In this study, surface sediments of the Pearl River Estuary were collected from 29 stations and investigated the spatial distribution, pollution level, quantitative source apportionment, and source-specific ecological risk of 10 heavy metals. The mean concentrations followed the order of Mn > Zn > Cr > Cu > Ni > Pb > As > Co > Cd > Hg. In terms of spatial distribution, it showed that the heavy metals were enriched in the inner Pearl River Estuary with ‘extremely high’ level of Hg, whereas, Cd and Zn posed ‘moderate to high’ contamination potential. We apportioned four main sources using positive matrix factorization model, in which natural geogenic and industrial manufacturing sources accounted for 36.84% and 27.11% of the total, respectively. However, the source-specific risk assessment suggested that mixed anthropogenic sources were the main contributors, and ecological risks were strongly affected by anthropogenic imports from the surrounding cities.

This paper presents the utilization of Synthetic Aperture Radar (SAR) data for monitoring and detection of oil spills. In this work, a case study of an oil spill has been investigated using C-band Sentinel-1A SAR data to detect the oil spill that occurred on 28 January 2017, near Ennore port, Chennai, India. Oil spill damages marine ecosystems causing serious environmental effects. Quite often, oil spills on the sea/ocean surface are seen nowadays, mainly in major shipping routes. They are caused due to tanker collisions, illegal discharge from the ships, etc. An oil spill can be monitored and detected using various platforms such as vessel-based, airborne-based and satellite-based. Vessel based and airborne methods are expensive with less area coverage. This process also consumes more time. For ocean applications such as oil spill and Ship detection, optical sensors cannot image during bad weather. As SAR is an active sensor, weather independent, and has cloud penetrating capability, the images can be acquired during the day as well as at night. Radar Remote Sensing (RRS) has rapidly gained popularity for monitoring and detection of oil spills and ships for more than a decade. With the availability of the satellite images, detection of oil spill has improved due to its wide coverage and less revisit time. The present paper gives an overview of the methodologies used to detect oil spills on the SAR images using dual-pol Sentinel-1A Level 1 SLC data. This work clearly demonstrates the preprocessing steps of the Sentinel 1A data for oil spill detection. The oil spill was only visible in the VV channel, therefore, for ocean application VV channel image is preferred. SEASAT was the first space-borne SAR mission launched in 1978 by NASA to observe sea surface. The preprocessing was carried out at the European Space Agency (ESA), the Sentinel Application Platform (SNAP) toolbox and Envi 5.1 toolbox. Based on the Sigma naught values, oil spill can be discriminated with the ocean surface. The results obtained with the VV channel are satisfactory and one could map out the oil spill very well. Supervised classifiers SVM and NN were applied on the boxcar filtered 3 × 3 VV channel image to delineate the oil spill. The result of oil spill detection mapping is validated with Supervised SVM and Neural Network classifiers. The results show there is a good agreement between oil spill mapping and classified image using SVM and NN classified images. The Overall Accuracy (OA) obtained using SVM classifier is 98.13% with kappa coefficient as 0.95 and using NN classifier is 98.11% with kappa coefficients 0.95. This technique is considered to be a potential proxy for the detection and monitoring of Oil spills on water bodies. Application of SAR data for oil spill detection is considered to be first of its kind from Indian coasts. This study aims to detect the oil spill occurred due to collision of two LPG tankers with Sentinel-1A SLC data in Chennai coast area.

This study has been carried out to understand the geochemistry of elements namely, iron (Fe) and phosphorus (P) in the core sediments of an urbanized tropical mangrove ecosystem along the Southwest coast of India. The study revealed the coupling of iron and phosphorus in which the reductive conditions induced reductive dissolution and upward transport of Fe, causing surface coprecipitation of phosphorus incorporated Fe oxyhydroxides. The accumulation and transformation of phosphorus were significantly influenced by processes viz., phosphorus regeneration due to organic matter mineralization and adsorption to inorganic iron oxides/Ca bound minerals in the surface sediments, and phosphorus retention in the sedimentary column by transformation into refractory organic phosphates. Bioavailable phosphorus (BAP) accounted for more than 50% of TP, so that the mangrove sediments act as an important internal nutrient source of iron and phosphorus for coastal eutrophication.

This empirical study examines the factors enhancing environmental governance for marine plastic litter abatement in Manila, the Philippines. We use a combined covariance-based hybrid structural equation modeling (SEM) and DPSIR framework, with data collected via an online survey from 456 barangays in Manila, the Philippines. The survey was processed and analyzed using a combined model, validated through interviews and focused group discussions. With Higher-Order Model good internal consistency (0.917) and achieved measures of CFI (0.992), RMSEA (0.036), and SRMR (0.019), the findings revealed that environmental governance (COVID-19 waste), community participation, socio-economic factors, and solution measures have positively affected marine plastic litter (MPL) abatement. Notwithstanding, environmental governance (SWM policies and guidelines) has a negative impact on MPL abatement. There is, however, no link between waste infrastructure and MPL abatement. The findings provide significant perspectives in Manila to enhance environmental governance for MPL abatement. This paper presents policy-actions implications drawn from DPSIR-SEM.

