Health risk assessment of PM2.5 heavy metals in county units of northern China based on Monte Carlo simulation and APCS-MLR

Identifying high-risk volatile organic compounds in residences of Chinese megacities: A comprehensive health-risk assessment

Indoor volatile organic compounds (VOCs) pose considerable health hazards. However, research on hazardous VOCs in Chinese residences has been conducted on a limited spectrum. This study used Monte Carlo simulations with data from Beijing, Shanghai, and Shenzhen to assess VOC health risks in Chinese homes. We identified high-risk VOCs and analyzed the impact of geographic location, age group, activity duration, and inhalation rate on VOC exposure, including lifetime risks. Formaldehyde, acrolein, naphthalene, and benzene posed the highest risks. Notably, acrolein made the leading contribution to non-cancer risks across all megacities. Naphthalene had elevated cancer and non-cancer risks in Shenzhen. This study highlights the need to investigate acrolein and naphthalene, which are currently unregulated but pose substantial health risks. The cumulative cancer risk (TCR) decreases from adults to children, while the cumulative non-cancer risk (HI) is higher for children. In all cities, the average TCR for adults exceeds the tolerable threshold of 10-4, and the average HI values surpass the safety threshold of 1. Nearly 100 % of the population faces a lifetime cancer risk above 10-4, and over 71 % face a non-cancer risk exceeding 10 (tenfold the benchmark). This study underscores the critical need for developing control strategies tailored to VOCs.

Assessment of health risks based on different populations and sources of heavy metals on agricultural lane in Tengzhou City by APCS-MLR models

To identify the sources of heavy metals in local soils and their risks to human health. This study quantified the concentrations of eight heavy metals in 504 soil samples collected in Tengzhou, China. The ecological risks of a single heavy metal (EI), a comprehensive ecological risk index (RI), and a health risk assessment model were used to evaluate the level of contamination in the city. The results of the research study indicate that there are different levels of heavy metal pollution in rural and urban agricultural areas in Tengzhou. Moreover, the spatial variability of mercury (Hg) is considerable, reaching 0.96, indicating a significant impact of anthropogenic activities. For the ecological risk, the heavy metal element with the highest EI value was mercury with a mean value of 67.22 and a peak value of 776.00. The heavy metal with the lowest mean EI value was Zn with only 1.03. Meanwhile, the average RI is only 128.59, but some areas have an RI as high as 842.2. The sources of heavy metals were identified using principal component analysis, correlation analysis, and an absolute principal component score multiple linear regression model (APCS-MLR). The non-carcinogenic risk for children, the carcinogenic risk for children, and the carcinogenic risk for adults were 1.23, 2.42×10-4 and 1.00×10-4, respectively, and these values exceeded their respective recommended values, and As and Cr had some carcinogenic hazards. Heavy metals in the soil come from natural, industrial, traffic and agricultural sources and represent 39.59%, 29.48%, 25.17% and 5.77%, respectively. The main source of heavy metals in local agricultural soils is the geological background, and the government needs to strengthen the monitoring of As and Cr in drinking water resources, as well as reduce traffic pollution and factory waste emissions to reduce Hg in soils.

Revealing the dual impact of VOCs on recycled rubber workers: Health risk and odor perception

Volatile organic compounds (VOCs) pose potential hazards to human health and contribute significantly to odor pollution. This study examined VOC emissions from a representative recycled rubber industry, evaluating the occupational health risks for frontline workers in various workshops. Variables such as gender and workshop-specific concentration variations were considered using Monte Carlo simulation methods. Employees in the five production workshops and office areas face noncarcinogenic health risks with hazard indices (HIs) greater than 1, with the rubber compounding phase presenting the highest risk. Acetaldehyde is identified as the primary noncarcinogenic health risk substance, with hazard quotient (HQ) values exceeding 1 in all workshops. Carcinogenic health risks vary by area, with the highest risks found in compounding and refining workshops. Formaldehyde poses the greatest risk in rubber grinding workshops and offices, with cumulative weights exceeding unacceptable levels of M80.58 % and W77.56 % in grinding and M94.98 % and W92.24 % in the office. Male workers face 4-7 % greater noncarcinogenic VOC health risks than females and 5-14 % greater carcinogenic risks from individual VOCs, increasing their susceptibility to health risks caused by VOCs. Additionally, our analysis of odor identification and intensity classification revealed that 53 VOCs are capable of causing odor pollution, with several substances reaching odor levels of 2 or higher. The predominant perceived odors, as reflected in the odor wheel, include categories such as "solvent/aromatic" and "sweet/fruit," with aldehydes being the primary odor-causing substances. In summary, emissions of VOCs from rubber industrial processes not only pose substantial health risks to workers but also contribute significantly to odor pollution. Consequently, enterprises must prioritize optimizing workplace conditions to ensure the occupational health and well-being of their employees.

