtiaq et al. 2021 ). Chen et al. ( 2004 ) estimated that around 530 tons of PAHs contribute to Hangzhou city’s water bodies annually from atmospheric sources whereas 30.7 tons per year from water runoff (Chen et al. 2004 ). Due to PAHs’ hydrophobic characteristics adhere to the particulate matter in water and ultimately end up in the sediments (Aziz et al. 2014a ; Ofori et al. 2021 ). In Pakistan, limited studies have been carried out related to surface water and sediments pollution with organic contaminants, including PAHs. There is a lack of baseline data on polycyclic aromatic hydrocarbons contamination. Only the surface water of the Soan River and Chenab River at upper Panjab have been monitored to determine PAHs (Farooq et al. 2011a ; Aziz et al. 2014a ). None of the studies have been conducted on the Indus River at lower Sindh. The Kotri barrage is the last controlling structure on the Indus River before the Arabian Sea with a designed capacity of 8.7 lacs cusecs water flow (World 2018 ). It has four non-perennial canals; three at the left bank and one on the right (Report et al. 2005 ). The three canals on the left banks are Akram Wah, Pinyari, and Phuleli, which pass through the densely populated periphery of Hyderabad city, which is the 8th largest city of Pakistan [20] (Mahessar et al. 2015 ). These canals are the primary source of water supply for drinking, irrigation, industrial, and domestic use to the cities of Hyderabad, Sajawal, Badin, and Tando Muhammad Khan (Sohag and Syed 2014 ). These canals’ ecology has been affected due to their proximity to densely populated areas and the anthropogenic activities carried out near these canals. Moreover, emissions in the atmosphere from industries and heavy vehicles might impart PAHs through wet or dry deposition and impair the water quality and ecology of the canals. Besides that, municipal and industrial wastewater is released into LB-canals from Hyderabad cities through multiple drains. Furthermore, people living near these canals are poor and use coal and wood as a burning source for cooking which might also impart PAHs in water. Therefore, this study was carried out to investigate 16 priority listed PAHs in surface water and sediments of the canals. Water and sediment samples were collected from different locations from Akram, Pinyari, and Phuleli Wah (canals) from Kotri barrage to Hyderabad city (Husri Town) in both pre-monsoon and post-monsoon season. The level of PAHs, source identification, and principal component analysis have also been investigated. Moreover, the United States Environmental Protection Agency (USEPA) toxic equivalent factor (TEF) approach was used to investigate the ecological risk associated with PAH contamination in water and sediments. The level of PAHs in water and sediments was also compared with PAHs level reported in the world. 2. Materials & Methods 2.1 Study area with sampling points Left Bank Canals of Kotri Barrage, i.e., Akram Pinyari, and Phuleli Wah, pass through Hyderabad city located in the south of Pakistan’s Sindh province. These canals are used for industrial, domestic and agricultural purposes. These canals are badly affected by anthropogenic activities like burning solid waste along the banks of canals, dumping cattle’s manure, and drainage of municipal and industrial effluents. These are all major sources of organic content, especially PAHs. From each canal three water samples of Phuleli, were collected, i.e., from canals starting, mid of the city, and Husri town located about 11 km from Hyderabad. Sampling was done in two rounds, i.e., during pre-monsoon and post-monsoon, to identify the variability of PAHs in both seasons. Therefore, 18 water samples were collected in each season from nine sampling locations, as shown in Fig. 1 and Table S1 . Water samples were collected in amber glass bottles of 1L capacity to avoid sun exposure, nearly 6 inch below top surface, to avoid floating particulates. Before sampling, bottles were washed with nitric acid (0.1 M) and then rinsed with deionized water and finally with methanol. Samples were labeled and placed in a cooler with ice pads till transported to the laboratory. Before extraction, all water samples were refrigerated at 4℃ till analyzed. While two sediment samples, from each Pinyari, Phuleli, and Akram Wahs from the canals starting and at the end of the city near Husri town, were collected as shown in Fig. 1 . In total, 12 sediment samples were collected during both seasons. Samples were collected in a 100 mL steel container using a grab-sampler tool from the bottom of the canals, closed tightly with a cap, and kept in a cooler with ice pads. All samples were labeled and placed in the freezer at -20 o C before extraction in the laboratory. <> 2.2 Extraction of Samples In the laboratory, water samples were filtered to remove debris using 11-micron filter paper. EPA recommended method Liquid-Liquid extraction was used for sample extraction. Firstly, 500 mL of water sample was poured into a separating funnel with 50mL n-hexane and 25mL dichloromethane. The funnel was shaken periodically and vented to release pressure. The funnel was suspended vertically to separate the organic and aqueous layer when pressure generation stopped. Both organic extracts were collected in a flask through sodium sulfate and concentrated in a rotary evaporator. 3 mL of dichloromethane and 7 mL of n-hexane were poured in a flask that contained organic extracts. Samples were purified in a glass column filled with silica gel (1g) and alumina (1g) after purification. Samples were concentrated in a rotary evaporator up to 1mL. Finally transferred in an amber glass vial for analysis (USEPA 2018 ). Sediment samples were placed in an oven at 60 ℃ for 24 hours to remove moisture content. Dried samples were ground by using mortar and pestle. Sediment samples were extracted using what man extraction thimble in Soxhlet apparatus with 250 mL of dichloromethane for 16 hours and concsentrated in rotary evaporator up to 2mL (USEPA 2018 ; Hadibarata et al. 2019 ). The sediment samples were fractionated by using a column for the purification of samples alumina (2.5g) and with silica (5g). Before purification n-hexane was used for washing of column. For the elution, 25 mL dichloromethane and n-hexane were passed through the column. A 27 mL mixture of n-hexane and 3 mL of dichloromethane were added to the extract, passed through the column, concentrated in a rotary evaporator up to 1 mL, and finally poured into the glass vial for analysis in Chromatography-flame Ionization Detector (GC-FID). 2.3 Experimental Analysis: In the laboratory, gas chromatography (Shimadzu GC-2010) with flame ionization detector (GC-FID) was used for the analysis. The main parts of GC contain a hydrogen generator, column (30m length x 0.32mm inner dia x 0.25µm), air pump and injector system. Nitrogen was used as a carrier gas. Initially, when the system started, the oven temperature was set at 100°C (initial time: 02 min) to 280°C at a rate of 5°C /min and held for 25 min. Inlet temperature was 250°C, and detector temperatures were 300°C, respectively. A 0.5, 1 and 1.5µL of PAHs standard mixtures were injected in injection point respectively which include sixteen PAHs of different number of rings and molecular weight as shown in Table S1 . During analysis, retention time, peak height, and peak area of compounds were noted. Availability of PAHs in samples was differed in the column, identified by the detector, and shown in the chromatogram. PAHs in samples were known by their similarities of retention time, peak height, and peak area with the standards in the chromatogram. 2.4 Quality control and assurance Quality control and assurance were strictly implemented during water and sediment sampling and analysis. Extraction of all samples were done within seven days of sampling. Routine analysis of lab blanks and fields was performed to monitor the possible contamination during storage, transportation, and analysis. None of the polycyclic aromatic hydrocarbons were detected in lab and field blanks. Acenapthaened10, chysene-d12, naphthalene-d8, perylene-d12, and phenanthrene-d10 were utilized with their calculated mean recoveries as a recovery standard of 68.35%, 75.47%, 84.84%, and 86.34%. The detection limit was calculated as three times the standard deviation of the PAHs in procedural blanks. The PAHs were not found in field and lab blanks; detection limits for such PAHs were quantified as the number of analytes per sample. 2.5 Statistical Analysis The correlation between PAHs’ physicochemical properties and their distribution pattern was analyzed using the Statistical package for social science (SPSS-13.0). The significance difference (P ¼ 0.05) in PAHs concentrations at several locations was assessed through the Kruskal-Wallis test based on median values not distributed normally. The PAHs contamination source was determined using diagnostic ratio test and Principal component analysis (PCA) were used for determination of PAHs contamination source. All the data were standardized before PCA analysis to remove dimensional effects on the components. 3. Results & Discussion 3.1 Occurrence of PAHs in Water Surface water from nine sampling points mentioned in Table S2 and Fig. 1 was analyzed to determine the concentration of sixteen PAHs carcinogenic compounds listed in the priority list of EPAs. The concentrations of PAHs from the mentioned locations in the Akram, Pinyari, and Phuleli canals were determined during pre-monsoon and post monsoon season. The variations in concentration were found at different sampling points of canals due to the addition of different pollution sources along the length of canal. All the samples collected in both seasons were found to be contaminated with 16 different lower molecular weight (LMW) and higher molecular weight (HMW) polycyclic aromatic hydrocarbons (PAHs). The cumulative results are described in Table 1 , whereas the percent compositions in both seasons are shown in Figs. 2 and 3 . The total concentration of ∑ 16 PAHs in pre-monsoon was in the range of 76.51 to 5663.1 ng/L. The location S1, located near Kotri Barrage, was contaminated with maximum PAHs concentration, i.e., 5663.1 ng/L, which is exceptionally high. Table 1 The cumulative concentration of PAHs in water and sediments of Left-bank Canals Sampling Locations ∑ 16 PAH ∑LMW ∑HMW Water (ng/L) Sediment (ng/g) Water (ng/L) Sediment (ng/g) Water (ng/L) Sediment (ng/g) S1 Pr 76.51 8802.34 26.22 849.91 50.30 7952.42 Po 5663.06 2976.77 6.39 416.96 5656.6 2559.81 S2 Pr 822.60 3571.52 15.38 133.94 807,23 3437.56 Po 247.5 11939.21 75.34 1421.74 172.17 10517.47 S3 Pr 22.26 6509.28 8.43 97.71 13.83 6411.57 Po 201.72 10778.53 5.67 5045.44 196.05 5733.10 S4 Pr 446.18 --- 35.4 --- 410.77 --- Po 79.11 --- 7.28 --- 71.83 --- S5 Pr 836.46 --- 38.77 --- 797.68 --- Po 491.64 --- 16.92 --- 474.72 --- S6 Pr 73.09 --- 26.25 --- 46.84 --- Po 60.35 --- 7.21 --- 53.14 --- S7 Pr 45.46 1459.94 8.95 170.11 36.51 1289.83 Po 257.03 4139.26 16.8 405.98 240.23 3733.28 S8 Pr 88.15 43179.24 25.94 17141.48 62.21 26037.7 Po 261.14 15238.33 13.06 10870.43 248.08 4367.9 S9 Pr 50.63 9139.53 1.58 546.94 49.05 8592.59 Po 4752.19 6548.51 219.97 1816.41 4532.2 4732.10 Pr = Pre-monsoon, Po = Post-monsoon, LMW = Low Molecular weight, HMW = High Molecular Weight In contrast, the lowest cumulative concentration of 60.35 ng/L was observed at location S6 on Akram Wah. The location S9 was the point where the