Pollution Scenarios Research Articles

Analysis of Pollutant Accumulation in the Invasive Bivalve Perna viridis: Current Status in the Colombian Caribbean 2020–2023

The Colombian Caribbean faces environmental challenges due to urbanization, industrialization, and maritime activities, which introduce pollutants such as heavy metals, hydrocarbons, and microplastics into aquatic ecosystems. Perna viridis (Asian green mussel), an invasive species that has been established in Cartagena Bay since 2009, exhibits potential bioaccumulation capacity, making it a promising biomonitor. This study assessed the concentrations of mercury (Hg), cadmium (Cd), lead (Pb), and selenium (Se) in P. viridis across two key sites—a port area at the Cartagena Bay (CB) and Virgen marsh (VM) in Colombia—from 2020 to 2023. Seasonal variations driven by La Niña and El Niño phenomena significantly influenced metal concentrations, with transitional periods modulating pollutant accumulation. The levels of trace metals in soft tissue of P. viridis (dry weight) ranged from 0.0003 to 0.0039 µg/g (Cd), 0.04 to 0.21 µg/g (Hg), 0.05 to 1.18 µg/g (Pb), and 0.0029 to 0.0103 µg/g (Se). In suspended particulate matter (SPM), Cd ranged from 0.07 to 0.33 µg/g; Pb ranged from 4.94 to 25.66 µg/g; and Hg ranged from 0.18 to 1.20 µg/g. Results revealed differences in metal concentrations between sites and seasons, highlighting the role of environmental and anthropogenic factors in pollutant distribution. The findings confirm P. viridis as an effective biomonitor of complex pollution scenarios in Cartagena Bay. However, its invasive status highlights ecological risks to be addressed, such as interaction with native bivalves and benthic community structures. These results emphasize the need for ongoing monitoring efforts to mitigate pollution and preserve marine biodiversity in the Colombian Caribbean.

Emamectin Benzoate and Microplastics Led to Skeletal Muscle Atrophy in Common Carp via Induced Oxidative Stress, Mitochondrial Dysfunction, and Protein Synthesis and Degradation Imbalance.

Pesticides and plastics have brought convenience to agricultural production and daily life, but they have also led to environmental pollution through residual chemicals. Emamectin benzoate (EMB) is among the most widely used insecticides, which can cause environmental pollution and harm the health of organisms. Additionally, microplastics (MPs), a relatively new type of pollutant, not only are increasing in residual amounts within water bodies and aquatic organisms but also exacerbate pollution by adsorbing other pollutants, leading to a mixed pollution scenario. Nevertheless, the toxicity and mechanism of EMB and MPs on common carp skeletal muscle have not been elucidated. Therefore, we established exposure models for EMB and MPs, and methods such as hematoxylin and eosin staining, immunofluorescence staining, JC-1 staining, and western blotting were employed to investigate the underlying mechanisms of skeletal muscle damage. The results of in vivo and in vitro experiments indicated that exposure to EMB or MPs led to oxidative stress, which in turn caused mitochondrial fusion/fission imbalance (with decreased Mfn1, Mfn2, and OPA1 and increased DRP1), reduced mitochondrial membrane potential, decreased ATP content, reduced protein synthesis, and increased degradation, ultimately resulting in skeletal muscle atrophy. Joint exposure caused more severe damage than single exposure, and the addition of NAC can effectively alleviate skeletal muscle atrophy. In summary, exposure to EMB and/or MPs induced excessive reactive oxygen species (ROS) production, giving rise to mitochondrial dysfunction and an imbalance in skeletal muscle protein synthesis and degradation, ultimately resulting in skeletal muscle atrophy in common carp.