Daily PM2.5 concentration prediction based on variational modal decomposition and deep learning for multi-site temporal and spatial fusion of meteorological factors

Air pollution, particularly PM2.5, has long been a critical concern for the atmospheric environment. Accurately predicting daily PM2.5 concentrations is crucial for both environmental protection and public health. This study introduces a new hybrid model within the "Decomposition-Prediction-Integration" (DPI) framework, which combines variational modal decomposition (VMD), causal convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM), and attention mechanism (AM), named as VCBA, for spatio-temporal fusion of multi-site data to forecast daily PM2.5 concentrations in a city. The approach involves integrating air quality data from the target site with data from neighboring sites, applying mathematical techniques for dimensionality reduction, decomposing PM2.5 concentration data using VMD, and utilizing Causal CNN and BiLSTM models with an attention mechanism to enhance performance. The final prediction results are obtained through linear aggregation. Experimental results demonstrate that the VCBA model performs exceptionally well in predicting daily PM2.5 concentrations at various stations in Taiyuan City, Shanxi Province, China. Evaluation metrics such as RMSE, MAE, and R2 are reported as 2.556, 1.998, and 0.973, respectively. Compared to traditional methods, this approach offers higher prediction accuracy and stronger spatio-temporal modeling capabilities, providing an effective solution for accurate PM2.5 daily concentration prediction.

Associations between atmospheric PM2.5 exposure and carcinogenic health risks: Surveillance data from the year of lowest recorded levels in Beijing, China

Scant research has pinpointed the year of minimum PM2.5 concentration through extensive, uninterrupted monitoring, nor has it thoroughly assessed carcinogenic risks associated with analyzing numerous components during this nadir in Beijing. This study endeavored to delineate the atmospheric PM2.5 pollution in Beijing from 2015 to 2022 and to undertake comprehensive evaluation of carcinogenic risks associated with the composition of atmospheric PM2.5 during the year exhibiting the lowest concentration. PM2.5 concentrations were monitored gradually in 9 districts of Beijing for 7 consecutive days per month from 2015 to 2022, and 32 kinds of PM2.5 components collected in the lowest PM2.5 concentration year were analyzed. This comprehensive dataset served as the basis for carcinogenic risk assessment using Monte Carlo simulation. And we applied the Positive Matrix Factorization (PMF) method to identity the sources of atmospheric PM2.5. Furthermore, we integrated this source appointment model with risk assessment model to discern the origins of these risks. The findings revealed that the annual average PM2.5 concentration in 2022 stood at 43.1 μg/m3, marking the lowest level recorded. The mean carcinogenic risks of atmospheric PM2.5 exposure calculated at 6.30E-6 (empirical 95% CI 1.09E-6 to 2.25E-5) in 2022. The PMF model suggested that secondary sources (35.4%), coal combustion (25.6%), resuspended dust (15.1%), biomass combustion (14.1%), vehicle emissions (7.1%), industrial emissions (2.0%) and others (0.7%) were the main sources of atmospheric PM2.5 in Beijing. The mixed model revealed that coal combustion (2.41E-6), vehicle emissions (1.90E-6) and industrial emissions (1.32E-6) were the main sources of carcinogenic risks with caution. Despite a continual decrease in atmospheric PM2.5 concentration in recent years, the lowest concentration levels still pose non-negligible carcinogenic risks. Notably, the carcinogenic risks associated with metals and metalloids exceeded that of PAHs. And the distribution of risk sources did not align proportionally with the distribution of PM2.5 mass concentration.