second-highest concentration of higher molecular weight PAHs, i.e., 4752.19 ng/L, was depicted. The average concentration of 1334.86 ng/L was found in the pre-monsoon period. The concentrations of HMW were maximum in percentage at samples from all the locations. The level of individual PAH in pre-monsoon season along standard deviation is summarized in Table S3. The total concentration is the summation of 16 different PAHs with a higher concentration of long ring benzoic compounds, which include BaP, BbF, dBahA, and BkF. The primary sources of long ring PAHs are automobile emissions, mainly diesel oil emission and oil (Kavouras et al. 2001 ). In the pre-monsoon season, the water flow at Kotri barrage is relatively low. Maintenance work is often carried out in this season, which might be the reason for higher PAHs concentration at location S1 due to the release of lubricating oil during gate maintenance. The other source of BkF and BbF contaminations could be agricultural runoffs, wood, and grass burning (Tian et al. 2009a ; Park et al. 2011 ). Benzopyrene is associated with coal burning, diesel, or traffic exhaust (Hong et al. 2007a ). Moreover, almost all the sampling locations were contaminated with BbF and Chr due to the excess release of wastewater and municipal solid waste burning in the vicinity of the canals and atmospheric fallout (Park et al. 2011 ). The domestic and industrial effluents from Hyderabad city, either untreated or partially treated, drain into the canals; therefore, the concentration of these pollutants decreased with spatial distribution from the point of discharge towards the downstream. In the post-monsoon season, the total concentration was in the range of 22.26 to 836.46 ng/L, as shown in Table 1 . The location S5 was found with maximum total PAH concentration, i.e., 836.46 ng/L, where cottage industry wastewater and domestic solid waste from Hyderabad city are being discharged. In contrast, the lowest concentration was observed at location S3, i.e., 22.26 ng/L. S3 is located near Kotri barrage at Akram Wah, from where water is supplied to Hyderabad city for drinking purposes. The location S2 was contaminated with maximum percent of HMW-PAHs i.e., BaP with a concentration of 822.60 ng/L. This site is near Jamshoro Joint Venture Limited (JJVL) oil and gas exploration plant from where the wastewater drains, which is the primary source of higher molecular weight PAHs. However, on average, 273.48 ng/L concentration of PAHs was observed in the post-monsoon season. The concentration of individual PAHs in the post-monsoon season is summarized in Table S4. In general, the samples collected in pre-monsoon show higher concentration than the post-monsoon season owing to the lower water flow rate in pre-monsoon. Henceforth, the increased flow is responsible for lower concentration in the post-monsoon season because of dilution. <> 3.2 Occurrence of PAHs in Sediments Due to PAHs’ hydrophobic property, most of these chemicals are not dissolved in water, therefore, adsorbed on the surface of sediments (Abdel-shafy and Mansour 2016 ). Thus, sediment samples from 6 different locations have been collected in pre-monsoon and post-monsoon season to analyze 16 different LMW and HMW polycyclic aromatic hydrocarbons. The total concentrations of PAHs in sediment samples are summarized in Table 1 whereas, percentage compositions are shown in Fig. 3 (a) and (b) for both seasons. Moreover, the individual PAH level in sediments samples is summarized in Table S5 and S6, along with their minimum, maximum, and standard deviation. The total concentration in the pre-monsoon season was found in the range of 2976.70 to 15238.33 ng/g. The location S8 was contaminated with the highest cumulative PAHs concentration, i.e., 15238.33 ng/g, containing about 35% pyrene (5333.50 ng/g) alone. Fluoranthene was the highest occurring PAH with a concentration of 2345.63 ng/g, accounting for 15.39%. The lowest concentration of total PAHs was detected at location S2 with 2976.70 ng/g, containing 33% chrysene with a maximum percentage. In the post-monsoon season, PAHs’ commutative concentration in sediment samples was 285.54 to 43179.24 ng/g. The highest total PAHs concentration was observed in sediments samples of location S8 containing BbF with a maximum percentage of 12.21%. Location S3 was found with minimum cumulative concentration. <> <> 3.3 Principal Component Analysis The major source of PAHs in surface water and sediments include industrial effluent, domestic wastewater, oil spillage, incomplete combustion of coal, and other atmospheric fallout (Abdel-shafy and Mansour 2016 ; Škrbić et al. 2021 ; Turaki Usman et al. 2021 ). The left-bank canals of Kotri barrage comprehensively receive organic-rich wastewater from various sources. Therefore, it is quite difficult to identify one or specific source. A single PAH might have multiple sources; therefore, Principal Components Analysis (PCA) based correlation was used to identify source apportionment. Previously, researchers have used different ratio of lower and higher molecular weight PAHs (LMW/HMW) such as Phen/An, An / (Phen + An), Fluor/ (Fluor + Pyr), BaA/(BaA + Chr), Ind/ (Ind + BgP) and Fluor/Pyr. PCA was performed based on these ratios to identify the potential sources and their relation. PCA is most often utilized to identify pollution sources to signify the differences and similarities in sources. The data set calculated using the PCA approach with six factors loading with greater than one eigenvalue (Eigen values > 1) is described in Table 2 . F1 illustrated 37.39 percent total variance, which was dominated with phen, Fluor, BaA, BkF, BghiP, BaP, and Chr. The major source of phenanthrene is from coal combustion(Harrison and Dourish 1996 ), Fluor from workshop effluent or automobile service station wastewater (Park et al. 2011 ), BkF, and BaA from vehicular generated products, including gas and diesel emission (Larsen and Baker 2003 ), BaP and Chr from industrial emissions and wastewater (Hong et al. 2007b ). BghiP is also from industrial sources and fuel combustion (Park et al. 2011 ). F1 includes the chemicals associated with multiple sources such as emissions from industries, coal, and wood burning. The dominant compounds explained by F2 with a maximum 21.78 percent total variance include AC, dBahA, Phen, Ind, Acphthy, dBahA, Flou. The major source of these pollutants is workshops exhaust and emissions from vehicles (Guo et al. 2003 ; Park et al. 2011 ).The left bank canal passes through the periphery of densely populated areas of Hyderabad city. The wastewater from automobile service stations situated at different locations in the city discharges wastewater into canals through multiple drains without any treatment, which is the primary reason for contamination. Moreover, huge traffic passes along the canals from where emission is deposited in water bodies through dry deposition as shown in Figs. 4 and 5 . Table 2 Values of factor loadings for 16 PAHs in Kotri Barrage LB-Canals Compounds F1 F2 F3 F4 F5 F6 Ac 0.001 0.90 -0.26 -0.01 -0.34 0.01 Acphthy -0.19 0.62 0.65 0.16 0.36 -0.08 An -0.37 0.39 -0.46 -0.34 0.57 -0.23 BaA 0.87 -0.15 -0.36 0.19 -0.005 0.21 BaP 0.91 0.03 -0.34 0.21 0.09 -0.06 BbF -0.39 0.45 -0.17 0.75 0.05 0.17 BghiP 0.94 0.07 -0.27 0.17 0.08 -0.02 BkF 0.92 0.04 -0.34 0.19 0.08 -0.01 Chr 0.92 -0.08 -0.16 0.10 0.25 -0.19 dBahA -0.22 0.62 -0.56 -0.11 -0.39 -0.20 Fluor 0.67 0.62 0.23 -0.30 -0.11 0.10 Flur -0.41 0.11 -0.49 -0.46 0.48 0.35 Ind -0.427 0.66 -0.47 0.39 0.023 -0.019 Nap 0.56 0.43 0.70 -0.13 0.11 0.06 Phen 0.51 0.70 0.44 -0.23 0.03 0.02 Pyr -0.29 0.12 0.24 0.89 0.13 -0.02 Eigen Value 5.10 3.49 2.72 2.22 1.078 0.360 % Variance 37.40 21.80 17.02 13.9 6.74 2.24 Factor 3 was dominated by acenaphthylene (0.680) and naphthalene (0.646) with a total variance of 17.02%. Near the canals, few industries utilize petroleum products as a fuel from where waste in the form of water and emission is released, which might contribute to naphthalene contamination in water. Oil spills, exhaust from burning fuels, gasoline industrial effluents are the primary source of naphthalene contamination (Zakaria et al. 2002 ; Boonyatumanond et al. 2007 ). Factor 4 contributes 13.86% with dominancy of benzo(b)fluoranthene and pyrene. Low-income families living along the canals utilize bio-mass, coal, wood, and grass as a burning source for cooking, contributing to pyrene and benzo(b)fluoranthene (Park et al. 2011 ). Factor 5 depicted a 6.74 percent total variance with dominant fluoranthene and anthracene as dominant compounds. These chemicals are released from municipal solid waste disposal and petrochemical wastewater (Yang et al. 2002 ; Tian et al. 2009b ). The municipal solid waste from Hyderabad city is dumped openly along with the Akram, Pinyari, and Phuleli banks. Factor 6 was conquered by benzo(b)fluoranthene with a total variance of 2.24% that was very prominent in all the sampling locations with higher concentrations. <> <> <> 3.3 Comparison of ∑ PAH detected in the world. The PAHs concentration in water and sediments samples of LB-canals was compared comprehensively with the PAHs concentration reported in different rivers worldwide. The water and sediment of the left-bank canals were found to be contaminated with the highest overall mean ∑PAHs concentrations in the region of 60.35 -5663.06 ng/L and 2976.7–15238.3 ng/g in water and sediment in the pre-monsoon season, respectively. The concentrations in post-monsoon were in the range of 22.26–836.46 ug/l and 258.54–43179.24 ng/g in water and sediments, respectively. The overall concentration of PAHs in left-bank canals was extremely high compared to the reported PAHs in water and deposits worldwide. The summary of PAHs comparison is demonstrated in Table 3 . The buffalo river (South Africa), Gomti river (India), and Cauca River (Colombia) were the rivers with the highest PAHs contaminations. In turn, the lower concentration in water and sediments were detected in the Tiber (Italy), Danube (Hungry), and Gao-ping (Taiwan) rivers. For detection of PAHs Gas Chromatography (GC) and High-Performance Liquid Chromatography (HPLC) techniques are widely used. Table 3 Concentration ranges of ∑PAHs in surface water and sediments collected from various locations in the world. River Name Country No. of PAHs ∑ PAHs Ranges References Water (ng/L) Sediments (ng/g) Buffalo River Estuary South Africa 16 14910–206000 1107–22,310 [36] Gomti river India 16 0-84000 5–3723 [37] Hoogly and Brahmaputra India 16 0–30000 0–636 [38] Damodar basin India 16 0-36000 0-582 [39] Kor River Iran 16 45.4–375.1 167.4–530.3 [40] Shadegan wetland China 16 42.2-136.4 10-331.4 [36] Qiantang River China 15 70.3–1844.4 91.3–614.4 [41] Danube River Hungary 17 67–96 35.2–288.3 [42] Moson Danube Hungary 16 46–639 8.3–1,202.5 [43] Tiber River Italy 6 23.9–72.0 157.8–271.6 [44] Brisbane River Australia 16 -- 148–3079 [11] Boston Harbor USA 16 -- 7300–358000 [45] Columbia River Portland USA 4 -- 1600–13200 [46] Prai River Malaysia 16 -- 1102–7938 [47] Sasa River Nigeria 16 0-349 11.95-528.78 [2] Liaohe river basin China 16 0-615 0-60057 [48] Cauca Colombia 12 52.1-12888.2 -- [49] Soltan Abad River Iran 16 43.5–385 180–504.0 [50] Gao-ping River, Taiwan 16 0.01–9.4 8–356 [51] Daliao River watershed China 18 946-13449 62–841 [52] Masan Bay Korea 16 -- 207–2670 [53] Amazon River Estuary Brazil 16 -- 1.8–158 [54] Yangtze River Estuary China 16 -- 89.52–208.02 [5] Yangtze River China 16 321.8–6234.9 