Natural background level, source apportionment and health risk assessment of potentially toxic elements in multi-layer aquifers of arid area in Northwest China.

Groundwater contaminated by potentially toxic elements has become an increasing global concern for human health. Therefore, it is crucial to identify the sources and health risks of potentially toxic elements, especially in arid areas. Despite the necessity, there is a notable research gap concerning the sources and risks of these elements within multi-layer aquifers in such regions. To address this gap, 54 phreatic and 24 confined groundwater samples were collected from an arid area in Northwest China. This study aimed to trace the sources and evaluate the human health risks of potentially toxic elements by natural background level (NBL), positive matrix factorization (PMF) model, and health risk model. Findings revealed exceeding levels of potentially toxic elements existed in phreatic and confined aquifers. Source apportionment and NBL results indicated that mineral dissolution, evaporation, redox reactions, and human activities were the main factors for elevated concentrations of potentially toxic elements. High Fe and Mn concentrations were attributed to reduction environments, while F accumulation resulted from slow runoff, and irrigation from the Yellow River. Due to high F levels, more than one-third of groundwater samples (phreatic: 33.14 %, confined: 56.22 %) posed non-carcinogenic health risks to population groups. Adults displayed higher carcinogenic risks (phreatic: 19.47 %, confined: 34.16 %) than infants (phreatic: 0 %, confined: 0 %) and children (phreatic: 1.26 %, confined: 7.97 %) owing to the toxic elements of Cr. The confined aquifer presented greater health risks than the phreatic aquifer. Consequently, controlling the levels of F and Cr in multi-layered aquifers is key to reducing health risks. These findings provide valuable insights into protecting groundwater from contamination by potentially toxic elements in multi-layered aquifers worldwide.

Spatial heterogeneity: Necessary and feasible for revealing soil trace elements pollution, sources, risks, and their links.

The source diversity and health risk of trace elements (TEs) in soil make it necessary to reveal the relationship between pollution, source, and risk. However, neglect of spatial heterogeneity restricts the reliability of existing identification methods. In this study, spatial heterogeneity is proposed as a necessary and feasible factor for accurately dissecting the pollution-source-risk link of soil TEs. A comprehensive framework is developed by integrating positive matrix factorization, Geodetector, and risk evaluation tools, and successfully applied in a mining-intensive city in northern China. Overall, the TEs are derived from natural background (28.5 %), atmospheric deposition (25.6 %), coal mining (21.8 %), and metal industry (24.1 %). The formation mechanism of heterogeneity for high-variance TEs (Se, Hg, Cd) is first systematically deciphered by revealing the heterogeneous source-sink relationship. Specifically, Se is dominated (76.5 %) by heterogeneous coal mining (q=0.187), Hg is determined (92.6 %) by the heterogeneity of metal mining (q=0.183) and smelting (q=0.363), and Cd is caused (50.9 %) by heterogeneous atmospheric deposition (q>0.254) co-influenced by the terrains and soil properties. Highly heterogeneous sources are also noteworthy for their potential to pose extreme risks (THI=1.122) in local areas. This study highlights the necessity of integrating spatial heterogeneity in pollution and risk assessment of soil TEs.

Source identification of heavy metals and metalloids in soil using open-source Tellus database and their impact on ecology and human health.

The presence of heavy metals and metalloids (metal(loid)s) in the food chain is a global problem, and thus, metal(loid)s are considered to be Potentially Toxic Elements (PTEs). Arsenic (As), lead (Pb), mercury (Hg), and cadmium (Cd) are identified as prominent hazards related to human health risks throughout the food chain. This study aimed to carry out a source attribution for metal(loid)s in shallow topsoil of north-midlands, northwest, and border counties of the Republic of Ireland, followed by an assessment of the potential ecological and human health risks. The positive Matrix Factorization (PMF) was used for source characterization of PTEs, followed by the Monte Carlo simulation method, used for a probabilistic model to evaluate potential human health risks. The mean concentrations of prioritized metal(loid)s in the topsoil range in the order of Pb (28.83 mg kg-1) > As (7.81 mg kg-1) > Cd (0.51 mg kg-1) > Hg (0.11 mg kg-1) based on the open-source Tellus dataset. This research identified three primary sources of metal(loid) pollution: geogenic sources (36 %), mixed sources of historical mining and natural origin (33 %), and anthropogenic activities (31 %). The ecological risk assessment showed that Ireland's soil exhibits low-moderate pollution levels however, concerns remain for Cd and As levels. All metal(loid)s except Cd showed acceptable non-carcinogenic risk, while Cd and As accounted for high to moderate potential cancer risks. Potato consumption (if grown on land with elevated metal(loid) levels), Cd concentration in soil, and bioaccumulation factor of Cd in potatoes were the three most sensitive parameters. In conclusion, metal(loid)s in Ireland present low to moderate ecological and human health risks. It underscores the need for policies and remedial strategies to monitor metal(loid) levels in agricultural soil regularly and the production of crops with low bioaccumulation in regions with elevated metal(loid) levels.