The Impact of Different Fertilization Methods on Soil Heavy Metal Pollution and Restoration Methods

Soil heavy metal contamination, exacerbated by the long-term use of phosphate and organic fertilizers, poses a significant threat to agriculture and global ecosystems. Accumulation of heavy metals such as arsenic (As), cadmium (Cd), lead (Pb), and mercury (Hg) in soils can endanger human health and ecosystem services. This paper evaluates the content of heavy metals in various fertilizers and reviews existing remediation technologies. Among these, plant-microbe collaborative remediation shows promise for mitigating heavy metal pollution, although its effectiveness in multi-pollutant environments remains underexplored. Current research reveals a gap between laboratory results and practical applications, with limited studies on long-term ecological impacts. Future research should prioritize addressing complex pollution scenarios and developing efficient, eco-friendly remediation strategies to promote sustainable agriculture and environmental protection

Complexities of riverfront development for the hilly city of Paonta Sahib in India.

The rapid urbanization, industrial growth, and socio-cultural activities along riverbanks in hilly cities are transforming land use and intensifying water infrastructure challenges. Paonta Sahib, a culturally significant town in Himachal Pradesh on the Yamuna River, along the foothills of the Himalayas exemplifies these pressures due to its religious tourism, industrialization, and mining activities. This study explores sustainable riverfront development at Paonta Sahib, addressing socio-cultural, environmental, and technical concerns essential for eco-sensitive urban planning. A Strength, Weakness, Opportunity and Threat (SWOT) analysis highlights strengths such as Paonta Sahib's strong cultural identity and economic potential, alongside weaknesses like limited water infrastructure and unregulated land use. Opportunities for eco-sensitive zoning and circular economy practices are proposed as strategies to mitigate environmental impacts, with financial projections indicating a 68 million INR annual cost recovery over a 35-year development period. Additionally, pollutant scenario analysis is recommended to support effective water quality management. Findings emphasize the importance of collaborative efforts between local authorities, technical experts, and communities to address the extreme hydrological, environmental, and planning challenges faced by riverbank cities. This balanced approach seeks to enhance Paonta Sahib's urban identity while preserving ecological integrity, offering a model for sustainable development in similar hilly settlements. The proposed framework aims to guide future policies for resilient riverfront urbanization, emphasizing adaptive planning, community engagement, and infrastructure that support both economic growth and environmental sustainability.

Accounting for microorganisms yields stricter water quality criteria and elevated ecological risks of antibiotics: A case study of sulfonamides in the Yangtze River Delta.

The derivation of water quality criteria (WQC) for antibiotics is influenced by the inclusion of various organisms' toxicity data, including microbial data, though no definitive conclusions have been reached. This study focuses on sulfonamide antibiotics, common in the Yangtze River Delta (YRD), to assess the influences of different organisms' toxicity data on determining WQCs and subsequent evaluation of ecological risks. A total of 263 toxicity data points from eight sulfonamides, including sulfamethoxazole (SMX) and sulfamethazine (SM2), were selected to derive WQCs using Species Sensitivity Distribution (SSD) methods. Three WQC types were calculated: based on native species (WQC-n), a combination of native and non-native species (WQC-nn), and a combination of species and microorganisms (WQC-nnm). While WQC-nn showed minimal differences from WQC-n, the inclusion of microbial data resulted in more conservative short-term WQCs (SWQC-nnm), calculated as 256.90 μg/L for SMX and 196.09 μg/L for SM2, approximately half of SWQC-nn values (435.20 μg/L for SMX and 491.11 μg/L for SM2). Monitoring data from the past 15 years in the YRD revealed a 133 % increase in ecological risks when using LWQC-nnm compared to LWQC-n and LWQC-nn, particularly under the worst-case pollution scenarios. However, there was a slight temporal decline in overall ecological risks. The study concludes that incorporating microbial toxicity data results in more protective WQCs and underscores the need for further research to develop WQCs that safeguard sensitive organisms and better reflect real-world exposure scenarios, e.g., the mixture exposure.

Increasing microplastic concentrations have nonlinear impacts on the physiology of reef-building corals.

