Regional Pollution Research Articles

Cross-validation of methods for quantifying the contribution of local (urban) and regional sources to PM2.5 pollution: application in the Eastern Mediterranean (Cyprus).

A comprehensive (1-year-long) daily-resolved filter-based PM2.5 chemical speciation database was built over Cyprus (Eastern Mediterranean), encompassing various sites with different typologies (urban traffic, urban background and regional background). Such experimental strategy was designed and implemented with the view to quantify the contribution of local (Cypriot cities) versus regional (Eastern Mediterranean & Middle East) pollution sources on fine PM levels in Cyprus using the “Lenschow” approach (Lenschow et al., 2001). On an annual basis, fine PM fraction originated mainly from regional sources (53–61 %), while during winter a totally different pattern was observed, with local PM sources being the dominant ones (up to 70 %) due to enhanced biomass burning for domestic heating and unfavorable meteorological conditions enhancing stagnation and accumulation of air pollution close to the ground. At that period, the urban PM2.5 was found to be predominantly made of carbonaceous species (> 70 %). Dust from local sources unexpectedly dominated the summertime local PM2.5 (37–47 %).The results derived from “Lenschow” approach were quantitatively compared against an independent PM source apportionment approach using Positive Matrix Factorization (US EPA PMF 5.0) to assess more-local versus more-regional PM sources. We show here that both approaches applied over Cyprus have led to consistently similar results, further cross-validating the robustness of the two techniques. The influence of regional hotspots was further confirmed by using the Potential Source Contribution Function (PSCF) model which pinpointed the Middle East as the main source region of fine PM pollution affecting Cyprus.

Detailed analysis of air pollution in the Canadian prairie region: A step toward net-zero emission.

Industrial, agricultural, and natural pollution pose a critical problem for the Prairie provinces of Canada, with significant environmental and health concerns. This study addresses a critical knowledge gap by assessing the cumulative impacts of pollutants in the Prairie region, which hosts 40% of the Canada's indigenous population, often living near these pollution sources. By innovatively integrating Sentinel-5P satellite data, Google Earth Engine, ArcGIS, and Python, we show the trends in CO, NO₂, HCHO, SO₂, and aerosols from 2019 to 2023 at high resolution for the entire region, which sheds new light on the dynamics that operate beyond conventional air quality monitoring. Key findings are summer peaks for NO₂ and aerosols in southern Saskatchewan, related to agriculture, while winter peaks for CO and SO₂ in Alberta and Saskatchewan signal the need for renewable heating options. Alberta had the highest levels for most of the pollutants; however, CO concentrations were the highest in Manitoba. By integrating satellite data with ground-based measures, we also offer a more comprehensive and accurate analysis to pinpoint regional pollution issues, to help toward development of data-driven air quality strategies, and to enhance alignment of federal-provincial initiatives. These insights promote targeted interventions lowering exposure risk while encouraging practical sustainability in the Prairie region, and aid Canada in achieving its net-zero emission goal.

Weighted Comprehensive Risk Assessment and Pollution Analysis of Long-Term Printing and Dyeing Sludge Landfills in an Industrialized Chinese City.

Sludge landfilling is widely used in China, accounting for approximately 65% of total sludge disposal, due to its simplicity and cost-effectiveness. However, with increasing land scarcity and stricter environmental regulations, the Chinese government has emphasized reducing sludge landfilling. Despite these efforts, sludge historically disposed of in landfills continues to pose risks, including heavy metal leaching and contamination of groundwater and soil. Comprehensive risk assessments for multi-contaminant industrial sludge in long-term landfills remain limited. This study conducted a risk survey and pollution assessment at a long-term sludge landfill in a typical industrial city in China. The sludge at the site was found to be mildly alkaline (pH 7.30-8.29) and had a low calorific value (1.37E+03-1.61E+03 kcal/kg), with significant dewatering challenges (1.23×1015 s2/g). The overall pollution load was relatively low, with a regional Pollution Load Index (PLI) of 0.65. However, due to extreme pollutants, the Nemerow Pollution Index (NPI) reached 9.49, indicating severe pollution. The single-factor index assessment indicates high pollution levels for Zn, Sb, BaP, and total petroleum hydrocarbons (TPHs). Ecological risk is primarily associated with Hg, Sb, BaP, InP, and TPHs. However, the weighted comprehensive risk assessment method proposed in the study identifies Zn, Pb, Sb, and TPHs as priority pollutants, with the main pollution hotspots being SZ4, SZ5, and SZ9. Some pollutants, such as Ni, antibiotics, polychlorinated biphenyls, and certain polycyclic aromatic hydrocarbons, were not detected in the sludge. Through principal component analysis and positive matrix factorization analysis, multiple sources of pollution at the landfill were identified, including the dyeing industry, electronics manufacturing, traffic emissions, fuel combustion, and urban runoff. This analysis highlights heavy metal pollution (Cr, Hg, Pb) and organic pollutants (PAHs, TPHs, DBA) resulting from industrial and urban activities. The results offer key insights to guide future sludge treatment and disposal at this landfill.