The concentration and probabilistic health risk assessment attribute to PAHs in indoor air of Hormozgan aluminum plant, Iran

We measured PAHs concentrations to understand the potential short and long-term health risks to workers. In the anode cooking area, the lowest and highest concentrations of PAHs were found for DahA (dibenzo[a,h]anthracene) at 0.373 ± 0.326 µg/m3 and Chry (chrysene) at 1.923 ± 1.258 µg/m3, respectively. In the anode-making area, these concentrations were higher, with DahA at 0.435 ± 0.221 µg/m3 and Chry peaking at 3.841 ± 1.702 µg/m3. Risk assessment based on these concentrations indicates a hierarchical order of individual PAHs risks in the anode cooking area, led by BaP (benzo[a]pyrene), followed by other specific PAHs compounds. The total hazard quotient (THQ) for PAH exposure in both anode-making and cooking areas significantly exceeds the threshold for considered cancer risk, emphasizing the considerable danger to workers. This study underscores the urgent need to mitigate exposure to PAHs in industrial settings to protect worker health from the carcinogenic risks of such hazardous compounds.

Quantitative Effects of Anthropogenic and Natural Factors on Heavy Metals Pollution and Spatial Distribution in Surface Drinking Water Sources in the Upper Huaihe River Basin in China

The water quality of sources in the Huaihe River Basin significantly affects the lives and health of approximately 16.7% of China's population. Identifying and quantifying pollution sources and risks is essential for effective water resource management. This study utilized Monte Carlo simulations and Geodetector to assess water quality and eutrophication, as well as to evaluate the sources of heavy metals and the associated health risks for both adults and children. The results showed that eutrophication of water sources in Huaihe River was severe, with an overall EI value of 37.92; 67.8% of the water sources were classified as mesotrophic and 32.2% classified as eutrophic. Water quality and eutrophication levels in the southern mountainous regions were better than those in the densely populated northern areas. Adults were found to have a higher carcinogenic risk than children, whereas children faced a higher noncarcinogenic risk than adults. Cr presented the highest carcinogenic risk, affecting more than 99.8% of both adults and children at levels above 1 × 10-6 but not exceeding 1 × 10-4. The noncarcinogenic risk from metals did not surpass a level of 1, except for Pb. As was primarily influenced by agricultural activities and transportation, whereas Cd, Cr, and Pb were mainly affected by industrial activities, particularly in local textile industries such as knitting and clothing manufacturing. The analysis demonstrated that the influence of anthropogenic factors on heavy metal distribution was significantly enhanced by indirect natural factors. For example, the explanatory power of Precipitation and Road Network Density on As was 0.362 and 0.189, respectively, whereas their interaction had an explanatory power as high as 0.673. This study indicates that the geodetector method is effective in elucidating the factors influencing heavy metal distribution in water, thereby providing valuable insights into pollution sources in global drinking water.

Assessment of the migration characteristics and source-oriented health risks of heavy metals in the soil and groundwater of a legacy contaminated by the chlor-alkali industry in central China

The chlor-alkali industry (CAI) is crucial for global chemical production; however, its operation has led to widespread heavy metal (HM) contamination at numerous sites, which has not been thoroughly investigated. This study analysed 122 soil and groundwater samples from a typical CAI site in Kaifeng, China. Our aim was to assess the ecological and health risks, identify the sources, and examine the migration characteristics of HMs at this site using Monte Carlo simulation, absolute principal component score-multiple linear regression (APCS-MLR), and the potential environmental risk index (Ei). Our findings revealed that the exceedance rates for Cd, Pb, Hg, and Ni were 71.96%, 45.79%, 49.59%, and 65.42%, respectively. Mercury (Hg) displayed the greatest coefficient of variation across all the soil layers, indicating a significant anthropogenic influence. Cd and Hg were identified as having high and extremely high potential environmental risk levels, respectively. The spatial distributions of the improved Nemerow index (INI), total ecological risk (Ri), and HM content varied considerably, with the most contaminated areas typically associated with the storage of raw and auxiliary materials. Surface aggregation and significant vertical transport were noted for HMs; As and Ni showed substantial accumulation in subsoil layers, severely contaminating the groundwater. Self-organizing maps categorized the samples into two different groups, showing strong positive correlations between Cd, Pb, and Hg. The APCS-MLR model suggested that industrial emissions were the main contributors, accounting for 60.3% of the total HM input. Elevated hazard quotient values for Hg posed significant noncarcinogenic risks, whereas acceptable levels of carcinogenic risk were observed for both adults (96.60%) and children (97.83%). This study significantly enhances historical CAI pollution data and offers valuable insights into ongoing environmental and health challenges.

