Assessing Chlorophyll-a Variations in Caspian Sea during the COVID-19 Pandemic.

The COVID-19 pandemic's disruptions to human activities prompted serious environmental changes. Here, we assessed the variations in coastal water quality along the Caspian Sea, with a focus on the Iranian coastline, during the lockdown. Utilizing Chlorophyll-a data from MODIS-AQUA satellite from 2015 to 2023 and Singular Spectrum Analysis for temporal trends, we found a 22% Chlorophyll-a concentration decrease along the coast, from 3.2 to 2.5 mg/m³. Additionally, using a deep learning algorithm known as Long Short-Term Memory Networks, we found that, in the absence of lockdown, the Chlorophyll-a concentration would have been 20% higher during the 2020-2023 period. Furthermore, our spatial analysis revealed that 98% of areas experienced about 18% Chlorophyll-a decline. The identified improvement in coastal water quality presents significant opportunities for policymakers to enact regulations and make local administrative decisions aimed at curbing coastal water pollution, particularly in areas experiencing considerable anthropogenic stress.

Development of a "big data" groundwater microbial contamination index and spatial comparisons with enteric infection rates in southern Ontario.

Big data have become increasingly important for policymakers and scientists but have yet to be employed for the development of spatially specific groundwater contamination indices or protecting human and environmental health. The current study sought to develop a series of indices via analyses of three variables: Non-E. coli coliform (NEC) concentration, E. coli concentration, and the calculated NEC:E. coli concentration ratio. A large microbial water quality dataset comprising 1,104,094 samples collected from 292,638 Ontarian wells between 2010 and 2021 was used. Getis-Ord Gi* (Gi*), Local Moran's I (LMI), and space-time scanning were employed for index development based on identified cluster recurrence. Gi* and LMI identify hot and cold spots, i.e., spatially proximal subregions with similarly high or low contamination magnitudes. Indices were statistically compared with mapped well density and age-adjusted enteric infection rates (i.e., campylobacteriosis, cryptosporidiosis, giardiasis, verotoxigenic E. coli (VTEC) enteritis) at a subregional (N = 298) resolution for evaluation and final index selection. Findings suggest that index development via Gi* represented the most efficacious approach. Developed Gi* indices exhibited no correlation with well density, implying that indices are not biased by rural population density. Gi* indices exhibited positive correlations with mapped infection rates, and were particularly associated with higher bacterial (Campylobacter, VTEC) infection rates among younger sub-populations (p < 0.05). Conversely, no association was found between developed indices and giardiasis rates, an infection not typically associated with private groundwater contamination. Findings suggest that a notable proportion of bacterial infections are associated with groundwater and that the developed Gi* index represents an appropriate spatiotemporal reflection of long-term groundwater quality. Bacterial infection correlations with the NEC:E. coli ratio index (p < 0.001) were markedly different compared to correlations with the E. coli index, implying that the ratio may supplement E. coli monitoring as a groundwater assessment metric capable of elucidating contamination mechanisms. This study may serve as a methodological blueprint for the development of big data-based groundwater contamination indices across the globe.

Greenhouse gas emission potential of tropical coastal sediments in densely urbanized area inferred from metabarcoding microbial community data.

Although benthic microbial community offers crucial insights into ecosystem services, they are underestimated for coastal sediment monitoring. Sepetiba Bay (SB) in Rio de Janeiro, Brazil, holds long-term metal pollution. Currently, SB pollution is majorly driven by domestic effluents discharge. Here, functional prediction analysis inferred from 16S rRNA gene metabarcoding data reveals the energy metabolism profiles of benthic microbial assemblages along the metal pollution gradient. Methanogenesis, denitrification, and N2 fixation emerge as dominant pathways in the eutrophic/polluted internal sector (Spearman; p < 0.05). These metabolisms act in the natural attenuation of sedimentary pollutants. The methane (CH4) emission (mcr genes) potential was found more abundant in the internal sector, while the external sector exhibited higher CH4 consumption (pmo + mmo genes) potential. Methanofastidiosales and Exiguobacterium, possibly involved in CH4 emission and associated with CH4 consumers respectively, are the main taxa detected in SB. Furthermore, SB exhibits higher nitrous oxide (N2O) emission potential since the norB/C gene proportions surpass nosZ up to 4 times. Blastopirellula was identified as the main responsible for N2O emissions. This study reveals fundamental contributions of the prokaryotic community to functions involved in greenhouse gas emissions, unveiling their possible use as sentinels for ecosystem monitoring.