The impact of air pollution on influenza incidence in high-altitude regions: a time-stratified case-crossover study based on Qinghai Province.

The unique characteristics of air pollution in high-altitude regions may significantly influence the transmission and incidence of influenza. However, current research on this phenomenon is limited, and further investigation is urgently needed. This study collected influenza outpatient data from Qinghai Province between January 1, 2016, and December 31, 2021. We employed a time-stratified case-crossover design combined with conditional Poisson regression models to quantitatively analyze the relationship between air pollutants (PM2.5, SO2, NO2) and influenza incidence and explored the moderating role of temperature in this relationship. Additionally, stratified analyses were conducted to identify potential vulnerable populations. The study results indicated that exposure to PM2.5, SO2, and NO2 was positively associated with the risk of influenza incidence. For every 10µg/m³ increase in the concentration of PM2.5, SO2, and NO2, the percentage change in relative risk (RR) of influenza incidence was 0.35% (95% CI: 0.02%, 0.68%), 2.24% (95% CI: 1.42%, 3.06%), and 1.91% (95% CI: 1.16%, 2.67%), respectively. Under low-temperature conditions, the impact of pollutants other than O3 on influenza incidence was particularly pronounced. Children, the elderly, and individuals living at altitudes of 3000-3500m were more sensitive to these pollutants. This study revealed a close link between air pollution and influenza in high-altitude regions, with greater health risks under low-temperature conditions. The findings underscore the necessity of strengthening air quality monitoring and raising public awareness of environmental health.

Validation of Psychometric Tools for Assessing Fatigue, Mood, and Sleep Quality: Application in the PREVES-STOP Study

Background and Objectives: Environmental pollution in regions like the Sarno River Basin in southern Italy significantly affects physical and psychological health. This study aimed to validate three novel psychometric tools—REST, HEAL-BDLC, and PEACE—for assessing fatigue, mood disturbances, and sleep quality in environmentally exposed populations. While correlations with heavy metal exposure will be addressed in a separate manuscript, this study focuses solely on psychometric validation. Materials and Methods: The PREVES-STOP Initiative recruited 88 participants aged 30–65 years from the Sarno River Basin. Participants completed psychometric questionnaires tailored to measure fatigue (REST), symptoms of depression and anxiety (HEAL-BDLC), and sleep quality (PEACE). Internal consistency, construct validity, and reliability were analyzed using Cronbach’s alpha, correlation analyses, and principal component analysis (PCA). A subgroup received a nutraceutical intervention for us to explore their responsiveness to change over a two-week period. Results: REST (α = 0.969), HEAL-BDLC (α = 0.962), and PEACE (α = 0.736) demonstrated strong reliability. PCA confirmed the unidimensional structure of REST and the two-component structure of HEAL-BDLC (depression and anxiety dimensions) and PEACE (insomnia and sleep quality). Correlations with established measures, such as the WHO Well-Being Index, supported construct validity. Among the intervention participants, significant improvements were observed in fatigue (−12.5 REST median score), mood (−13.0 HEAL-BDLC median score), sleep (+1.5 PEACE median score), and overall well-being (+4.0 WHO-5 median score). Conclusions: REST, HEAL-BDLC, and PEACE are reliable and valid instruments for assessing nuanced health outcomes in environmentally exposed populations. They hold potential for guiding public health interventions and evaluating environmental remediation impacts. These findings lay the groundwork for future studies linking psychometric outcomes with heavy metal exposure.