To breathe or not to breathe: Inhalational exposure to heavy metals and related health risk

This study reviewed scientific literature on inhalation exposure to heavy metals (HMs) in various indoor and outdoor environments and related carcinogenic and non-carcinogenic risk. A systematic search in Web of Science, Scopus, PubMed, Embase, and Medline databases yielded 712 results and 43 articles met the requirements of the Population, Exposure, Comparator, and Outcomes (PECO) criteria. Results revealed that HM concentrations in most households exceeded the World Health Organization (WHO) guideline values, indicating moderate pollution and dominant anthropogenic emission sources of HMs. In the analyzed schools, universities, and offices low to moderate levels of air pollution with HMs were revealed, while in commercial environments high levels of air pollution were stated. The non-carcinogenic risk due to inhalation HM exposure exceeded the acceptable level of 1 in households, cafes, hospitals, restaurants, and metros. The carcinogenic risk for As and Cr in households, for Cd, Cr, Ni, As, and Co in educational environments, for Pb, Cd, Cr, and Co in offices and commercial environments, and for Ni in metros exceeded the acceptable level of 1 × 10-4. Carcinogenic risk was revealed to be higher indoors than outdoors. This review advocates for fast and effective actions to reduce HM exposure for safer breathing.

Comprehensive analysis of metal(loid)s and associated metal(loid) resistance genes in atmospheric particulate matter

Despite global concerns about metal(loid)s in atmospheric particulate matter (PM), the presence of metal(loid) resistance genes (MRGs) in PM remains unknown. Therefore, we conducted a comprehensive investigation of the metal(loid)s and associated MRGs in PMs in two seasons (summer and winter) in Xiamen, China. According to the geoaccumulation index (Igeo), most metal(loid)s, except for V and Mn, exhibited enrichment in PM, suggesting potential anthropogenic sources. By employing Positive Matrix Factorization (PMF) model, utilizing a dataset encompassing both total and bioaccessible metal(loid)s, along with backward trajectory simulations, traffic emissions were determined to be the primary potential contributor of metal(loid)s in summer, whereas coal combustion was observed to have a dominant contribution in winter. The major contributor to the carcinogenic risk of metal(loid)s in both summer and winter was predominantly attributed to coal combustion, which serves as the main source of bioaccessible Cr. Bacterial communities within PMs showed lower diversity and network complexity in summer than in winter, with Pseudomonadales being the dominant order. Abundant MRGs, including the As(III) S-adenosylmethionine methyltransferase gene (arsM), Cu(I)-translocating P-type ATPase gene (copA), Zn(II)/Cd(II)/Pb(II)-translocating P-type ATPase gene (zntA), and Zn(II)-translocating P-type ATPase gene (ziaA), were detected within the PMs. Seasonal variations were observed for the metal(loid) concentration, bacterial community structure, and MRG abundance. The bacterial community composition and MRG abundance within PMs were primarily influenced by temperature, rather than metal(loid)s. This research offers novel perspectives on the occurrence of metal(loid)s and MRGs in PMs, thereby contributing to the control of air pollution.

Insight Study of Trace Elements in PM2.5 During Nine Years in Delhi, India: Seasonal Variation, Source Apportionment, and Health Risks Assessment

This study investigated the concentrations, seasonal variations, sources, and human health risks associated with exposure to heavy elements (As, Al, Pb, Cr, Mn, Cu, Zn, and Ni) of PM2.5 at an urban location of Delhi (28° 38' N, 77° 10' E; 218 m amsl), India, from January 2013 to December 2021. The average mass concentration of PM2.5 throughout the study period was estimated as 127 ± 77 µg m-3, which is exceeding the National Ambient Air Quality Standards (NAAQS) limit (annual: 40 µg m-3; 24 h: 60 µg m-3). The seasonal mass concentrations of PM2.5 exhibited at the order of post-monsoon (192 ± 110 µgm-3) > winter (158 ± 70 µgm-3) > summer (92 ± 44 µgm-3) and > monsoon (67 ± 32 µgm-3). The heavy elements, Al (1.19 µg m-3), Zn (0.49 µg m-3), Pb (0.43 µg m-3), Cr (0.21 µg m-3), Cu (0.21 µg m-3), Mn (0.07 µg m-3), and Ni (0.14 µg m-3) exhibited varying concentrations in PM2.5, with the highest levels observed in the post-monsoon season, followed by winter, summer, and monsoon seasons. Six primary sources throughout the study period, contributing to PM2.5 were identified by positive matrix factorization (PMF), such as dust (paved/crustal/soil dust: 29.9%), vehicular emissions (17.2%), biomass burning (15.4%), combustion (14%), industrial emissions (14.2%), and Br-rich sources (9.2%). Health risk assessments, including hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR), were computed based on heavy elements concentrations in PM2.5. Elevated HQ values for Cr and Mn linked with adverse health impacts in both adults and children. High carcinogenic risk values were observed for Cr in both adults and children during the winter and post-monsoon seasons, as well as in adults during the summer and monsoon seasons. The combined HI value exceeding one suggests appreciable non-carcinogenic risks associated with the examined elements. The findings of this study provide valuable insights into the behaviour and risk mitigation of heavy elements in PM2.5, contributing to the understanding of air quality and public health in the urban environment of Delhi.