The pollution of marine environments with plastics, particularly microplastic (MP, i.e., plastic particles <5mm), is a major threat to marine biota, including corals. While the effects of MPs are increasingly well understood, knowledge of how different concentrations of naturally occurring MP mixtures affect reef-building corals is still limited. Therefore, we aimed to elucidate the relationship of MP concentrations and their effects on reef-building corals. For this, we exposed two reef-building coral species (Stylophora pistillata and Pocillopora verrucosa) in a 12-week experiment to MPs at a gradient of concentrations (0, 0.1, 1, 10, and 100mg·L-1). Specifically, we examined effects on the coral host physiology (i.e., surface and volume growth, calcification, necrosis, and polyp activity), and the photosynthetic activity of the photosymbionts (i.e., effective and maximum quantum yield, maximum relative electron transport rate, minimum saturating irradiance, and light capture efficiency). To mimic natural conditions, we used a MP mixture consisting of six polymers in forms of fibers and fragments. Both coral species showed reduced growth rates, necrosis, lower polyp activity, and an upregulation of photosynthesis, which intensified with increasing MP concentrations. While the effects on the coral host mostly showed basic linear or nonlinear dose-response relationships, the effects on the photosymbionts revealed more complex nonlinear dose-response relationships, and photosynthesis was only upregulated after a species-specific threshold. We found that high and extreme pollution scenarios caused strong adverse effects on coral physiology, while current low to moderate concentrations had minor effects. Increasing concentrations had amplifying effects, likely due to the disproportionately higher frequency of entanglement, leading to more frequent direct contact and potential transfer of toxins or pathogens. These results suggest that corals can cope with current average pollution levels. However, they also highlight the need for measures to limit permanent increases of MP pollution to protect the health of coral reefs.

Insights into the effects of river network topology on sudden pollution risks

The risk of sudden water pollution is one of the biggest obstacles to ensuring the safety of river basin water environments. While external pressure factors such as illegal discharge have been extensively studied with regard to their impact on the risk of sudden pollution, the influence of the river network topology has received limited attention. To fill this gap, extensive computational experiments were conducted in this study to investigate the effects of river network topology on the potential risk of sudden pollution. Based on the real-world characteristics of dendritic river networks, we used optimal channel networks to generate various river network topologies, represented by seven indicators that encompass morphology, connectivity, and structure. The water quality model simulated the spatial and temporal responses of the samples to a wide range of sudden pollution scenarios, and quantified the associated risk of sudden pollution using three proxy indicators: the maximum standard-exceeding multiple, proportion of standard-exceeding river length, and duration of exceedance. The results showed that among the seven indicators, the average outlet path (Do) and geometric fractal dimension (Dg) had a significant impact on risk. This is because network topology alters hydrological signatures such as discharge, velocity, and travel time. Moreover, multi-group analysis of structural equations revealed that the aspect ratio influences the impact of structural and connectivity indicators on risk by modulating pollution range and concentration. This study revealed the topological factors of the risk of sudden water pollution in dendritic river networks, emphasizing the regulatory role of topology in potential sudden water pollution risk and providing valuable insights for river management and planning.

Analysis of electric field and leakage current of glass and porcelain insulators under clean and polluted conditions: A comparative study of three profiles

Electric field (EF) enhancement in insulating systems may occur due to both internal and external factors including inefficient design, manufacturing defects, and depositions of pollutants. Consequently, phenomena like partial discharge, unexpected flashover, and even breakdown of the insulator may take place. In this work, aiming to suggest relatively better performance, a comparative study of porcelain and glass insulators under clean and polluted conditions was conducted using finite element-based software, COMSOL Multiphysics. Three profiles of both the insulators namely, standard, anti-fog, and open were modelled, and the effects of their geometry and varying electric conductivity of the surrounding air were analyzed on EF distribution and leakage current (LC). These parameters were also investigated under the deposition of water droplets and various pollution scenarios. Results of the performed computations demonstrated that by making air conductivity high, LC enhanced significantly while EF was affected the least. The presence of water droplets in the vicinity of live electrode and deposition of pollution near the end fittings created the strongest impact on EF distribution. Among the studied configurations, standard profile of porcelain material appeared to be the most promising for suppressing effects of the simulated stresses.

