Pollution Control Measures Research Articles

Spatiotemporal Dynamic Analysis of Eutrophication Status Based on Machine Learning-Based Retrieval Algorithm: Case Study in Liangzi Lake, Hubei, China

The routine monitoring of eutrophication is an important measure for observing the variation in water quality and protecting the ecological health of lakes. However, in situ information reflects eutrophication levels within a limited distance and period. In this study, we retrieved the trophic level index (TLI) based on Landsat 8 remote sensing images and using a machine learning (ML) method in Liangzi Lake in Hubei Province, China. The results showed that random forest (RF) outperformed other ML algorithms in estimating the TLI, evaluated by its higher fitness through the Monte Carlo method (median values of R2, RMSE, and MAE are 0.54, 0.047, and 0.037, respectively). In general, 8% of the areas of Liangzi Lake presented an increasing eutrophication level from 2014 to 2022, and 20.1% of the areas reached a mild eutrophication level in 2022. In addition, we found that temperature and anthropogenic activities may impact the eutrophication conditions of the lake. This work uses remote sensing imagery and a ML method to monitor the dynamics of the lake’s eutrophication status, thereby providing a valuable reference for pollution control measures and enhancing the efficiency of water resource management.

Sustainable Urban Development: A Comprehensive Model for Assessing Health Risks from Compounded Pollution in Xi’an

Global climate change and rapid urbanization have brought unprecedented environmental challenges, especially in rapidly expanding cities like Xi’an, posing potential challenges to sustainable development if not accompanied by adequate greenery, thoughtful layouts, and pollution control measures. The increasing frequency and intensity of urban air pollution (e.g., PM2.5, PM10, O3) and extreme climate events (e.g., heatwaves) have heightened health risks for residents. Existing studies mostly focus on single pollution or climate factors, neglecting the compounded effects of these factors. To fill this research gap, this study presents a health risk assessment model, specifically by analyzing the compounded effects of heatwaves and air pollution. By integrating hazard, exposure, and vulnerability factors using the entropy weight–TOPSIS method, the results reveal significant spatial differences in health risks across various regions of Xi’an. The findings provide valuable guidance for urban planners and policymakers to better address environmental hazards, reduce health risks, and promote sustainable urban development.

Uncovering the Anthropogenic Influences on Water Quality: A Case of Lake Victoria Shores, Entebbe, Uganda

Lakes serve as vital ecosystems, providing freshwater resources and habitats for diverse species. However, human activities, particularly around lakeshores, have led to significant environmental degradation, including heavy metal contamination. Lake Victoria, the second-largest freshwater lake globally, has been severely impacted by pollution from industrial, agricultural, and urban sources. This research aims at examining the influence of the anthropogenic activities on the water quality of Lake Victoria. Specifically, the study tried to determine the activities undertaken at the Lake shores of Lake Victoria; determined the physico-chemical parameters of the water from the shores and the heavy metal concentration in the water samples obtained from the shores of Lake Victoria. This study utilized a cross-sectional and experimental research designs to assess water quality and anthropogenic influences around Lake Victoria. A total of 150 residents from selected communities were surveyed using a semi-structured questionnaire to gather demographic information, perceptions of water quality and the activities carried out within the shores of Lake Victoria. Water samples were collected from multiple sites along the lake shores for analysis of heavy metals using the Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Water quality parameters were determined In-situ using a multi-parameter water testing kit and Hanna instrument. Results showed that the anthropogenic activities that could have contributed to water degradation include: fishing, transport, agriculture and construction among others. Apart from pH which was outside the permissible limits, all the other water parameters were within the WHO permissible limits. Considering the heavy metal concentration, all the sampled sites apart from one inlet, had the concentrations above the WHO permissible levels an indication of significant heavy metal contamination in the Lake Victoria shores. These findings highlight the urgent need for targeted pollution control measures and regular monitoring to mitigate further environmental degradation. Effective interventions, including stricter regulations and sustainable land use practices within the Victoria shores are essential for safeguarding the lake's ecosystem and the health of surrounding communities.