Integration of Total Maximum Daily Load (TMDL) and Environmental Flow Assessment (EFA) Concepts as an Adaptive Approach to Pollutant Loading Management in Asia: A Review

Water scarcity and pollution are escalating challenges in Asia, impacting ecological systems and human livelihoods. This paper reviews the integration of Total Maximum Daily Load (TMDL) and Environmental Flow Assessment (EFA) in water management to address the dual issues of water quality and quantity. TMDL focuses on regulating the number of pollutants entering water bodies to meet quality standards, while EFA ensures that enough water is available to support aquatic ecosystems. Their independent application, however, often leads to gaps—TMDL can overlook ecological needs, while EFA may neglect pollution control. The integration of these two frameworks offers a more holistic solution, especially in water-stressed regions like Southeast Asia, where moderate water availability is exacerbated by urbanization, industrialization, and agricultural runoff. Case studies from Malaysia, Indonesia, and China reveal the limitations of applying TMDL and EFA separately and underscore the necessity of addressing both ecological flow requirements and pollution limits. This paper identifies key pollutants such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), heavy metals, and total suspended solids (TSS), particularly in urban and semi-urban areas, and highlights the importance of tailoring strategies to the specific needs of different regions. By combining TMDL and EFA, policymakers can better manage pollutant loads, secure ecological health, and address Asia’s pressing water management issues. This review emphasizes the need for adaptable, integrated water management strategies that account for seasonal fluctuations, competing water demands, and regional water availability and pollution differences.

Monitoring and Comparative Analysis of NO2 and HCHO in Shanghai Using Dual-Azimuth Scanning MAX-DOAS and TROPOMI

This study employed dual-azimuth scanning MAX-DOAS to monitor vertical column densities of NO2 and HCHO in Shanghai during the summer and winter of 2023, and compared the results with Sentinel-5P TROPOMI data. Dual-azimuth scanning revealed a generally consistent trend in gas concentrations (r > 0.95), but concentrations at 90° were higher than those at 0°, especially near the surface. This suggests that averaging multiple azimuth angles is necessary to better represent regional pollution levels. During the observation period, diurnal patterns revealed that NO2 exhibited a “double peak” in the morning and evening, which was more pronounced in the summer, while HCHO peaked between 13:00 and 15:00. Comparisons with the TROPOMI data demonstrated overall good agreement. However, the probability of TROPOMI’s NO2 and HCHO measurements being lower than those of MAX-DOAS was 80% and 62.5%, respectively. Furthermore, TROPOMI tended to overestimate at high concentrations, with overestimation reaching 41.14% for NO2 when exceeding 9.54 × 1015 molecules/cm2 and 25.93% for HCHO when exceeding 1.26 × 1016 molecules/cm2. Sensitivity analysis of the sampling distance (0–40 km) between TROPOMI samples and the ground-based site, and the sampling time (±5 to ±60 min) relative to the TROPOMI overpass, revealed that using a sampling distance of 15–25 km for NO2 and 10–20 km for HCHO, along with appropriately shortening sampling times in the winter and extending them in the summer, can effectively enhance the consistency between satellite and ground-based observations. These findings not only reveal the spatiotemporal distribution characteristics of regional pollutants but optimize the sampling time and distance parameters for satellite–ground observation validation, providing data support for improving and enhancing the accuracy of satellite retrieval algorithms.

Is air pollution a challenge for climate change in mountainous country Nepal?

Connectivity between pollution and climate change has been justified by the researchers. Different types of air pollutants are increasing air pollution, damaging ecosystem and challenging for climate change. Mainly industrialized and growing economies are blamed for deteriorating environment caused by pollution. Economically weak and developing countries like Nepal are bearing high cost of such air pollution led climate change. Nepal lies in the top 10 highly polluted country in the world and recently it is facing growing causality caused by climate change. Identifying the nature and type of air pollution could help Nepal to minimize adverse impact of climate change as well as demand for climate fund with regional pollutant countries. In this context, this study aims to expose the possible climate risk created by internal and external led air pollution in Nepal based on the review of past research papers. Available secondary data have also been used for analyzing challenge created by air pollution for climate change in Nepal. The study found the influence of transport of regional air pollutants, mobility and forest fire as a challenge for climate change in Nepal.