Long-term contributions of VOC sources and their link to ozone pollution in Bronx, New York City.

Changes in energy and environmental policies along with changes in the energy markets of New York State over the past two decades, have spurred interest in evaluating their impacts on emissions from various energy generation sectors. This study focused on quantifying these effects on VOC (volatile organic compounds) emissions and their subsequent impacts on air quality within the New York City (NYC) metropolitan area. NYC is an EPA nonattainment region for ozone (O3) and likely is a VOC limited region. NYC has a complex coastal topography and meteorology with low-level jets and sea/bay/land breeze circulation associated with heat waves, leading to summertime O3 exceedances and formation of secondary organic aerosol (SOA). To date, no comprehensive source apportionment studies have been done to understand the contributions of local and long-range sources of VOCs in this area. This study applied an improved Positive Matrix Factorization (PMF) methodology designed to incorporate atmospheric dispersion and photochemical reaction losses of VOCs to provide improved apportionment results. Hourly measurements of VOCs were obtained from a Photochemical Assessment Monitoring Station located at an urban site in the Bronx from 2000 to 2021. The study further explores the role of VOC sources in O3 and SOA formation and leverages advanced machine learning tools, XGBoost and SHAP algorithms, to identify synergistic interactions between sources and provided VOC source impacts on ambient O3 concentrations. Isoprene demonstrated a substantial influence in the source contribution of the biogenic factor, emphasizing its role in O3 formation. Notable contributions from anthropogenic emissions, such as fuel evaporation and various industrial processes, along with significant traffic-related sources that likely contribute to SOA formation, underscore the combined impact of natural and human-made sources on O3 pollution. Findings of this study can assist regulatory agencies in developing appropriate policy and management initiatives to control O3 pollution in NYC.

Source Apportionment and Human Health Risks of Potentially Toxic Elements in the Surface Water of Coal Mining Areas.

Contamination with potentially toxic elements (PTEs) frequently occurs in surface water in coal mining areas. This study analyzed 34 surface water samples collected from the Yunnan-Guizhou Plateau for their hydrochemical characteristics, spatial distribution, source apportionment, and human health risks. Our statistical analysis showed that the average concentrations of PTEs in the surface water ranked as follows: Fe > Al > Zn > Mn > Ba > B> Ni > Li > Cd > Mo > Cu > Co > Hg > Se > As > Pb > Sb. The spatial analysis revealed that samples with high concentrations of Fe, Al, and Mn were predominantly distributed in the main stream, Xichong River, and Yangchang River. Positive matrix factorization (PMF) identified four sources of PTEs in the surface water. Hg, As, and Se originated from wastewater discharged by coal preparation plants and coal mines. Mo, Li, and B originated from the dissolution of clay minerals in coal seams. Elevated concentrations of Cu, Fe, Al, Mn, Co, and Ni were attributed to the dissolution of kaolinite, illite, chalcopyrite, pyrite, and minerals associated with Co and Ni in coal seams. Cd, Zn, and Pb were derived from coal melting and traffic release. The deterministic health risks assessment showed that 94.12% of the surface water samples presented non-carcinogenic risks below the health limit of 1. Meanwhile, 73.56% of the surface water samples with elevated As posed level III carcinogenic risk to the local populations. Special attention to drinking water safety for children is warranted due to their lower metabolic capacity for detoxifying PTEs. This study provides insight for PTE management in sustainable water environments.