Integrating material flow analysis into hydrological model for water environment management of large-scale urban-rural mixed catchment

Simultaneous simulation of urban and rural hydrological processes is important for water environment management of mixed land-uses catchments. However, the discharge paths of pollution in the urban drainage system are not described in traditional catchment hydrological models. In this study, an urban-rural water environment (URWE) model is developed through incorporating the material flow analysis (MFA) and the soil and water assessment tool (SWAT) into a general framework. The URWE model is an advancement with respect to traditional hydrological models in terms of simultaneously simulating the urban organized and rural decentralized discharges of pollution. Due to the low data requirement and high computational efficiency of MFA, URWE model is applicable to large-scale catchment with wide urban area. The URWE model is applied to a typical urban-rural mixed catchment, the Dianchi Catchment (China), where the pollution characteristics are analyzed and the pollution control measures are investigated. Results indicate that the URWE model outperforms the conventional SWAT model for both water quantity and quality simulations, with an 8.5 % improvement in average coefficient of determination (R2) and a 67.4 % improvement in average Nash coefficient (NSE). Rural best management practice, rainwater-sewage separation, and storage capacity expansion are identified as the most cost-effective measures for COD, TN, and TP reduction, respectively. Contributions of this study are to improve the accuracy of water environment simulation in urban-rural mixed catchment, as well as to help decision-makers develop synergistic urban-rural water environment management measures.

Heterogeneity of population exposure to particulate matter pollution and its socioeconomic driving mechanism in Shaanxi Province, China

The rapid pace of economic and social development has led to a surge of particulate matter (PM) pollution incidents, which is detrimental to human health. Air quality in China has improved in recent years, but differences in PM exposure remain due to spatial heterogeneity in pollution and population. The identification of socioeconomic factors associated with PM pollution has attracted widespread attention. Current research predominantly targets cities, overlooking regional and county scale disparities. An analytical framework is established to evaluate the spatial heterogeneity in PM exposure and to identify the socioeconomic factors contributing to its pollution. The results revealed that: (1) the Theil index increased from 0.06 to 0.12, indicating a gradual increase in the inequality of PM exposure in Shaanxi Province. The differences within the Guanzhong Plain are obvious and the interregional differences substantially outweigh the intraregional variations. (2) Energy transition is pivotal in curbing air pollution in a region and economic growth consistently fuels particulate emissions. (3) For effective pollution mitigation, further emphasis on vegetation preservation and environmental inputs is imperative. The findings of this research provide decision support for optimizing air pollution control measures at the county scale.

Seasonal trends and light extinction effects of PM2.5 chemical composition from 2021 to 2022 in a typical industrial city of central China

This study investigates the concentrations, chemical compositions, and sources of PM2.5 in Huangshi, China. Daily average PM2.5 levels ranged from 8.43 to 193.08 μg m−3, with an annual mean of 54.13 μg m−3, exceeding China's annual secondary standard of 35 μg m−3. Seasonal mean concentrations peaked in winter and were lowest in summer. Organic carbon (OC) and elemental carbon (EC) had annual means of 4.89 μg m−3 and 0.94 μg m−3, respectively. Water-soluble inorganic ions (WSIIs) accounted for 52.17% of PM2.5, with NO3−, SO42−, and NH4+ being the major components. The NO3−/SO42− ratio averaged 1.65, indicating a transition from coal combustion to vehicle emissions as the primary pollution source. Chemical mass reconstruction revealed that NH4NO3, (NH4)2SO4, and organic matter (OM) accounted for 65.3% of PM2.5 mass. Seasonal variations in light extinction (bext) highlighted the impact of secondary inorganic salts on visibility, with an annual average bext of 346.30 ± 246.98 Mm−1. Airmass clusters and potential source region analysis suggested PM2.5 and its components were primarily originated from local and nearby regions. These findings underscore the effectiveness of local pollution control measures, changing pollution sources, and the necessity for targeted emission controls to improve air quality and visibility in urban areas.

