Suspended Matter And Chlorophyll-a Dynamics Along The Coasts of Western Java and Banten

Suspended Matter And Chlorophyll-a Dynamics Along The Coasts of Western Java and Banten | 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 Suspended Matter And Chlorophyll-a Dynamics Along The Coasts of Western Java and Banten Qurnia Wulan Sari, Putri Adia Utari, Rifqi Diyan Nugraha, Hasna May Nurlaila, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7742560/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Oil spills are recurring hazards for tropical coastal ecosystems, yet their ecological impacts remain insufficiently understood in monsoon-dominated waters such as northern Java, Indonesia. Two large spills in Karawang (July 2019 and April 2021) provided a natural experiment to evaluate how suspended matter and phytoplankton respond to acute disturbances under contrasting seasonal conditions. Unlike earlier studies focusing on single incidents, this work integrates multiple parameters and events to reveal long-term ecosystem trajectories. We analyzed satellite-derived datasets from 2019–2023, including Sentinel-3 OLCI Total Suspended Matter (TSM) and Suspended Particulate Matter (SPM), Aqua-MODIS Chlorophyll-a (Chl-a), ERA5 winds, and NOAA OISST sea surface temperatures. Spatial anomalies, seasonal climatologies, and site-specific time-series at Lontar, Karawang, and Cirebon were combined with linear trend analyses to separate natural variability from anthropogenic disturbance. Both spill events caused sharp increases in TSM and SPM, with July 2019 producing broader anomalies due to east monsoon transport, while April 2021 impacts were more localized. Chl-a anomalies dropped most strongly at Karawang, indicating phytoplankton suppression from turbidity and hydrocarbon stress, with weaker declines west and east. Over 2019–2023, suspended matter showed significant decreases while Chl-a trended upward, suggesting clearer waters enhanced light penetration and supported partial biological recovery. These findings demonstrate that optical recovery is faster than ecological recovery, with oil spill legacies persisting unevenly across northern Java’s coastal waters. Oil spill Chl-a Suspended Matter (SPM and TSM) Satellite remote sensing Java Sea Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 1 Introduction The coastal waters of Karawang are indispensable habitats that facilitate ecological processes of the marine ecosystem, including primary productivity, biodiversity maitenance, and the preservation of optimal water quality, thereby contributing to the sustenance of the northern coast of West Java (Nugraha et al., 2021 ; Suwanto et al., 2021 ; Wicaksono et al., 2021 ). Both local marine ecosystem and regional environmental stability require the health of coastal waters as key ecological functions to underpin the sustainability of fisheries, coral reefs, mangroves and other marine ecosystems (Zuhri et al., 2023 ). However, increasing anthropogenic pressures such as industrialization, coastal development, and particularly oil spills are steadily impairing the ecological functions of these marine ecosystems (de O.S. et al., 2021; Sharma et al., 2024 ). Oil spills pose significant threats to marine life by contaminating water, destroying breeding habitats, and introducing toxic substances into the food chain (Asif et al., 2022 ). Consequently, immediate and effective measures are essential to protect and manage these coastal habitats to ensure long-term ecological resilience in the Karawang coastal waters. Numerous studies have shown anthropogenic environmental threats of oil spills, with profound implications for water quality, ecosystem structure, and local communities (Bi et al., 2025 ; Khoi et al., 2023 ; Ma et al., 2023 ). In July 2019, a significant oil spill occurred off the coast of Karawang, West Java, Indonesia, releasing large volumes of crude oil into surrounding waters (Effendi et al., 2022 ; Kurniawan et al., 2024 ). The extent of the contamination affected a broad area along the northern coast of Java, including the provinces of Western Java and Banten. An oil spill incident that also occurred off the coast of Karawang in 2019 resulted in significant environmental damage, with impacts extending to the Jakarta area (Sari et al., 2021). Such incidents raise critical environmental concerns, particularly regarding changes in key biogeochemical parameters such as Total Suspended Matter (TSM), Suspended Particulate Matter (SPM), and Chlorophyll-a (Chl-a), which are widely used as indicators of coastal water quality and ecological health (Ashphaq et al., 2023 ; Gohin et al., 2020 ; Shampa et al., 2024 ). The spatial and temporal variability of TSM, SPM, and Chl-a in coastal regions is influenced by a complex interplay of natural drivers (monsoonal winds, riverine discharge, and oceanic circulation) and anthropogenic pressures (land-use change, industrial runoff, and aquaculture expansion)(Chaichitehrani et al., 2018 ; D’Sa et al., 2007 ; Maslukah et al., 2022 ). Conversely, oil spills introduce a severe and often extended disturbances to coastal ecosystems. The chemical and physical properties of petroleum hydrocarbons can decrease phytoplankton growth, change how particles behave in the water, and affect the way sediments interact with the water column (Bacosa et al., 2022 ; Okeke et al., 2022 ; Zhu et al., 2022 ). Monitoring the spatial and temporal changes in these coastal parameters helps reveal both immediate and lasting ecological responses to instabilities, and reinforce the development of effective strategies for coastal management (Hewitt & Thrush, 2007 ; Sukhotin & Berger, 2013 ). (Chen et al., 2014; Wang et al., 2018). By analyzing multi-temporal satellite observations, this research aimed to detect anomalies and trends in the distribution of TSM, SPM, and Chl-a concentrations before and after the oil spill events (Hu et al., 2011). Establishing a baseline of pre-spill conditions and comparing it with post-spill data enables a quantitative assessment of the environmental impact (Sun et al., 2020). The insights gained from this analysis are intended to support evidence-based decision-making for coastal management, restoration planning, and disaster response (Wang et al., 2018). Furthermore, the findings provide valuable contributions toward understanding the ecological consequences of oil spills in tropical marine environments, particularly in the context of safeguarding biodiversity and sustaining coastal livelihoods along the northern coast of Java Island (Chen et al., 2014). This study aims to investigate the spatial-temporal dynamics of TSM, SPM, and Chl-a concentrations in the coastal waters of western Java province and Banten, with a specific focus on the periods before and after the Karawang oil spill events. By utilizing the Sentinel-3 OLCI data for comprehensive spatial coverage and continuous monitoring of water quality (Masoud, 2022 ; Pahlevan et al., 2022 ; Rodrigues et al., 2022 ) in the coastal waters of western Java province and Banten. Although the OLCI sensor provides a coarser spatial resolution (300 m) compared to Sentinel-2 MSI and Landsat sensors, it offers sufficient resolution to capture meaningful spatial patterns of water quality across the reservoir (Bar et al., 2023 ; Toming et al., 2017 ). More importantly, OLCI's high temporal resolution—achieving near-daily revisit frequency—represents a significant advantage over MSI and Landsat for continuous environmental observation. Equipped with 21 spectral bands spanning 400–1020 nm, OLCI is particularly well-suited for inland water monitoring and the detection of algal blooms (Kravitz et al., 2020 ). Furthermore, the Sentinel-3 OLCI data can identify anomalies and trends in water quality parameters associated with oil contamination. The results are expected to improve the understanding of coastal system responses to oil spills in tropical environments and contribute to the development of effective monitoring, mitigation, and restoration frameworks in similar high-risk coastal zones. 2 Materials and methods 2.1 Research area The study was performed in the northern coast of west Java, with Karawang District identified as the area most severely impacted by the oil spill. The northern part of West Java Province is the productive Java Sea, characterized by the presence of numerous oil wells and functions as an important shipping route through the Java Sea. Lontar station (106.2 oE − 106.4oE, 5.9 oS − 6.2 oS), Karawang station (107.4 oE − 107.6oE, 6.0 oS − 6.4 oS) and Cirebon Station (108.3 oE − 108.5oE, 6.3 oS − 6.7 oS) are all situated along the northern coast of west Java, adjacent to the Java Sea (Fig. 1 ). This region lies within the coastal transition zone between the western Java Sea and the Sunda Shelf, a geologically shallow and ecologically productive marine basin. The area includes coastal ecosystems such as mangroves, seagrasses, and coral reefs, all of which are highly sensitive to oil contamination and changes in particulate loading and nutrient dynamics. 2.2 Data This study employed global monthly datasets of Total Suspended Matter (TSM), Suspended Particulate Matter (SPM), and Chlorophyll-a (Chl-a) derived from the Ocean and Land Colour Instrument (OLCI) sensor, available through the GlobColour project ( https://hermes.acri.fr/ ), for the period of 2019 to 2023 (Table 1 ). These satellite-based products provide a consistent and comprehensive time series of ocean color parameters, facilitating large-scale assessments of water quality. The TSM dataset was generated using the OC5 algorithm, which is specifically optimized for Case 2 waters coastal and turbid environments where inorganic particles are predominant over phytoplankton. To ensure fidelity in nearshore environments, algorithms were calibrated with regional in situ measurements, consistent with approaches tested in other coastal systems (Bi et al., 2011; Qiu, 2013; Liu et al., 2020; Li et al., 2021a,b). The use of OLCI’s 300 m resolution enabled detailed assessments of resuspension events, sediment fluxes, and turbidity plumes associated with both monsoonal processes and anthropogenic perturbations. For historical reference and algorithm validation, additional ocean color datasets from MERIS full-resolution imagery (300 m), spanning 2003–2012, were examined, with preprocessing masks applied to mitigate contamination from clouds, aerosols, and sun glint (Rast & Bézy, 1995; Monahan & O’Muircheartaigh, 1980). Meanwhile, Chl-a data were obtained from the Aqua-MODIS monthly global ocean color product, covering the period from October 2017 to September 2023, with a nominal resolution of 4.5 km. To minimize land adjacency effects, pixels within 5 km of the shoreline were excluded, and observations affected by cloud cover were masked out. Following standard ocean-color practices, concentrations were log-transformed to account for their log-normal distribution (Campbell, 1995), and monthly averages were computed to capture seasonal and interannual variability. Empirical Orthogonal Function (EOF) analysis was applied to decompose the spatial and temporal structure of Chl-a variability, with the first two modes explaining a combined 67% of the total variance, underscoring the role of both monsoonal forcing and episodic disturbances in shaping phytoplankton dynamics. To place these bio-optical indicators in the context of physical forcing, ancillary oceanographic datasets were incorporated. Wind field data were obtained from the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), providing hourly 10 m wind components at ~ 0.25° resolution. These reanalysis products enabled assessment of seasonal monsoon regimes and mesoscale wind variability, which were subsequently correlated with surface anomaly patterns in SPM, TSM, and Chl-a. Sea Surface Temperature (SST) and its anomalies were retrieved from the NOAA Optimum Interpolation SST (OISST) product, blending satellite infrared and in situ buoy observations to produce daily global maps at ~ 0.25° resolution. Table 1 Satellite Data Data Horizontal Resolution Temporal Resolution Source Chl-a 4 km Monthly 1 March 2019–31 July 2023 Global Colour monthly OLCIB product SPM 300 m Monthly 1 March 2019–31 July 2023 Global Colour monthly OLCIB TSM 300 m Monthly 1 March 2019–31 July 2023 Global Colour monthly OLCIB Wind 0.25⁰x0.25⁰ Monthly 1 January 2019–31 December 2023 Marine Copernicus Sea Surface Temperature (SST) 0.04⁰x0.04⁰ Monthly 1 January 2019–31 December 2023 Aqua Modis Terra 2.3 Methods The data analysis was conducted in three sequential steps: detrending, climatology calculation, and anomaly calculation , following common practices in oceanographic and climate studies (Proietti, T., & Giovannelli, A., 2025 ) To remove long-term linear changes, the original time series ( \(\:{Y}_{t}\) ) was first detrended using the Eq. 1 : $$\:{Y}_{t}=a.t+b+{\epsilon\:}_{t}$$ 1 where \(\:{Y}_{t}\) is the observed value at time \(\:t\) , \(\:a\) is the slope of the linear trend, \(\:b\) is the intercept, and \(\:{\epsilon\:}_{t}\) is the residual. The detrended series is obtained as Eq. 2 : $$\:{X}_{t}={Y}_{t}-\left(a.t+b\right)$$ 2 This step ensures that subsequent analysis focuses on short-term variability rather than gradual background shifts.The climatology calculation was computed to capture the mean seasonal cycle, which represents the typical conditions for each month across the study period with Eq. 3 : $$\:{\stackrel{-}{X}}_{m}=\frac{1}{N}\sum\:_{y=1}^{N}{X}_{y,m}$$ 3 where \(\:{\stackrel{-}{X}}_{m}\) is the climatological mean for month m, \(\:{X}_{y,m}\) is the detrended value in year yyy and month mmm, and NNN is the number of years (here, 2019–2023). This step removes recurring seasonal variations. TheAnomalies were then calculated by subtracting the climatological mean from the detrended data as Eq. 4 : $$\:{A}_{t}={X}_{t}-{\stackrel{-}{X}}_{m\left(t\right)}$$ 4 where \(\:{A}_{t}\) is the anomaly at time t, \(\:{X}_{t}\) is the detrended value at time t, and \(\:{\stackrel{-}{X}}_{m\left(t\right)}\) is the climatological mean of the corresponding month. This final step highlights deviations from both the long-term trend and the average seasonal cycle, allowing for the identification of unusual or extreme events. 