72.4–3995.2 [55] Kotri Barrage, Left Bank Canals (Pre-monsoon) Pakistan 16 60.35 -5663.06 2976.7–15238.3 This Study Kotri Barrage, Left Bank Canals (Post-monsoon) Pakistan 16 22.26–836.46 258.54–43179.24 This Study <> 3.4 Toxicity of carcinogenic C-PAHs IARC (1987) has identified BaA, BaP, BbF, BkF, Chr, dBahA, and Ind as potential carcinogens (1983). The carcinogenic PAHs (C-PAHs) in water and sediments samples were in the range of 0.216 -1298.61 ng/L and 1.32 -3284.3 ng/g, respectively (Fig S1 (a) and (b)). The C-PAH concentration in LB-canals was higher than the Soan River and Gomati River (Kumar et al. 2020 ). Owing to the absence of guidelines for threshold limits by the government of Pakistan, the level of C-PAHs in left-bank canals of the Indus River were compared with guidelines of different countries. In this study, the carcinogenicity of seven C-PAHs was calculated by employing toxic equivalent factors (TEF) with relevance to BaP as suggested by USEPA, 1993 (Agency 1979 ). Equation-3 was used to calculate the total equivalents (TEQ) of the carcinogenic PAHs (C-PAHs) (Aziz et al. 2014b ; Han et al. 2019 ). TEQ = C i ×TEF i (3) Where Ci and TEF represent the initial concertation and total equivalent factor of the C-PAHs, the total TEQ of PAHs in water samples of left-bank canals of Indus River were in the range of 0.0092 to 526 ng/l at locations S1 and S7. In sediment samples, total TEQs of PAHs were in the range of 0.08 to 2098.2 ng/g at locations S4 and S5, respectively, with an average of 182.82 ng/g. The TEQs of seven PAHs in water and sediments are shown in Figure S2(a) and (b). The total concentration of C-PAHs in sediments and water was recorded highest at sites S5 and S1, but highest carcinogenic potential of ∑ 7 PAH concentrations were at S1. This is because BaP highest concentration was found at S1, which has higher carcinogenetic potential. While TEQ of all C-PAH values was greater than one, it should be lowered to one. 3.5 Ecological Risk Assessment Ecological risk assessment (ERA) via Risk Quotients (RQ) was used to assess the unwanted impacts of environmental pollutants on the ecological system. To evaluate the ecosystem risk due to PAHs in the LB-canals of river Indus, Risk Quotients of negligible permissible concentration (RQ NPCs ) and maximum permissible concentration (RQ MPCs ) for specific and sum of PAHs were calculated and compared with their quality-reference values. The reference values for organic pollutants in Pakistan did not exist; therefore, in this study, Kalf et al. ( 1997 ) reported values were used (Kalf et al. 1997 ). The detailed methodology of risk evaluation is described in the published paper (Cao et al. 2010 ). In principle, if both RQ NPCs and RQ MPCs are > 1 for specific PAH, then immediate actions are required because the risk is high. While RQ NPCs are > 1 and RQ MPCs are < 1, then the risk related to PAHs pollutants is middle. Classification of risk for summation of PAHs is given in Table S7. The average and median values of RQ NPCs and RQ MPCs for individual PAHs are stated in Table 4 . The results depicted that RQ NPCs and RQ MPCs for all individual PAHs in sediments represent medium to high risk except Nap which shows low risk in the aquatic system of the left bank canals of the Indus River. In contrast, RQ NPCs and RQ MPCs for all individual PAHs in water show low risk from five PAHs, medium risk from seven PAHs in the left bank canals of the Indus River aquatic system. Median values of RQ were used to assess the average risk level as accuracy of the mean RQ values can be influenced by extreme values. The median values of RQ were lower than the average RQ values, indicating that the related risk of each PAH is low-medium in sediment and water and is of significant concern in the left bank canals of the Indus River. The table shows that four-ring compounds are main contributor in the left bank canals ecosystem risk. HMW PAHs are more carcinogenic and mutagenic as compared to LMW PAHs. Hence, the risk related to specific PAHs concentration is higher in the left bank canals of the Indus River. To control the sources of HMW and LMW compounds mitigation measures should be taken in the left bank canals of the Indus River. Based on ring number, the pattern of risk burden in water is followed in the order: 4 rings > 5 rings > 6 rings > 3ring > 2 rings while in sediments pattern of the risk burden is observed in the order: 4 rings > 3 rings > 5 rings > 6rings > 2 rings. The contribution percentage of minimum PAHs concentration by the ring is summarized in Table S7. Table 4 Risk quotients for negligible and maximum permissible concentrations for individual PAHs. Compounds Water Sediments RQ NPCs RQ MPCs RQ NPCs RQ MPCs RQ NPCs RQ MPCs RQ NPCs RQ MPCs Mean Median Mean Median Mean Median Mean Median Naphthalene 12 1200 s 0.00 0.000 0.00 1.40 140.00 0.49 0.00 0.00 0.00 Acenaphthylene 0.7 70 0.512 0.13 0.005 0.00 1.20 120.00 35.95 8.35 0.36 0.08 Acenaphthene 0.7 70 0.228 0.16 0.002 0.00 1.20 120.00 23.88 7.99 0.24 0.08 Fluorene 0.7 70 1.415 0.70 0.014 0.01 1.20 120.00 76.90 30.25 0.77 0.30 Phenanthrene 3 300 0.819 0.53 0.008 0.01 5.1 510 115.86 18.31 1.16 0.18 Anthracene 0.7 70 11.695 3.50 0.117 0.04 1.2 120 692.95 193.53 6.93 1.94 Fluoranthene 3 300 1.572 0.38 0.016 0.00 26 2,600 15.44 1.88 0.15 0.02 Pyrene 0.7 70 19.639 2.91 0.196 0.03 1.2 120 1045.44 168.89 10.45 1.69 Benzo(a)anthracene 0.1 10 792.291 10.30 7.923 0.10 3.6 250 81.35 11.90 1.17 0.17 Chrysene 3.4 340 7.894 4.88 0.079 0.05 107 10,700 9.50 5.03 0.10 0.05 Benzo(b)fluoranthene 0.1 10 2304.423 388.50 23.044 3.88 3.6 250 609.94 589.71 8.78 8.49 Benzo(k)fluoranthene 0.4 40 403.665 0.00 4.037 0.00 24 2,400 27.42 6.73 0.27 0.07 Benzo(a)pyrene 0.4 50 238.480 0.00 1.908 0.00 27 260 18.43 2.87 1.91 0.30 Banzo(a,h)anthracene 0.5 50 42.690 0.43 0.427 0.00 27 260 14.59 0.42 1.52 0.04 Benzo(g,h,i)perylene 0.3 30 405.909 0.00 4.059 0.00 75 7500 9.89 0.16 0.10 0.00 indeno(1,2,3-c,d)pyrene 0.4 40 92.052 15.49 0.921 0.15 59 5900 22.31 5.32 0.22 0.05 ∑PAHs 4323.31 427.91 42.76 4.28 2800.36 1051.33 34.14 13.47 For all locations RQ∑PAHs (NPCs) > 1 and RQ∑PAHs (MPCs) > 1. By comparing RQs for ∑PAHs with the quality references given in Table S8, it is demonstrated that the risk related with ∑PAHs at all locations is high. Overall, the results suggested that the ecosystem risk due to the PAHs in the left bank canals of the Indus River is high. Surface water contamination due to ∑PAHs could be categorized into four groups: highly polluted (1000 ng/L), moderate-polluted (250–1000 ng/L), lightly-polluted (50–250 ng/L), and micro-polluted (10–50 ng/L) (Aziz et al. 2014d ). The concentration of ∑PAHs in the surface water of Indus River’s LB-canals ranged from 66.72 to 2869.79 ng/L. Therefore, surface water of the left bank canals of the Indus River is lightly-highly contaminated in terms of PAHs pollution. <> Conclusions The total lower and higher molecular weight PAHs in both sediment and water samples of LB-canals of Kotri barrage were in higher concentrations than the WHO permissible limit in both pre-monsoon and post-monsoon seasons. These canals flow through the periphery of densely populated areas and receive untreated or partially treated municipal and industrial wastewater and multiple domestic wastes drains produced in nearby residential areas on canal roads. Moreover, municipal solid waste is openly dumped in considerable quantities in the vicinity of all three canals, which ultimately leads to the flowing water with the waves and pollutes the canals. Among the three canals, the Phuleli canal bank was massively covered with domestic solid waste. The massive, heavy-duty traffic flow also embarks the PAHs in canals through the dry or wet deposition. Location at the mid-city was found with the highest concentration of PAHs among all nine locations. Moreover, the carcinogenic C-PAHs concentration was higher in water and sediments of all the left-bank canals. Henceforth, the result of this study depicts that the water quality of these canals is not suitable for drinking or irrigation purposes; therefore, there is a dire need to take mitigations measures to minimize further deterioration of canals. Declarations Acknowledgment The authors are highly thankful to the U.S.-Pakistan Center for Advanced Studies in Water (USPCASW), and Center for Environmental Studies, Mehran University of Engineering and Technology, Jamshoro, Sindh Pakistan, and Pakistan Council of Scientific and Industrial Research (PCSIR), Karachi, Pakistan. Funding Declaration No funding was acquired from any organization. Data Availability Data will be available on request. Declaration of Competing of Interest The Authors confirm that they do not have any known competing of interest. References Abdel-shafy HI, Mansour MSM (2016) A review on polycyclic aromatic hydrocarbons : Source, environmental impact , effect on human health and remediation. 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08:55:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1207782,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-3984144/v1/2400051b6d03d61874cec987.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Seasonal Occurrence and Ecological Risk Assessment of Polycyclic Aromatic Hydrocarbons in sediments and water of Left-Bank canals of Indus River, Pakistan","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWater pollution with toxic organic chemicals, specifically those characterized as carcinogenic, is one of the major threats we all are facing around the globe. Surface water is most often utilized for drinking and agricultural purposes. If contaminated with these pollutants might affect aquatic and human life (Adekunle et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Škrbić et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Polycyclic aromatic hydrocarbons (PAHs) are essential hazardous chemicals with compressed structures of 2 or more aromatic rings have variable toxicity and carcinogenic properties (Lv et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Abdel-shafy and Mansour \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Due to their toxic impacts on flora and fauna, the United States Environmental Protection Agencies (USEPA) listed them as priority organic contaminants (Aziz et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014b\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Exposure to PAHs might damage DNA and genotoxicity in humans (Igwe and Ukaogo \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Varjani et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUS-EPA highlighted sixteen different PAHs in the priority list based on their toxicity which includes Naphthalene (Nap) acenaphthene (Ac), anthracene (An), acehnaphthylene (AcPhth), chrysene (Chr), benzo(k)fluoranthene (BkF), benzo[a]anthracene (BaP), benzo(ghi)perylene (BgP), pyrene (Pyr), fluoranthene (Flour), fluorine (Fluo), indeno (1,2,3\u0026ndash;c, d) pyrene (Ind), phenanthrene (Phen) (Keith \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These chemicals enter the ecosystem through natural (prairie fire, volcanoes, and forest fire) and anthropogenic sources. Anthropogenic sources include industrial and domestic wastewater discharge, solid waste disposal, agricultural runoff, oil spills, automobile emission, coal, and wood-burning (Aziz et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014c\u003c/span\u003e). Moreover, PAHs may enter the aquatic environment through atmospheric