Enhancing water quality monitoring through the integration of deep learning neural networks and fuzzy method.

The escalating growth of the global population has led to degraded water quality, particularly in seawater environments. Water quality monitoring is crucial to understanding the dynamic changes and implementing effective management strategies. In this study, water samples from the southwestern regions of Iran were spatially analyzed in a GIS environment using geostatistical methods. Subsequently, a water quality map was generated employing large and small fuzzy membership functions. Additionally, advanced prediction models using neural networks were employed to forecast future water pollution trends. Fuzzy method results indicated higher pollution levels in the northern regions of the study area compared to the southern parts. Furthermore, the water quality prediction models demonstrated that the LSTM model exhibited superior predictive performance (R2 = 0.93, RMSE = 0.007). The findings also underscore the impact of urbanization, power plant construction (2010 to 2020), and inadequate urban wastewater management on water pollution in the studied region.

Microplastic ingestion by sea turtles around Tokyo Bay: Level of water pollution influences ingestion amounts.

We investigated the contents inside the esophagus and stomach of turtles inside and outside of the Tokyo Bay area, which face high and low risks of microplastic (MP) exposure, respectively. 65 synthetic particles were recovered from 8 out of 22 turtles, using ATR-FTIR followed by density separation with calcium chloride solution. Statistical analysis indicated that turtles in high-risk areas ingested significantly more MPs than those in low-risk areas. As the inflow of MPs from major rivers influences pollution levels in the ocean, the results of this study highlight the importance of major rivers for MP ingestion by turtles. Additionally, we discussed the current methodology's shortcomings and addressed scope for subsequent research, along with suggestions on future conservation.

Identify the seasonal differences in water quality and pollution sources between river-connected and gate-controlled lakes in the Yangtze River basin.

The river-connected Dongting Lake (DT) and Poyang Lake (PY), and the gate-controlled Taihu Lake (TH) and Chaohu Lake (CH) are the four important lakes in the Yangtze River Basin. The comprehensive Water Quality Index (WQI), the Eutrophication Integrated Index (TLI(Σ)), and the Positive Matrix Factorization (PMF) model were employed to evaluate water quality and the contribution of pollution sources for these lakes. The results show that WQI for all lakes indicated generally good water quality, with DT scoring 73.52-86.18, the highest among them. During the wet season, the eutrophication degree of river-connected lake was medium, and that of gate-controlled lakes was high. The surface runoff and agricultural non-point sources are the main pollution sources for both types of lakes, but their impact is more pronounced in gate-controlled lakes during the wet season. The study provides evidence support for scientific understanding of water quality problems and management strategies in these areas.

The Brazilian National Plan to Combat Marine Litter: A critical assessment.

The Brazilian National Plan to Combat Marine Litter was launched in March 2019 and in its context, 577 campaigns were carried out to clean up beaches, rivers, estuaries and mangroves, until January 2023, at an estimated cost of US$ 16,733,000.00. The volume collected in four years represented only 0.0041 % of the total solid waste discharged annually in the maritime waters under the country's jurisdiction. The direct benefit to society was only US$ 173,751.41 at market value for the litter collected. Litter lesser than 2.5 cm was left out, not been characterized. The results achieved deserve reflection and critical evaluation, in order to allow improvements, serving as reference. The participation of around 43,000 people in cleanup campaigns is an indication of environmental citizenship and an asset that cannot be overlooked by managers, demanding focus, tangible results and benefits in terms of environmental quality, well-being and savings on public cleaning services costs.

Evaluating the surface water pollution risk of mineral resource exploitation via an improved approach: a case study in Liaoning Province, Northeastern China.

Pollution from mineral exploitation is an important risk factor affecting surface water environment in mineral regions. It is urgent to construct a simple and accurate model to assess the surface water pollution risk from mineral exploitation in the regional scale. Thus, taking a mining province namely Liaoning in northeastern China as the study area, we proposed a framework to simulate the transport process of pollutants from mineral exploitation points to the surrounding surface water based on the "source-sink" theory. In our framework, we adopted the regional growth method (RGM) to extract the potential polluted water area as the certain "sink" considering the influence of the topography, and then applied Minimum Cumulative Resistance (MCR) model to assess the surface water pollution risk from mineral exploitation. The results revealed that: (1) 9.5% of the water areas were located at the potential impact area of MEPs. (2) The total value of resistance surface in Liaoning is relatively low, and gradually decreased from west to east. (3) MEPs in Liaoning had a high risk and seriously threatened the surface water environment, among 2125 MEPs, 733 MEPs (32.99%) were assessed as extremely high risk level, and about 35% of the MEPs were distributed within 10KM buffer zone of surface water. (4) Water pollution risk of MEPs in Dalian, Tieling, Fuxin and Dandong need to be emphasized. (5) Compared to previous studies, we considered the topographical influence before applying MCR model directly, so the results of water pollution risk were more reliable. This study provides a methodological support and scientific reference for the water environment protection and regional sustainable development.

