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.

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.

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.

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.

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.

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.

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.

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.

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.

Assessment of ecological status of Uppanar and Vellar estuaries through multivariate pollution indices.

Multivariate pollution degree indices were utilized to evaluate the environmental condition of the Uppanar and Vellar estuaries. The Trophic Index (TRIX) indicates a state of "moderate eutrophication" with a value of 4.92, while the Trophic State Index (TSI) ranged from 40.3 to 57.2, categorizing the trophic states from "oligotrophic" to "eutrophic". The Comprehensive Pollution Index (CPI) showed a range of 0.13 to 0.94, classifying pollution levels from "unpolluted" to "slightly polluted". The study revealed that the Uppanar and Vellar estuaries underwent seasonal variations, transitioning from an oligotrophic state during the post-monsoon and summer periods to a eutrophic state in the pre-monsoon and monsoon seasons. The application of multivariate statistical tools allowed the identification of pollution indicator species to assess the estuarine systems. The insights gained from this study can be valuable for assessing other ecosystems facing similar anthropogenic activities, providing a basis for informed management and conservation strategies.

Health impact assessment of the surface water pollution in China.

China suffers from severe surface water pollution. Health impact assessment could provide a novel and quantifiable metric for the health burden attributed to surface water pollution. This study establishes a health impact assessment method for surface water pollution based on classic frameworks, integrating the multi-pollutant city water quality index (CWQI), informative epidemiological findings, and benchmark public health information. A relative risk level assignment approach is proposed based on the CWQI, innovatively addressing the challenge in surface water-human exposure risk assessment. A case study assesses the surface water pollution-related health impact in 336 Chinese cities. The results show (1) between 2015 and 2022, total health impact decreased from 3980.42 thousand disability-adjusted life years (DALYs) (95 % Confidence Interval: 3242.67-4339.29) to 3260.10 thousand DALYs (95 % CI: 2475.88-3641.35), measured by total cancer. (2) The annual average health impacts of oesophageal, stomach, colorectal, gallbladder, and pancreatic cancers added up to 2621.20 thousand DALYs (95 % CI: 2095.58-3091.10), revealing the significant health impact of surface water pollution on digestive cancer. (3) In 2022, health impacts in the Beijing-Tianjin-Hebei and surroundings, the Yangtze River Delta, and the middle reaches of the Yangtze River added up to 1893.06 thousand DALYs (95 % CI: 1471.82-2097.88), showing a regional aggregating trend. (4) Surface water pollution control has been the primary driving factor to health impact improvement, contributing -3.49 % to the health impact change from 2015 to 2022. It is the first city-level health impact map for China's surface water pollution. The methods and findings will support the water management policymaking in China and other countries suffering from water pollution.

Not only in the crowd: Benthic litter characterization in a low population density area still reveals widespread pollution and local malpractices.

Various anthropogenic activities affect marine coastal habitats, leading to heavy litter pollution. However, whilst high litter concentrations are nowadays common in the proximity of metropolises, few studies investigated the magnitude of this phenomenon around coastal villages and small towns. We hereby characterized the benthic litter occurring in the trawlable grounds of the Gulf of Policastro (Tyrrhenian Sea, central-western Mediterranean), a low population density area that becomes a popular tourist destination during summer. We furthermore tested differences between two depths (∼100-200 and ∼500-600 m) and the impact of tourism on the shallower waters. The area was characterized by a litter abundance of 651.12 ± 130.61 item/km2, with plastic being almost totalitarian (93%). The shallower waters hosted two-thirds of the litter found. Almost all (∼95%) the litter items had a land-based origin, while the sea-based litter was mostly found at higher depths. About 14% of the litter was found to be fouled, with the development of litter-associated communities that somehow mimic the natural ones living on hard substrates. The higher litter presence noticed during the touristic peak (July-August) suggests that tourism is an important source of local litter, although it contributed to the local accumulation in a synergic way with other factors. The majority of the litter items presumably originated from the nearby coastline, while the deeper waters were or are used as a dumping site by the local trawling fleet. The discovery of such a critical waste accumulation and management in a somehow remote area contributes to widen the perspectives on the presence of benthic litter mostly in territories characterized by wide anthropization. Moreover, it confirms that appropriate local policies and communication plans are urged even at a regional level to stimulate citizen consciousness and mitigate the ever growing litter pollution.

Residents' Willingness to Pay for Water Pollution Treatment and Its Influencing Factors: a Case Study of Taihu Lake Basin.

This study designs a double-bounded dichotomous questionnaire, and uses the Contingent Valuation Method (CVM) to estimate residents' willingness to pay(WTP) for water pollution control along the Taihu Lake Basin. The results of the returned questionnaire show that 82.76% of the residents are willing to pay. CVM estimation results show that the average WTP of residents for water pollution control is 138.86 yuan/year. In addition, the influencing factors of WTP are explored using a Logistic regression model, and the heterogeneity of WTP among residents of different genders is analyzed. The study found that: (1) The younger the residents, the higher their WTP; (2) The higher the income, the higher the residents' WTP for water pollution control; (3) Residents with higher educational level are more willing to pay; (4) The higher the degree of residents' understanding of water pollution control policies, the higher the WTP; (5) The higher the degree of residents' recognition of pro-environmental behavior, the higher the WTP; (6) Male residents' WTP is mainly affected by cognitive factors such as their understanding of governance policies and their approval of pro-environmental behaviors, while female residents' WTP is mainly affected by personal attributes, such as age, income, and the number of household laborers. Furthermore, this study proposes targeted measures to improve residents' WTP from three aspects: the government enriches the channels for residents to participate in water pollution control, the social media enriches the popularization of water environment knowledge, and the school strengthens the education of environmental protection knowledge, considering the differences in residents' characteristics. Therefore, this study can provide a theoretical reference and decision-making basis for encouraging residents to participate in water pollution control, promote the construction of a beautiful watershed, and provide a reference for other basins.