fallout such as precipitation or dry deposition (Duodu et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It has been reported that 10 to 80 percent of polycyclic aromatic hydrocarbons contribute to ocean pollution from atmospheric fallout (Farooq et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2011b\u003c/span\u003e; Ishtiaq et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Chen et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) estimated that around 530 tons of PAHs contribute to Hangzhou city\u0026rsquo;s water bodies annually from atmospheric sources whereas 30.7 tons per year from water runoff (Chen et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Due to PAHs\u0026rsquo; hydrophobic characteristics adhere to the particulate matter in water and ultimately end up in the sediments (Aziz et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e; Ofori et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Pakistan, limited studies have been carried out related to surface water and sediments pollution with organic contaminants, including PAHs. There is a lack of baseline data on polycyclic aromatic hydrocarbons contamination. Only the surface water of the Soan River and Chenab River at upper Panjab have been monitored to determine PAHs (Farooq et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2011a\u003c/span\u003e; Aziz et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e). None of the studies have been conducted on the Indus River at lower Sindh. The Kotri barrage is the last controlling structure on the Indus River before the Arabian Sea with a designed capacity of 8.7 lacs cusecs water flow (World \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It has four non-perennial canals; three at the left bank and one on the right (Report et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The three canals on the left banks are Akram Wah, Pinyari, and Phuleli, which pass through the densely populated periphery of Hyderabad city, which is the 8th largest city of Pakistan [20] (Mahessar et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These canals are the primary source of water supply for drinking, irrigation, industrial, and domestic use to the cities of Hyderabad, Sajawal, Badin, and Tando Muhammad Khan (Sohag and Syed \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThese canals\u0026rsquo; ecology has been affected due to their proximity to densely populated areas and the anthropogenic activities carried out near these canals. Moreover, emissions in the atmosphere from industries and heavy vehicles might impart PAHs through wet or dry deposition and impair the water quality and ecology of the canals. Besides that, municipal and industrial wastewater is released into LB-canals from Hyderabad cities through multiple drains. Furthermore, people living near these canals are poor and use coal and wood as a burning source for cooking which might also impart PAHs in water. Therefore, this study was carried out to investigate 16 priority listed PAHs in surface water and sediments of the canals. Water and sediment samples were collected from different locations from Akram, Pinyari, and Phuleli Wah (canals) from Kotri barrage to Hyderabad city (Husri Town) in both pre-monsoon and post-monsoon season. The level of PAHs, source identification, and principal component analysis have also been investigated. Moreover, the United States Environmental Protection Agency (USEPA) toxic equivalent factor (TEF) approach was used to investigate the ecological risk associated with PAH contamination in water and sediments. The level of PAHs in water and sediments was also compared with PAHs level reported in the world.\u003c/p\u003e"},{"header":"2. Materials \u0026 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area with sampling points\u003c/h2\u003e \u003cp\u003eLeft Bank Canals of Kotri Barrage, i.e., Akram Pinyari, and Phuleli Wah, pass through Hyderabad city located in the south of Pakistan\u0026rsquo;s Sindh province. These canals are used for industrial, domestic and agricultural purposes. These canals are badly affected by anthropogenic activities like burning solid waste along the banks of canals, dumping cattle\u0026rsquo;s manure, and drainage of municipal and industrial effluents. These are all major sources of organic content, especially PAHs.\u003c/p\u003e \u003cp\u003eFrom each canal three water samples of Phuleli, were collected, i.e., from canals starting, mid of the city, and Husri town located about 11 km from Hyderabad. Sampling was done in two rounds, i.e., during pre-monsoon and post-monsoon, to identify the variability of PAHs in both seasons. Therefore, 18 water samples were collected in each season from nine sampling locations, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Water samples were collected in amber glass bottles of 1L capacity to avoid sun exposure, nearly 6 inch below top surface, to avoid floating particulates. Before sampling, bottles were washed with nitric acid (0.1 M) and then rinsed with deionized water and finally with methanol. Samples were labeled and placed in a cooler with ice pads till transported to the laboratory. Before extraction, all water samples were refrigerated at 4℃ till analyzed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWhile two sediment samples, from each Pinyari, Phuleli, and Akram Wahs from the canals starting and at the end of the city near Husri town, were collected as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In total, 12 sediment samples were collected during both seasons. Samples were collected in a 100 mL steel container using a grab-sampler tool from the bottom of the canals, closed tightly with a cap, and kept in a cooler with ice pads. All samples were labeled and placed in the freezer at -20\u003csup\u003eo\u003c/sup\u003eC before extraction in the laboratory.\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eStudy area map with sampling Points\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Extraction of Samples\u003c/h2\u003e \u003cp\u003eIn the laboratory, water samples were filtered to remove debris using 11-micron filter paper. EPA recommended method Liquid-Liquid extraction was used for sample extraction. Firstly, 500 mL of water sample was poured into a separating funnel with 50mL n-hexane and 25mL dichloromethane. The funnel was shaken periodically and vented to release pressure. The funnel was suspended vertically to separate the organic and aqueous layer when pressure generation stopped. Both organic extracts were collected in a flask through sodium sulfate and concentrated in a rotary evaporator. 3 mL of dichloromethane and 7 mL of n-hexane were poured in a flask that contained organic extracts. Samples were purified in a glass column filled with silica gel (1g) and alumina (1g) after purification. Samples were concentrated in a rotary evaporator up to 1mL. Finally transferred in an amber glass vial for analysis (USEPA \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSediment samples were placed in an oven at 60 ℃ for 24 hours to remove moisture content. Dried samples were ground by using mortar and pestle. Sediment samples were extracted using what man extraction thimble in Soxhlet apparatus with 250 mL of dichloromethane for 16 hours and concsentrated in rotary evaporator up to 2mL (USEPA \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hadibarata et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The sediment samples were fractionated by using a column for the purification of samples alumina (2.5g) and with silica (5g). Before purification n-hexane was used for washing of column. For the elution, 25 mL dichloromethane and n-hexane were passed through the column. A 27 mL mixture of n-hexane and 3 mL of dichloromethane were added to the extract, passed through the column, concentrated in a rotary evaporator up to 1 mL, and finally poured into the glass vial for analysis in Chromatography-flame Ionization Detector (GC-FID).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Experimental Analysis:\u003c/h2\u003e \u003cp\u003eIn the laboratory, gas chromatography (Shimadzu GC-2010) with flame ionization detector (GC-FID) was used for the analysis. The main parts of GC contain a hydrogen generator, column (30m length x 0.32mm inner dia x 0.25\u0026micro;m), air pump and injector system. Nitrogen was used as a carrier gas. Initially, when the system started, the oven temperature was set at 100\u0026deg;C (initial time: 02 min) to 280\u0026deg;C at a rate of 5\u0026deg;C /min and held for 25 min. Inlet temperature was 250\u0026deg;C, and detector temperatures were 300\u0026deg;C, respectively. A 0.5, 1 and 1.5\u0026micro;L of PAHs standard mixtures were injected in injection point respectively which include sixteen PAHs of different number of rings and molecular weight as shown in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. During analysis, retention time, peak height, and peak area of compounds were noted. Availability of PAHs in samples was differed in the column, identified by the detector, and shown in the chromatogram. PAHs in samples were known by their similarities of retention time, peak height, and peak area with the standards in the chromatogram.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Quality control and assurance\u003c/h2\u003e \u003cp\u003eQuality control and assurance were strictly implemented during water and sediment sampling and analysis. Extraction of all samples were done within seven days of sampling. Routine analysis of lab blanks and fields was performed to monitor the possible contamination during storage, transportation, and analysis. None of the polycyclic aromatic hydrocarbons were detected in lab and field blanks. Acenapthaened10, chysene-d12, naphthalene-d8, perylene-d12, and phenanthrene-d10 were utilized with their calculated mean recoveries as a recovery standard of 68.35%, 75.47%, 84.84%, and 86.34%. The detection limit was calculated as three times the standard deviation of the PAHs in procedural blanks. The PAHs were not found in field and lab blanks; detection limits for such PAHs were quantified as the number of analytes per sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe correlation between PAHs\u0026rsquo; physicochemical properties and their distribution pattern was analyzed using the Statistical package for social science (SPSS-13.0). The significance difference (P\u003csup\u003e\u0026frac14;\u003c/sup\u003e0.05) in PAHs concentrations at several locations was assessed through the Kruskal-Wallis test based on median values not distributed normally. The PAHs contamination source was determined using diagnostic ratio test and Principal component analysis (PCA) were used for determination of PAHs contamination source. All the data were standardized before PCA analysis to remove dimensional effects on the components.