Quantitative source apportionment of faecal indicator bacteria from anthropogenic and zoogenic sources of faecal contamination.

Recreational bathing waters are complex systems with diverse inputs from multiple anthropogenic and zoogenic sources of faecal contamination. Faecal contamination is a substantial threat to water quality and public health. Here we present a comprehensive strategy to estimate the contribution of faecal indicator bacteria (FIB) from different biological sources on two at-risk beaches in Dublin, Ireland. The daily FIB loading rate was determined for three sources of contamination: a sewage-impacted urban stream, dog and wild bird fouling. This comparative analysis determined that the stream contributed the highest daily levels of FIB, followed by dog fouling. Dog fouling may be a significant source of FIB, contributing approximately 20 % of E. coli under certain conditions, whereas wild bird fouling contributed a negligible proportion of FIB (<3 %). This study demonstrates that source-specific quantitative microbial source apportionment (QMSA) strategies are vital to identify primary public health risks and target interventions to mitigate faecal contamination.

Confined within a sugarcane monoculture: A participatory assessment of water pollution and potential health risks in the community of El Tiple, Colombia.

Communities neighboring monoculture plantations are vulnerable to different forms of pollution associated with agro-industrial operations. Herein, we examine the case of El Tiple, a rural Afro descendant community embedded within one of the largest sugarcane plantations in the Americas. We implemented a participatory approach to assess water pollution, exposure via water ingestion, and non-carcinogenic health risks associated with the use of local water sources available to the community. We conducted household surveys to unveil demographic characteristics and family dynamics linked to water consumption. Additionally, we measured water quality parameters and assessed the concentration glyphosate, its major metabolite (aminomethylphosphonic acid) and metals and metalloids. Drinking water El Tiple households is sourced from three primary sources: the local aqueduct system, water delivery trucks, and private deep wells. Tests on water samples from both the local aqueduct and delivery trucks showed no traces of pesticides, metals, or metalloids surpassing regulatory limits set by Colombian or EPA standards. However, we found concentration of contaminants of primary concern, including mercury (up to 0.0052 ppm) and lead (up to 0.0375 ppm) that exceed the permissible regulatory thresholds in water from groundwater wells. Residents of the peripheric subdivisions of El Tiple are four times more reliant on well water extraction than residents of the central area of the town due to lack of access to public drinking water and sanitation infrastructure. Finally, adult women and school-age children have a higher health risk associated with exposure to local pollutants than adult men due to their constant presence in the town. We conclude that expanding the coverage of clean water and sanitation infrastructure to include all households of the community would be the most recommended measure to minimize exposure and risk via ingestion of water pollutants.

Assessing groundwater quality and its association with child undernutrition in India.

BACKGROUND AND OBJECTIVES: Groundwater contamination poses a significant health challenge in India, particularly impacting children. Despite its importance, limited research has explored the nexus between groundwater quality and child nutrition outcomes. This study addresses this gap, examining the association between groundwater quality and child undernutrition, offering pertinent insights for policymakers. DATA AND METHODS: The study uses data from the fifth round of the National Family Health Survey (NFHS) and the Central Groundwater Board (CGWB) to analyze the association between groundwater quality and child nutritional status. The groundwater quality data were collected by nationwide monitoring stations programmed by CGWB, and the child undernutrition data were obtained from the NFHS-5, 2019-21. The analysis included descriptive and logistic regression model. The study also considers various demographic and socio-economic factors as potential moderators of the relationship between groundwater quality and child undernutrition. FINDINGS: Significant variation in groundwater quality was observed across India, with numerous regions displaying poor performance. Approximately 26.53 % of geographical areas were deemed unfit for consuming groundwater. Environmental factors such as high temperatures, low precipitation, and arid, alluvial, laterite-type soils are linked to poorer groundwater quality. Unfit-for-consumption groundwater quality increased the odds of undernutrition, revealing a 35 %, 38 %, and 11 % higher likelihood of stunting, underweight, and wasting in children, with higher pH, Magnesium, Sulphate, Nitrate, Total Dissolved Solids, and Arsenic, levels associated with increased odds of stunting, underweight, and wasting. Higher temperatures (>25 °C), high elevations (>1000 m), and proximity to cultivated or industrial areas all contribute to heightened risks of child undernutrition. Children consuming groundwater, lacking access to improved toilets, or living in rural areas are more likely to be undernourished, while females, higher-income households, and those consuming dairy, vegetables, and fruits daily exhibit lower odds of undernutrition. POLICY IMPLICATIONS: Policy implications highlight the urgent need for investment in piped water supply systems. Additionally, focused efforts are required to monitor and improve groundwater quality in regions with poor water quality. Policies should emphasize safe sanitation practices and enhance public awareness about the critical role of safe drinking water in improving child health.