Assessment of trace metal levels in water, sediment and fish tissue from Lake Small Abaya, Ethiopia

The environmental impact of trace metal contamination is a concern for Lake Small Abaya, Ethiopia, because of nearby agricultural and industrial activities. This study assessed the levels of trace metals (Pb, Zn, Cd, Cu, Fe, Mn, and Cr) in water, sediment, and fish samples, as well as the physicochemical parameters of the water. Samples were collected from five sites and analyzed via graphite furnace atomic absorption spectrometry (GFAAS). The mean concentrations in the water were Zn: 0.6971 mg/l, Fe: 0.5628 mg/l, Cu: 0.1168 mg/l, Mn: 0.2129 mg/l, Pb: 0.0057 mg/l, Cr: 0.0021 mg/l, and Cd: 0.0014 mg/l. In the sediments, the mean concentrations were as follows: Fe, 33.066 mg/kg; Zn, 18.263 mg/kg; Mn, 22.777 mg/kg; Cu, 7.5663 mg/kg; Pb, 0.0751 mg/kg; Cr, 0.0233 mg/kg; and Cd, 0.0183 mg/kg. The fish samples presented mean concentrations of Fe: 21.855 mg/kg, Zn: 12.686 mg/kg, Cu: 0.3185 mg/kg, Mn: 0.9181 mg/kg, Pb: 0.0089 mg/kg, Cd: 0.0075 mg/kg, and Cr: 0.0015 mg/kg. All the metal concentrations were generally below the World Health Organization (WHO) regulatory limits. The physicochemical parameters indicated slightly alkaline to neutral conditions, with electrical conductivity and total dissolved solids within acceptable ranges. These findings suggest that current agricultural and industrial activities do not significantly contribute to trace metal pollution. However, continued monitoring and pollution control measures are recommended to ensure the long-term health and sustainability of the lake. This study highlights the importance of effective environmental management strategies to safeguard this crucial aquatic resource.

Forecasting mortality and DALYs from air pollution in SAARC nations

This study investigates the projected impact of air pollution on mortality and Disability-Adjusted Life Years (DALYs) across SAARC countries. Utilizing Time Series and Machine Learning methodologies such as Autoregressive Integrated Moving Average, Exponential Smoothing, and Neural Network, the research aims to accurately forecast the mortality and DALYs attributed to air pollution from 2020 to 2030. Statistical analyses reveal a consistent upward trend in deaths and DALYs during the forecasting period, primarily driven by Ambient Particulate Matter Pollution (APM) and Ambient Ozone Pollution (AOP). Comparing the predictive accuracy of the models, Neural Network outperformed other methods, as indicated by Root Mean Square Error (RMSE) values. Specifically, the study finds that deaths and DALYs due to Ambient Particulate Matter pollution are least prevalent in the Maldives, while India and Pakistan exhibit the highest rates, and deaths and DALYs due to Ambient Ozone pollution are lowest in the Maldives and highest in Bangladesh and Pakistan. Moreover, deaths and DALYs attributed to Household Air Pollution (HAP) are lowest in Pakistan and highest in Nepal. These findings underscore the urgent need for air pollution control measures and informed policymaking in SAARC countries to mitigate the escalating health burden associated with air pollution.