Assessing public support for air pollution mitigation and control policies: health, socioeconomic, and ideological predictors in an overburdened and vulnerable region of the U.S.

BackgroundThe San Joaquin Valley (SJV) in California is one of the most polluted regions in the U.S. This study examined favorability for air pollution mitigation policies, interventions, and identified predictors amongst region’s residents.MethodsA cross-sectional online survey asked about health status and conditions, self-protective behaviors, attitudes toward air pollution recommendations, air quality information knowledge and mitigation behaviors, as well as whether their views were favorable or unfavorable towards policy and interventions. EuroQOL-5D-3L was utilized to estimate quality-of-life distribution equity and air pollution policy favorability.ResultsA total of 310 adults residing in the SJV participated in the survey. The mean age was 42.90 years, with 34% having asthma. People with asthma reported the lowest health-related quality of life (HRQoL) compared to other air pollution “sensitive” groups. Concerns included the costs, charge and attributes of adopting hybrid or electric vehicles. Residents supported air pollution control and public space preservation, with socioeconomic factors and health state being significant predictors. Left-wing ideologies favor policies charging polluters, controlling emissions, and preserving public spaces, whereas right-wing views negatively predict support for electric vehicle charges and local organization interventions.ConclusionsResults may help air pollution control policymakers, public health agencies, environmental justice organizations, and the health equity research community understand the reasons for differential responses to air pollution interventions and mitigation efforts. This new knowledge could assist stakeholders in recommending sustainable and cost-effective interventions for improving air quality, elicit behavior change, and climate change adaptation in the region.

Quantum-inspired neural networks for time-series air pollution prediction and control of the most polluted region in the world

Quantum-inspired neural networks for time-series air pollution prediction and control of the most polluted region in the world

Spatiotemporal Distribution and Potential Source Areas of PM2.5 Pollution in Xianyang City, Guanzhong Basin

This study employed PM2.5 concentration data for Xianyang City spanning the years 2014 to 2021, in conjunction with the global data assimilation system （GDAS）. Various analytical techniques, including backward trajectory clustering analysis, potential source contribution function （PSCF）, concentration weighted trajectory analysis （CWT）, and relevant statistical methods, were employed to investigate the temporal and spatial variations in PM2.5 pollution. Furthermore, this research aimed to elucidate the source characteristics and potential areas contributing to PM2.5 pollution within Xianyang City. The results revealed a fluctuation in PM2.5 pollution concentration in Xianyang City from 2014 to 2021, with an initial increase followed by a subsequent decrease. The peak average annual concentration, reaching 81.25 μg·m-3, was recorded in 2016. Seasonal variations indicated higher PM2.5 concentrations in autumn and winter, contrasting with lower levels in spring and summer. Winter exhibited the highest PM2.5 concentration at 116 μg·m-3, while the lowest was recorded in summer at 31.58 μg·m-3. Spatially, the annual mean distribution of PM2.5 in Xianyang City demonstrated heightened pollution in the southern and central regions, juxtaposed with lower pollution in the northern areas. Cluster analysis highlighted that Xianyang City experienced substantial influence from northwest airflow during spring, autumn, and winter, while short-distance transport dominated during the summer months. PSCF and CWT analyses indicated that the high-value potential source contribution areas were most extensive during winter, followed by spring and autumn. Conversely, the high-value area in summer was the smallest. The potential source areas were concentrated within Xianyang City and extended northwest to southeast, encompassing regions in western Inner Mongolia, central and eastern Gansu Province, central and southern Ningxia, and central Henan. In analyzing periods of heavy pollution, the study demonstrated that PM2.5 pollution in Xianyang City was primarily induced by westerly airflow. High PM2.5 concentrations were influenced by the surrounding areas of Xianyang City and the source zone, akin to regions with high potential source values during the winter. As a consequence, mitigating PM2.5 pollution in Xianyang City necessitates stringent control measures for both local and regional pollution sources. Additionally, regional collaborative efforts should be emphasized to prevent external pollution sources from exacerbating persistent pollution episodes in the region.

Evaluation of Bayesian Maximum Entropy Data Fusion Approaches to Estimate Styrene, Benzene, Toluene, Ethylbenzene, and Xylenes and to Inform Epidemiological Analyses in the US Gulf States.