Identification and ranking of oil pollution by developing a preventive management and emergency response model against pollution: A case study of a mega port on the northern coast of the Persian Gulf

Oil pollution remains a critical environmental challenge in maritime transportation, significantly impacting marine ecosystems and coastal communities. This study investigates oil pollution incidents at the loading and unloading docks of Imam Khomeini Port and aims to develop a comprehensive prevention and emergency response management model. We conducted a thorough evaluation of environmental components, specifically Total Petroleum Hydrocarbons (TPHs), and utilized the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify and prioritize risks. Key findings revealed four emergency pollution scenarios, highlighting critical areas that require immediate intervention. Our analysis underscored essential agenda items for effective emergency response planning, scoring 4.4 for environmental resource conservation and 4.35 for pre-incident responsibility assignment. Furthermore, a McKinsey Gap Analysis identified seven strategic priorities for the emergency response plan, indicating substantial weaknesses in the strategy (1.65) and skills (1.75) dimensions, demonstrating inadequate crisis preparedness. These results emphasize the urgent need for a robust emergency response model tailored to mitigate oil pollution risks. By addressing identified gaps, this study provides a strategic framework for enhancing environmental management practices at the port, fostering more sustainable operations in the Persian Gulf region. Ultimately, our findings advocate for collaborative efforts among stakeholders, including national and international organizations, to implement rigorous environmental policies and effective monitoring systems to safeguard marine environments against oil pollution.

Evidence from In Situ Bioassays and Suspect Analysis Revealed the Region-Specific Aquatic Risk across Socioeconomic Gradients in China.

Various contaminants are present in aquatic environment and pose potential threats to pelagic and benthic organisms, calling for effective risk assessment. Traditional risk assessments based on target analysis are useful when the principal contaminants responsible for ecological risk are known; however, these approaches become challenging when dealing with chemical mixtures. In addition, the compositions of chemical mixtures often differ in regions with different levels of socioeconomic development, requiring risk assessment methods that are applicable under different pollution scenarios. Herein, in situ bioassays were conducted with two native species, Chinese rare minnows (Gobiocypris rarus) and Asian clams (Corbicula fluminea), in economically developed watersheds in China (Pearl River Basin (PRB) and Taihu Lake Basin (THB)) and agriculture-dominated Poyang Lake Basin (PYB). Significant lethal and sublethal effects (e.g., neurotoxicity, reproductive toxicity, and metabolic and oxidative stress) were observed in fish and clams irrespective of economic gradients. Notably, ecological effects differed significantly between water and sediment phases within the same region. Target (98 contaminants) and suspect screening (942 contaminants) revealed regional-specific characteristics. Ecological risk assessments using a weight of evidence approach demonstrated that both water and sediment in the PRB were at moderate to high risk, as was the sediment in the less developed PYB. However, the characteristics of mixture pollution varied greatly among regions. Suspect screening identified many pollutants that are not regularly monitored but are present at high environmental concentrations and are linked to local industrial production. These distinct mixture risk characteristics across different basins suggest that mitigating aquatic pollution requires region-specific management measures.

A multifunctional coconut shell biochar modified by titanium dioxide for heavy metal removal in water/soil and tetracycline degradation

Heavy metals and tetracycline pollute the environment and endanger human health. This work prepared a multifunctional coconut shell biochar (Ti-XBC) through NaHCO3 activation and TiO2 modification. The modified coconut shell biochar was characterized by various methods. Ti-4BC exhibited excellent removal performance for heavy metals. The maximum adsorption capacity of Ti-4BC on Cd2+, Pb2+, Cr3+, and Cr6+ reached 104.2, 136.8, 101.2, 112.4 mg/g in water. The adsorption of Ti-4BC for four metal ions had a competitive effect in the binary metal system. It also reduced the mobility of four heavy metal ions in soil. Density functional theory (DFT) calculations were employed to explain the mechanism of heavy metal removal. Additionally, the degradation performance and mechanism of Ti-4BC towards tetracycline were investigated. The results indicated that the maximum degradation rate was 99.4%. Overall, this work developed a multifunctional material capable of both removing heavy metals and degrading antibiotics, addressing the issue of single-function in biochar. This provided a novel approach for tackling complex and diverse environmental pollution scenarios.