The groundwater salinization is a global problem that degrades water quality and endangers sustainable use of water resources, particularly in coastal areas. In this paper, 24 water samples were collected from 12 monitoring wells during the dry (January) and wet (June) seasons for analyzing the salinization and hydrogeochemical characteristics of groundwater in Dongshan Island of China through combined hydrogeochemical and multivariate statistical approaches. Results showed that groundwater in the study area is primarily Cl–Na and followed by Cl–Ca·Mg type in the dry season, Cl–Na and followed by Cl–Ca·Mg and HOC₃·Cl–Na type in the wet season. The groundwater chemistry is predominantly controlled by carbonate, gypsum, and silicate dissolution. However, some areas are strongly influenced by seawater intrusion, sewage infiltration and reverse ion exchange process. Around 40% of water samples from the dry season and 50% from the wet season are at injuriously, highly and severely saline levels while other samples at slightly and moderately saline levels, suggesting that groundwater in the area is partially recharged by seawater. Furthermore, the NO₃⁻/Cl⁻ versus Cl⁻ diagram and principal component analysis (PCA) indicated nitrate pollution in groundwater that is subjected to anthropogenic activities such as domestic sewage, agricultural and industrial practices, which lead to degradation of groundwater quality in the area. The findings of this study provide helpful insights for understanding the genesis and hydrogeochemical evolution of groundwater in those coastal areas.

In this study, based on data collected by citizen science, we studied the abundance, spatial and temporal distribution of marine litter in three beaches of the Moroccan Mediterranean. A total of 14,042 litter items were collected with an average abundance of 0.58 items/m². The most of litter were composed of anthropic polymeric materials, representing 74 % of the total litter collected. Plastics account for the majority of the items collected and are mainly caps/lids, crisp/sweet packets, plastic/polystyrene, cigarette butts and small plastic bags. Litter abundance displayed significant seasonal differences, with the highest during summer. Tourism and poor waste management practices are the major sources of plastic on the beaches surveyed. The use of the Clean Coast Index (CCI) and the Plastics Abundance Index (PAI) permits the classification of the three beaches in the Moroccan Mediterranean as a “moderately clean” coastal area with a “very high abundance” of plastics. In addition, the Hazardous Items Index (HII) allows classification of the region as highly polluted by hazardous litter. Best management measures are needed to promote the environmental quality of the beaches of the Moroccan Mediterranean.

In this study, we examined the distribution of polycyclic aromatic hydrocarbons (PAHs) in sediments from the Mahanadi River Estuary (MRE), identified sources, and evaluated the ecological toxicity. The PAHs distributions in MRE ranged from 13.1 to 685.4 ng g⁻¹ (dry weight), with a mean value of 192.91 ± 177.56 ng g⁻¹ (dry weight). Sediments at sites S11, S8, and S13 have the highest 3-rings, 4-rings, and 5-rings PAHs, respectively. In MRE, pyrene has a significantly higher concentration with a mean value of 30.51 ng g⁻¹, followed by Fluoranthene (86.2 ng g⁻¹), Chrysene (67.4 ng g⁻¹), and Benzo(k)fluoranthene (54.2 ng g⁻¹). Site S8 had a higher total PAH concentration than sites S11, S13, and S1. The diagnostic and principal component analysis suggests that PAHs originated from petroleum, oil, biomass, and coal combustion. Higher toxic and mutagenic equivalent quotients indicate potential aquatic toxicity and a need for continuous monitoring of MRE for PAHs pollution.

Biocides used in offshore oil and gas operations could be present in water discharges, and thus identifying such chemicals and their hazard could help address concerns regarding non-target organisms. Aquatic toxicity data, queried from different sources and augmented with predictive models, were used to develop species sensitivity distributions and their corresponding 5th percentile hazard concentrations (HC5s). Curated data, including over 1000 empirical records for 137 species, indicated no evidence of bias when comparing sensitivity between marine and freshwater species, even when predicted data were used. HC5s facilitated estimation of an acute-to-chronic ratio (ACR = 10), appropriate for most chemicals and useful in filling data gaps. Comparison of chronic-HC5s with the default approach for deriving predicted no effect concentrations showed that the latter systematically overstates aquatic hazard. The present approach shows promise of using acute-to-chronic HC5 ratios for defining assessment factors for different chemical classes, instead of the use of generic assessment factors.

The Sepetiba Bay (SB; SE Brazil) has been severely affected by growing of urbanization and industrial activity. This work aims to analyze the evolution of contamination by metals of sediments in SB. The results show a marked increasing trend in the concentrations of potentially toxic elements (PTEs), which is consistent with the rapid populational and industrial growth, mostly since 1970 CE. The remobilization and redistribution of sediments by currents have contributed to the dispersion of metals from the main source of pollutants to relatively distant regions. “Moderately to strongly polluted” sediments are also recorded in some sites in deeper sedimentary layers (namely in preindustrial periods), probably due to lithologic sources of the sediments. The concentrations of PTEs in SB are relatively high when compared with those found globally and in other Brazilian water bodies. Samples of high-resolution sediment cores confirmed that potential ecological risk to the coastal system is influenced not only through human actions but also by natural causes.