[Pollution Characteristics and Source Apportionment of Heavy Metals in Topsoil of Counties Along the Shandong Section of the Yellow River].

The 25 counties along the Shandong section of the Yellow River are the core areas for promoting the ecological protection and high-quality development of the Yellow River in Shandong Province. Moreover, it is of great significance to study the current situation, sources, and potential risks of heavy metal pollution in the topsoil in this region. In this study, 103 soil samples were collected from the 25 counties along the Shandong section of the Yellow River, and the contents of eight heavy metals （As, Cu, Pb, Cr, Zn, Ni, Cd, and Hg） were determined. The pollution characteristics of heavy metals were analyzed and evaluated using the geological accumulation index and potential ecological risk index. Correlation analysis and the positive matrix factorization （PMF） model were used to analyze the sources of heavy metals. The results showed that the average contents of Cu and Cr were lower than that of the background values of soils, whereas the average contents of As, Pb, Zn, Ni, Cd, and Hg were 1.16, 1.42, 1.05, 1.14, 2.29, and 1.85 times higher than that of the background values, respectively, and the average contents of all eight elements were lower than the screening value of soil pollution risk in agricultural land. In terms of different heavy metal variations, the coefficient of variation （CV） of Cu and Cd was higher than 0.500, indicating high variations, whereas As, Pb, Cr, Zn, Ni, and Hg showed moderate variation. Cd and Hg were slightly polluted, whereas the other six elements were not polluted. Cd and Hg had a moderate potential ecological risk level, whereas the other six elements were at a low level. Correlation analysis and PMF model showed that the sources of heavy metals in the study area were influenced by four factors, i.e., agricultural activities, natural sources, industrial emissions, and atmospheric dust from coal combustion and vehicle exhaust emissions, and the relative contribution rates were 32.4%, 34.9%, 16.5%, and 16.2%, respectively.

Pollution Characteristics of Heavy Metals in PM1 and Source-Specific Health Risks in the Tianjin Airport Community, China.

The airport and its surrounding areas are home to a variety of pollution sources, and air pollution is a recognized health concern for local populated regions. Submicron particulate matter (PM1 with an aerodynamic diameter of <1 mm) is a typical pollutant at airports, and the enrichment of heavy metals (HMs) in PM1 poses a great threat to human health. To comprehensively assess the source-specific health effects of PM1-bound HMs in an airport community, PM1 filter samples were collected around the Tianjin Binhai International Airport for 12 h during the daytime and nighttime, both in the spring and summer, and 10 selected HMs (V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, and Pb) were analyzed. The indicatory elements of aircraft emissions were certified as Zn and Pb, which accounted for more than 60% of the sum concentration of detected HMs. The health risks assessment showed that the total non-cancer risks (TNCRs) of PM1-bound HMs were 0.28 in the spring and 0.23 in the summer, which are lower than the safety level determined by the USEPA, and the total cancer risk (TCR) was 2.37 × 10-5 in the spring and 2.42 × 10-5 in the summer, implying that there were non-negligible cancer risks in the Tianjin Airport Community. After source apportionment with EF values and PMF model, four factors have been determined in both seasons. Consequently, the source-specific health risks were also evaluated by combining the PMF model with the health risk assessment model. For non-cancer risk, industrial sources containing high concentrations of Mn were the top contributors in both spring (50.4%) and summer (44.2%), while coal combustion with high loads of As and Cd posed the highest cancer risk in both seasons. From the perspective of health risk management, targeted management and control strategies should be adopted for industrial emissions and coal combustion in the Tianjin Airport Community.

Arsenic-contaminated groundwater of the Western Banat (Pannonian basin): Hydrogeochemical appraisal, pollution source apportionment, and Monte Carlo simulation of source-specific health risks.