Factors affecting the different growth rates of PM2.5：Evidence from composition variation, formation mechanisms, and importance analysis of water-soluble inorganic ions with case study in northern China

PM2.5 affects air quality, therefore, understanding the mechanism of PM2.5 growth is essential to figure out mitigation measures. Hourly real-time concentrations of water-soluble inorganic ions (WSIIs), including anions and cations, in fine particulate matter (PM2.5) were measured in Baoji, northwest China. During the winter monitoring period, the concentrations of PM2.5 and most WSIIs exhibited similar trends. Mass proportions of SNA [i.e., sulfate (SO42−), nitrate (NO3−), ammonium (NH4+)] in PM2.5 gradually increased with air deterioration, while equivalent ratios of anions to cations also increased. The heterogeneous aqueous reactions and/or gas-phase homogeneous reactions promoted the formation of secondary inorganics, especially during the haze events. Rapid transformations of primary gaseous precursors to secondary pollutants could lead to the substantial formation of SO42− and NO3−. In terms of particle growth rate, the mass proportions of SNA in PM2.5 decreased from General Growth (GG) to Explosive Growth (EG) events. Furthermore, the particle growth rates did not coincide with the pollution levels, while it occurred most frequently during the Transition Period, instead of the Polluted Period. The diurnal variation of SNA at different PM2.5 growth rates has been discussed. The results of the Random Forest (RF) model showed that RH was an important factor for EG of PM2.5, while low RH was a reliable reason for the relatively low mass proportion of SNA. The results of this study could advance our understanding of particle growth and provide scientific evidence to support the establishment of unique air quality control measures under different pollution scenarios in Fenwei Plain, China.

EHT and environmental justice at EPA Victoria: Aspirations and regulatory realities

Abstract EPA Victoria (Australia) is a statutory authority that regulates polluting activities and advises other Victorian government departments on relevant policy settings. In 2016, a public health function was installed at EPA Vic to provide emergency health messaging during pollution events, review research evidence of environmental-health relationships and assess industry-contracted health risk assessments of polluting entities. An Environmental Health Tracking Network (EHTN) is under development to support these activities. The EHTN is an agile data and analytical infrastructure for translating expertise across an expanding multidisciplinary network of public health researchers, EPA operational staff and public sector policy makers. Its current interactive dashboards calculate health impacts and associated costs of air pollution scenarios, model land-use influences on land and water contamination and identify coincidences of sociodemographic-, urban environment- and pollution exposure-disadvantage in a high spatial resolution environmental justice (EJ) framework. Regulatory leverage of EHTN intelligence, however, requires legislated EJ thresholds and/or legally tractable costing of industry-externalised human health impacts. Thus, to establish triggers for more stringent conditions on polluting activities and promote equity of interventions and regulations, novel regionally and EJ specific health risk functions are required. Considering these ambitions and challenges, the EHTN at EPA Vic is focussed on 1) identifying and characterising vulnerable populations at high spatial resolution, 2) estimating associated exposure-health effect size modifications using primary epidemiological methods and 3) applying these to health impact and cost assessments of pollution and waste. We seek defensible grounds on which to impose more stringent standards for polluters and redress entrenched social, health and economic disadvantage. Speakers/Panelists Hanna Tolonen THL, Helsinki, Finland

Microplastics–biofilm in aquatic ecosystem: Formation, pollutants complexation, greenhouse gas emission and ecotoxicology

The omnipresent microplastics (MPs) have gradually become a significant environmental problem due to its adverse consequences for ecological systems. MPs serve as substrates for biofilms colonization, which enhances adsorption of harmful contaminants on MPs surface in the aquatic ecosystem. The present study provides a critical discussion on the mechanism involved in MPs–biofilm formation, microbial colonization and the robust factors influencing the process in the aquatic ecosystem. Subsequently, the impact of MPs–biofilm on adsorption of inorganic and organic contaminants is explored. The ecological significance of MPs–biofilm associated pollutant complex for promoting greenhouse gases (GHGs) emissions from aquatic ecosystem is extensively discussed for understanding the climatic risk. Furthermore, the discussion is extended over ecotoxicological impact of MPs–biofilm on aquatic biodiversity and humans. The protective extracellular polymeric substances secreted by colonised bacteria over MPs during biofilm formation creates sticky MPs surface for heteroaggregates formation with swift adsorption of chemical compounds and microorganisms. MPs with functional aromatic groups facilitate the bacterial adhesion on the surface, but affect formation of biofilm. Alternatively, MPs–biofilm promotes the Mn and Fe hydrous oxides formation that can co–precipitate with heavy metal ions and facilitate in remediation measures. However, MPs biodegradation generates GHGs emission per unit mass, comparably more from freshwater than marine ecosystem. Considering the toxicity, MPs–biofilm induces the oxidative response in fishes, causing painful death and thus, destroys aquatic biodiversity. This study will be useful to address MPs–biofilm associated pollution scenario via trace, test and treat strategy involving future engineering research framework for ecological restoration.