3 Results and discussions Climatologically, the study area experiences two distinct monsoon seasons: the southeast monsoon (dry season, May to September) and the northwest monsoon (wet season, November to March). These monsoon cycles greatly influence surface wind fields, precipitation patterns, runoff, and stratification, all of which interact dynamically with oil spill transport and fate. The coastal geomorphology is characterized by a gently sloping continental shelf and soft-bottom substrates that are susceptible to sediment resuspension, which further modulates water clarity, light penetration, and primary productivity. Figure 2 shows the climatology spatial distribution condition of (a, d) Chl-a (mg m⁻³), (b, e) SPM (g m⁻³), and (c, f) TSM (g m⁻³) during the peak of the East Monsoon (June–August, JJA; upper panels) and the West Monsoon (December–February, DJF; lower panels) along the northern coast of Java illustrates the climatological baseline conditions that frame seasonal variability in suspended matter and phytoplankton biomass. This baseline is crucial for distinguishing oil spill anomalies from the natural dynamics of monsoon-driven forcing. During the east monsoon (JJA), panels 2a–2c reveal elevated SPM and TSM concentrations along nearshore waters of Banten, Jakarta Bay, and Karawang, reflecting strong southeasterly winds that enhance sediment resuspension while limiting river discharge. In these months, Chl-a concentrations (panel 2a) remain low across much of the northern coast, indicating that light limitation under turbid conditions suppresses phytoplankton productivity. Offshore regions show clearer waters with reduced TSM and SPM, but Chl-a is also low, highlighting nutrient limitation under dry-season circulation. Meanwhile, the west monsoon (DJF) climatology (panels 2d–2f) displays increased rainfall and riverine inputs from the Citarum, Cisadane, and Ciliwung rivers, leading to higher SPM and TSM near estuaries (panels 2e and 2f). Despite turbidity, Chl-a values (panel 2d) increase substantially, particularly in Indramayu and Cirebon waters, suggesting that nutrient enrichment offsets reduced light penetration and promotes phytoplankton growth. In summary, Fig. 2 demonstrates the dual monsoon regime of northern Java: the east monsoon is defined by sediment resuspension and light limitation, while the west monsoon is characterized by nutrient enrichment that supports phytoplankton blooms. These climatological patterns establish the seasonal reference against which the oil spill anomalies of 2019 and 2021 must be interpreted, ensuring that deviations in TSM, SPM, and Chl-a can be attributed confidently to anthropogenic disturbance rather than monsoon background variability. During the east monsoon, elevated SPM and TSM concentrations dominate nearshore zones of West Java and Banten, reflecting sediment resuspension and reduced freshwater inflow, while Chl-a values remain relatively low offshore, indicating light-limitation under high turbidity. In contrast, the west monsoon is characterized by stronger riverine inputs, leading to enhanced nutrient delivery that sustains phytoplankton growth (higher Chl-a) even under moderately elevated SPM and TSM. This seasonal duality highlights the critical role of monsoon-driven hydrodynamics in shaping the balance between turbidity-induced light limitation and nutrient enrichment, thereby structuring coastal ecosystem productivity across northern Java. Following the description of the climatological conditions in the study area (Fig. 2 ), Fig. 3 presents the datasets used to examine the effects of oil spill events on water quality. The pre-spill conditions are shown for March–April 2019 (Fig. 3 a–b), while the spill events in July–August 2019 (Fig. 3 c–d) and April–May 2021 (Fig. 3 e–f) capture the immediate impacts on the aquatic system. Post-spill conditions during March–July 2023 (Fig. 3 g–j) illustrate the subsequent recovery and water quality dynamics in the region. Figure 3 depicts the anomaly distribution of Suspended Particulate Matter (SPM, mg/L) along the northern coast of Java, revealing clear spatial and temporal contrasts. Positive anomalies are concentrated near estuarine plumes and shallow coastal zones, especially in the Karawang waters and extending toward Cirebon. These anomalies reflect enhanced turbidity driven either by monsoonal river discharge during wet seasons or wave-induced resuspension on shallow shelves. Offshore regions, by contrast, are dominated by neutral to negative anomalies, indicating periods of reduced suspended input or enhanced sediment settling in calmer hydrodynamic environments. Prior to the July 2019 spill, fluctuations were seasonal, with positive pulses aligned with rainfall and runoff. However, the July 2019 event triggered a sharp intensification of positive anomalies in Karawang, linked to southwesterly winds that promoted mixing and the interaction of hydrocarbons with fine particles, producing aggregates that prolonged suspension in the water column. A similar but broader pattern emerged after the April 2021 oil spill, where positive anomalies spread beyond Karawang to eastern sectors, including Cirebon. This indicates a larger spatial footprint of disturbance, amplified by hydrocarbon dispersal and sediment resuspension. Although anomalies gradually diminished, nearshore Karawang remained elevated for months, demonstrating a lagged recovery relative to offshore waters. The alternation between positive nearshore and negative offshore anomalies highlights the interplay of natural forcing and oil-spill-induced amplification of turbidity. Comparable findings have been reported in other estuarine systems, such as the Hooghly Estuary in India (Bar et al., 2023 ) and Turkish coasts using Sentinel-based monitoring (Wei et al., 2021 ; D’Sa et al., 2007 ), where episodic pollution events intensify suspended particulate concentrations. Collectively, Fig. 3 underscores that oil spills exacerbate monsoonal turbidity, with Karawang as the persistent hotspot of elevated SPM anomalies. Figure 4 illustrates the anomaly of spatial and temporal variability of SPM across the northern coast of Java, with an emphasis on the Karawang region. SPM, which consists of both organic and inorganic particles suspended in the water column, serves as a key indicator of water turbidity, sediment transport, and potential contamination pathways. Its relevance in the context of oil spills lies in the compound interaction between petroleum substances and particulate matter. Following a spill, hydrocarbons can bind to suspended particles, altering their density and transport behavior, while mechanical disturbance from spill response or storm-induced agitation can resuspend settled sediments. Hence, SPM provides a critical lens through which we assess both the direct and indirect impacts of oil contamination. During the pre-event periods (March to April 2019 and July to August 2021), SPM levels appeared relatively stable across the study region. Concentrations were highest near estuarine outlets and gradually diminished moving offshore, reflecting a typical fluvial influence on coastal sedimentation. These spatial patterns were consistent with the expected behavior of particulate discharge from major rivers such as the Citarum and Cilamaya. In the absence of major meteorological disturbances, the SPM anomalies during these pre-spill periods remained within expected climatological variance. However, post-event observations—particularly from November 2019 through November 2021 revealed a dramatic shift. The anomaly maps display pronounced increases in SPM concentrations within the Area of Interest (AOI), with some anomalies extending well beyond the coastal boundary into offshore regions of the Java Sea. Figure 5 presents a detailed spatial representation of Chl-a anomalies along the Northern Coast of Java, with particular emphasis on the Karawang coastal zone, which was directly impacted by the oil spill events in July 2019 and April 2021. As a vital indicator of phytoplankton biomass, Chl-a plays a crucial role in assessing ecological productivity and water quality. It is highly responsive to fluctuations in nutrient concentrations, stratification in the water column, and the introduction of pollutants such as hydrocarbons, all of which can trigger shifts in phytoplankton communities and trophic interactions. Thus, mapping Chl-a anomalies offers valuable insight into the biological consequences of oil pollution in marine environments. Figure 5 highlights the spatiotemporal variability of Chlorophyll-a (Chl-a, mg m⁻³) anomalies along the northern coast of Java during pre-spill, spill, and post-spill conditions. Prior to July 2019, anomalies remained near baseline, with modest positive values near estuaries such as the Citarum and Cisadane, reflecting nutrient-driven productivity typical of the west monsoon (Maslukah et al., 2022 ). Following the July 2019 and April 2021 oil spills, strong negative anomalies emerged in the Karawang sector, coinciding with peaks in suspended particulate matter. These declines reflect dual pressures of reduced light penetration due to turbidity and hydrocarbon toxicity suppressing phytoplankton growth, consistent with post-spill Chl-a suppression observed in the Bohai Sea (Wang et al., 2020 ). While declines were most severe and persistent at Karawang, nearby regions such as Lontar and Cirebon exhibited weaker anomalies, underscoring spatial heterogeneity in spill impacts. In the post-spill period, recovery trajectories were uneven. Western sectors, particularly Lontar and Jakarta, showed positive Chl-a anomalies by 2022, suggesting improved light penetration as suspended matter decreased and nutrient enrichment sustained productivity (Shampa et al., 2024 ). However, Karawang waters remained biologically stressed, with anomalies persisting below baseline despite turbidity normalization, echoing field assessments that documented lingering water quality degradation after the spill (Effendi et al., 2022 ). These results confirm that while physical clarity recovers relatively quickly, biological systems respond more slowly and unevenly. This pattern mirrors global evidence that oil spills induce rapid phytoplankton collapse but protracted recovery shaped by hydrocarbon residues, nutrient dynamics, and local hydrodynamics (Bi et al., 2025 ; Asif et al., 2022 ). Figure 6 captures the spatiotemporal of SSTA (°C) across the northern coast of Java during pre-spill, spill, and post-spill periods. In the baseline months of March and April 2019, waters were relatively warm with mild positive anomalies concentrated in the eastern sector, consistent with seasonal heating during the late transition toward the southeast monsoon. By July and August 2019, coinciding with the oil spill in Karawang, negative anomalies emerged prominently along the coast. These cooler-than-average signatures likely reflected the combined effects of oil slick coverage—reducing solar penetration into the water column—and enhanced mixing associated with the disturbance (Wang et al., 2020 ; Bi et al., 2025 ). A similar pattern reappeared during April and May 2021, where localized cooling anomalies coincided with the second spill event. The persistence of negative anomalies during these episodes suggests that oil contamination altered the surface energy balance, suppressing stratification and redistributing heat vertically (Asif et al., 2022 ). Ecologically, these oscillations are significant: cooler anomalies during spill periods could dampen microbial activity and slow hydrocarbon degradation (Bacosa et al., 2022 ; Zhu et al., 2022 ), while the recovery toward baseline underscores the resilience of regional circulation and air–sea fluxes (Simanjuntak & Lin, 2022 ; Sudradjat et al., 2024 ).