Exploring Burden of Disease Metrics in EU legislation: A Systematic Analysis

Abstract Background The burden of disease (BoD) methodology is a valuable tool for evidence-based policymaking. However, there is currently no systematic analysis available regarding its use in the European Union (EU) legislation framework. This study aims to describe the implementation of BoD methodology in EU legislation. Methods A search was conducted on EUR-Lex, the official and most comprehensive platform to access EU legal documents. The main inclusion criteria in the analyses were date of publication (between 2004 and 2023, accounting for EU-25) and inclusion of BoD metrics (years of life lost - YLL, years lived with disability - YLD or disability-adjusted life years - DALY). Descriptive and network analysis were conducted to analyse the legislation content. Results Out of 2592 documents, 191 met the set criteria. Ten were legally binding, and 69% were published after 2018. The European Commission (n = 152) was the most regular issuing institution. BoD was mainly used as an argument (n = 93) and for impact assessment (n = 50). The metrics were commonly presented in the main text (n = 122) and in the annex (n = 48). EuroVoc domains like environment and social questions prevailed. The most frequent EuroVoc terms were climate change policy (n = 45), EU environmental policy (n = 32) and pollution control measures (n = 32). Discussion Despite the growing recognition of BoD metrics in supporting policymaking, only 191 documents published over the past 20 years within the EU legislation make reference to this methodology. Greater efforts in knowledge dissemination and directing research towards specific policy uptake may increase the application of BoD studies in EU policies. By advocating for increased awareness, promoting collaboration between researchers and policymakers, and targeting research efforts towards specific policy needs, a more comprehensive integration of BoD methodologies into EU legislation can be achieved, contributing for evidence-informed policies. Key messages • There were only 191 documents of the EU legislative documents published in the past 20 years mention burden of disease metrics, mainly addressing environmental and social issues. • There is a need to increase EU policy uptake from BoD studies, by conducting policy-oriented research, and building capacity among researchers and policymakers on BoD methodology.

Long-term analysis of BTEX concentrations and health risks in semi-arid urban regions

Rajasthan, experiencing rapid industrialization and urbanization, faces critical air quality challenges, particularly concerning toxic volatile organic compounds (VOCs) such as BTEX (Benzene, Toluene, Ethylbenzene, Xylene). This study presents a long-term analysis of BTEX concentrations across various cities in Rajasthan, India, using data from the Central Pollution Control Board (CPCB) from 2017 to 2022. The findings revealed that the average ∑BTEX concentrations increased from 4.15 µg/m3 in 2017 to 12.29 µg/m3 in 2022, with a temporary decline in 2020. The Hazard Quotient (HQ) values for BTEX exposure ranged from 0.052 to 0.15 for males, 0.056 to 0.17 for females, and 0.09 to 0.29 for children over the study period, indicating higher health risks for children. Similarly, the Lifetime Cancer Risk (LCR) values varied from 6.04 × 10⁻⁶ to 1.92 × 10⁻5 for males, 1.09 × 10⁻⁶ to 2.24 × 10⁻5 for females, and 1.17 × 10⁻5 to 3.73 × 10⁻5 for children. The results demonstrate that children are at a greater cancer risk from BTEX exposure compared to adults. This study emphasizes the urgent need for effective air pollution control measures and continuous monitoring to protect public health, particularly vulnerable populations like children.

Spatial distribution, ecological and human health risks of potentially toxic elements (PTEs) in river Ravi, Pakistan: A comprehensive study

Significant quantities of potentially toxic elements have been and are still being discharged into Pakistan's rivers through natural sources and anthropogenic activities. The present study provides a comprehensive study of potentially toxic element contamination in the water and sediment of the Ravi River, Pakistan. The research aims to examine the extent of pollution, its ecological risks, and the potential human health impacts through detailed geospatial analysis and statistical correlation. Water and sediment representative samples were taken and analyzed for potentially toxic elements, including Cobalt (Co), Cadmium (Cd), Zinc (Zn), Nickel (Ni), Arsenic (As), Chromium (Cr), Lead (Pb), Copper (Cu), and Manganese (Mn). Various pollution indices, such as the “Geo-accumulation Index (Igeo), Modified degree of Contamination (mCd), Nemerow comprehensive pollution index (Pt), Contamination factor (CF), Enrichment factor (EF), Pollution Load Index (PLI), and Potential Ecological Risk Index (PERI),” were calculated to determine the contamination levels and ecological risks. The results indicated significant spatial variability in metal concentrations, with higher levels observed in industrial and urban areas (near Lahore). Cd and As were identified as the most critical pollutants, exhibiting high Igeo, CF, EF, and PERI values. The PLI revealed that several regions along the river are heavily polluted. Pt shows high comprehensive pollution near Lahore and moderate to high pollution in surrounding areas. According to mCd, most of the study area, especially sampling points near Lahore, ranges between 8 and 16, indicating a high degree of pollution. The Human Health Risk (HHR) assessment, considering ingestion, inhalation, and dermal contact pathways, highlighted that children are particularly vulnerable, showing higher Hazard Quotient (HQ) and Hazard Index (HI) values for several metals. Correlation analysis revealed significant relationships between certain metals, suggesting common sources of contamination, likely from industrial discharges and urban runoff. The comprehensive mapping and statistical analysis underscore the urgent need for implementing effective pollution control measures to mitigate the risks posed by potentially toxic element contamination in the Ravi River. This study provides critical insights for policymakers and environmental managers to prioritize areas for remediation and to develop strategies to protect both ecological and human health in the region.