Due to rapid urbanization and industrial growth, groundwater globally is continuously deteriorating, posing significant health risks to humans. This study employed a comprehensive methodology to analyze groundwater in the Western Banat Plain (Serbia). Using Piper and Gibbs plots, hydrogeochemistry was assessed, while the entropy-weighted water quality index (EWQI) was used to evaluate groundwater quality. Pollution sources were identified using positive matrix factorization (PMF) accompanied by Pearson correlation and hierarchical cluster analysis, while Monte Carlo simulation assessed health risks associated with groundwater consumption. Results showed that groundwater, mainly Ca-Mg-HCO3 type, is mostly suitable for drinking. Geogenic pollution, agricultural activities, and sewage were major pollution sources. Consumption of contaminated groundwater poses serious non-carcinogenic and carcinogenic health risks. Additionally, arsenic from geogenic source was found to be the main health risks contributor, considering its worryingly elevated concentration, ranging up to 364 µg/L. These findings will be valuable for decision-makers and researchers in managing groundwater vulnerability. PRACTITIONER POINTS: Groundwater is severely contaminated with As in the northern part of the study area. The predominant hydrochemical type of groundwater in the area is Ca-Mg-HCO3. The PMF method apportioned three groundwater pollution sources. Monte Carlo identified rock dissolution as the primary health risk contributor. Health risks and mortality in the study area are positively correlated.

[Characteristics and Source Analysis of VOCs Pollution During Emergency Response in Tianjin].

To elucidate the characteristics of VOCs chemical components during heavy pollution episodes, hourly online VOCs data derived from 11 heavy pollution events in Tianjin from 2019 to 2020 were employed. The positive matrix factorization （PMF） and conditional bivariate probability function （CBPF） were employed to analyze the sources of VOCs during heavy pollution episodes. The results indicated that the average VOCs volume fraction during these episodes was recorded at 35.7×10-9. Furthermore, it was observed that during the winter emergency response period, there was a discernible increase in the volume fraction of VOCs when compared to that during the autumn season. Specifically, there was a notable upswing of 48% in the olefins category, whereas alkanes registered a 4% increase. Additionally, the VOCs component structure changed significantly during the heavy pollution episodes. During the orange warning period, the proportion of alkanes increased by 36%, and the proportion of acetylene decreased by 32%. During the yellow warning period, the proportion of alkanes increased by 14%, and the proportion of acetylene decreased by 5%. During the emergency response period, motor vehicle emission sources, natural gas evaporative sources, and solvent use sources were the main contributors of VOCs in environmental receptors, contributing 17.5%, 15.4%, and 15.2%, respectively. Compared with that during the period antecedent to the emergency response, the contribution of vehicle emission sources and diesel volatile sources to VOCs in environmental receptors decreased by 2.0% to 5.5% and 2.1% to 6.6%, respectively, and the contribution of solvent use sources decreased by 0.2% to 2.4% during the yellow warning period. During the orange warning period, the contribution of motor vehicle emission sources was reduced by 0.1% to 8.3%, and the contribution of solvent use sources was reduced by 0.5% to 6.2%.

[Sensitivity Analysis of Atmospheric Ozone and Source Apportionment of Volatile Organic Compounds in Yinchuan City].

Based on the observation data of O3 concentration in Yinchuan in 2022, the monthly variation characteristics of O3 concentrations were analyzed. Further, based on the observation data of meteorological elements, conventional pollutants, and volatile organic compounds （VOCs） concentrations at an urban site in Yinchuan from May to July, the difference in meteorological elements and precursor concentrations between the polluted days and the non-polluted days were compared. Then, the O3 sensitivity and the VOCs sources were discussed using the Framework for 0-D Atmospheric Modeling （F0AM） and positive matrix factorization （PMF） model, respectively. The results showed that： ① The O3 pollution occurred from May to July in 2022, and the concentrations of O3-8h-90per were 156 µg·m-3, 170 µg·m-3, and 174 µg·m-3, respectively, with exceeding standard rates of 9.7%, 26.7%, and 29.0%, respectively. ② Compared with those on the non-polluted days, the hourly mean values of temperature, total solar radiation, and concentrations of various precursors on the O3-polluted days increased, including the volume concentrations of propane, isobutane, ethane, n-butane, and dichloromethane, which increased significantly by 33.1%, 29.1%, 25.0%, 22.7%, and 21.3%, respectively. The results showed that the combined increase in pollutant emissions and adverse meteorological conditions contributed to the formation of O3. ③ From May to July 2022, the top five VOCs species in terms of ozone formation potential （OFP） value on whole, non-polluted, and polluted days were the same. They were acetaldehyde, m/p-xylene, ethylene, isoprene, and toluene, mainly from solvent use sources, natural sources, and chemical industry emissions. ④ The local O3 production was mostly controlled by VOCs, and the relative incremental reactivity （RIR） results revealed that O3 production showed strong positive sensitivity to alkene and aromatic hydrocarbon but showed negative sensitivity to NOx on both polluted and non-polluted days. The relative contributions of active species such as acetone, ethylene, and isobutane to O3 production were high, and the implementation of an emission reduction scheme with the ratio of VOCs to NOx emission reduction much greater than 1 could effectively reduce the local O3 concentration. ⑤ The main sources of atmospheric VOCs in Yinchuan were motor vehicle emission sources （32.3%）, process sources （20.7%）, combustion sources （19.2%）, solvent use sources （12.7%）, gasoline volatile sources （9.1%）, and natural sources （6%）, and the contribution rate of motor vehicle emission sources on polluted days increased by 4.6% compared with that on non-polluted days, indicating that the motor vehicle emission source was an important object of summer VOCs control in Yinchuan.