The Gulf States are home to industries emitting styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX). Presently, adverse health effects of ambient SBTEX exposure in highly polluted regions, such as the Gulf States, must be evaluated. Epidemiologists, however, are limited by inadequate estimates of ambient SBTEX. Using Bayesian Maximum Entropy, SBTEX estimation methods of varying resource intensity were evaluated, including simple kriging (least intense), incorporation of observational and emissions data trends (moderately intense), and data fusion of observed and Comprehensive Air quality Model with extensions (CAMx) data (most intense). Generally, as resource intensity increased, so did SBTEX estimation performance, where SBTEX Spearman R values increased by 0.48 on average from the least to most intense methods. Data fusion of observed and CAMx data was identified as the best ambient SBTEX estimation method in the Gulf States. Exposure estimates revealed that Gulf States residences within commuting distance of high industrial activity experienced 1.64 times higher 97.5th percentile daily exposures to SBTEX on average than those living in less industrialized areas, which could contribute to total occupational and ambient exposure disparities. Furthermore, ambient benzene exposure was greater than the acceptable one-in-a-million excess cancer risk threshold for 75% of estimated residence locations in the Gulf States.

Evaluation and source identification of water pollution.

Maintaining good surface water quality is essential for protecting ecosystems and human health. Henan Province has long faced challenges related to water scarcity and severe water pollution. To support effective management of water pollution in Henan Province and provide insights for regional water pollution management, we collected extensive water quality monitoring data and applied spatial autocorrelation along with random forest to analyze the sources of heavily polluted areas. Results indicate that the spatial pollution pattern of surface water quality in Henan Province can be generally classified as insignificant pollution in the north, heavy pollution in the central regions, and light pollution in the south. Heavily polluted areas are mainly located in Zhengzhou, Luoyang, and Kaifeng. Key indicators affecting water quality in these regions are chemical oxygen demand (CODMn), dissolved oxygen (DO), ammonia nitrogen (NH3-N), and total phosphorus (TP), with urban sewage and industrial wastewater identified as the main causes of deterioration. These results not only provide a scientific basis for the systematic management of surface water quality pollution in Henan Province but also provide a reference for regional water pollution management.

Mapping NOx emissions in Cyprus using TROPOMI observations: evaluation of the flux-divergence scheme using multiple parameter sets

The production of nitrogen oxides (NOx = NO + NO2) is substantial in urban areas and from fossil fuel-fired power plants, causing both local and regional pollution, with severe consequences for human health. To estimate their emissions and implement air quality policies, authorities often rely on reported emission inventories. The island of Cyprus is de facto divided into two different political entities, and as a result, such emissions inventories are not systematically available for the whole island. We map NOx emissions in Cyprus for two 6-month periods in 2021 and 2022 with a flux-divergence scheme, using spaceborne retrievals of nitrogen dioxide (NO2) columns at high spatial resolution from the TROPOMI instrument, as well as horizontal wind data to derive advection and concentrations of OH, NO, and NO2 to derive chemical processes. Emissions are estimated under three different sets of parameters using ECMWF data and WRF-Chem simulations. These sets are chosen for their differences in spatial resolution and representation of wind and air composition. Exploiting the low emissions in Cyprus, we show that the flux-divergence method is limited by the resolution of wind and hydroxyl radical, the signal-to-noise ratio of the observed tropospheric column densities, and the NOx:NO2 ratio above the main pollution sources. Such limitations lead to large discrepancies in the emissions calculated with the three different sets of parameters, making it difficult to estimate NOx emissions for the five power plants of the island without high uncertainties. Nevertheless, the obtained emissions display a higher seasonality than reported or inventory emissions. For the two power plants in the south, the different mean daytime output estimates appear to be significantly higher than the bottom-up estimates. They are also higher than those from the power plants in the south combined, despite a much lower production capacity, illustrating the application of different environmental norms and the use of different technologies and fuels in the two parts of Cyprus.

Assessment of microplastic ecological risk and environmental carrying capacity of agricultural soils based on integrated characterization: A case study.