⁴ Yet, the persistence of localized cool spots near Karawang highlights how oil spills leave an imprint not only on particulate and biological parameters but also on physical thermal regimes. By modulating temperature fields, spills influence both the pace of ecosystem recovery and the biogeochemical processes driving it, making SSTA a crucial diagnostic in linking oil-induced stress with broader oceanographic variability (Maslukah et al., 2022 ; Effendi et al., 2022 ). Figure 7 (a–b) illustrate prevailing winds before the July 2019 oil spill, while Fig. 7 (c–d) capture during-spill conditions in July–August 2019, Panels (e–f) display the wind field during the April–May 2021 oil spill, meanwhile panels (g–j) depict post-spill conditions in 2023. Stronger wind magnitudes (warm colors) coincide with enhanced surface mixing and sediment resuspension, whereas weaker winds (cool colors) correspond to calmer conditions and reduced circulation. Fig. 8, Fig. 9 and Fig. 10 illustrate the time series Time-series variability of SPM (g/m³), TSM (g/m³), and Chl-a (mg/m³) anomalies at Lontar Station, Karawang, and Cirebon Water, respectively. The Chl-a anomalies (green) often display an inverse relationship, reflecting suppressed phytoplankton biomass during high-turbidity conditions. The shaded grey zones correspond to the July 2019 and April 2021 oil spill events, when suspended matter increased abruptly, while Chl-a anomalies dropped below baseline, indicating suppression of primary productivity due to combined effects of hydrocarbon contamination, reduced light penetration, and increased particulate loading. The anomalies of SPM (orange) and TSM (blue) reveal moderate fluctuations compared to Lontar and Karawang, reflecting a combination of riverine input, monsoonal forcing, and coastal circulation in the eastern sector of the study area on Fig. 9. Peaks in suspended matter are evident during wet-season transitions, but with lower amplitude relative to the oil spill-affected Karawang waters. Chl-a anomalies (green) remain relatively stable, indicating a more resilient phytoplankton response in Cirebon compared to other stations. The shaded grey intervals mark the July 2019 and April 2021 oil spill events, showing weaker impacts at Cirebon, consistent with its greater distance from the spill epicenter and the influence of local hydrodynamics in dissipating contamination. During the pre-spill reference periods, specifically March to April 2019 and July to August 2021, Chl-a concentrations across the study area remained within normal seasonal ranges. These prevent phases were characterized by relatively stable baselines, punctuated only by minor positive anomalies that appeared in proximity to the mouths of major rivers. These localized fluctuations were likely due to natural nutrient input from riverine discharges, such as those from the Citarum and Cilamaya rivers, which are known to enrich nearshore waters and stimulate seasonal productivity. However, beginning in November 2019, immediately following the initial spill event, the spatial pattern of Chl-a shifted dramatically. The post-spill anomaly maps reveal consistently high concentrations of Chl-a within the Area delineated in the Fig. (blue line box) corresponds to the zone directly adjacent to the spill source and its probable path of influence. The geographic spread of the Chl-a anomaly post-event did not exhibit random diffusion but instead mirrored the known hydrographic structures and current systems of the northern Java Sea. The anomalies closely followed the trajectory of coastal currents and the dispersal plumes of adjacent rivers, indicating that nutrient transport and mixing played a dominant role in shaping the spatial expression of these anomalies. The anomalous concentrations extended 20 to 30 kilometers offshore from the Karawang coast, forming clear, plume-like structures along dominant current flows and wind directions. These features suggest that horizontal advection—rather than purely localized productivity—was responsible for redistributing nutrients and phytoplankton biomass farther into offshore waters. The persistence and configuration of these Chl-a-rich bands reinforce the role of regional hydrodynamics in amplifying the impact of pollution beyond the immediate spill site. Temporally, the Chl-a anomalies displayed remarkable persistence. From November 2019 through November 2021, satellite data indicated sustained elevation in surface Chl-a concentrations across all post-spill observation windows. This anomaly pattern was particularly pronounced during the wet monsoon periods in January and March of both 2020 and 2021. These months typically bring enhanced precipitation and runoff, yet the magnitude of the observed anomalies suggests more than seasonal river discharge alone. The enduring presence of elevated Chl-a during these periods likely reflects a long-term biological response to oil-derived nutrient enrichment and ongoing microbial degradation of hydrocarbons. Oil residues and degradation byproducts often introduce additional organic and inorganic nutrients into the water column, creating conditions conducive to prolonged phytoplankton growth. Moreover, increased turbidity from sediment resuspension could further limit water clarity and stratify the water column, trapping nutrients and encouraging bloom formation in surface layers. Interestingly, even in July to August 2021 a time marked as pre-spill relative to the April 2021 event Chl-a levels remained elevated above climatological averages. This unexpected trend suggests either a cumulative legacy effect from the earlier 2019 spill, a delay in ecosystem recovery, or possibly a smaller, undocumented pollution event preceding the April 2021 blowout. The latter possibility cannot be discounted, especially given the intense industrial activity and shipping traffic in the region, which increases the likelihood of minor discharges or chronic leakage contributing to background contamination. Alternatively, the anomaly could reflect a system that has entered a new biogeochemical state, where oil-related nutrient inputs have triggered a shift in the baseline productivity of the region. The ecological ramifications of such sustained Chl-a elevation are far-reaching. High phytoplankton biomass, while initially appearing beneficial from a productivity standpoint, often leads to ecological imbalance when sustained over long durations. The risk of harmful algal blooms (HABs) increases, especially in systems where nutrient inputs are not matched by sufficient flushing or mixing. These blooms can release toxins, reduce dissolved oxygen levels, and shade benthic habitats. In the northern Java shelf, where circulation is generally weak and turbidity is naturally high, prolonged phytoplankton blooms can exacerbate hypoxic conditions, particularly in deeper or semi-enclosed bays. This is especially concerning for the Karawang region, where seagrass beds, mangroves, and coastal fisheries form vital components of both biodiversity and local livelihoods. Indeed, reports of fish mortality and declining water quality in 2020 correspond with the timing and location of Chl-a anomalies, supporting the hypothesis that oil-related eutrophication had cascading impacts on ecosystem health. In conclusion, the anomaly map of Chl-a for the Northern Coast of Java serves as a biological footprint of the oil spills’ impact. The data points toward a sustained eutrophic response, driven by oil residues and amplified by natural hydrodynamic forces. The spatial coherence of the anomalies with both river plumes and coastal currents underscores the importance of understanding circulation dynamics when evaluating pollution effects. Furthermore, the prolonged nature of the anomalies highlights the slow recovery trajectory of coastal ecosystems affected by oil contamination. Figure 1 thus provides compelling evidence of how a single pollution event can leave an ecological legacy lasting years, fundamentally altering productivity patterns and ecosystem function in tropical coastal waters. Figure 11 illustrates the Spearman correlations between SPM, TSM, and Chl-a during the peak phases northern Java waters of the east monsoon (a-c) in upper panel and the west monsoon (d-e) in lower panel. The maps highlight how physical and biological interactions shift under contrasting monsoonal regimes. During the east monsoon peak (JJA), correlations between SPM–Chl-a and TSM–Chl-a were predominantly negative along the Karawang–Cirebon coastal zone, with coefficients reaching − 0.6 to − 0.8. This pattern indicates that enhanced turbidity from wave-driven resuspension and sediment inflows suppressed phytoplankton productivity by limiting light penetration. In contrast, localized positive correlations in western sectors (Banten and Jakarta Bay) suggest that high particulate matter may co-occur with elevated phytoplankton biomass where nutrient inputs from rivers and anthropogenic sources are abundant. Meanwhile, TSM–SPM correlations approached + 1 across most of the coast, underscoring their consistent and coupled response to sediment dynamics during the dry season. In the west monsoon peak (DJF), the correlations shifted markedly: SPM–Chl-a and TSM–Chl-a became strongly positive (+ 0.6 to + 0.8) across much of the northern coast, particularly in Karawang and Indramayu. This indicates that while turbidity was elevated during the rainy season, riverine discharges supplied large nutrient loads, which offset light limitation and stimulated phytoplankton growth. Such a seasonal reversal captures the ecological trade-off common in tropical estuaries: during dry monsoon months light limitation dominates, while during wet monsoon months nutrient enrichment prevails. The TSM–SPM correlation remained high (+ 0.8 to + 1) in both seasons, confirming that sediment-driven processes consistently structure the optical properties of the coastal waters. These patterns are consistent with earlier work in Semarang Bay, where strong interactions between Chl-a and TSM were observed, mediated by both sediment discharge and local nutrient dynamics (Maslukah et al., 2022 ). In Jakarta Bay and the northern coast of Java, studies also reported that monsoon-driven variability, together with nutrient inputs from the Ciliwung, Cisadane, and Citarum rivers, shaped seasonal phytoplankton blooms, with light limitation dominating the east monsoon and nutrient enrichment during the west monsoon (Kurniawan et al., 2024 ). Similar mechanisms were described for Balikpapan Bay, where rainy-season runoff was linked to phytoplankton enhancement despite increased turbidity (Widiawan, 2021 ). On a broader scale, the trade-off between turbidity and nutrient enrichment has also been observed in global systems such as the Bohai Sea, where the balance between suspended sediments and nutrient fluxes determines whether Chl-a responds positively or negatively to particulate matter (Wang, et al. 2020 ). Figure 12 shows long-term trends in Chl-a, SPM, and TSM across northern Java from April 2019 to March 2023 (p < 0.05). Positive Chl-a trends are strongest in the western nearshore (Banten–Jakarta), while negative trends dominate offshore and central West Java, reflecting persistent biological stress after the 2019 and 2021 oil spills. In contrast, SPM and TSM trends are broadly negative, with the steepest declines offshore and small positive anomalies near estuaries (Karawang, Indramayu), consistent with localized resuspension and riverine loading. Physical clarity recovered within one to two years, but Chl-a remained suppressed longest in Karawang, underscoring delayed biological recovery. Positive Chl-a trends near Jakarta likely reflect nutrient enrichment from rivers and urban inputs, while negative offshore trends indicate legacy light limitation and possible hydrocarbon residues affecting microbial cycling. Declining SPM/TSM point to regional sediment stabilization, whereas estuarine hotspots show continued turbidity without parallel phytoplankton gains. A Similar contrasts between turbidity-driven light limitation and nutrient stimulation have been reported in Semarang Bay (Maslukah et al., 2022 ), while Balikpapan Bay studies highlight patchy and delayed recovery after spills (Widiawan, 2021 ). A wider synthesis confirms oil spills often cause short-term physical but long-term biological disruption, with outcomes modulated by monsoon mixing and river inputs (Kurniawan et al., 2024 ). Seasonal dynamics also govern Chl-a responses, switching between negative (light limitation) and positive (nutrient-driven) correlations, as documented in Indonesian estuaries (Simanjuntak and Lin, 2022 ; Sudradjat et al., 2024 ). In this context, Fig. 12 highlights faster physical normalization versus slower, spatially uneven biological rebound, with implications for aquaculture resilience. The integrated analysis of results demonstrates that northern Java’s coastal ecosystems are strongly shaped by the interplay of monsoonal forcing and anthropogenic oil spill disturbances. The climatological baseline (Fig. 2 ) highlights a dual monsoon regime: the east monsoon (JJA) is characterized by sediment resuspension and light limitation, while the west monsoon (DJF) is defined by riverine enrichment, elevated turbidity near estuaries, and enhanced phytoplankton growth. This seasonal contrast mirrors previous findings from Semarang Bay and the Lesser Sunda region, where monsoon dynamics regulate the balance between nutrient supply and light availability for primary producers (Maslukah et al., 2022 ; Simanjuntak & Lin, 2022 ). Superimposed on this seasonal framework, the July 2019 and April 2021 oil spills generated sharp, localized anomalies. SPM and TSM surged in Karawang (Fig. 3 – 4 ), with the July 2019 event producing broader and more persistent anomalies than April 2021. This difference reflects both seasonal context and hydrodynamics: during the east monsoon, prevailing southeasterly winds facilitated plume advection westward, while the transitional April spill resulted in more confined but intense nearshore turbidity. Such amplification of suspended matter by oil–sediment aggregation has been documented in the northern Gulf of Mexico and the Hooghly estuary (D’Sa et al., 2007 ; Bar et al., 2023 ). The resulting turbidity spikes coincided with localized cooling (Fig. 5 ), suggesting that surface oil films reduced solar absorption and altered stratification—an imprint also observed in the Bohai Sea after the 2011 spill (Wang et al., 2020 ). Biological impacts, reflected in Chl-a anomalies (Fig. 7 –9), were immediate and severe. Karawang experienced the strongest and longest suppression of phytoplankton biomass, while Lontar