[Analysis of Heavy Metal Sources in Farmland Soil of Sewage Irrigation and Industrial Complex Area Based on APCS-MLR and PMF].

The contents of eight heavy metals （Cr, Ni, Cu, Zn, Cd, Pb, As, and Hg） were determined based on the surface soil samples of sewage irrigation and industrial complex in Kaifeng City. The absolute factor analysis-multiple linear regression （APCS-MLR） model and positive matrix factorization （PMF） model were used to analyze the sources and contribution rates of heavy metals in soil combined with correlation analysis and systematic cluster analysis. The results showed that： ① The average values of ω（Cr）, ω（Ni）, ω（Cu）, ω（Zn）, ω（Cd）, ω（Pb）, ω（As）, and ω（Hg） in the study area were 52.19, 25.00, 42.03, 323.53, 1.79, 53.45, 9.43, and 0.20 mg·kg-1, respectively, and Cr, Ni, and As are lower than the background values of tidal soil. Cu, Zn, Cd, Pb, and Hg are higher than the background values of the tidal soil. ② There were four sources of the eight heavy metals： natural sources, agricultural sewage irrigation sources, industrial atmospheric sedimentation sources, and transportation sources. Cr and Ni were mainly from natural sources； Cu, Zn, Cd, and Pb were mainly from agricultural sewage irrigation and transportation sources； As was mainly from natural sources and agricultural sewage irrigation； and Hg was mainly from industrial atmospheric sedimentation. ③ The APCS-MLR and PMF source analysis results indicated that industrial and agricultural activities were the main sources of heavy metals in the soil of the study area. The average contribution rates of APCS-MLR in the nine sampling areas of the research area were 76.01% （natural sources and agricultural sewage irrigation sources）, 22.71% （industrial atmospheric sedimentation sources and transportation sources）, and 1.28% （unknown sources）. The average contribution rates of PMF were 59.66% （natural sources and agricultural sewage irrigation sources） and 40.34% （industrial atmospheric sedimentation sources and transportation sources）. The source analysis results of the LZ, XZ, NLT, PT, YLZ, and BC models were basically consistent, and WL was better in the APCS-MLR model, whereas SG and QT were better in the PMF model. The research results can provide a scientific basis for the prevention and control of soil heavy metal pollution and environmental remediation.

A study on source identification of contaminated soil with total petroleum hydrocarbons (aromatic and aliphatic) in the Ahvaz oil field.