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results \u0026 Discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Occurrence of PAHs in Water\u003c/h2\u003e \u003cp\u003eSurface water from nine sampling points mentioned in Table S2 and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e was analyzed to determine the concentration of sixteen PAHs carcinogenic compounds listed in the priority list of EPAs. The concentrations of PAHs from the mentioned locations in the Akram, Pinyari, and Phuleli canals were determined during pre-monsoon and post monsoon season. The variations in concentration were found at different sampling points of canals due to the addition of different pollution sources along the length of canal. All the samples collected in both seasons were found to be contaminated with 16 different lower molecular weight (LMW) and higher molecular weight (HMW) polycyclic aromatic hydrocarbons (PAHs). The cumulative results are described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, whereas the percent compositions in both seasons are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The total concentration of \u0026sum;\u003csub\u003e16\u003c/sub\u003ePAHs in pre-monsoon was in the range of 76.51 to 5663.1 ng/L. The location S1, located near Kotri Barrage, was contaminated with maximum PAHs concentration, i.e., 5663.1 ng/L, which is exceptionally high.\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\u003eThe cumulative concentration of PAHs in water and sediments of Left-bank Canals\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"20\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSampling Locations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u0026sum;\u003csub\u003e16\u003c/sub\u003ePAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003e\u0026sum;LMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c18\" namest=\"c14\"\u003e \u003cp\u003e\u0026sum;HMW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWater\u003c/p\u003e \u003cp\u003e(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSediment\u003c/p\u003e \u003cp\u003e(ng/g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eWater\u003c/p\u003e \u003cp\u003e(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003eSediment\u003c/p\u003e \u003cp\u003e(ng/g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eWater\u003c/p\u003e \u003cp\u003e(ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c18\" namest=\"c17\"\u003e \u003cp\u003eSediment\u003c/p\u003e \u003cp\u003e(ng/g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e8802.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e849.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e50.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e7952.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5663.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2976.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e416.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e5656.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e2559.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e822.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3571.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e133.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e807,23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e3437.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e247.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e11939.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e75.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1421.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e172.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e10517.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e6509.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e97.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e13.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e6411.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e201.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e10778.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e5045.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e196.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e5733.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e446.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e410.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e71.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c17\" namest=\"c15\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e836.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e797.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e491.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e474.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e46.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e53.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1459.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e170.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e36.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e1289.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e4139.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e405.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e240.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e3733.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e43179.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e17141.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e62.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e26037.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e261.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e15238.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e10870.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e248.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e4367.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eS9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e9139.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e546.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e49.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e8592.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4752.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e6548.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e219.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1816.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c12\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c15\" namest=\"c13\"\u003e \u003cp\u003e4532.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003e4732.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c19\" namest=\"c18\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c20\" namest=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"20\"\u003e\u003cem\u003ePr\u0026thinsp;=\u0026thinsp;Pre-monsoon, Po\u0026thinsp;=\u0026thinsp;Post-monsoon, LMW\u0026thinsp;=\u0026thinsp;Low Molecular weight, HMW\u0026thinsp;=\u0026thinsp;High Molecular Weight\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn contrast, the lowest cumulative concentration of 60.35 ng/L was observed at location S6 on Akram Wah. The location S9 was the point where the second-highest concentration of higher molecular weight PAHs, i.e., 4752.19 ng/L, was depicted. The average concentration of 1334.86 ng/L was found in the pre-monsoon period. The concentrations of HMW were maximum in percentage at samples from all the locations. The level of individual PAH in pre-monsoon season along standard deviation is summarized in Table S3.\u003c/p\u003e \u003cp\u003eThe total concentration is the summation of 16 different PAHs with a higher concentration of long ring benzoic compounds, which include BaP, BbF, dBahA, and BkF. The primary sources of long ring PAHs are automobile emissions, mainly diesel oil emission and oil (Kavouras et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). In the pre-monsoon season, the water flow at Kotri barrage is relatively low. Maintenance work is often carried out in this season, which might be the reason for higher PAHs concentration at location S1 due to the release of lubricating oil during gate maintenance. The other source of BkF and BbF contaminations could be agricultural runoffs, wood, and grass burning (Tian et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009a\u003c/span\u003e; Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Benzopyrene is associated with coal burning, diesel, or traffic exhaust (Hong et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007a\u003c/span\u003e). Moreover, almost all the sampling locations were contaminated with BbF and Chr due to the excess release of wastewater and municipal solid waste burning in the vicinity of the canals and atmospheric fallout (Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The domestic and industrial effluents from Hyderabad city, either untreated or partially treated, drain into the canals; therefore, the concentration of these pollutants decreased with spatial distribution from the point of discharge towards the downstream.\u003c/p\u003e \u003cp\u003eIn the post-monsoon season, the total concentration was in the range of 22.26 to 836.46 ng/L, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The location S5 was found with maximum total PAH concentration, i.e., 836.46 ng/L, where cottage industry wastewater and domestic solid waste from Hyderabad city are being discharged. In contrast, the lowest concentration was observed at location S3, i.e., 22.26 ng/L. S3 is located near Kotri barrage at Akram Wah, from where water is supplied to Hyderabad city for drinking purposes. The location S2 was contaminated with maximum percent of HMW-PAHs i.e., BaP with a concentration of 822.60 ng/L. This site is near Jamshoro Joint Venture Limited (JJVL) oil and gas exploration plant from where the wastewater drains, which is the primary source of higher molecular weight PAHs. However, on average, 273.48 ng/L concentration of PAHs was observed in the post-monsoon season. The concentration of individual PAHs in the post-monsoon season is summarized in Table S4. In general, the samples collected in pre-monsoon show higher concentration than the post-monsoon season owing to the lower water flow rate in pre-monsoon. Henceforth, the increased flow is responsible for lower concentration in the post-monsoon season because of dilution.\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. \u003cb\u003eOccurrence of 16 PAHs in water samples of left-bank canals of Kotri barrages (a) pre-monsoon (b) post-monsoon seasons\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Occurrence of PAHs in Sediments\u003c/h2\u003e \u003cp\u003eDue to PAHs\u0026rsquo; hydrophobic property, most of these chemicals are not dissolved in water, therefore, adsorbed on the surface of sediments (Abdel-shafy and Mansour \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Thus, sediment samples from 6 different locations have been collected in pre-monsoon and post-monsoon season to analyze 16 different LMW and HMW polycyclic aromatic hydrocarbons. The total concentrations of PAHs in sediment samples are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e whereas, percentage compositions are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (a) and (b) for both seasons. Moreover, the individual PAH level in sediments samples is summarized in Table S5 and S6, along with their minimum, maximum, and standard deviation. The total concentration in the pre-monsoon season was found in the range of 2976.70 to 15238.33 ng/g. The location S8 was contaminated with the highest cumulative PAHs concentration, i.e., 15238.33 ng/g, containing about 35% pyrene (5333.50 ng/g) alone. Fluoranthene was the highest occurring PAH with a concentration of 2345.63 ng/g, accounting for 15.39%. The lowest concentration of total PAHs was detected at location S2 with 2976.70 ng/g, containing 33% chrysene with a maximum percentage.\u003c/p\u003e \u003cp\u003eIn the post-monsoon season, PAHs\u0026rsquo; commutative concentration in sediment samples was 285.54 to 43179.24 ng/g. The highest total PAHs concentration was observed in sediments samples of location S8 containing BbF with a maximum percentage of 12.21%. Location S3 was found with minimum cumulative concentration.