and Cirebon showed weaker declines. This response highlights the dual stress of reduced light penetration under elevated turbidity and the toxic effects of hydrocarbons on phytoplankton physiology. Similar patterns of delayed biological recovery compared to faster turbidity normalization. have been observed in Balikpapan Bay and Brazilian spill sites (Widiawan, 2021 ; De Oliveira Estevo et al., 2021 ). Importantly, Figs. 11 and 12 reveal that from 2019 to 2023, SPM and TSM exhibited predominantly negative trends, indicating clearer waters, while Chl-a displayed heterogeneous but increasing trajectories, particularly near Banten and Jakarta Bay. This divergence suggests a shift from a system constrained by turbidity to one increasingly driven by nutrient dynamics—a transition with important implications for harmful algal bloom (HAB) risk (Shampa et al., 2024 ). The role of climate variability provides additional context. The study period coincided with the prolonged 2020–2022 La Niña (Harahap et al., 2023; Mujiasih et al., 2023 ; Sidauruk et al., 2023 ) which typically enhances rainfall and riverine discharge. Yet, the data revealed declining sediment inputs, suggesting that upstream controls such as reservoir trapping and land-use change may have overridden rainfall-driven sediment delivery. This hypothesis is consistent with global evidence showing that watershed interventions can decouple runoff from sediment fluxes (Proietti & Giovannelli, 2025 ). The observation that Chl-a trends increased as SPM and TSM declined underscores how water clarity “opened the gate” for phytoplankton proliferation, even under variable climatic forcing. From a broader perspective, the findings situate northern Java within global patterns of oil spill impacts. While the physical anomalies of turbidity and SSTA were relatively short-lived, biological suppression was longer-lasting and spatially uneven, echoing evidence from Arctic, subtropical, and tropical coasts (Bi et al., 2025 ; Asif et al., 2022 ; Zhu et al., 2022 ). The novelty of this study lies in its multi-parameter, multi-event synthesis: no prior research in northern Java has simultaneously tracked two major spills over a four-year window, integrating SPM, TSM, Chl-a, wind, and SST with both anomaly and trend analyses. This approach not only disentangles anthropogenic disturbances from monsoonal background variability but also demonstrates how physical clarity recovers faster than ecological function—a critical insight for managing sensitive aquaculture and fisheries systems along this heavily utilized coastline. 4 Conclusion In conclusion, this study's findings contribute to our understanding of the impact of an oil spill event on water quality in the study area. By analyzing TSM, SPM, and Chl-a concentrations during pre-event, event, and post-event conditions, the study sheds light on the ecological repercussions of oil spills and aids in formulating sustainable management practices to safeguard coastal environments.The results highlight the acute impact of the oil spill event on water quality, as evidenced by significant changes in TSM, SPM, and Chl-a concentrations during July and August 2019. Such environmental disturbances can lead to adverse effects on marine biodiversity, coastal habitats, and local communities relying on coastal resources. The post-event datasets indicate a degree of recovery in water quality indicators over time, suggesting the resilience of the coastal ecosystem to natural processes and possible management interventions. However, continued monitoring and comprehensive assessments are necessary to fully understand the long-term effects of the oil spill and the overall health of the coastal environment. The findings of this study provide valuable information for coastal management and restoration efforts. Understanding the impact and recovery of water quality after an oil spill event is crucial for devising effective strategies to mitigate future incidents and safeguard the ecological integrity of coastal regions. Additionally, continued monitoring of TSM, SPM, and Chl-a concentrations is essential for early detection of environmental changes and prompt response to potential threats in the future. Declarations Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution Q. W. Sari: drafted the manuscript, curated data, developed methods, conducted analysis and Funding. P. A. Utari: Conceptualization, Supervised, Software, Methodology, Writing – review & editing and funding. R. D. Nugraha: Data curation and analysis data. M. L. Syamsuddin, Y. M. Suherman, S. R. Anggraeni and M. U. K. Agung: editing, and critically reviewed the manuscript. H. M. Nurlaila: Project Administration, supported data curation and visualization. Acknowledgments The assistance of artificial intelligence (AI) tools in the preparation of this manuscript. The AI system was utilized to assist with grammar, style, and structure improvements, while the authors are responsible for the content and conclusions presented in this paper. The authors acknowledge the financial support from the Riset Keunggulan Keilmuan Unpad (RKKU) program, Grant No.1003/UN6.3.1/PT.00/2025 by Qurnia Wulan Sari. References Arabi, B., Salama, M. S., Pitarch, J., & Verhoef, W. (2020). Integration of in-situ and multi-sensor satellite observations for long-term water quality monitoring in coastal areas. Remote Sensing of Environment , 239 , 111632. https://doi.org/10.1016/j.rse.2020.111632 Ashphaq, M., Srivastava, P. K., & Mitra, D. (2023). 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1","display":"","copyAsset":false,"role":"figure","size":174631,"visible":true,"origin":"","legend":"\u003cp\u003eGeographical location of the study sites along the northern coast of West Java Province and Banten, Indonesia. Solid squares indicate the three monitoring stations: Lontar (west, near Tangerang), Karawang (central, directly impacted by the 2019 oil spill), and Cirebon (east, near the transition to the Central Java coastline).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/d2f9f82102c010d2cad27096.png"},{"id":92616962,"identity":"c5949412-ba88-4722-a1cf-7f27e50f52a5","added_by":"auto","created_at":"2025-10-01 17:41:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":937987,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of (a, d) Chl-a (mg m⁻³), (b, e) SPM (g m⁻³), and (c, f) TSM (g m⁻³) during the peak of the East Monsoon (June–August, JJA; upper panels) and the West Monsoon (December–February, DJF; lower panels) along the northern coast of Java.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/544c2035e0182dcd077e948a.png"},{"id":92616961,"identity":"eded83e9-b852-4fe3-bc49-3f3986164200","added_by":"auto","created_at":"2025-10-01 17:41:50","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":499246,"visible":true,"origin":"","legend":"\u003cp\u003eAnomaly distribution of Total Suspended Matter (TSM, g/m³) in northern Java waters describe the oositive TSM anomalies (brown) and Negative anomalies (blue) pre, during, and post the 2019 and 2021 oil spills.\u003c/p\u003e","description":"","filename":"image3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/613ccfdeec500fad37353b49.jpg"},{"id":92617994,"identity":"bd182c5a-5bd4-4f12-a4f5-37293e3568f9","added_by":"auto","created_at":"2025-10-01 17:57:50","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":337719,"visible":true,"origin":"","legend":"\u003cp\u003eAnomaly map of SPM (g/m³) concentration along the northern coast of Javawith positive anomalies (brown) and negative anomalies (blue) that indicate periods of turbidity level and suspended load.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/eafb8286595a09417de99a63.jpeg"},{"id":92617406,"identity":"ff47b0cf-9ae3-480d-a305-7809a77e3d15","added_by":"auto","created_at":"2025-10-01 17:49:50","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":261036,"visible":true,"origin":"","legend":"\u003cp\u003eAnomaly map of surface Chl-a (mg/m³) concentration along the northern coast of Java. Positive anomalies indicate elevated phytoplankton biomass relative to the baseline period, while negative anomalies reflect reduced productivity. The solid box marks the Area of Interest (AOI) encompassing Karawang coastal waters, which were directly impacted by the July 2019 and April 2021 oil spill.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/71618c5042925e4f480794bf.jpeg"},{"id":92616968,"identity":"a404c18b-8b6b-459f-bcc0-7be7d1d839b6","added_by":"auto","created_at":"2025-10-01 17:41:50","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":296276,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial and temporal variability of SSTA (°C) along the northern coast of Java from 2019 to 2023. 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Warmer colors (red) represent positive anomalies relative to climatology, whereas cooler colors (blue) indicate negative deviations.\u003c/p\u003e","description":"","filename":"image6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/7214e243fb1195a2dc76b7d6.jpeg"},{"id":92618146,"identity":"ebb2f0ff-0277-44f1-83ae-82a781f92c00","added_by":"auto","created_at":"2025-10-01 18:05:50","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":358363,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial and temporal variability of surface wind direction (vectors) and wind magnitude (m/s, color scale) along the northern coast of Java from 2019 to 2023.\u003c/p\u003e","description":"","filename":"image7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/54613a381cec6baac7148675.jpeg"},{"id":92617407,"identity":"0c14e6bc-ee51-4999-89e9-9376151a88fa","added_by":"auto","created_at":"2025-10-01 17:49:50","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":642730,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series variability of SPM (g/m³), TSM (g/m³), and Chl-a (mg/m³) anomalies at Lontar Station (106.2°E–106.4°E; 5.9°S–6.2°S) from March 2019 to July 2023. The SPM (orange) and TSM (blue) anomalies.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/4b16946c04c415e6e26d152f.png"},{"id":92617995,"identity":"b43120bd-105a-4be7-bed6-ef1b0bd69fe1","added_by":"auto","created_at":"2025-10-01 17:57:50","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":192490,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series variability of SPM (g/m³), TSM (g/m³), and Chl-a (mg/m³) anomalies at Karawang Station (107.4°E–107.6°E; 6.0°S–6.4°S) from March 2019 to July 2023. SPM (orange) and TSM (blue) anomalies display episodic peaks.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/cbf54c12c4907767bac245d8.png"},{"id":92616982,"identity":"813c692d-9e2f-43f9-9707-40510a79421f","added_by":"auto","created_at":"2025-10-01 17:41:51","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":595834,"visible":true,"origin":"","legend":"\u003cp\u003eTime-series variability of SPM (g/m³), TSM (g/m³), and Chl-a (mg/m³) anomalies at Cirebon Station (108.3°E–108.5°E; 6.3°S–6.7°S) from March 2019 to July 2023.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/3acbd3f17c8ee4c7b4145182.png"},{"id":92617996,"identity":"d41ac5e7-026c-459c-9f43-e35f493634dd","added_by":"auto","created_at":"2025-10-01 17:57:50","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":2234478,"visible":true,"origin":"","legend":"\u003cp\u003eSpearman correlation maps between Suspended Particulate Matter (SPM), Total Suspended Matter (TSM), and Chlorophyll-a (Chl-a) during peak monsoon periods in northern Java waters. Upper panels (a–c) represent the East Monsoon peak (June–August, JJA) and lower panels (d–f) represent the West Monsoon peak (December–February, DJF)\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/ff601c8a8ac5dab3494f62b8.png"},{"id":92616979,"identity":"dd7916a3-88ba-4b04-b9a0-e4dde8a7eabb","added_by":"auto","created_at":"2025-10-01 17:41:51","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":1643747,"visible":true,"origin":"","legend":"\u003cp\u003eLong-term trends of (a) Chl-a (mg/m³ per year), (b) SPM (g/m³ per year), and (c) TSM, (g/m³ per year) in northern Java waters for the period April 2019–March 2023, with statistical significance indicated (p \u0026lt; 0.05, stippled areas).\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/2426da5ca485378b1739f2ce.png"},{"id":100154004,"identity":"29e25277-a457-49f9-b8f7-68e4a1507f1e","added_by":"auto","created_at":"2026-01-13 13:54:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8816958,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7742560/v1/4ca0c2da-6111-4155-ab7d-5d29057f9725.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Suspended Matter And Chlorophyll-a Dynamics Along The Coasts of Western Java and Banten","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eThe coastal waters of Karawang are indispensable habitats that facilitate ecological processes of the marine ecosystem, including primary productivity, biodiversity maitenance, and the preservation of optimal water quality, thereby contributing to the sustenance of the northern coast of West Java (Nugraha et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Suwanto et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Wicaksono et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Both local marine ecosystem and regional environmental stability require the health of coastal waters as key ecological functions to underpin the sustainability of fisheries, coral reefs, mangroves and other marine ecosystems (Zuhri et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, increasing anthropogenic pressures such as industrialization, coastal development, and particularly oil spills are steadily impairing the ecological functions of these marine ecosystems (de O.S. et al., 2021; Sharma et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Oil spills pose significant threats to marine life by contaminating water, destroying breeding habitats, and introducing toxic substances into the food chain (Asif et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequently, immediate and effective measures are essential to protect and manage these coastal habitats to ensure long-term ecological resilience in the Karawang coastal waters.