The oil industry in Khuzestan province (Southwest Iran) is one of the main reasons contributing to the pollution of the environment in this area. TPH, including both aromatic and aliphatic compounds, are important parameters in creating pollution. The present study aimed to investigate the source of soil contamination by TPH in the Ahvaz oil field in 2022. The soil samples were collected from four oil centers (an oil exploitation unit, an oil desalination unit, an oil rig, and a pump oil center). An area outside the oil field was determined as a control area. Ten samples with three replicates were taken from each area according to the standard methods. Aromatic and aliphatic compounds were measured by HPLC and GC methods. The positive matrix factorization (PMF) model and isomeric ratios were used to determine the source apportionment of aromatic compounds in soil samples. The effects range low and effects range median indices were also used to assess the level of ecological risk of petroleum compounds in the soil samples. The results showed that Benzo.b.fluoranthene had the highest concentration with an average of 5667.7 ug/kg in soil samples in the Ahvaz oil field. The highest average was found in samples from the pump oil center area at 7329.48 ug/kg, while the lowest was found in control samples at 1919.4 ug/kg-1. The highest level of aliphatic components was also found in the pump oil center, with a total of 3649 (mg. Kg-1). The results of source apportionment of petroleum compounds in soil samples showed that oil activities accounted for 51.5% of the measured PAHs in soil. 38.3% of other measured compounds had anthropogenic origins, and only 10.1% of these compounds were of biotic origin. The results of the isomeric ratios also indicated the local petroleum and pyrogenic origin of PAH compounds, which is consistent with the PMF results. The analysis of ecological risk indices resulting from the release of PAHs in the environment showed that, except for fluoranthene, other PAHs in the oil exploitation unit area were above the effects range median level (ERM) and at high risk. The results of the study showed that soil pollution by total petroleum hydrocarbons (TPH), both aromatic and aliphatic, is at a high level, and is mainly caused by human activities, particularly oil activities.

Effects of seasonal management programs on PM2.5 in Seoul and Beijing using DN-PMF: Collaborative efforts from the Korea-China joint research.

South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 µg/m3, 34 %, Secondary sulfate: 5.67 µg/m3, 22 %, Motor vehicle: 1.83 µg/m3, 7.2 %, Biomass burning: 2.30 µg/m3, 9.1 %, Residual oil combustion: 1.66 µg/m3, 6.5 %, Industry: 2.15 µg/m3, 8.5 %, Incinerator: 1.39 µg/m3, 5.5 %, Coal combustion: 0.363 µg/m3, 1.4 %, Road dust/soil: 0.941 µg/m3, 3.7 %, Aged sea salt: 0.356 µg/m3, 1.4 %). The SMP significantly decreased PM2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 µg/m3, 28 %, Sulfate: 8.27 µg/m3, 18 %, Motor vehicle: 3.77 µg/m3, 8.4 %, Biomass burning: 2.70 µg/m3, 6.0 %, Incinerator: 4.50 µg/m3, 10 %, Coal combustion: 3.52 µg/m3, 7.8 %, Industry: 5.01 µg/m3, 11 %, Road dust/soil: 2.92 µg/m3, 6.5 %, Aged sea salt: 1.63 µg/m3, 3.6 %). Significant reductions in PM2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies.

Determining priority control factors for heavy metal management in urban road dust based on source-oriented probabilistic ecological-health risk assessment: A study in Xi'an during peak pollution season.

Urban road dust (URD) is essential for transporting heavy metals (HMs), which can be a major danger to both the environment and human health. Moreover, URD has the potential to be carried into bodies of water, leading to contamination of the aquatic ecosystem. A study was conducted in Xi'an, a city in northwestern China known for high air pollution levels, during January 2024 - a period characterized by peak pollution due to frequent low wind speeds and temperature inversions. The research investigated the presence of 10 types of HMs (Cu, Zn, Cd, Cr, Pb, As, Ni, Hg, Co, and Mn) in URD. Findings revealed elevated levels of Cu, Zn, Cd, Cr, Pb, As, and Hg in URD compared to background levels. Hg showed the most significant contamination (moderate to heavy), followed by moderate contamination of Cd, and lower levels of As, Zn, and Cu. The main sources of HMs were traffic (58.2%), mixed natural and industrial (30.3%), and industrial (11.5%). The ecological risk in the area was deemed to be very high, primarily because of Hg and Cd. Based on probabilistic health risk assessments, it was determined that non-carcinogenic risks were deemed acceptable for all groups. Nevertheless, the possibility of carcinogenic risks should not be disregarded. Strategies for controlling ecological-health risks prioritize mixed natural and industrial sources, with a focus on Hg, Cd, and As in URD. The results offer a foundation for policymakers to create specific control strategies.