Robust regenerable metal-selenide-chitosan photocatalyst for the effective removal of Bromothymol Blue (BB) from wastewater

Water scarcity has been a crucial debate in recent years regarding the critical scenario of water pollution. The water body is continuously contaminated by organic effluents of textile industries, including pigmented dye pollutants. To tackle water bodies contamination, there is a need to develop an eco-friendly and efficient method for removing toxic dyes. Herein, ternary metal selenide nanocomposites of barium nickel selenide (NBSe-NPs) were synthesized by the solvothermal method supported by chitosan microsphere (NBSe-NPs-CM). Recovery of the catalyst was convenient by capping nanoparticles in the microsphere to maintain effective stability, biocompatibility, and well-designed surface coating. FTIR spectrum verified nanocomposite synthesis and chitosan microsphere (NBSe-CM) formation. SEM observations of nanocomposites and NBSe-CM indicated an average size of 13.78 nm and 253 μm, respectively. The presence of barium, nickel, and selenium elements in the NBS-NPs was verified by EDX analysis. The nanocomposites had a crystallite size of 15.73 nm. The photocatalyst exhibited a narrow bandgap of only 1.3 eV based on Tauc's plot. In addition, the synthesized microsphere demonstrated an efficient photocatalytic degradation (97 %) of Bromothymol Blue dye within 100 min under optimized operating conditions (pH of 6.0, dye concentration of 40 ppm, catalyst dosage of 0.25 g). The photocatalysis process followed the pseudo-first-order kinetics. The repeatability studies showed a slight decline in the catalyst's efficiency after four successive cycles. The DFT study shows that the NBSe-CM is energetically stable with more considerable negative binding energy, and the dye molecule interacts more strongly with the NBSe-CM surface. The findings highlight the exceptional characteristics of the newly designed ternary-metal-selenide-containing chitosan-microspheres for degrading dye contaminants from textile effluents.

Microplastic pollution scenario and its effects on public health and ecosystem: a Bangladesh perspective

Microplastic pollution scenario and its effects on public health and ecosystem: a Bangladesh perspective

Development and optimization of an Artificial Neural Network (ANN) model for predicting the cadmium fixation efficiency of biochar in soil

This study addresses the issue of soil cadmium pollution and the common problem of data missing during the training of artificial neural network models. A substantial amount of characteristic data regarding the immobilization of cadmium in soil through biochar was collected from the literature. Subsequently, data was organized and analyzed using correlation matrix analysis and feature importance analysis. The results revealed that the feature importance of biochar (52%) was relatively significant. A novel approach is introduced, involving a non-deterministic optimization technique based on linear interpolation to supplement the missing data within the dataset. The completed dataset effectively preserves the distributional characteristics of the original data, thereby enhancing the training performance of the neural network model. Through three phases, namely data incompleteness, data supplementation, and genetic algorithm optimization, the neural network model was progressively refined. The outcome of this iterative process is a high-performance artificial neural network model capable of predicting the efficiency of biochar in immobilizing cadmium in soil. The significance of these findings lies in their potential to advance the application of machine learning in environmental science, particularly in addressing complex pollution scenarios.