\u003c/p\u003e\u003cp\u003eNumerous studies have shown anthropogenic environmental threats of oil spills, with profound implications for water quality, ecosystem structure, and local communities (Bi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Khoi et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ma et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In July 2019, a significant oil spill occurred off the coast of Karawang, West Java, Indonesia, releasing large volumes of crude oil into surrounding waters (Effendi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kurniawan et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The extent of the contamination affected a broad area along the northern coast of Java, including the provinces of Western Java and Banten. An oil spill incident that also occurred off the coast of Karawang in 2019 resulted in significant environmental damage, with impacts extending to the Jakarta area (Sari et al., 2021). Such incidents raise critical environmental concerns, particularly regarding changes in key biogeochemical parameters such as Total Suspended Matter (TSM), Suspended Particulate Matter (SPM), and Chlorophyll-a (Chl-a), which are widely used as indicators of coastal water quality and ecological health (Ashphaq et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Gohin et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shampa et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe spatial and temporal variability of TSM, SPM, and Chl-a in coastal regions is influenced by a complex interplay of natural drivers (monsoonal winds, riverine discharge, and oceanic circulation) and anthropogenic pressures (land-use change, industrial runoff, and aquaculture expansion)(Chaichitehrani et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; D\u0026rsquo;Sa et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Maslukah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Conversely, oil spills introduce a severe and often extended disturbances to coastal ecosystems. The chemical and physical properties of petroleum hydrocarbons can decrease phytoplankton growth, change how particles behave in the water, and affect the way sediments interact with the water column (Bacosa et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Okeke et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Monitoring the spatial and temporal changes in these coastal parameters helps reveal both immediate and lasting ecological responses to instabilities, and reinforce the development of effective strategies for coastal management (Hewitt \u0026amp; Thrush, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sukhotin \u0026amp; Berger, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). (Chen et al., 2014; Wang et al., 2018).\u003c/p\u003e\u003cp\u003eBy analyzing multi-temporal satellite observations, this research aimed to detect anomalies and trends in the distribution of TSM, SPM, and Chl-a concentrations before and after the oil spill events (Hu et al., 2011). Establishing a baseline of pre-spill conditions and comparing it with post-spill data enables a quantitative assessment of the environmental impact (Sun et al., 2020). The insights gained from this analysis are intended to support evidence-based decision-making for coastal management, restoration planning, and disaster response (Wang et al., 2018). Furthermore, the findings provide valuable contributions toward understanding the ecological consequences of oil spills in tropical marine environments, particularly in the context of safeguarding biodiversity and sustaining coastal livelihoods along the northern coast of Java Island (Chen et al., 2014).\u003c/p\u003e\u003cp\u003eThis study aims to investigate the spatial-temporal dynamics of TSM, SPM, and Chl-a concentrations in the coastal waters of western Java province and Banten, with a specific focus on the periods before and after the Karawang oil spill events. By utilizing the Sentinel-3 OLCI data for comprehensive spatial coverage and continuous monitoring of water quality (Masoud, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pahlevan et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Rodrigues et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) in the coastal waters of western Java province and Banten. Although the OLCI sensor provides a coarser spatial resolution (300 m) compared to Sentinel-2 MSI and Landsat sensors, it offers sufficient resolution to capture meaningful spatial patterns of water quality across the reservoir (Bar et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Toming et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). More importantly, OLCI's high temporal resolution\u0026mdash;achieving near-daily revisit frequency\u0026mdash;represents a significant advantage over MSI and Landsat for continuous environmental observation. Equipped with 21 spectral bands spanning 400\u0026ndash;1020 nm, OLCI is particularly well-suited for inland water monitoring and the detection of algal blooms (Kravitz et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, the Sentinel-3 OLCI data can identify anomalies and trends in water quality parameters associated with oil contamination. The results are expected to improve the understanding of coastal system responses to oil spills in tropical environments and contribute to the development of effective monitoring, mitigation, and restoration frameworks in similar high-risk coastal zones.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Research area\u003c/h2\u003e\u003cp\u003eThe study was performed in the northern coast of west Java, with Karawang District identified as the area most severely impacted by the oil spill. The northern part of West Java Province is the productive Java Sea, characterized by the presence of numerous oil wells and functions as an important shipping route through the Java Sea. Lontar station (106.2 oE\u0026thinsp;\u0026minus;\u0026thinsp;106.4oE, 5.9 oS\u0026thinsp;\u0026minus;\u0026thinsp;6.2 oS), Karawang station (107.4 oE\u0026thinsp;\u0026minus;\u0026thinsp;107.6oE, 6.0 oS\u0026thinsp;\u0026minus;\u0026thinsp;6.4 oS) and Cirebon Station (108.3 oE\u0026thinsp;\u0026minus;\u0026thinsp;108.5oE, 6.3 oS\u0026thinsp;\u0026minus;\u0026thinsp;6.7 oS) are all situated along the northern coast of west Java, adjacent to the Java Sea (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This region lies within the coastal transition zone between the western Java Sea and the Sunda Shelf, a geologically shallow and ecologically productive marine basin. The area includes coastal ecosystems such as mangroves, seagrasses, and coral reefs, all of which are highly sensitive to oil contamination and changes in particulate loading and nutrient dynamics.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Data\u003c/h2\u003e\u003cp\u003eThis study employed global monthly datasets of Total Suspended Matter (TSM), Suspended Particulate Matter (SPM), and Chlorophyll-a (Chl-a) derived from the Ocean and Land Colour Instrument (OLCI) sensor, available through the GlobColour project (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://hermes.acri.fr/\u003c/span\u003e\u003cspan address=\"https://hermes.acri.fr/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), for the period of 2019 to 2023 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These satellite-based products provide a consistent and comprehensive time series of ocean color parameters, facilitating large-scale assessments of water quality. The TSM dataset was generated using the OC5 algorithm, which is specifically optimized for Case 2 waters coastal and turbid environments where inorganic particles are predominant over phytoplankton. To ensure fidelity in nearshore environments, algorithms were calibrated with regional in situ measurements, consistent with approaches tested in other coastal systems (Bi et al., 2011; Qiu, 2013; Liu et al., 2020; Li et al., 2021a,b). The use of OLCI\u0026rsquo;s 300 m resolution enabled detailed assessments of resuspension events, sediment fluxes, and turbidity plumes associated with both monsoonal processes and anthropogenic perturbations.\u003c/p\u003e\u003cp\u003eFor historical reference and algorithm validation, additional ocean color datasets from MERIS full-resolution imagery (300 m), spanning 2003\u0026ndash;2012, were examined, with preprocessing masks applied to mitigate contamination from clouds, aerosols, and sun glint (Rast \u0026amp; B\u0026eacute;zy, 1995; Monahan \u0026amp; O\u0026rsquo;Muircheartaigh, 1980). Meanwhile, Chl-a data were obtained from the Aqua-MODIS monthly global ocean color product, covering the period from October 2017 to September 2023, with a nominal resolution of 4.5 km. To minimize land adjacency effects, pixels within 5 km of the shoreline were excluded, and observations affected by cloud cover were masked out. Following standard ocean-color practices, concentrations were log-transformed to account for their log-normal distribution (Campbell, 1995), and monthly averages were computed to capture seasonal and interannual variability. Empirical Orthogonal Function (EOF) analysis was applied to decompose the spatial and temporal structure of Chl-a variability, with the first two modes explaining a combined 67% of the total variance, underscoring the role of both monsoonal forcing and episodic disturbances in shaping phytoplankton dynamics.\u003c/p\u003e\u003cp\u003eTo place these bio-optical indicators in the context of physical forcing, ancillary oceanographic datasets were incorporated. Wind field data were obtained from the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), providing hourly 10 m wind components at ~\u0026thinsp;0.25\u0026deg; resolution. These reanalysis products enabled assessment of seasonal monsoon regimes and mesoscale wind variability, which were subsequently correlated with surface anomaly patterns in SPM, TSM, and Chl-a. Sea Surface Temperature (SST) and its anomalies were retrieved from the NOAA Optimum Interpolation SST (OISST) product, blending satellite infrared and in situ buoy observations to produce daily global maps at ~\u0026thinsp;0.25\u0026deg; resolution.\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\u003eSatellite Data\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eData\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHorizontal Resolution\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTemporal Resolution\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChl-a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 km\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMonthly\u003c/b\u003e\u003c/p\u003e\u003cp\u003e1 March 2019\u0026ndash;31 July 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGlobal Colour monthly OLCIB product\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSPM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e300 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMonthly\u003c/b\u003e\u003c/p\u003e\u003cp\u003e1 March 2019\u0026ndash;31 July 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGlobal Colour monthly OLCIB\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTSM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e300 m\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMonthly\u003c/b\u003e\u003c/p\u003e\u003cp\u003e1 March 2019\u0026ndash;31 July 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGlobal Colour monthly OLCIB\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.25⁰x0.25⁰\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMonthly\u003c/b\u003e\u003c/p\u003e\u003cp\u003e1 January 2019\u0026ndash;31 December 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMarine Copernicus\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSea Surface Temperature (SST)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.04⁰x0.04⁰\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMonthly\u003c/b\u003e\u003c/p\u003e\u003cp\u003e1 January 2019\u0026ndash;31 December 2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAqua Modis Terra\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Methods\u003c/h2\u003e\u003cp\u003eThe data analysis was conducted in three sequential steps: \u003cb\u003edetrending, climatology calculation, and anomaly calculation\u003c/b\u003e, following common practices in oceanographic and climate studies (Proietti, T., \u0026amp; Giovannelli, A., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eTo remove long-term linear changes, the original time series (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{t}\\)\u003c/span\u003e\u003c/span\u003e) was first detrended using the Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{Y}_{t}=a.t+b+{\\epsilon\\:}_{t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Y}_{t}\\)\u003c/span\u003e\u003c/span\u003eis the observed value at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:a\\)\u003c/span\u003e\u003c/span\u003e is the slope of the linear trend, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:b\\)\u003c/span\u003e\u003c/span\u003e is the intercept, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}_{t}\\)\u003c/span\u003e\u003c/span\u003e is the residual. The detrended series is obtained as Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{X}_{t}={Y}_{t}-\\left(a.t+b\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThis step ensures that subsequent analysis focuses on short-term variability rather than gradual background shifts.The climatology calculation was computed to capture the mean seasonal cycle, which represents the typical conditions for each month across the study period with Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:{\\stackrel{-}{X}}_{m}=\\frac{1}{N}\\sum\\:_{y=1}^{N}{X}_{y,m}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{X}}_{m}\\)\u003c/span\u003e\u003c/span\u003e is the climatological mean for month m, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{y,m}\\)\u003c/span\u003e\u003c/span\u003e is the detrended value in year yyy and month mmm, and NNN is the number of years (here, 2019\u0026ndash;2023). This step removes recurring seasonal variations. TheAnomalies were then calculated by subtracting the climatological mean from the detrended data as Eq.