Determination of contamination, source, and risk of potentially toxic metals in fine road dust in a karst region of Southwest China.

Understanding the pollution situation of potentially toxic metals (PTMs) in fine road dust (FRD) in emerging industrialized cities and identifying priority control factors is crucial for urban environmental management, resident health protection, and pollution control. This study conducted a comprehensive investigation on PTMs pollution in FRD in Zunyi, a representative emerging industrialized city in the karst region of southwestern China. The average contents of Ni, Cr, Mn, Cu, Zn, Ba, Pb, V, and Co in the FRD were 43.2, 127.0, 1232.1, 134.4, 506.6, 597.8, 76.1, 86.8, and 16.2 mg kg-1, respectively, which were obviously higher than the corresponding background levels of the local soil except for V and Co. The comprehensive pollution level of the determined PTMs in the FRD was very high, primarily caused by Zn and Cu. The sources of PTMs in Zunyi FRD were traffic, industrial, construction, and natural sources, accounting for 38.0, 23.7, 21.9, and 16.4% of the total PTMs content, respectively. The PTMs in Zunyi FRD exhibited a low to moderate overall ecological risk level, mainly contributed by Cu and traffic source. The cancer risks of PTMs in Zunyi FRD were high for all populations. The non-carcinogenic risk of PTMs in Zunyi FRD was acceptable for adults, but cannot be ignored for children. According to the source-specific probabilistic health risk estimation results, the priority control source is industrial source and the priority control PTM is Cr. Local governments need to give more attention to the carcinogenic risks and health hazards posed by PTMs in the FRD.

Chemical composition of cloud and rainwater at a high-altitude mountain site in western India: source apportionment and potential factors.

This study focuses on the chemical composition of cloud water (CW) and rainwater (RW) collected at Sinhagad, a high-altitude station (1450 m AMSL) located in the western region of India. The samples were collected during the monsoon over two years (2016-2017). The chemical analysis suggests that the concentration of total ionic constituents was three times higher in CW than in RW, except for NH4+ (1.0) and HCO3- (0.6). Compared to RW, high concentrations of SO42- and NO3- were observed in CW. The weighted average RW pH (6.5 ± 0.3) was slightly more alkaline than CW pH (6.1 ± 0.5). This can be attributed to the high concentrations of neutralizing ions such as nss-Ca2+, nss-Mg2+, K+, and NH4+, indicating the greater extent of wet scavenging during rainfall. These ions counteract the acidity generated by SO42- and NO3-. A high correlation between Ca2+, Na+, K+, NO3-, and SO42- makes it difficult to estimate the contribution of SO42- from different sources. Anthropogenic sulfur emissions and soil dust significantly influence the ionic composition of clouds and rain. Positive matrix factorization (PMF) was used to identify the contribution of different sources to the samples. In the CW, the extracted factors were cooking and vehicles, aging sea salt, agriculture, and dust. In RW, the factors were industries, cooking and vehicles, agriculture and dust, and aging sea salt. The findings of this study have significant implications for the monsoon build-up, ecosystems, agriculture, and climate change.

Characteristics and Source Apportionment of Volatile Organic Compounds in a Coastal Industrial Area: A Case Study in the Yangtze River Delta of China.

In recent years, the coastal area in East China has experienced elevated volatile organic compounds (VOCs) levels during specific periods. VOCs have become one of the major atmospheric pollutants in these areas. In this study, 64 compounds including alkanes, alkenes, halohydrocarbons, aromatics, and oxygenated VOCs (OVOCs) were obtained by the TO-15 method through a 12-month campaign in industrial, urban and suburban areas in the Yangtze River Delta of China. The overall trends of total VOC (TVOC) concentrations at eight sampling sites were as follows: winter > autumn > spring > summer. The proportion of VOC categories was various at industrial sites, while OVOCs and halohydrocarbons had high proportions at urban sites and suburban sites, respectively. Coating, vehicle emission, petrochemical source, industrial source, and gasoline volatilization were identified as the major VOC emission sources by the positive matrix factorization model. Petrochemical and coating sources were the prime VOC sources at industrial sites. Aromatics contributed the most ozone formation potential at industrial sites, while OVOCs provided the main contributions at both urban and suburban sites during four seasons. According to the health risk assessment, a high probability of non-carcinogenic risk existed at three industrial sites. Special attention should be given to certain VOCs, such as acrolein and 1,2-dibromoethane in industrial areas.