Comparative assessment of pollution control measures for urban water bodies in urban small catchment by SWMM

Under the current increasingly serious water pollution situation in urban, the comprehensive treatment and protecting measures in urban small catchment are the necessary step to the water pollution treatment, not only focus on the water bodies themself. In this paper, the Luojiagang river channel and its catchment in Wuhan, which has been heavily impacted by water pollution, are taken as an example for the comparative assessment of pollution control measures in order to explore the effective and sustainable schemes including the LID (Low Impact Development---LID) by using SWMM model (Storm Water Management Model---SWMM). Through the comparison of pollution treatment measures based on scenarios simulation with the baseline scenarios, it was found that the reduction effects of pollutant peak concentrations at the outlet node of Luojiagang River had the decreasing order of: the combined measures (COS) > LID control > the water diversion from Donghu Lake (WAD) > the sewage treatment (SET) > the sediment dredging (SED), and the reduction effects of total pollutant load had the decreasing order of: LID > COS > SET > SED > WAD. The results show that the control of non-point source pollution is the key for the improvement of water quality in Luojiagang River, and LID plays important role in the reduction of both pollutant peak concentrations and load. This study has the implication for the decision making of the water pollution controlling schemes in urban small catchment.

Assessing the impact of meteorological factors and air pollution on respiratory disease mortality rates: a random forest model analysis (2017-2021).

Air pollution poses a significant threat to the health of all living beings on our planet. It has been scientifically established as a crucial factor affecting mortality rates, respiratory illnesses, mental well-being, and overall health. This study aimed to investigate the impact of air pollution and meteorological factors on respiratory disease mortality rates in Mashhad in 2017-2021 using a Random Forest (RF) model. At first, the daily statistics of meteorological parameters (pressure, humidity, temperature, solar radiation) during 2017-2021 were collected. The information related to pollutants pollutants such as PM2.5 (which is defined as particulate matter with less than 2.5 micrometer diameter and potentially harmful to humans), PM10 (Particles with a diameter of 10 micrometers or less that can negatively impact both human health and environmental conditions.), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) was collected. the mortality statistics from respiratory diseases were collected from the Health system registaration (Sina). Then we used the RF regression model in Excel and Python software to investigate the interaction between the mentioned variables. The escalating trend of air pollution in Mashhad has led to an expected increase in respiratory-related hospitalizations. This necessitates urgent air pollution control measures. Concurrently, the study of pollutants and climatic elements, as substantiated by global epidemiological studies, is crucial. In Mashhad, the second most polluted city in Iran, climatic factors like humidity, sunshine duration, temperature, pressure, and sunlight intensity exacerbate atmospheric pollution levels, impacting human health and ecosystems. The R2, RSME, and MAE of RF model are 0.73, 2.52, and 2 which indicate that the model has successfully identified the relationship between input variables and the target variable, and it will exhibit high accuracy in predictions. In this study, the most influential factor was identified when the Variance Inflation (VI) factor reached a value of 0.548. This indicates a strong correlation between this factor and the death rate of patients during the specified period. Furthermore, we analyzed by excluding the day and month plans from our model. The results showed that the factor with the highest coefficient in the executive model was related to pressure, with a VI value of 0.049. This suggests that pressure plays a significant role in our model and has a substantial effect on the death rate of patients. In the study of various pollutants, it was found that PM10 had the most significant impact on the mortality rate of patients with respiratory conditions, with a VI of 0.039. Following PM10, the pollutants with the next highest coefficients of importance were NO2 (VI = 0.034), SO2 (VI = 0.033), PM2.5 (VI = 0.029), and CO (VI = 0.025), respectively. Furthermore, the study observed a notable increase in the mortality rate of respiratory patients over time. Specifically, for every five days, the death rate increased by 35.5%. Indeed, climate change and air pollution significantly contribute to the mortality rate from respiratory diseases. Therefore, it is crucial for individuals, particularly those with respiratory conditions, to heed meteorological warnings.