\u0026nbsp;\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e:\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{A}_{t}={X}_{t}-{\\stackrel{-}{X}}_{m\\left(t\\right)}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{A}_{t}\\)\u003c/span\u003e\u003c/span\u003e is the anomaly at time t, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{X}_{t}\\)\u003c/span\u003e\u003c/span\u003e is the detrended value at time t, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\stackrel{-}{X}}_{m\\left(t\\right)}\\)\u003c/span\u003e\u003c/span\u003e is the climatological mean of the corresponding month. This final step highlights deviations from both the long-term trend and the average seasonal cycle, allowing for the identification of unusual or extreme events.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results and discussions","content":"\u003cp\u003eClimatologically, the study area experiences two distinct monsoon seasons: the southeast monsoon (dry season, May to September) and the northwest monsoon (wet season, November to March). These monsoon cycles greatly influence surface wind fields, precipitation patterns, runoff, and stratification, all of which interact dynamically with oil spill transport and fate. The coastal geomorphology is characterized by a gently sloping continental shelf and soft-bottom substrates that are susceptible to sediment resuspension, which further modulates water clarity, light penetration, and primary productivity. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the climatology spatial distribution condition of (a, d) Chl-a (mg m⁻\u0026sup3;), (b, e) SPM (g m⁻\u0026sup3;), and (c, f) TSM (g m⁻\u0026sup3;) during the peak of the East Monsoon (June\u0026ndash;August, JJA; upper panels) and the West Monsoon (December\u0026ndash;February, DJF; lower panels) along the northern coast of Java illustrates the climatological baseline conditions that frame seasonal variability in suspended matter and phytoplankton biomass. This baseline is crucial for distinguishing oil spill anomalies from the natural dynamics of monsoon-driven forcing.\u003c/p\u003e\u003cp\u003eDuring the east monsoon (JJA), panels 2a\u0026ndash;2c reveal elevated SPM and TSM concentrations along nearshore waters of Banten, Jakarta Bay, and Karawang, reflecting strong southeasterly winds that enhance sediment resuspension while limiting river discharge. In these months, Chl-a concentrations (panel 2a) remain low across much of the northern coast, indicating that light limitation under turbid conditions suppresses phytoplankton productivity. Offshore regions show clearer waters with reduced TSM and SPM, but Chl-a is also low, highlighting nutrient limitation under dry-season circulation. Meanwhile, the west monsoon (DJF) climatology (panels 2d\u0026ndash;2f) displays increased rainfall and riverine inputs from the Citarum, Cisadane, and Ciliwung rivers, leading to higher SPM and TSM near estuaries (panels 2e and 2f). Despite turbidity, Chl-a values (panel 2d) increase substantially, particularly in Indramayu and Cirebon waters, suggesting that nutrient enrichment offsets reduced light penetration and promotes phytoplankton growth. In summary, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrates the dual monsoon regime of northern Java: the east monsoon is defined by sediment resuspension and light limitation, while the west monsoon is characterized by nutrient enrichment that supports phytoplankton blooms.\u003c/p\u003e\u003cp\u003eThese climatological patterns establish the seasonal reference against which the oil spill anomalies of 2019 and 2021 must be interpreted, ensuring that deviations in TSM, SPM, and Chl-a can be attributed confidently to anthropogenic disturbance rather than monsoon background variability. During the east monsoon, elevated SPM and TSM concentrations dominate nearshore zones of West Java and Banten, reflecting sediment resuspension and reduced freshwater inflow, while Chl-a values remain relatively low offshore, indicating light-limitation under high turbidity. In contrast, the west monsoon is characterized by stronger riverine inputs, leading to enhanced nutrient delivery that sustains phytoplankton growth (higher Chl-a) even under moderately elevated SPM and TSM. This seasonal duality highlights the critical role of monsoon-driven hydrodynamics in shaping the balance between turbidity-induced light limitation and nutrient enrichment, thereby structuring coastal ecosystem productivity across northern Java.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFollowing the description of the climatological conditions in the study area (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the datasets used to examine the effects of oil spill events on water quality. The pre-spill conditions are shown for March\u0026ndash;April 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea\u0026ndash;b), while the spill events in July\u0026ndash;August 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec\u0026ndash;d) and April\u0026ndash;May 2021 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee\u0026ndash;f) capture the immediate impacts on the aquatic system. Post-spill conditions during March\u0026ndash;July 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg\u0026ndash;j) illustrate the subsequent recovery and water quality dynamics in the region.\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e depicts the anomaly distribution of Suspended Particulate Matter (SPM, mg/L) along the northern coast of Java, revealing clear spatial and temporal contrasts. Positive anomalies are concentrated near estuarine plumes and shallow coastal zones, especially in the Karawang waters and extending toward Cirebon. These anomalies reflect enhanced turbidity driven either by monsoonal river discharge during wet seasons or wave-induced resuspension on shallow shelves. Offshore regions, by contrast, are dominated by neutral to negative anomalies, indicating periods of reduced suspended input or enhanced sediment settling in calmer hydrodynamic environments. Prior to the July 2019 spill, fluctuations were seasonal, with positive pulses aligned with rainfall and runoff. However, the July 2019 event triggered a sharp intensification of positive anomalies in Karawang, linked to southwesterly winds that promoted mixing and the interaction of hydrocarbons with fine particles, producing aggregates that prolonged suspension in the water column.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eA similar but broader pattern emerged after the April 2021 oil spill, where positive anomalies spread beyond Karawang to eastern sectors, including Cirebon. This indicates a larger spatial footprint of disturbance, amplified by hydrocarbon dispersal and sediment resuspension. Although anomalies gradually diminished, nearshore Karawang remained elevated for months, demonstrating a lagged recovery relative to offshore waters. The alternation between positive nearshore and negative offshore anomalies highlights the interplay of natural forcing and oil-spill-induced amplification of turbidity. Comparable findings have been reported in other estuarine systems, such as the Hooghly Estuary in India (Bar et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Turkish coasts using Sentinel-based monitoring (Wei et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; D\u0026rsquo;Sa et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), where episodic pollution events intensify suspended particulate concentrations. Collectively, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e underscores that oil spills exacerbate monsoonal turbidity, with Karawang as the persistent hotspot of elevated SPM anomalies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates the anomaly of spatial and temporal variability of SPM across the northern coast of Java, with an emphasis on the Karawang region. SPM, which consists of both organic and inorganic particles suspended in the water column, serves as a key indicator of water turbidity, sediment transport, and potential contamination pathways. Its relevance in the context of oil spills lies in the compound interaction between petroleum substances and particulate matter. Following a spill, hydrocarbons can bind to suspended particles, altering their density and transport behavior, while mechanical disturbance from spill response or storm-induced agitation can resuspend settled sediments. Hence, SPM provides a critical lens through which we assess both the direct and indirect impacts of oil contamination.\u003c/p\u003e\u003cp\u003eDuring the pre-event periods (March to April 2019 and July to August 2021), SPM levels appeared relatively stable across the study region. Concentrations were highest near estuarine outlets and gradually diminished moving offshore, reflecting a typical fluvial influence on coastal sedimentation. These spatial patterns were consistent with the expected behavior of particulate discharge from major rivers such as the Citarum and Cilamaya. In the absence of major meteorological disturbances, the SPM anomalies during these pre-spill periods remained within expected climatological variance. However, post-event observations\u0026mdash;particularly from November 2019 through November 2021 revealed a dramatic shift. The anomaly maps display pronounced increases in SPM concentrations within the Area of Interest (AOI), with some anomalies extending well beyond the coastal boundary into offshore regions of the Java Sea.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents a detailed spatial representation of Chl-a anomalies along the Northern Coast of Java, with particular emphasis on the Karawang coastal zone, which was directly impacted by the oil spill events in July 2019 and April 2021. As a vital indicator of phytoplankton biomass, Chl-a plays a crucial role in assessing ecological productivity and water quality. It is highly responsive to fluctuations in nutrient concentrations, stratification in the water column, and the introduction of pollutants such as hydrocarbons, all of which can trigger shifts in phytoplankton communities and trophic interactions. Thus, mapping Chl-a anomalies offers valuable insight into the biological consequences of oil pollution in marine environments. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e highlights the spatiotemporal variability of Chlorophyll-a (Chl-a, mg m⁻\u0026sup3;) anomalies along the northern coast of Java during pre-spill, spill, and post-spill conditions. Prior to July 2019, anomalies remained near baseline, with modest positive values near estuaries such as the Citarum and Cisadane, reflecting nutrient-driven productivity typical of the west monsoon (Maslukah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFollowing the July 2019 and April 2021 oil spills, strong negative anomalies emerged in the Karawang sector, coinciding with peaks in suspended particulate matter. These declines reflect dual pressures of reduced light penetration due to turbidity and hydrocarbon toxicity suppressing phytoplankton growth, consistent with post-spill Chl-a suppression observed in the Bohai Sea (Wang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). While declines were most severe and persistent at Karawang, nearby regions such as Lontar and Cirebon exhibited weaker anomalies, underscoring spatial heterogeneity in spill impacts. In the post-spill period, recovery trajectories were uneven. Western sectors, particularly Lontar and Jakarta, showed positive Chl-a anomalies by 2022, suggesting improved light penetration as suspended matter decreased and nutrient enrichment sustained productivity (Shampa et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, Karawang waters remained biologically stressed, with anomalies persisting below baseline despite turbidity normalization, echoing field assessments that documented lingering water quality degradation after the spill (Effendi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These results confirm that while physical clarity recovers relatively quickly, biological systems respond more slowly and unevenly. This pattern mirrors global evidence that oil spills induce rapid phytoplankton collapse but protracted recovery shaped by hydrocarbon residues, nutrient dynamics, and local hydrodynamics (Bi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Asif et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e captures the spatiotemporal of SSTA (\u0026deg;C) across the northern coast of Java during pre-spill, spill, and post-spill periods. In the baseline months of March and April 2019, waters were relatively warm with mild positive anomalies concentrated in the eastern sector, consistent with seasonal heating during the late transition toward the southeast monsoon. By July and August 2019, coinciding with the oil spill in Karawang, negative anomalies emerged prominently along the coast. These cooler-than-average signatures likely reflected the combined effects of oil slick coverage\u0026mdash;reducing solar penetration into the water column\u0026mdash;and enhanced mixing associated with the disturbance (Wang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Bi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA similar pattern reappeared during April and May 2021, where localized cooling anomalies coincided with the second spill event. The persistence of negative anomalies during these episodes suggests that oil contamination altered the surface energy balance, suppressing stratification and redistributing heat vertically (Asif et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Ecologically, these oscillations are significant: cooler anomalies during spill periods could dampen microbial activity and slow hydrocarbon degradation (Bacosa et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), while the recovery toward baseline underscores the resilience of regional circulation and air\u0026ndash;sea fluxes (Simanjuntak \u0026amp; Lin, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sudradjat et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).