\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. \u003cb\u003eOccurrence of 16 PAHs in Sediment samples of LB-canals of Kotri barrages (a) pre-monsoon (b) post-monsoon seasons\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eThe cumulative concentration of PAHs in water and sediments of Left-bank Canals\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Principal Component Analysis\u003c/h2\u003e \u003cp\u003eThe major source of PAHs in surface water and sediments include industrial effluent, domestic wastewater, oil spillage, incomplete combustion of coal, and other atmospheric fallout (Abdel-shafy and Mansour \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Škrbić et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Turaki Usman et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The left-bank canals of Kotri barrage comprehensively receive organic-rich wastewater from various sources. Therefore, it is quite difficult to identify one or specific source. A single PAH might have multiple sources; therefore, Principal Components Analysis (PCA) based correlation was used to identify source apportionment. Previously, researchers have used different ratio of lower and higher molecular weight PAHs (LMW/HMW) such as Phen/An, An / (Phen\u0026thinsp;+\u0026thinsp;An), Fluor/ (Fluor\u0026thinsp;+\u0026thinsp;Pyr), BaA/(BaA\u0026thinsp;+\u0026thinsp;Chr), Ind/ (Ind\u0026thinsp;+\u0026thinsp;BgP) and Fluor/Pyr. PCA was performed based on these ratios to identify the potential sources and their relation.\u003c/p\u003e \u003cp\u003ePCA is most often utilized to identify pollution sources to signify the differences and similarities in sources. The data set calculated using the PCA approach with six factors loading with greater than one eigenvalue (Eigen values\u0026thinsp;\u0026gt;\u0026thinsp;1) is described in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. F1 illustrated 37.39 percent total variance, which was dominated with phen, Fluor, BaA, BkF, BghiP, BaP, and Chr. The major source of phenanthrene is from coal combustion(Harrison and Dourish \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), Fluor from workshop effluent or automobile service station wastewater (Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), BkF, and BaA from vehicular generated products, including gas and diesel emission (Larsen and Baker \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), BaP and Chr from industrial emissions and wastewater (Hong et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007b\u003c/span\u003e). BghiP is also from industrial sources and fuel combustion (Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). F1 includes the chemicals associated with multiple sources such as emissions from industries, coal, and wood burning. The dominant compounds explained by F2 with a maximum 21.78 percent total variance include AC, dBahA, Phen, Ind, Acphthy, dBahA, Flou. The major source of these pollutants is workshops exhaust and emissions from vehicles (Guo et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).The left bank canal passes through the periphery of densely populated areas of Hyderabad city. The wastewater from automobile service stations situated at different locations in the city discharges wastewater into canals through multiple drains without any treatment, which is the primary reason for contamination. Moreover, huge traffic passes along the canals from where emission is deposited in water bodies through dry deposition as shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\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\u003eValues of factor loadings for 16 PAHs in Kotri Barrage LB-Canals\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcphthy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.23\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\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\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\u003e0.91\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\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.06\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\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\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\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.02\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\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.01\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\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edBahA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNap\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.43\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\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\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\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEigen Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% Variance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.24\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\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFactor 3 was dominated by acenaphthylene (0.680) and naphthalene (0.646) with a total variance of 17.02%. Near the canals, few industries utilize petroleum products as a fuel from where waste in the form of water and emission is released, which might contribute to naphthalene contamination in water. Oil spills, exhaust from burning fuels, gasoline industrial effluents are the primary source of naphthalene contamination (Zakaria et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Boonyatumanond et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Factor 4 contributes 13.86% with dominancy of benzo(b)fluoranthene and pyrene. Low-income families living along the canals utilize bio-mass, coal, wood, and grass as a burning source for cooking, contributing to pyrene and benzo(b)fluoranthene (Park et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Factor 5 depicted a 6.74 percent total variance with dominant fluoranthene and anthracene as dominant compounds. These chemicals are released from municipal solid waste disposal and petrochemical wastewater (Yang et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Tian et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2009b\u003c/span\u003e). The municipal solid waste from Hyderabad city is dumped openly along with the Akram, Pinyari, and Phuleli banks. Factor 6 was conquered by benzo(b)fluoranthene with a total variance of 2.24% that was very prominent in all the sampling locations with higher concentrations.\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. \u003cb\u003eValues of factor loadings for 16 PAHs in Kotri Barrage LB-Canals\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. \u003cb\u003eThe Cross-plot demonstrates the Ratio of factors F1 to F2.\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. \u003cb\u003eThe Cross-plot demonstrates the dominant PAHs compounds.\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Comparison of \u003cem\u003e\u0026sum;\u003c/em\u003ePAH detected in the world.\u003c/h2\u003e \u003cp\u003eThe PAHs concentration in water and sediments samples of LB-canals was compared comprehensively with the PAHs concentration reported in different rivers worldwide. The water and sediment of the left-bank canals were found to be contaminated with the highest overall mean \u0026sum;PAHs concentrations in the region of 60.35 -5663.06 ng/L and 2976.7\u0026ndash;15238.3 ng/g in water and sediment in the pre-monsoon season, respectively. The concentrations in post-monsoon were in the range of 22.26\u0026ndash;836.46 ug/l and 258.54\u0026ndash;43179.24 ng/g in water and sediments, respectively. The overall concentration of PAHs in left-bank canals was extremely high compared to the reported PAHs in water and deposits worldwide. The summary of PAHs comparison is demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The buffalo river (South Africa), Gomti river (India), and Cauca River (Colombia) were the rivers with the highest PAHs contaminations. In turn, the lower concentration in water and sediments were detected in the Tiber (Italy), Danube (Hungry), and Gao-ping (Taiwan) rivers. For detection of PAHs Gas Chromatography (GC) and High-Performance Liquid Chromatography (HPLC) techniques are widely used.\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\u003eConcentration ranges of \u0026sum;PAHs in surface water and sediments collected from various locations in the world.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRiver Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo. of PAHs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cem\u003e\u0026sum;\u003c/em\u003ePAHs Ranges\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReferences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWater (ng/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSediments (ng/g)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuffalo River Estuary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSouth Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14910\u0026ndash;206000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1107\u0026ndash;22,310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[36]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGomti river\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0-84000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u0026ndash;3723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[37]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoogly and Brahmaputra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026ndash;30000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026ndash;636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[38]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDamodar basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0-36000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0-582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[39]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKor River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.4\u0026ndash;375.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e167.4\u0026ndash;530.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[40]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShadegan wetland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.2-136.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10-331.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[36]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQiantang River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.3\u0026ndash;1844.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.3\u0026ndash;614.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[41]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDanube River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHungary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67\u0026ndash;96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.2\u0026ndash;288.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[42]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoson Danube\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHungary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u0026ndash;639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3\u0026ndash;1,202.