Microplastic pollution in agricultural soils poses a significant threat to soil quality and environmental sustainability. This study investigated the composition, abundance, distribution, ecological risk, and environmental carrying capacity of microplastic pollution in the Tarim River Basin (TRB), China. The risk quotient combined with soil environmental carrying capacity (SECC) approaches was proposed to evaluate ecological risks and soil sustainability. Microplastic abundances ranged from 0 to 4000 items/kg (average=570 items/kg), with polyethylene (PE) polytetrafluoroethylene (PTFE) and polypropylene (PP) as dominant polymers. In addition, various factors affecting the occurrence of microplastics were analyzed. Agricultural mulching and drip irrigation were associated with higher microplastic levels. The risk assessment showed that among the different shapes, size ranges and categories of microplastics, fragmented (film), large-sized microplastics and PE had the highest risk, respectively. While current levels are within SECC limits, early warning model predicts PE and PP may reach threshold limits in recent years. This study provides crucial insights for managing microplastic pollution in agricultural regions, emphasizing the need for targeted mitigation strategies to maintain soil ecology sustainability.

Decoding the disproportionate risk factor landscape of global type 2 diabetes burden in adults: An attribution analysis from 1990 to 2050.

Limited systematic assessments of risk factor contributions to the global burden of type 2 diabetes (T2D) across subpopulations hinder targeted policies and resource allocation. Utilizing the Global Burden of Disease study (GBD) 2019, we analyzed the disability-adjusted life-years (DALYs) for T2D attributable to 15 risk factors in adults (aged 25+ years) globally and by sex, age, Socio-demographic Index (SDI), and GBD region, from 1990 to 2019. Additionally, we assessed future trends of these risk factors through 2050. High body-mass index (BMI) emerged as the predominant risk factor in all subpopulations in 2019, with its impact projected to double by 2050. During 1990-2019, males were more affected by smoking, while females by secondhand smoke and household air pollution. The related DALYs increased with age, except for high BMI and smoking peaking at 60-74 years. In 2019, diet high in processed meat ranked second in high SDI regions, contrasting with household air pollution in low SDI regions. National disparities were observed, with Fiji recording the highest rates of DALYs related to both high BMI and dietary risks in 2019, which were approximately 50 and 15 times higher than those observed in Japan, respectively. Tailored interventions targeting major contributing risk factors specific to each subpopulation are key to the success of the global combat against T2D.

Spatiotemporal variability of groundwater chemistry, source identification and health risks in the southern Chinese Loess Plateau

Groundwater pollution of the loess plateau regions has become a global concern due to its vulnerability to natural and anthropogenic influences. In this study, 146 water samples were investigated to identify the spatiotemporal variability in groundwater chemistry, pollution sources and nitrate health risks in two interconnected river basins of a typical loess region. The results showed that except for bicarbonate, spatiotemporal variability of hydrochemical components in Malian River Basin (ML) was generally greater than that in Upper Jinghe River basin (JH-U) due to the hydrogeological conditions, and the hydrochemical facies in two river basins transformed from SO4·Cl and Cl·SO4 types to HCO3 and HCO3·SO4 types. The results of integrated-weight quality index (IWQI) showed that 77.8 % (1970s), 33.3 % (2004), 34.3 % (2015) of samples in ML exceeded the standard limits of Class IV groundwater quality, displaying a high pollution level with an improvement trend, while groundwater quality in JH-U indicated a very low pollution level with a deterioration trend. The geogenic source was identified as a main factor affecting groundwater quality, with contributions of 59.2 % and 48.7 % in JH-U and ML (2015), respectively. The anthropogenic sources including agricultural activities (20.7 % and 21.8 % in JH-U and ML) and coal mining activities (20.1 % and 29.5 % in JH-U and ML) also played a role in affecting groundwater quality. The nitrate health risk assessment demonstrated that 39.1 % and 20.3 % of groundwater samples (2015) significantly exceeded the standard threshold (Hazard Index = 1), implying a higher health risk to children than adults, and the nitrate health risk in ML was obviously greater than that in JH-U. This study provides novel insight into the spatiotemporal variability in groundwater chemistry, quality and health risk in loess regions under the influence of geogenic and anthropogenic factors.