Risk assessment and source apportionment of available atmospheric heavy metal in a typical sandy area reservoir in Inner Mongolia, China

This study evaluated dry and wet deposition of atmospheric heavy metals (HMs) in a sandy area of Inner Mongolia, China, with the Dahekou Reservoir, Xilin Gol League, adopted as the study area. Monthly monitoring of atmospheric HM dry and wet deposition was conducted over one year (2021 to 2022) at 12 monitoring points, producing 144 dry and wet deposition samples, respectively. The sample contents of eight HMs (Cr, Ni, Pb, Cu, Zn, Mn, As, and Cd) were determined to estimate the fluxes of available forms of heavy metal (AHM) in dry and wet deposition. The potential ecological index (Eri), risk assessment coding (RAC), and ratio of secondary phase to primary phase (RSP) were used to evaluate the impact of atmospheric HM dry deposition on ecological security. Correlation analysis, principal component analysis, and the absolute principal component scores-multiple linear regression (APCS-MLR) receptor model were used to quantitatively analyze the sources of AHMs in atmospheric dry and wet deposition. The results showed that the study area experienced annual dry and wet deposition fluxes of AHMs of 1712.59 kg and 534.97 kg, respectively. Atmospheric heavy metal dry deposition over the entire year presented a strong ecological risk, with Cd contributing most to this risk. Risk assessment of HM speciation showed that the greatest risks of migration and transformation were for Cd and Pb. The APCS-MLR receptor model identified five and three sources of dry and wet deposition, respectively, in order of proportion of total contribution of: natural wind and sand > road traffic and coal combustion > mineral mining > other human activities > industrial soot.

Long- and short-term health benefits attributable to PM2.5 constituents reductions from 2013 to 2021: A spatiotemporal analysis in China

Long- and short-term exposure to constituents of fine particulate matter (PM2.5) substantially affects human health. However, assessments of the health and economic benefits of reducing PM2.5 constituents are scarce. This study estimates the number of premature deaths from all-cause, cardiovascular (CVD), and respiratory diseases avoided due to reductions in daily and annual average concentrations of PM2.5 constituents. The Environmental Benefits Mapping and Analysis Program was used for two scenarios: we used yearly concentrations of PM2.5 constituents from 2013 to 2020 as the baseline concentration surface (Scenario I), and 2021 as the baseline year (Scenario II). With reductions in daily and annual average concentrations of PM2.5 constituents, 309,099 (95 % confidence interval [CI]: 37,265-571,485) and 195,297 (95 % CI: 178,192-211,914) premature deaths were avoided in Scenario I, respectively; meanwhile, 347,296 (95 % CI: 79,258-604,758) and 201,567 (95 % CI: 185,038-217,530) premature deaths were avoided in Scenario II, respectively. Moreover, economic benefits associated with the prevention of premature deaths were estimated using the willingness to pay (WTP) and modified human capital (AHC) methods. The total estimated economic benefits amounted to 563.32 billion RMB (WTP) and 322.03 billion RMB (AHC) in Scenario I. In Scenario II, the associated economic benefits were 751.48 billion RMB (WTP) and 427.56 billion RMB (AHC), accounting for 0.657 and 0.374 % of China's gross domestic product in 2021, respectively. Additionally, we analyzed the sensitivity of CVD-related premature deaths to the concentrations of PM2.5 constituents, and found that CVD-related premature deaths were more sensitive to black carbon.