Research on the flow velocity characteristics of oil contaminated with particulates using PIV

PurposeThe paper aims to clarify the influence of the equivalent particles number (EPN) change on the flow velocity characteristic.Design/methodology/approachThe paper opted for an exploratory study using PIV technology to obtain the transient flow toxicity vector of oil in the square pipeline.FindingsThe paper provides empirical insights about the influence of EPN on the flow average velocity which is most prominent in the middle of the pipeline, and smaller EPN values have a greater impact.Originality/valueThese influence laws of EPN can be used to obtain the dynamic characteristics of oil, which provides theoretical support for oil pollution control and effective treatment measures and lays a preliminary foundation for the online monitoring of particles in oil.

Evaluation and pollution analysis of water environment of state-controlled river in Zaozhuang City from 2016 to 2022

The quality of water environment is closely linked to the survival and development of human beings. Thanks to the Water Pollution Prevention and Control Action Plan, the quality of the water environment has improved significantly. However, challenges remain in the surface water environment due to human activities in the basin. We analyze the surface water quality of the six state-controlled rivers in Zaozhuang City, which are key tributaries to the Nansi Lake and the water storage and distribution area of the South-to-North Water Diversion East Project. Physical-chemical parameters and metal pollutants were detected from 2016 to 2022. The Various indices were used for evaluating the surface water environmental quality and pollution issue. Although there were significant inter-year differences in each river, the results of Water quality index and Nemerow composite index analysis indicated that the water quality of the six rivers has continuously improved over the years. Nevertheless, as this research reports, such as considerable annual fluctuations in pollution factors, obvious pollution characteristics in river basins, and difficulty in controlling non-point source pollution, which still restrict the further improvement of the water environment. Each river presents various water environment problems due to differences in industrial structures within its basin. Through the analysis of production and lifestyle in each basin, the main pollution sources of each river were evaluated and determined. Based on the type and characteristics of pollution sources, control measures and optimization strategies are proposed for the improvement of the water environment.

Estimation of atmospheric lead emissions from coal in China: from past to the future under China’s Dual-Carbon policy

Lead, known for its widespread application and high toxicity, has long been a focus of research. Since the prohibition of leaded gasoline in 2000, China has witnessed a shift in the primary sources of atmospheric lead emissions towards coal consumption. We conducted a systematic study on the abundance and distribution of lead in Chinese coal and used model analysis to predict atmospheric lead emissions from different sources. Provincially, the lead content in coal exhibited considerable variation, ranging from 5.27 μg/g to 128.94 μg/g. When incorporating coal reserves in distinct regions as weighting factors, the weighted average lead content in Chinese coal was calculated to be 14.03 μg/g, exceeding the global average by over 80%, which has resulted in substantial atmospheric lead emissions through coal combustion in China. Among the sectors utilizing coal, industrial activities emerged as the foremost contributor to atmospheric lead emissions, accounting for over 90% of the overall release. Considering China's Dual-Carbon Policy, it is expected that lead emissions from coal consumption will decrease by 15%-20% from the peak in 2014 to 2030 but will still approach 10,000 tons. Considering various technologies and carbon emission targets based on China's published policies, the most optimistic emission reduction scenario envisions a decline in coal usage to 190 million tons by 2060, resulting in atmospheric lead emissions of a mere 517.01 tons—a noteworthy reduction to one-twentieth of the present level. Therefore, by controlling coal consumption, especially the use of coal in industrial production processes, and implementing pollution control measures, it is possible to effectively reduce atmospheric lead emissions in the near future under China's two-carbon goal.