⁴ Yet, the persistence of localized cool spots near Karawang highlights how oil spills leave an imprint not only on particulate and biological parameters but also on physical thermal regimes. By modulating temperature fields, spills influence both the pace of ecosystem recovery and the biogeochemical processes driving it, making SSTA a crucial diagnostic in linking oil-induced stress with broader oceanographic variability (Maslukah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Effendi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(a\u0026ndash;b) illustrate prevailing winds before the July 2019 oil spill, while Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e(c\u0026ndash;d) capture during-spill conditions in July\u0026ndash;August 2019, Panels (e\u0026ndash;f) display the wind field during the April\u0026ndash;May 2021 oil spill, meanwhile panels (g\u0026ndash;j) depict post-spill conditions in 2023. Stronger wind magnitudes (warm colors) coincide with enhanced surface mixing and sediment resuspension, whereas weaker winds (cool colors) correspond to calmer conditions and reduced circulation.\u003c/p\u003e\n\u003cp\u003eFig. 8, Fig. 9 and Fig. 10 illustrate the time series Time-series variability of SPM (g/m\u0026sup3;), TSM (g/m\u0026sup3;), and Chl-a (mg/m\u0026sup3;) anomalies at Lontar Station, Karawang, and Cirebon Water, respectively. The Chl-a anomalies (green) often display an inverse relationship, reflecting suppressed phytoplankton biomass during high-turbidity conditions. The shaded grey zones correspond to the July 2019 and April 2021 oil spill events, when suspended matter increased abruptly, while Chl-a anomalies dropped below baseline, indicating suppression of primary productivity due to combined effects of hydrocarbon contamination, reduced light penetration, and increased particulate loading.\u0026nbsp;\u003c/p\u003e\u003cp\u003eThe anomalies of SPM (orange) and TSM (blue) reveal moderate fluctuations compared to Lontar and Karawang, reflecting a combination of riverine input, monsoonal forcing, and coastal circulation in the eastern sector of the study area on Fig.\u0026nbsp;9. Peaks in suspended matter are evident during wet-season transitions, but with lower amplitude relative to the oil spill-affected Karawang waters. Chl-a anomalies (green) remain relatively stable, indicating a more resilient phytoplankton response in Cirebon compared to other stations. The shaded grey intervals mark the July 2019 and April 2021 oil spill events, showing weaker impacts at Cirebon, consistent with its greater distance from the spill epicenter and the influence of local hydrodynamics in dissipating contamination. During the pre-spill reference periods, specifically March to April 2019 and July to August 2021, Chl-a concentrations across the study area remained within normal seasonal ranges.\u003c/p\u003e\u003cp\u003eThese prevent phases were characterized by relatively stable baselines, punctuated only by minor positive anomalies that appeared in proximity to the mouths of major rivers. These localized fluctuations were likely due to natural nutrient input from riverine discharges, such as those from the Citarum and Cilamaya rivers, which are known to enrich nearshore waters and stimulate seasonal productivity. However, beginning in November 2019, immediately following the initial spill event, the spatial pattern of Chl-a shifted dramatically. The post-spill anomaly maps reveal consistently high concentrations of Chl-a within the Area delineated in the Fig. (blue line box) corresponds to the zone directly adjacent to the spill source and its probable path of influence.\u003c/p\u003e\u003cp\u003eThe geographic spread of the Chl-a anomaly post-event did not exhibit random diffusion but instead mirrored the known hydrographic structures and current systems of the northern Java Sea. The anomalies closely followed the trajectory of coastal currents and the dispersal plumes of adjacent rivers, indicating that nutrient transport and mixing played a dominant role in shaping the spatial expression of these anomalies. The anomalous concentrations extended 20 to 30 kilometers offshore from the Karawang coast, forming clear, plume-like structures along dominant current flows and wind directions. These features suggest that horizontal advection\u0026mdash;rather than purely localized productivity\u0026mdash;was responsible for redistributing nutrients and phytoplankton biomass farther into offshore waters. The persistence and configuration of these Chl-a-rich bands reinforce the role of regional hydrodynamics in amplifying the impact of pollution beyond the immediate spill site.\u003c/p\u003e\u003cp\u003eTemporally, the Chl-a anomalies displayed remarkable persistence. From November 2019 through November 2021, satellite data indicated sustained elevation in surface Chl-a concentrations across all post-spill observation windows. This anomaly pattern was particularly pronounced during the wet monsoon periods in January and March of both 2020 and 2021. These months typically bring enhanced precipitation and runoff, yet the magnitude of the observed anomalies suggests more than seasonal river discharge alone. The enduring presence of elevated Chl-a during these periods likely reflects a long-term biological response to oil-derived nutrient enrichment and ongoing microbial degradation of hydrocarbons. Oil residues and degradation byproducts often introduce additional organic and inorganic nutrients into the water column, creating conditions conducive to prolonged phytoplankton growth. Moreover, increased turbidity from sediment resuspension could further limit water clarity and stratify the water column, trapping nutrients and encouraging bloom formation in surface layers.\u003c/p\u003e\u003cp\u003eInterestingly, even in July to August 2021 a time marked as pre-spill relative to the April 2021 event Chl-a levels remained elevated above climatological averages. This unexpected trend suggests either a cumulative legacy effect from the earlier 2019 spill, a delay in ecosystem recovery, or possibly a smaller, undocumented pollution event preceding the April 2021 blowout. The latter possibility cannot be discounted, especially given the intense industrial activity and shipping traffic in the region, which increases the likelihood of minor discharges or chronic leakage contributing to background contamination. Alternatively, the anomaly could reflect a system that has entered a new biogeochemical state, where oil-related nutrient inputs have triggered a shift in the baseline productivity of the region.\u003c/p\u003e\u003cp\u003eThe ecological ramifications of such sustained Chl-a elevation are far-reaching. High phytoplankton biomass, while initially appearing beneficial from a productivity standpoint, often leads to ecological imbalance when sustained over long durations. The risk of harmful algal blooms (HABs) increases, especially in systems where nutrient inputs are not matched by sufficient flushing or mixing. These blooms can release toxins, reduce dissolved oxygen levels, and shade benthic habitats. In the northern Java shelf, where circulation is generally weak and turbidity is naturally high, prolonged phytoplankton blooms can exacerbate hypoxic conditions, particularly in deeper or semi-enclosed bays. This is especially concerning for the Karawang region, where seagrass beds, mangroves, and coastal fisheries form vital components of both biodiversity and local livelihoods. Indeed, reports of fish mortality and declining water quality in 2020 correspond with the timing and location of Chl-a anomalies, supporting the hypothesis that oil-related eutrophication had cascading impacts on ecosystem health.\u003c/p\u003e\u003cp\u003eIn conclusion, the anomaly map of Chl-a for the Northern Coast of Java serves as a biological footprint of the oil spills\u0026rsquo; impact. The data points toward a sustained eutrophic response, driven by oil residues and amplified by natural hydrodynamic forces. The spatial coherence of the anomalies with both river plumes and coastal currents underscores the importance of understanding circulation dynamics when evaluating pollution effects. Furthermore, the prolonged nature of the anomalies highlights the slow recovery trajectory of coastal ecosystems affected by oil contamination. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e thus provides compelling evidence of how a single pollution event can leave an ecological legacy lasting years, fundamentally altering productivity patterns and ecosystem function in tropical coastal waters.\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e illustrates the Spearman correlations between SPM, TSM, and Chl-a during the peak phases northern Java waters of the east monsoon (a-c) in upper panel and the west monsoon (d-e) in lower panel. The maps highlight how physical and biological interactions shift under contrasting monsoonal regimes. During the east monsoon peak (JJA), correlations between SPM\u0026ndash;Chl-a and TSM\u0026ndash;Chl-a were predominantly negative along the Karawang\u0026ndash;Cirebon coastal zone, with coefficients reaching \u0026minus;\u0026thinsp;0.6 to \u0026minus;\u0026thinsp;0.8. This pattern indicates that enhanced turbidity from wave-driven resuspension and sediment inflows suppressed phytoplankton productivity by limiting light penetration.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn contrast, localized positive correlations in western sectors (Banten and Jakarta Bay) suggest that high particulate matter may co-occur with elevated phytoplankton biomass where nutrient inputs from rivers and anthropogenic sources are abundant. Meanwhile, TSM\u0026ndash;SPM correlations approached\u0026thinsp;+\u0026thinsp;1 across most of the coast, underscoring their consistent and coupled response to sediment dynamics during the dry season. In the west monsoon peak (DJF), the correlations shifted markedly: SPM\u0026ndash;Chl-a and TSM\u0026ndash;Chl-a became strongly positive (+\u0026thinsp;0.6 to +\u0026thinsp;0.8) across much of the northern coast, particularly in Karawang and Indramayu. This indicates that while turbidity was elevated during the rainy season, riverine discharges supplied large nutrient loads, which offset light limitation and stimulated phytoplankton growth. Such a seasonal reversal captures the ecological trade-off common in tropical estuaries: during dry monsoon months light limitation dominates, while during wet monsoon months nutrient enrichment prevails.\u003c/p\u003e\u003cp\u003eThe TSM\u0026ndash;SPM correlation remained high (+\u0026thinsp;0.8 to +\u0026thinsp;1) in both seasons, confirming that sediment-driven processes consistently structure the optical properties of the coastal waters. These patterns are consistent with earlier work in Semarang Bay, where strong interactions between Chl-a and TSM were observed, mediated by both sediment discharge and local nutrient dynamics (Maslukah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In Jakarta Bay and the northern coast of Java, studies also reported that monsoon-driven variability, together with nutrient inputs from the Ciliwung, Cisadane, and Citarum rivers, shaped seasonal phytoplankton blooms, with light limitation dominating the east monsoon and nutrient enrichment during the west monsoon (Kurniawan et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Similar mechanisms were described for Balikpapan Bay, where rainy-season runoff was linked to phytoplankton enhancement despite increased turbidity (Widiawan, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). On a broader scale, the trade-off between turbidity and nutrient enrichment has also been observed in global systems such as the Bohai Sea, where the balance between suspended sediments and nutrient fluxes determines whether Chl-a responds positively or negatively to particulate matter (Wang, et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e shows long-term trends in Chl-a, SPM, and TSM across northern Java from April 2019 to March 2023 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Positive Chl-a trends are strongest in the western nearshore (Banten\u0026ndash;Jakarta), while negative trends dominate offshore and central West Java, reflecting persistent biological stress after the 2019 and 2021 oil spills. In contrast, SPM and TSM trends are broadly negative, with the steepest declines offshore and small positive anomalies near estuaries (Karawang, Indramayu), consistent with localized resuspension and riverine loading. Physical clarity recovered within one to two years, but Chl-a remained suppressed longest in Karawang, underscoring delayed biological recovery. Positive Chl-a trends near Jakarta likely reflect nutrient enrichment from rivers and urban inputs, while negative offshore trends indicate legacy light limitation and possible hydrocarbon residues affecting microbial cycling. Declining SPM/TSM point to regional sediment stabilization, whereas estuarine hotspots show continued turbidity without parallel phytoplankton gains.