Quantitative stakeholder-driven assessment of radiation protection issues via a PIANOFORTE online survey.

To enhance stakeholder engagement and foster the inclusion of interests of citizens in radiation protection research, a comprehensive online survey was developed within the framework of the European Partnership PIANOFORTE. This survey was performed in 2022 and presented an opportunity for a wide range of stakeholders to voice their opinions on research priorities in radiation protection for the foreseeable future. Simultaneously, it delved into pertinent issues surrounding general radiation protection. The PIANOFORTE e-survey was conducted in the English language, accommodating a diverse range of participants. Overall, 440 respondents provided their insights and feedback, representing a broad geographical reach encompassing 29 European countries, as well as Canada, China, Colombia, India, and the United States. To assess the outcomes, the Positive Matrix Factorization numerical model was applied, in addition to qualitative and quantitative assessment of individual responses, enabling the discernment of four distinct stakeholder groups with varying attitudes. While the questionnaire may not fully represent all stakeholders due to the limited respondent pool, it is noteworthy that approximately 70% of the participants were newcomers to comparable surveys, demonstrating a proactive attitude, a strong willingness to collaborate and the necessity to continuously engage with stakeholder groups. Among the individual respondents, distinct opinions emerged particularly regarding health effects of radiation exposure, medical use of radiation, radiation protection of workers and the public, as well as emergency and recovery preparedness and response. In cluster analysis, none of the identified groups had clear preferences concerning the prioritization of future radiation protection research topics.

Distribution and source analysis of soil toxic organic compounds of coal-electricity production base in arid and semi-arid region of China.

The presence and distribution of toxic organic compounds in soil pose significant challenges. Whether their distributional characteristics are more complex, especially in arid and semi-arid regions with harsh climatic conditions? This study analyzed the composition, classification, spatial distribution, and sources of 123 toxic organic compounds in 56 soil samples of coal-electricity production base. Those compounds were classified into 11 categories, mainly pesticides (41 compounds), organic synthesis intermediates (31 compounds), and drugs (23 compounds). Seventeen of those compounds were detected over the rate of 30 %, with 13 of them being under the Toxic Substances Control Act (TSCA) inventory. The primary sources of toxic organic compounds were determined using Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF), including the degradation of pesticide residues (22.03 %), emissions of plastic pellets (16.64 %), industrial waste emissions (12.80 %), emissions from livestock (12.74 %), plastic films (11.22 %) and coal-to-liquid projects (10.78 %). This research underscores the widespread presence of toxic organic compounds in soil, highlighting their origins and distribution patterns, which are essential for developing targeted environmental management strategies in arid and semi-arid regions.

Typical emerging contaminants in sewage treatment plant effluent, and related watersheds in the Pearl River Basin: Ecological risks and source identification.

Emerging contaminants pose a potential risk to aquatic ecosystems in the Pearl River Basin, China, owing to the high population density and active industry. This study investigated samples from eight sewage treatment plants, and five surface water bodies of related watersheds. To screen the risk of emerging contaminants (ECs), and clarify their sources, this study calculated the risk quotient of detected chemical and performed source identification/apportionment using the positive matrix factorization method. In total, 149 organic pollutants were identified. Pharmaceuticals showed significant concentrations in sewage treatment plant samples (120.87 ng/L), compared with surface water samples (1.13 ng/L). The ecological risk assessment identified three chemicals with a heightened risk to aquatic organisms: fipronil sulfide, caffeine, and roxithromycin. Four principal sources of contaminants were identified: pharmaceutical wastewater, domestic sewage, medical effluent, and agricultural runoff. Pharmaceutical wastewater was the primary contributor (60.4 %), to the cumulative EC concentration and to ECs in sewage treatment plant effluent. Agricultural drainage was the main source of ECs in surface water. This study provides a strategy to obtain comprehensive information on the aquatic risks and potential sources of EC species in areas affected by artificial activities, which is of substantial importance to pollutant management and control.