Remotely sensed estimates of long-term biochemical oxygen demand over Hong Kong marine waters using machine learning enhanced by imbalanced label optimisation.

In many coastal cities around the world, continuing water degradation threatens the living environment of humans and aquatic organisms. To assess and control the water pollution situation, this study estimated the Biochemical Oxygen Demand (BOD) concentration of Hong Kong's marine waters using remote sensing and an improved machine learning (ML) method. The scheme was derived from four ML algorithms (RBF, SVR, RF, XGB) and calibrated using a large amount (N > 1000) of in-situ BOD5 data. Based on labeled datasets with different preprocessing, i.e., the original BOD5, the log10(BOD5), and label distribution smoothing (LDS), three types of models were trained and evaluated. The results highlight the superior potential of the LDS-based model to improve BOD5 estimate by dealing with imbalanced training dataset. Additionally, XGB and RF outperformed RBF and SVR when the model was developed using log10(BOD5) or LDS(BOD5). Over two decades, the BOD5 concentration of Hong Kong marine waters in the autumn (Sep. to Nov.) shows a downward trend, with significant decreases in Deep Bay, Western Buffer, Victoria Harbour, Eastern Buffer, Junk Bay, Port Shelter, and the Tolo Harbour and Channel. Principal component analysis revealed that nutrient levels emerged as the predominant factor in Victoria Harbour and the interior of Deep Bay, while chlorophyll-related and physical parameters were dominant in Southern, Mirs Bay, Northwestern, and the outlet of Deep Bay. LDS provides a new perspective to improve ML-based water quality estimation by alleviating the imbalance in the labeled dataset. Overall, the remotely sensed BOD5 can offer insight into the spatial-temporal distribution of organic matter in Hong Kong coastal waters and valuable guidance for the pollution control.

A multi-tiered approach to assess fecal pollution in an urban watershed: Bacterial and viral indicators and sediment microbial communities.

Development of effective pollution mitigation strategies require an understanding of the pollution sources and factors influencing fecal pollution loading. Fecal contamination of Turkey Creek in Gulfport, Mississippi, one of the nation's most endangered creeks, was studied through a multi-tiered approach. Over a period of approximately two years, four stations across the watershed were analyzed for nutrients, enumeration of E. coli, male-specific coliphages and bioinformatic analysis of sediment microbial communities. The results demonstrated that two stations, one adjacent to a lift station and one just upstream from the wastewater-treatment plant, were the most impacted. The station adjacent to land containing a few livestock was the least impaired. While genotyping of male-specific coliphage viruses generally revealed a mixed viral signature (human and other animals), fecal contamination at the station near the wastewater treatment plant exhibited predominant impact by municipal sewage. Fecal indicator loadings were positively associated with antecedent rainfall for three of four stations. No associations were noted between fecal indicator loadings and any of the nutrients. Taxonomic signatures of creek sediment were unique to each sample station, but the sediment microbial community did overlap somewhat following major rain events. No presence of Escherichia coli (E. coli) or enterococci were found in the sediment. At some of the stations it was evident that rainfall was not always the primary driver of fecal transport. Repeated monitoring and analysis of a variety of parameters presented in this study determined that point and non-point sources of fecal pollution varied spatially in association with treated and/or untreated sewage.

The underestimated role of manganese in modulating the nutrient structure in a eutrophic seasonally-stratified reservoir.