Dynamics of antibiotic resistance genes in the sediments of a water-diversion lake and its human exposure risk behaviour.

The dynamics and exposure risk behaviours of antibiotic resistance genes (ARGs) in the sediments of water-diversion lakes remain poorly understood. In this study, spatiotemporal investigations of ARG profiles in sediments targeting non-water (NWDP) and water diversion periods (WDP) were conducted in Luoma Lake, a typical water-diversion lake, and an innovative dynamics-based risk assessment framework was constructed to evaluate ARG exposure risks to local residents. ARGs in sediments were significantly more abundant in the WDP than in the NWDP, but there was no significant variation in their spatial distribution in either period. Moreover, the pattern of ARG dissemination in sediments was unchanged between the WDP and NWDP, with horizontal gene transfer (HGT) and vertical gene transfer (VGT) contributing to ARG dissemination in both periods. However, water diversion altered the pattern in lake water, with HGT and VGT in the NWDP but only HGT in the WDP, which were critical pathways for the dissemination of ARGs. The significantly lower ARG sediment-water partition coefficient in the WDP indicated that water diversion could shift the fate of ARGs and facilitate their aqueous partitioning. Risk assessment showed that all age groups faced a higher human exposure risk of ARGs (HERA) in the WDP than in the NWDP, with the 45-59 age group having the highest risk. Furthermore, HERA increased overall with the bacterial carrying capacity in the local environment and peaked when the carrying capacity reached three (NWDP) or four (WDP) orders of magnitude higher than the observed bacterial population. HGT and VGT promoted, whereas ODF covering gene mutation and loss mainly reduced HERA in the lake. As the carrying capacity increased, the relative contribution of ODF to HERA remained relatively stable, whereas the dominant mechanism of HERA development shifted from HGT to VGT.

Innovative interpretable AI-guided water quality evaluation with risk adversarial analysis in river streams considering spatial-temporal effects.

Water security remains a critical issue given the looming threats of industrial pollution, necessitating comprehensive assessments of water quality to address seasonal fluctuations and influential factors while formulating effective strategies for decision makers. This study introduces a novel approach for evaluating water quality within a complex riverine zone in South Korea: Han River that encompasses five river streams situated at each junction of North and South streams (including Gyeongan Stream) that ultimately leading towards Paldang Lake. By utilizing the monthly water characteristic data from the year 2013-2022 across 14 different locations, the significant seasonal trends and potential influences on water quality are identified. The water quality here is calculated with the proposed method of sub-index water quality index (s-WQI). A combinatorial prediction approach of s-WQI for each location is conducted through a collective of data preprocessing approaches including Hampel filtering and feature selection in prior to the machine learning predictions. In return, light gradient boosting (LGB) is the most accurate predictor by outperforming other prediction algorithms, especially through LGB-Pearson and LGB-Spearman combinations for North and South stream intersections, and LGB-Pearson for Paldang Lake. To further evaluate the robustness of this evaluation and extending the results to a foreseeable scenario, a seasonal based Monte-Carlo Simulation with 10,000 attempts targeting the water characteristic distributions obtained from each location considered are carried out to identify the risk bounds within. The results are further interpreted with SHAP analysis on identifying the contributions of each water characteristics towards the water quality through local and global spectrum. This research yields practical implications, offering tailored strategies for water quality enhancement and early warning systems. The integration of AI-based prediction and feature selection underscores the transformative potential of computational techniques in advancing data-driven water quality assessments, shaping the future of environmental science research.

Plastic debris in lakes and reservoirs.

Plastic debris is thought to be widespread in freshwater ecosystems globally1. However, a lack of comprehensive and comparable data makes rigorous assessment of its distribution challenging2,3. Here we present a standardized cross-national survey that assesses the abundance and type of plastic debris (>250 µm) in freshwater ecosystems. We sample surface waters of 38 lakes and reservoirs, distributed across gradients of geographical position and limnological attributes, with the aim to identify factors associated with an increased observation of plastics. We find plastic debris in all studied lakes and reservoirs, suggesting that these ecosystems play a key role in the plastic-pollution cycle. Our results indicate that two types of lakes are particularly vulnerable to plastic contamination: lakes and reservoirs in densely populated and urbanized areas and large lakes and reservoirs with elevated deposition areas, long water-retention times and high levels of anthropogenic influence. Plastic concentrations vary widely among lakes; in the most polluted, concentrations reach or even exceed those reported in the subtropical oceanic gyres, marine areas collecting large amounts of debris4. Our findings highlight the importance of including lakes and reservoirs when addressing plastic pollution, in the context of pollution management and for the continued provision of lake ecosystem services.