Risk assessment of dietary perchlorate exposure in typical areas of fireworks manufacturing in China using a perchlorate intake model

Perchlorate can disrupt the production of thyroid hormones, impact metabolism, and even affect the cognitive development of infants and toddlers. Typical areas of fireworks manufacturing might face severe perchlorate pollution due to perchlorate is an important raw material. But related study has not been reported. We assess the risk caused by perchlorate and identify the critical exposure pathways for different age/gender groups in typical area of fireworks manufacturing. Liuyang city, a major fireworks manufacturing center in China, was selected as study region. Perchlorate concentrations were measured in 230 local food samples from Liuyang using LC/MS/MS. Risks for different age/gender groups were estimated using a perchlorate intake model. The detection rate of perchlorate in samples from all eight food groups, including vegetables, fruits, meat, seafood, egg, cereal, beans, and drinking water was 100%, and the perchlorate concentrations were higher than those reported in the United States, Canada, South Korea, Kuwait, and other regions of China. Liuyang residents are currently facing an extremely high perchlorate dietary exposure risk, with the mean Estimated Daily Intakes (EDIs) approximately 6–49 times higher than US EPA's recommended reference dose (RfD, 0.7 μg/kg bw/day), and 14–115 times higher than the tolerable daily intake (TDI, 0.3 μg/kg bw/day) established by EFSA. Breast milk and drinking water are identified as the primary exposure pathways for infants and toddlers under the age of two, contributing 44–86% and 13–41% to their total exposure, respectively. For individuals > two years, vegetable consumption (constituting 54–66% of exposures) and ingestion of drinking water (constituting 23–32% of exposures) represent the chief exposure routes. The Hazard Quotient (HQ) values for Liuyang City residents all exceed 2, indicating an extremely high non-carcinogenic risk associated with perchlorate. Scientific and systematic perchlorate pollution control measures should be taken by local government.

Assessing anthropogenic influences on the water quality of Gomati River using an innovative weighted fuzzy soft set based water pollution rating system

The increasing pollution of river systems poses a significant challenge to water quality management and public health. This study was conducted to evaluate the water quality of the Gomati River in India, focusing on the impact of anthropogenic activities on pollution levels across different seasons. The primary objective was to develop a comprehensive assessment model using an effective weighted fuzzy soft expert system (WFSES) to derive a weighted water pollution score (WWP-score) for rating water pollution levels based on various water quality parameters. To achieve this, we employed a fuzzy soft set (FSS) methodology integrated with a weighted fuzzy soft set (WFSS) model to analyze water quality indices at six sampling stations along the Gomati River, the largest river in Tripura, India. Originating from the Raima and Sarma streams, the river flows westward through key regions, providing 249.39 million cubic meters of water annually, essential for drinking, agriculture, fishing, and transportation. The study utilized crisp data summaries of key water quality parameters, including pH, total dissolved solids, total suspended solids, electrical conductivity, biochemical oxygen demand, dissolved oxygen, total hardness, chloride, total alkalinity, and total coliform, across the pre-monsoon, monsoon, and post-monsoon seasons from May 2022 to April 2023, guided by the distribution of waste discharge points. Fuzzy membership functions were defined for these parameters, and the root mean square (RMSQR) operation was used to combine multiple FSSs. The results revealed that the WWP-scores, a measure of water quality, ranged from 0.744 to 0.872 across the sampling stations, with Srimantapur exhibiting the highest level of pollution and Udaipur showing comparatively better quality. These scores indicate that water quality at all sites falls into the poor category, with Srimantapur experiencing the most severe contamination due to high levels of coliform bacteria and organic pollutants. The analysis highlights the impact of domestic wastewater and agricultural runoff on the river's health. This research offers a novel application of FSS and WFSS theory in environmental management, providing a robust framework for evaluating and ranking water quality across multiple parameters. The findings are valuable to the scientific community as they offer detailed insights into the pollution dynamics of the Gomati River and propose a methodological approach for assessing water quality in other river systems facing similar challenges. The study's results underscore the need for targeted pollution control measures and continuous monitoring to safeguard water resources and public health.