Analysis of Microplastic Contamination and Associated Human Health Risks in Clarias gariepinus and Oreochromis niloticus from Kubanni Reservoir, Zaria Nigeria

Environmental safety has become a major concern in recent years due to the global increase in microplastic pollution. These ubiquitous, tiny, and potentially toxic plastic particles enter aquatic environments through weathering of larger plastics and the release of microbeads. Although numerous studies have focused on microplastic pollution in developed regions, information from developing countries remains limited. This study assessed the presence of MPs and associated oxidative stress responses in two commercial fish species, Clarias gariepinus (Catfish) and Oreochromis niloticus (Nile Tilapia), from Kubanni reservoir, Zaria, Nigeria, over six months spanning both the dry and rainy seasons. Fibers were identified as the most abundant MP particles, followed by fragments, films, and beads, in the order of fibers > fragments > films > beads. The highest fiber concentrations were recorded in the gills, with Clarias garipinus showing 11.5 MP items/individual and Oreochromis niloticus showing 22.5 MP items/individual. Black microplastics were predominant, and the most common ingested MP ranged from 1.0 to 2.0 mm. The primary polymers identified were polypropylene and polyethylene terephthalate. Evidence of oxidative stress and cellular damage was observed in the gills, liver, and dorsal muscles of both fish species, which correlated with MPs ingestion. According to recommendations from the European Food Safety Authority regarding fish consumption by children and adults, individuals consuming Clarias gariepinus and Oreochromis niloticus from the Kubanni reservoir may be exposed to between 70 and 700 MP items/organ. The risk associated with consuming MPs found in fish gills and guts was notably higher, posing significant concerns for human health. This study provides insights into microplastic contamination in commercially important fish from the Kubanni Reservoir and highlights the environmental and public health risks associated with consuming contaminated fish from this ecosystem.

Mercury tolerance and bioremediation potential of mountain soil bacteria: Insights from Darjeeling, containing elevated levels of mercury.

More and more research is now being focused on the mercury contamination of remote mountain environments. This study aimed to explore the mountain soil of Tiger Hill, Darjeeling, through the lens of its mercury tolerant bacterial microbiome to characterize regional mercury pollution and isolate strains with mercury bioremediation potential. The soil bacteria isolated from the region displayed an extreme tolerance to mercury at previously unseen levels of up to 7mg/mL. The mercury removal capacity of the two best isolates, MTD11C and MTD11E, identified as strains of Brevundimonas naejangsanensis and Staphylococcus arlettae, exhibited a mercury removal capacity of 99.74% and 99.56 %, respectively. As per our research, such extreme tolerance to mercury as demonstrated by the bacterial strains has not been reported thus far. The prevalence of such tolerance in the microbiota of a region may well be an indication of the degree of mercury pollution harbored by it. Their tolerance to other heavy metals and antibiotics, as well as active plant growth promotion traits, were also characterized in this study. The topsoil of this region was estimated to contain elevated levels of mercury at around 0.52-2.39mgkg-1. Ecological risk assessment further showed the potential for harm to the environment posed by the level of mercury. Collected vegetation samples from tea plantations surrounding Tiger Hill displayed an accumulation of mercury in the leaves and roots of the tea plants as well, suggesting rampant mercury pollution that needs to be addressed.

Summer profiles: Tracing currently used organophosphorus pollutants in the surface seawater of the Arctic Ocean.

We investigate the spatial distribution and potential ecological impact of Currently Used Organophosphorus Pollutants (CUOPPs) in the Arctic Ocean, focusing on the East Siberian Sea, Laptev Sea, and high Arctic regions. Analyzing surface water samples collected during a scientific expedition aboard the "Xuelong 2" in August and September 2021, we detected 38 out of 83 targeted CUOPPs, including Phorate, Paraoxon, and Azinphos-ethyl, with concentrations exhibiting significant geographical variance. The results reveal a pronounced increase in CUOPP concentrations towards the Arctic poles, diverging markedly from the patterns observed in the East China Sea, thereby highlighting distinct regional pollution profiles and environmental interactions. Our findings suggest various potential sources and transport mechanisms for CUOPPs, indicating complex pollutant dynamics. Furthermore, the study delves into the influence of Arctic sea ice dynamics on the distribution patterns of CUOPPs, underscoring the pivotal role of environmental factors such as surface currents. Ecological risk assessments conducted for essential Arctic species pose a high ecological risk in the Arctic Ocean, with a "Summer Alert" effect. This investigation elucidates the intricate relationship between CUOPPs dispersal in the Arctic and the broader implications of climate change, offering critical insights into the emerging environmental challenges in polar ecosystems.