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[43]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTiber River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.9\u0026ndash;72.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e157.8\u0026ndash;271.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[44]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrisbane River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAustralia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\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\u003e148\u0026ndash;3079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[11]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoston Harbor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\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\u003e7300\u0026ndash;358000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[45]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColumbia River Portland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\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\u003e1600\u0026ndash;13200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[46]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrai River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalaysia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\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\u003e1102\u0026ndash;7938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[47]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSasa River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNigeria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0-349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.95-528.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[2]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiaohe river basin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0-615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0-60057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[48]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCauca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColombia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.1-12888.2\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\u003e[49]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoltan Abad River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.5\u0026ndash;385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e180\u0026ndash;504.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[50]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGao-ping River,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u0026ndash;9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u0026ndash;356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[51]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaliao River watershed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e946-13449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62\u0026ndash;841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[52]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMasan Bay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\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\u003e207\u0026ndash;2670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[53]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmazon River Estuary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\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\u003e1.8\u0026ndash;158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[54]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYangtze River Estuary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\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\u003e89.52\u0026ndash;208.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYangtze River\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e321.8\u0026ndash;6234.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72.4\u0026ndash;3995.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[55]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKotri Barrage, Left Bank Canals (Pre-monsoon)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePakistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.35 -5663.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2976.7\u0026ndash;15238.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThis Study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKotri Barrage, Left Bank Canals (Post-monsoon)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePakistan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.26\u0026ndash;836.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e258.54\u0026ndash;43179.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThis Study\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\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. \u003cb\u003eConcentration ranges of \u0026sum;PAHs in surface water and sediments collected from various locations in the world\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Toxicity of carcinogenic C-PAHs\u003c/h2\u003e \u003cp\u003eIARC (1987) has identified BaA, BaP, BbF, BkF, Chr, dBahA, and Ind as potential carcinogens (1983). The carcinogenic PAHs (C-PAHs) in water and sediments samples were in the range of 0.216 -1298.61 ng/L and 1.32 -3284.3 ng/g, respectively (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e (a) and (b)). The C-PAH concentration in LB-canals was higher than the Soan River and Gomati River (Kumar et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Owing to the absence of guidelines for threshold limits by the government of Pakistan, the level of C-PAHs in left-bank canals of the Indus River were compared with guidelines of different countries.\u003c/p\u003e \u003cp\u003eIn this study, the carcinogenicity of seven C-PAHs was calculated by employing toxic equivalent factors (TEF) with relevance to BaP as suggested by USEPA, 1993 (Agency \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1979\u003c/span\u003e). Equation-3 was used to calculate the total equivalents (TEQ) of the carcinogenic PAHs (C-PAHs) (Aziz et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014b\u003c/span\u003e; Han et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTEQ\u0026thinsp;=\u0026thinsp;C\u003csub\u003ei\u003c/sub\u003e \u0026times;TEF\u003csub\u003ei\u003c/sub\u003e (3)\u003c/p\u003e \u003cp\u003eWhere Ci and TEF represent the initial concertation and total equivalent factor of the C-PAHs, the total TEQ of PAHs in water samples of left-bank canals of Indus River were in the range of 0.0092 to 526 ng/l at locations S1 and S7. In sediment samples, total TEQs of PAHs were in the range of 0.08 to 2098.2 ng/g at locations S4 and S5, respectively, with an average of 182.82 ng/g. The TEQs of seven PAHs in water and sediments are shown in Figure S2(a) and (b). The total concentration of C-PAHs in sediments and water was recorded highest at sites S5 and S1, but highest carcinogenic potential of \u0026sum;\u003csub\u003e7\u003c/sub\u003ePAH concentrations were at S1. This is because BaP highest concentration was found at S1, which has higher carcinogenetic potential. While TEQ of all C-PAH values was greater than one, it should be lowered to one.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Ecological Risk Assessment\u003c/h2\u003e \u003cp\u003eEcological risk assessment (ERA) via Risk Quotients (RQ) was used to assess the unwanted impacts of environmental pollutants on the ecological system. To evaluate the ecosystem risk due to PAHs in the LB-canals of river Indus, Risk Quotients of negligible permissible concentration (RQ\u003csub\u003eNPCs\u003c/sub\u003e) and maximum permissible concentration (RQ\u003csub\u003eMPCs\u003c/sub\u003e) for specific and sum of PAHs were calculated and compared with their quality-reference values. The reference values for organic pollutants in Pakistan did not exist; therefore, in this study, Kalf et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) reported values were used (Kalf et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The detailed methodology of risk evaluation is described in the published paper (Cao et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In principle, if both RQ\u003csub\u003eNPCs\u003c/sub\u003e and RQ\u003csub\u003eMPCs\u003c/sub\u003e are \u0026gt;\u0026thinsp;1 for specific PAH, then immediate actions are required because the risk is high. While RQ\u003csub\u003eNPCs\u003c/sub\u003e are \u0026gt;\u0026thinsp;1 and RQ\u003csub\u003eMPCs\u003c/sub\u003e are \u0026lt;\u0026thinsp;1, then the risk related to PAHs pollutants is middle. Classification of risk for summation of PAHs is given in Table S7.\u003c/p\u003e \u003cp\u003eThe average and median values of RQ\u003csub\u003eNPCs\u003c/sub\u003e and RQ\u003csub\u003eMPCs\u003c/sub\u003e for individual PAHs are stated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The results depicted that RQ\u003csub\u003eNPCs\u003c/sub\u003e and RQ\u003csub\u003eMPCs\u003c/sub\u003e for all individual PAHs in sediments represent medium to high risk except Nap which shows low risk in the aquatic system of the left bank canals of the Indus River. In contrast, RQ\u003csub\u003eNPCs\u003c/sub\u003e and RQ\u003csub\u003eMPCs\u003c/sub\u003e for all individual PAHs in water show low risk from five PAHs, medium risk from seven PAHs in the left bank canals of the Indus River aquatic system. Median values of RQ were used to assess the average risk level as accuracy of the mean RQ values can be influenced by extreme values. The median values of RQ were lower than the average RQ values, indicating that the related risk of each PAH is low-medium in sediment and water and is of significant concern in the left bank canals of the Indus River. The table shows that four-ring compounds are main contributor in the left bank canals ecosystem risk. HMW PAHs are more carcinogenic and mutagenic as compared to LMW PAHs. Hence, the risk related to specific PAHs concentration is higher in the left bank canals of the Indus River. To control the sources of HMW and LMW compounds mitigation measures should be taken in the left bank canals of the Indus River. Based on ring number, the pattern of risk burden in water is followed in the order: 4 rings\u0026thinsp;\u0026gt;\u0026thinsp;5 rings\u0026thinsp;\u0026gt;\u0026thinsp;6 rings\u0026thinsp;\u0026gt;\u0026thinsp;3ring\u0026thinsp;\u0026gt;\u0026thinsp;2 rings while in sediments pattern of the risk burden is observed in the order: 4 rings\u0026thinsp;\u0026gt;\u0026thinsp;3 rings\u0026thinsp;\u0026gt;\u0026thinsp;5 rings\u0026thinsp;\u0026gt;\u0026thinsp;6rings\u0026thinsp;\u0026gt;\u0026thinsp;2 rings. The contribution percentage of minimum PAHs concentration by the ring is summarized in Table S7.\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\u003eRisk quotients for negligible and maximum permissible concentrations for individual PAHs.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCompounds\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eWater\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c17\" namest=\"c10\"\u003e \u003cp\u003eSediments\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRQ\u003csub\u003eNPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRQ\u003csub\u003eMPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRQ\u003csub\u003eNPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eRQ\u003csub\u003eMPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRQ\u003csub\u003eNPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRQ\u003csub\u003eMPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eRQ\u003csub\u003eNPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c17\" namest=\"c16\"\u003e \u003cp\u003eRQ\u003csub\u003eMPCs\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNaphthalene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003es\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e140.