\u003c/p\u003e\u003cp\u003eA Similar contrasts between turbidity-driven light limitation and nutrient stimulation have been reported in Semarang Bay (Maslukah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), while Balikpapan Bay studies highlight patchy and delayed recovery after spills (Widiawan, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). A wider synthesis confirms oil spills often cause short-term physical but long-term biological disruption, with outcomes modulated by monsoon mixing and river inputs (Kurniawan et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Seasonal dynamics also govern Chl-a responses, switching between negative (light limitation) and positive (nutrient-driven) correlations, as documented in Indonesian estuaries (Simanjuntak and Lin, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sudradjat et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this context, Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e highlights faster physical normalization versus slower, spatially uneven biological rebound, with implications for aquaculture resilience.\u003c/p\u003e\u003cp\u003eThe integrated analysis of results demonstrates that northern Java\u0026rsquo;s coastal ecosystems are strongly shaped by the interplay of monsoonal forcing and anthropogenic oil spill disturbances. The climatological baseline (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) highlights a dual monsoon regime: the east monsoon (JJA) is characterized by sediment resuspension and light limitation, while the west monsoon (DJF) is defined by riverine enrichment, elevated turbidity near estuaries, and enhanced phytoplankton growth. This seasonal contrast mirrors previous findings from Semarang Bay and the Lesser Sunda region, where monsoon dynamics regulate the balance between nutrient supply and light availability for primary producers (Maslukah et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Simanjuntak \u0026amp; Lin, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSuperimposed on this seasonal framework, the July 2019 and April 2021 oil spills generated sharp, localized anomalies. SPM and TSM surged in Karawang (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), with the July 2019 event producing broader and more persistent anomalies than April 2021. This difference reflects both seasonal context and hydrodynamics: during the east monsoon, prevailing southeasterly winds facilitated plume advection westward, while the transitional April spill resulted in more confined but intense nearshore turbidity. Such amplification of suspended matter by oil\u0026ndash;sediment aggregation has been documented in the northern Gulf of Mexico and the Hooghly estuary (D\u0026rsquo;Sa et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Bar et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The resulting turbidity spikes coincided with localized cooling (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), suggesting that surface oil films reduced solar absorption and altered stratification\u0026mdash;an imprint also observed in the Bohai Sea after the 2011 spill (Wang et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBiological impacts, reflected in Chl-a anomalies (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u0026ndash;9), were immediate and severe. Karawang experienced the strongest and longest suppression of phytoplankton biomass, while Lontar and Cirebon showed weaker declines. This response highlights the dual stress of reduced light penetration under elevated turbidity and the toxic effects of hydrocarbons on phytoplankton physiology. Similar patterns of delayed biological recovery compared to faster turbidity normalization.\u003c/p\u003e\u003cp\u003ehave been observed in Balikpapan Bay and Brazilian spill sites (Widiawan, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; De Oliveira Estevo et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Importantly, Figs.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e and \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e reveal that from 2019 to 2023, SPM and TSM exhibited predominantly negative trends, indicating clearer waters, while Chl-a displayed heterogeneous but increasing trajectories, particularly near Banten and Jakarta Bay. This divergence suggests a shift from a system constrained by turbidity to one increasingly driven by nutrient dynamics\u0026mdash;a transition with important implications for harmful algal bloom (HAB) risk (Shampa et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The role of climate variability provides additional context. The study period coincided with the prolonged 2020\u0026ndash;2022 La Ni\u0026ntilde;a (Harahap et al., 2023; Mujiasih et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sidauruk et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) which typically enhances rainfall and riverine discharge.\u003c/p\u003e\u003cp\u003eYet, the data revealed declining sediment inputs, suggesting that upstream controls such as reservoir trapping and land-use change may have overridden rainfall-driven sediment delivery. This hypothesis is consistent with global evidence showing that watershed interventions can decouple runoff from sediment fluxes (Proietti \u0026amp; Giovannelli, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The observation that Chl-a trends increased as SPM and TSM declined underscores how water clarity \u0026ldquo;opened the gate\u0026rdquo; for phytoplankton proliferation, even under variable climatic forcing. From a broader perspective, the findings situate northern Java within global patterns of oil spill impacts. While the physical anomalies of turbidity and SSTA were relatively short-lived, biological suppression was longer-lasting and spatially uneven, echoing evidence from Arctic, subtropical, and tropical coasts (Bi et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Asif et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe novelty of this study lies in its multi-parameter, multi-event synthesis: no prior research in northern Java has simultaneously tracked two major spills over a four-year window, integrating SPM, TSM, Chl-a, wind, and SST with both anomaly and trend analyses. This approach not only disentangles anthropogenic disturbances from monsoonal background variability but also demonstrates how physical clarity recovers faster than ecological function\u0026mdash;a critical insight for managing sensitive aquaculture and fisheries systems along this heavily utilized coastline.\u003c/p\u003e"},{"header":"4 Conclusion","content":"\u003cp\u003eIn conclusion, this study's findings contribute to our understanding of the impact of an oil spill event on water quality in the study area. By analyzing TSM, SPM, and Chl-a concentrations during pre-event, event, and post-event conditions, the study sheds light on the ecological repercussions of oil spills and aids in formulating sustainable management practices to safeguard coastal environments.The results highlight the acute impact of the oil spill event on water quality, as evidenced by significant changes in TSM, SPM, and Chl-a concentrations during July and August 2019. Such environmental disturbances can lead to adverse effects on marine biodiversity, coastal habitats, and local communities relying on coastal resources. The post-event datasets indicate a degree of recovery in water quality indicators over time, suggesting the resilience of the coastal ecosystem to natural processes and possible management interventions. However, continued monitoring and comprehensive assessments are necessary to fully understand the long-term effects of the oil spill and the overall health of the coastal environment. The findings of this study provide valuable information for coastal management and restoration efforts. Understanding the impact and recovery of water quality after an oil spill event is crucial for devising effective strategies to mitigate future incidents and safeguard the ecological integrity of coastal regions. Additionally, continued monitoring of TSM, SPM, and Chl-a concentrations is essential for early detection of environmental changes and prompt response to potential threats in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eDeclaration of competing interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eQ. W. Sari: drafted the manuscript, curated data, developed methods, conducted analysis and Funding. P. A. Utari: Conceptualization, Supervised, Software, Methodology, Writing \u0026ndash; review \u0026amp; editing and funding. R. D. Nugraha: Data curation and analysis data. M. L. Syamsuddin, Y. M. Suherman, S. R. Anggraeni and M. U. K. Agung: editing, and critically reviewed the manuscript. H. M. Nurlaila: Project Administration, supported data curation and visualization.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe assistance of artificial intelligence (AI) tools in the preparation of this manuscript. The AI system was utilized to assist with grammar, style, and structure improvements, while the authors are responsible for the content and conclusions presented in this paper. The authors acknowledge the financial support from the Riset Keunggulan Keilmuan Unpad (RKKU) program, Grant No.1003/UN6.3.1/PT.00/2025 by Qurnia Wulan Sari.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArabi, B., Salama, M. S., Pitarch, J., \u0026amp; Verhoef, W. (2020). 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Location assessment for coral reef transplantation program in Karawang Waters, Indonesia. \u003cem\u003eIOP Conference Series: Earth and Environmental Science, 1260 (1)\u003c/em\u003e. https://doi.org/10.10881755‑1315/1260/1/012019\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Oil spill, Chl-a, Suspended Matter (SPM and TSM), Satellite remote sensing, Java Sea","lastPublishedDoi":"10.21203/rs.3.rs-7742560/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7742560/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOil spills are recurring hazards for tropical coastal ecosystems, yet their ecological impacts remain insufficiently understood in monsoon-dominated waters such as northern Java, Indonesia. Two large spills in Karawang (July 2019 and April 2021) provided a natural experiment to evaluate how suspended matter and phytoplankton respond to acute disturbances under contrasting seasonal conditions. Unlike earlier studies focusing on single incidents, this work integrates multiple parameters and events to reveal long-term ecosystem trajectories. We analyzed satellite-derived datasets from 2019\u0026ndash;2023, including Sentinel-3 OLCI Total Suspended Matter (TSM) and Suspended Particulate Matter (SPM), Aqua-MODIS Chlorophyll-a (Chl-a), ERA5 winds, and NOAA OISST sea surface temperatures. Spatial anomalies, seasonal climatologies, and site-specific time-series at Lontar, Karawang, and Cirebon were combined with linear trend analyses to separate natural variability from anthropogenic disturbance. Both spill events caused sharp increases in TSM and SPM, with July 2019 producing broader anomalies due to east monsoon transport, while April 2021 impacts were more localized. Chl-a anomalies dropped most strongly at Karawang, indicating phytoplankton suppression from turbidity and hydrocarbon stress, with weaker declines west and east. Over 2019\u0026ndash;2023, suspended matter showed significant decreases while Chl-a trended upward, suggesting clearer waters enhanced light penetration and supported partial biological recovery. These findings demonstrate that optical recovery is faster than ecological recovery, with oil spill legacies persisting unevenly across northern Java\u0026rsquo;s coastal waters.\u003c/p\u003e","manuscriptTitle":"Suspended Matter And Chlorophyll-a Dynamics Along The Coasts of Western Java and Banten","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-01 17:41:45","doi":"10.21203/rs.3.rs-7742560/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0646674e-4332-4f86-a779-f1ce90c4b161","owner":[],"postedDate":"October 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-13T13:53:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-01 17:41:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7742560","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7742560","identity":"rs-7742560","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}