Accumulation and subsequent release of nutrients have great potential to trigger algal blooms in lakes and reservoirs. We conducted high vertical resolution (2 m interval) monitoring at ∼monthly intervals over a year for hydrological parameters, Chl-a, ammonium (NH4+), nitrate (NO3-) and different species of phosphorus (P) and manganese (Mn) in a 40-meter-deep subtropical reservoir (Shanmei Reservoir) in Fujian, southern China. In this seasonally stratified reservoir featured with high nutrient loading, the consistent trend in the ratio of dissolved inorganic nitrogen (DIN) to dissolved inorganic phosphorus (DIP) between the euphotic zone and the hypolimnion, coupled with its mirrored correlation with Chl-a concentration indicates that upward flux from the hypolimnion affects phytoplankton growth in the euphotic zone. The monthly variation of the depth-integrated multiple species of N and P indicates that during the stratification period in the hypoxic hypolimnion, approximately 80% of the DIP is removed, leading to a remarkable decoupling phenomenon between NH4+ and DIP. This process effectively increases the ratio of DIN to DIP in the hypolimnion, thereby significantly reducing the potential of algal blooms caused by the upward flux. A robust positive linear correlation between iron-manganese bound phosphorus (CBD-P) and particulate Mn was observed during stratification period implying that DIP was scavenged by sediment-released Mn throughout the water column. Vertical profiles during stratification showed that upward diffusion of Mn2+ facilitated the formation of Mn oxide zones near the oxycline. The most significant decrease in DIP inventory occurs when Mn oxide zones migrate either upwards from the bottom or downwards from the oxycline, indicating that the migration of Mn oxides on the vertical profile is a key factor in the decoupling of NH4+and DIP. Our findings underscore the importance of Mn cycling as an underappreciated DIP self-immobilization process in the water column of reservoirs characterized by high nutrient loading. Furthermore, we propose that denitrification and Mn cycling establish a consecutive feedback mechanism, preventing excessive nutrient accumulation in low oxygen bottom water. In the context of global changes, we anticipate a heightened prominence of this feedback mechanism.

Do storm overflows influence AMR in the environment and is this relevant to human health? A UK perspective on a global issue.

Antimicrobial resistance (AMR) is a global public health threat, and the environment has been identified as an important reservoir for resistant microorganisms and genes. Storm overflows (SOs) discharge wastewater and stormwater, and are found throughout many wastewater networks. While there are no data currently showing the impact of SOs on the environment with respect to AMR in the UK, there is a small but growing body of evidence globally highlighting the potential role of SOs on environmental AMR. This review aims to provide an overview of the current state of SOs, describe global data investigating the impact of SOs on environmental AMR, and discuss the implications of SOs regarding AMR and human health. In addition, the complexities of studying the effects of SOs are discussed and a set of priority research questions and policy interventions to tackle a potentially emerging threat to public health are presented.

Deciphering assembly processes, network complexity and stability of potential pathogenic communities in two anthropogenic coastal regions of a highly urbanized estuary.

The existence of potential pathogens may lead to severe water pollution, disease transmission, and the risk of infectious diseases, posing threats to the stability of aquatic ecosystems and human health. In-depth research on the dynamic of potential pathogenic communities is of significant importance, it can provide crucial support for assessing the health status of aquatic ecosystems, maintaining ecological balance, promoting sustainable economic development, and safeguarding human health. Nevertheless, the current understanding of the distribution and geographic patterns of potential pathogens in coastal ecosystems remains rather limited. Here, we investigated the diversity, assembly, and co-occurrence network of potential pathogenic communities in two anthropogenic coastal regions, i.e., the eight mouths (EPR) and nearshore region (NSE), of the Pearl River Estuary (PRE) and a total of 11 potential pathogenic types were detected. The composition and diversity of potential pathogenic communities exhibited noteworthy distinctions between the EPR and NSE, with 6 shared potential pathogenic families. Additionally, in the NSE, a significant pattern of geographic decay was observed, whereas in the EPR, the pattern of geographic decay was not significant. Based on the Stegen null model, it was noted that undominant processes (53.36%/69.24%) and heterogeneous selection (27.35%/25.19%) dominated the assembly of potential pathogenic communities in EPR and NSE. Co-occurrence network analysis showed higher number of nodes, a lower average path length and graph diameter, as well as higher level of negative co-occurrences and modularity in EPR than those in NSE, indicating more complex and stable correlations between potential pathogens in EPR. These findings lay the groundwork for the effective management of potential pathogens, offering essential information for ecosystem conservation and public health considerations in the anthropogenic coastal regions.