Mining of dynamic traffic-meteorology-atmospheric pollutant association rules based on Eclat method

With the rapid increase of urban vehicles, the atmospheric compound pollutants, notably PM2.5 and O3, have significantly increased and seriously affected public health. Traffic and meteorological conditions are the primary influencing factors of pollutant concentrations, and their spatial and temporal changes affect the dispersion of pollutants. Increasing use of high-resolution big data offers opportunities to explore these correlations. More extensive quantitative studies are essential for effective air pollution control. This study presents an Eclat algorithm to quantitatively reveal the relationship between traffic, meteorology and pollutants with hourly and 5-minute scale data in the urban area of Guangzhou. We establish a research framework covering temporal pollution analysis, multifactor rule mining, and spatial effects. The results show that PM2.5 and O3 exhibit coordinated trends on the daily scale influenced by traffic flow and meteorology conditions, but on the hourly scale, they are negatively correlated. At the 5-minute scale, synchronized variations occur only during specific periods. This finer scale better identifies association rules for high-concentration pollutant scenarios, and non-roadside sites outperform roadside sites in mining these associations. For example, when humidity is below 37%, atmospheric pressure is 1016.2–1020.3 Pa, wind speed is 1.7–2.6 m/s, and the traffic volume on Jiefang North Road exceeds 635 vehicles every 5 min, there is a 92.86% probability that the PM2.5 concentration at GYQ (a non-roadside monitoring site) will exceed 127 μg/m3. These findings enhance our understanding of how dynamic traffic and meteorological conditions impact atmospheric pollutants and provide a scientific basis for regional collaborative pollution prevention.

Extracting regional and temporal features to improve machine learning for hourly air pollutants in urban India

India is suffering from severe particulate matter (PM, including PM2.5 and PM10) pollution, while limited ground observations are insufficient to support a comprehensive understanding of its health risks. Machine learning (ML) has the potential to improve the estimation of PM distribution and exposure efficiently. Regional transport as well as accumulation and dispersion processes of PM and its components, which have significant impacts on PM concentrations, are crucial when building ML models, especially for sparsely observed regions like India. Here, geographic and temporal-rolling weighting methods were used to separately extract regional and temporal features for improving the performance of the ML model. The incorporation of temporal and regional features into the ML model significantly improved ML model performance, with root mean square error (RMSE) reduced by 21 % and 19% for PM2.5 and PM10 estimation, as well as an improvement in model underestimation for the heavy pollution scenarios. The spatial-temporal model shows out-of-sample test CV coefficients of determination (R2) of 0.87 and 0.88 for hourly PM2.5 and PM10. The ML model predicts an annual nationwide concentration of 68.3 μg/m3 for PM2.5 with a north (high, especially in Indo-Gangetic Plain) to south (low) distribution, which is consistent with high satellite aerosol optical depth (AOD) values. Boundary layer height is identified as the main meteorological factor influencing PM2.5 concentrations in winter. Characterizing the regional transport and cumulative dispersion processes of pollutants by extracting features can help in machine learning training, and this method can be further improved and applied to other studies.

The influence of river basin nitrogen pollution sources and their transport on microbial community structure

The characterization of variations in riverine microbiota that stem from contaminant sources and transport modes is important for understanding biogeochemical processes. However, the association between complex anthropogenic nitrogen pollution and bacteria has not been extensively investigated owing to the difficulties faced while determining the distribution of nitrogen contaminants in watersheds. Here, we employed the Nitrogen and Oxygen Stable Isotope Tools alongside microbiological analysis to explore microbial characteristics and their responses to complex nitrogen pollution patterns. Significant changes in microbial communities were observed in watersheds with different complex nitrogen pollution sources migrating. Complex nitrogen sources were closely associated with microbiota. The main sources of nitrogen pollution in the dry season watershed were Manurc and Sewage (M&amp;amp;S, 54.2%). M&amp;amp;S exhibited reduced microbial diversity, high number of denitrification groups, and increased nitrogen cycling compared with others. However, Soil Nitrogen sources (SN, 59.3%) in the watershed during the wet season were the main contributors of nitrogen in the watershed. Eluviation allows SN to increased microbial community similarity, in addition to facilitating microbial immobilization processes. Overall, this study expands our knowledge regarding microbial biogeochemistry in catchments and beyond by linking specific nitrogen pollution scenarios to microorganisms.