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcenaphthylene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e120.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e35.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e8.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcenaphthene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e120.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e23.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluorene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e120.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e76.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e30.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenanthrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e115.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e18.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnthracene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e692.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e193.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e6.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFluoranthene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2,600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e15.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePyrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1045.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e168.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(a)anthracene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e792.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e81.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e11.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChrysene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10,700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e9.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(b)fluoranthene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2304.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e388.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e609.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e589.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e8.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e8.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(k)fluoranthene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e403.665\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2,400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e27.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(a)pyrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e238.480\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e18.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBanzo(a,h)anthracene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.690\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e14.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzo(g,h,i)perylene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e405.909\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eindeno(1,2,3-c,d)pyrene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e22.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026sum;PAHs\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 \u003cp\u003e4323.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e427.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e2800.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1051.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e34.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e13.47\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\u003eFor all locations RQ\u0026sum;PAHs (NPCs)\u0026thinsp;\u0026gt;\u0026thinsp;1 and RQ\u0026sum;PAHs (MPCs)\u0026thinsp;\u0026gt;\u0026thinsp;1. By comparing RQs for \u0026sum;PAHs with the quality references given in Table S8, it is demonstrated that the risk related with \u0026sum;PAHs at all locations is high. Overall, the results suggested that the ecosystem risk due to the PAHs in the left bank canals of the Indus River is high. Surface water contamination due to \u0026sum;PAHs could be categorized into four groups: highly polluted (1000 ng/L), moderate-polluted (250\u0026ndash;1000 ng/L), lightly-polluted (50\u0026ndash;250 ng/L), and micro-polluted (10\u0026ndash;50 ng/L) (Aziz et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014d\u003c/span\u003e). The concentration of \u0026sum;PAHs in the surface water of Indus River\u0026rsquo;s LB-canals ranged from 66.72 to 2869.79 ng/L. Therefore, surface water of the left bank canals of the Indus River is lightly-highly contaminated in terms of PAHs pollution.\u003c/p\u003e \u003cp\u003e \u003cb\u003e\u0026lt;\u0026lt;\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. \u003cb\u003eRisk quotients for negligible and maximum permissible concentrations for individual PAHs.\u003c/b\u003e\u003cb\u003e\u0026gt;\u0026gt;\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusions\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe total lower and higher molecular weight PAHs in both sediment and water samples of LB-canals of Kotri barrage were in higher concentrations than the WHO permissible limit in both pre-monsoon and post-monsoon seasons. These canals flow through the periphery of densely populated areas and receive untreated or partially treated municipal and industrial wastewater and multiple domestic wastes drains produced in nearby residential areas on canal roads. Moreover, municipal solid waste is openly dumped in considerable quantities in the vicinity of all three canals, which ultimately leads to the flowing water with the waves and pollutes the canals. Among the three canals, the Phuleli canal bank was massively covered with domestic solid waste. The massive, heavy-duty traffic flow also embarks the PAHs in canals through the dry or wet deposition. Location at the mid-city was found with the highest concentration of PAHs among all nine locations. Moreover, the carcinogenic C-PAHs concentration was higher in water and sediments of all the left-bank canals. Henceforth, the result of this study depicts that the water quality of these canals is not suitable for drinking or irrigation purposes; therefore, there is a dire need to take mitigations measures to minimize further deterioration of canals.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are highly thankful to the U.S.-Pakistan Center for Advanced Studies in Water (USPCASW), and Center for Environmental Studies, Mehran University of Engineering and Technology, Jamshoro, Sindh Pakistan, and Pakistan Council of Scientific and Industrial Research (PCSIR), Karachi, Pakistan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;No funding was acquired from any organization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing of Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Authors confirm that they do not have any known competing of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdel-shafy HI, Mansour MSM (2016) A review on polycyclic aromatic hydrocarbons : Source, environmental impact , effect on human health and remediation. 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France\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Polycyclic aromatic hydrocarbons, Principal Component Analysis, left bank canals, Indus River, water and sediment samples","lastPublishedDoi":"10.21203/rs.3.rs-3984144/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3984144/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eKotri Barrage Left Bank Canals, i.e., Akram Pinyari, and Phuleli Wah, pass through Hyderabad Sindh, Pakistan. These canals are utilized for industrial, domestic, and agricultural purposes. These canals are badly affected by anthropogenic activities, which are major sources of organic content, especially PAHs. The present study aimed to investigate the presence, distribution, source, and ecological risk assessment of sixteen \u003cb\u003e\u0026sum;\u003c/b\u003e\u003csub\u003e\u003cb\u003e16\u003c/b\u003e\u003c/sub\u003e polycyclic aromatic hydrocarbons (PAHs) in water and sediments of Left-bank canals of River Indus-Pakistan in both pre \u0026amp; post monsoon seasons. From each canal 3 water and 2 sediment samples were collected in pre-monsoon and post-monsoon seasons. After collection of sample EPA liquid-liquid extraction were used for the extraction of samples then GC-chromatography was used to investigate the concentration of PAHs. The cumulative concentrations of \u0026sum;\u003csub\u003e\u003cb\u003e16\u003c/b\u003e\u003c/sub\u003ePAHs in the pre-monsoon season ranged between 22.26\u0026ndash;836.46 ng/l and 26.95\u0026ndash;49560 ng/g in water and sediments respectively. The total concentration of water and sediments in the post-monsoon season ranged between 76.51-5663.1 ng/L and 2976.70 -15238.33 ng/g respectively. The Principal Component Analysis (PCA) revealed that industrial and domestic wastewater discharge, solid waste burning, heavy vehicular exhaust, biomass combustion, and petroleum residues are the primary sources of PAH contamination. The toxic equivalent factor (TEF) depicted that Benzo(a)Pyrene and Banzo(a,h)anthracene are the contributing PAHs with higher carcinogenic exposure equivalent in both water and sediments. The left-bank canals of River Indus are highly contaminated with PAHs, thus posing a severe health issue to humans and aquatic life.\u003c/p\u003e","manuscriptTitle":"Seasonal Occurrence and Ecological Risk Assessment of Polycyclic Aromatic Hydrocarbons in sediments and water of Left-Bank canals of Indus River, Pakistan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-06 08:55:23","doi":"10.21203/rs.3.rs-3984144/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-04T17:46:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-03-14T05:41:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71070b2b-a2c0-4104-8270-751ca09860aa","date":"2024-03-09T21:56:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-09T19:05:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-04T08:36:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-04T08:36:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2024-02-24T06:41:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ee290d65-5cda-4613-ae84-c286bc83497d","owner":[],"postedDate":"March 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-11T15:59:11+00:00","versionOfRecord":{"articleIdentity":"rs-3984144","link":"https://doi.org/10.1007/s10661-024-13302-w","journal":{"identity":"environmental-monitoring-and-assessment","isVorOnly":false,"title":"Environmental Monitoring and Assessment"},"publishedOn":"2024-11-05 15:57:01","publishedOnDateReadable":"November 5th, 2024"},"versionCreatedAt":"2024-03-06 08:55:23","video":"","vorDoi":"10.1007/s10661-024-13302-w","vorDoiUrl":"https://doi.org/10.1007/s10661-024-13302-w","workflowStages":[]},"version":"v1","identity":"rs-3984144","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3984144","identity":"rs-3984144","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}