Diverse sources of fecal contamination in macroalgae wrack-affected environment adjacent to river outflow along the Baltic Sea coast.

We investigated the dynamics of feces-associated microorganisms in areas with wrack accumulation in the southeastern part of the Baltic Sea. Our study covered single-day (2021 ) and multi-day (2022) observations during the recreational season. We collected water, sand, and wrack samples and assessed the abundance of fecal indicator bacteria (FIB), as well metagenomic analysis was conducted to monitor changes in microbial composition. Based on metagenomic data we identified taxa associated with feces, sewage, and ruminant sources. Human-related fecal pollution based on genetic markers correlated with the presence of Lachnospiraceae, Prevotellaceae and Rickenellacea abundance. Higher abundance and diversity of feces-associated and ruminant-associated taxa and the presence of enteric pathogens were observed when wrack accumulated near the river outflow in 2021, suggesting a potential link with fecal pollution from the river. As a preventive measure, it is recommended to remove the wrack to reduce the risk of exposure to potential enteric pathogens if it is accumulated next to the river outflow.

A modified approach of the agricultural grey water footprint considering the nitrogen fixation effect of crops in China.

The rapidly growing demand for food in human societies has led to the extensive use of fertilizers, significantly contributing to water pollution. Grey water footprints (GWF) serve as a crucial method for measuring Non-point Source (NPS) pollution, particularly in agriculture. Traditional assessments of agricultural GWF neglect biologically fixed nitrogen and the use of organic fertilizers. This research proposed a modified method to assess the GWF of Chinese agriculture from 2000 to 2020, considering the impact of Nitrogen fixation in crops and the use of organic fertilizer. We also analyzed the determinants of Agricultural Nitrogen Fixation Intensity (ANFI) using the Logarithmic Mean Divisia Index (LMDI) method to better understand factors influencing agricultural GWF. Our findings include (1) Grain cereals (e.g., maize, rice, and wheat) significantly contribute to nitrogen fixation in crop organs, accounting for 87.7%, whereas the other six economic crops contribute the rest of 12.3%. Human wastes account for Nitrogen emissions for 1.40%, and emissions by livestock product, red meat contributes 16.26%, while white meat, eggs, and milk collectively contribute 82.34%. (2) Across China, there is an overestimation of GWF by 22.4 hundred million m3 per year, about 5.13% of the total GWF measured by traditional methods. It appears that the overestimation of GWF in plain regions with more arable land tends to be somewhat more pronounced compared to plateau and coastal municipalities. Biotechnological advancements in the capacity of nitrogen fixation for key crops (e.g., maize, wheat, rice) can alleviate agricultural water pollution. The modified methodology provides a robust scientific basis for a more precise application of GWF assessments, highlighting the substantial overestimation by traditional methods in China.

The collateral effects of COVID-19 on marine pollution.

The COVID-19 pandemic has gained significant attention to the intersection of public health crises and environmental challenges, particularly in the context of marine pollution. This paper examines the various impacts of the pandemic on marine environments, focusing on the pollution attributed to single-use plastics (SUPs) and personal protective equipment (PPE). Drawing on a comprehensive analysis of literature and case studies, the paper highlights the detrimental effects of increased plastic waste on marine ecosystems, biodiversity, and human health. Statistical data and graphical representations reveal the scale of plastic pollution during the pandemic, emphasizing the urgent need for mitigation strategies. The study evaluates innovative monitoring techniques and future recommendations, emphasizing stakeholder collaboration in sustainable waste management. By broadening geographic examples and comparative analyses, it provides a global perspective on the pandemic's impact, highlighting the importance of international cooperation for safeguarding marine ecosystems.

Tide of change: Urgency of a national marine litter policy in India.

The rise of plastics in the 20th century revolutionized modern life but inadvertently exacerbated the marine litter crisis. The proliferation of wastes such as single-use plastics has escalated pollution along the coastline, demanding coordinated, decisive, and unified action. While the absence of specific national marine litter policies is concerning, there is growing recognition of urgency to address this issue. A group of experts and stakeholders was involved through a multi-staged workshop to assess the generated information based on scientific evidence and formulate a framework for the National Marine Litter Policy (NMLP). This paper proposes policy options (4 targets & 20 strategies) to address marine litter pollution, especially plastics, and aims to elucidate the urgency and significance of implementing an NMLP as a comprehensive strategy to combat plastics pollution. Implementing dedicated policies and action plans tailored to the unique challenges faced by each country is a vital step towards sustainable oceans.