Impact of construction activities on the air quality of Agra city, Uttar Pradesh, India

The current research work was carried out to comprehensively assessed the impact of construction activities on the air quality. Seven sites were chosen along the metro line construction in Agra, Uttar Pradesh, India, to meet the study's goals. The monitoring was performed for 24 hours at each site using the respirable dust sampler (RDS) with a gaseous sampling attachment. The raw data was processed to calculate the Air Quality Index (AQI). The data obtained indicate that all the examined sites had PM10 (particulate matter having the diameter less than or equal to 10 micron) values above the National Ambient Air Quality Standards (NAAQ) values of 100 µg/m3, while SS-05 and SS-06 had PM2.5 (particulate matter having the diameter less than or equal to 2.5 micron) values above the NAAQ values of 60 µg/m3. Values of CO, SO2, and NO2 were discovered to be lower than the NAAQ standard limits. Because PM10's sub index (Si) was found to be the greatest across all locations, it was determined to be the criterion pollutant among all the metrics. Based on the AQI value, the research area's overall air quality was determined to be moderately polluted. At every location, a variety of management techniques, including mist guns, water spraying, and planting, are regularly used to reduce air pollution. Effective implementation of applied air pollution control measures is required to make the air clean and safe for breathing.

Assessing water quality and human health risk near coal mines and industrial area of Singrauli, India: special emphasis on toxic elements.

Water contamination is a major environmental issue, especially in rapidly growing industrialized areas like Singrauli. This study addresses research gaps regarding the hydrochemical characterization, health risk assessment, and source identification of contaminants. Hydrochemistry shows the concentrations of Na+, Ca2+, F-, Mn, As, Mo, Sr, and Ni were above the permissible limit for drinking usage. Water quality index (WQI), heavy metal pollution (HMPI), and evaluation indices (HMEI) revealed As, Mn, Cd, Mo, Co, and Ni were the key heavy elements contributing towards aqueous media pollution in the Singrauli area. Additionally, F was also considered one of the major contaminants. In health risk assessment, the higher values of hazard quotient (HQ) for non-carcinogens were associated with Mn, As, Mo, and F; and hazard index (HI) values > 1 were found in 70% and 55% of samples for children and adults, respectively. Carcinogenic risk (CR) for human health was associated with As. CR values in 56.7% (for adults) and 61.7% (for children) of the total samples exceeded 1 × 10-4. Monte Carlo simulation was applied and highlighted the significant risk factors responsible for both carcinogenic and non-carcinogenic health impacts. 19.2%, 7.3%, and 6.9% of the simulated HQ values for adults and 30.1%, 16.9%, and 10.6% for children were above the safe limit for F, As, and Mn, respectively. Additionally, only 43.8% and 24.8% of the simulated HI for adults and children were within the safe limit. Irrespective of age groups, all the simulated values of As in CR were above 1 × 10-6; and 60% (for adults) and 77.1% (for children) of the values were above 1 × 10-4. This outcome emphasizes the urgency of pollution control measures, especially for As, F, and Mn, to safeguard public health. Moreover, a multivariate statistical approach revealed that both geogenic and anthropogenic sources were responsible for contamination. Therefore, regular monitoring, filtration, and purification are mandatory to ensure safe drinking water for human consumption.