Establishing an emission inventory for ammonia, a key driver of haze formation in the southern North China plain during the COVID-19 pandemic

Despite the significant reduction in atmospheric pollutant levels during the COVID-19 lockdown, the presence of haze in the North China Plain remained a frequent occurrence owing to the enhanced formation of secondary inorganic aerosols under ammonia-rich conditions. Quantifying the increase or decrease in atmospheric ammonia (NH3) emissions is a key step in exploring the causes of the COVID-19 haze. Historic activity levels of anthropogenic NH3 emissions were collected through various yearbooks and studies, an anthropogenic NH3 emission inventory for Henan Province for 2020 was established, and the variations in NH3 emissions from different sources between COVID-19 and non-COVID-19 years were investigated. The validity of the NH3 emission inventory was further evaluated through comparison with previous studies and uncertainty analysis from Monte Carlo simulations. Results showed that the total NH3 emissions gradually increased from north-west to south-east, totalling 751.80 kt in 2020. Compared to the non-COVID-19 year of 2019, the total NH3 emissions were reduced by approximately 4 %, with traffic sources, waste disposal and biomass burning serving as the sources with the top three largest reductions, approximately 33 %, 9.97 % and 6.19 %, respectively. Emissions from humans and fuel combustion slightly increased. Meanwhile, livestock waste emissions decreased by only 3.72 %, and other agricultural emissions experienced insignificant change. Non-agricultural sources were more severely influenced by the COVID-19 lockdown than agricultural sources; nevertheless, agricultural activities contributed 84.35 % of the total NH3 emissions in 2020. These results show that haze treatment should be focused on reducing NH3, particularly controlling agricultural NH3 emissions.

Exposure to air pollution and gains in body weight and waist circumference among middle-aged and older adults

INTRODUCTION

Emerging research suggested a nexus between air pollution exposure and risks of overweight and obesity, while existing longitudinal evidence was extensively sparse, particularly in densely populated regions. This study aimed to quantify concentration-response associations of changes in weight and waist circumference (WC) related to air pollution in Chinese adults.

METHODS

We conceived a nationally representative longitudinal study from 2011 to 2015, by collecting 34,854 observations from 13,757 middle-aged and older adults in 28 provincial regions of China. Participants' height, weight and WC were measured by interviewers using standardized devices. Concentrations of major air pollutants including fine particulate matter (PM_2.5), nitrogen dioxide (NO₂) and ozone (O₃) predicted by well-validated spatiotemporal models were assigned to participants according to their residential cities. Possible exposure biases were checked through 1000 random simulated exposure at individual level, using a Monte Carlo simulation approach. Linear mixed-effects models were applied to estimate the relationships of air pollution with weight and WC changes, and restricted cubic spline functions were adopted to smooth concentration-response (C-R) curves.

RESULTS

Each 10-μg/m³ rise in PM_2.5, NO₂ and O₃ was associated with an increase of 0.825 (95% confidence interval: 0.740, 0.910), 0.921 (0.811, 1.032) and 1.379 (1.141, 1.616) kg in weight, respectively, corresponding to WC gains of 0.688 (0.592, 0.784), 1.189 (1.040, 1.337) and 0.740 (0.478, 1.002) cm. Non-significant violation for linear C-R relationships was observed with exception of NO₂-weight and PM_2.5/NO₂-WC associations. Sex-stratified analyses revealed elevated vulnerability in women to gain of weight in exposure to PM_2.5 and NO₂. Sensitive analyses largely supported our primary findings via assessing exposure estimates from 1000 random simulations, and performing reanalysis based on non-imputed covariates and non-obese participants, as well as alternative indicators (i.e., body mass index and waist-to-height ratio).

CONCLUSIONS

We found positively robust associations of later-life exposure to air pollutants with gains in weight and WC based on a national sample of Chinese adult men and women. Our findings suggested that mitigation of air pollution may be an efficient intervention to relieve obesity burden.

Health risk assessment of heavy metals in road dust from the fourth-tier industrial city in central China based on Monte Carlo simulation and bioaccessibility

Health risks caused by heavy metal (HM) exposure in road dust has attracted extensive attention, but few studies have focused on the health risks of residents living in small- and medium-sized cities with rapid industrialization and urbanization. Thus, 140 road dust samples were collected across Anyang, a typical fourth-tier industrial city in central China, which were analysed for 10 different HMs (Mn, Zn, Pb, V, Cr, As, Cd, Ni, Cu and Co). Monte Carlo simulation and bioaccessibility were used to quantify the health risks of heavy metals comprehensively in road dust. Results revealed a remarkable accumulation of Mn, Zn, Pb, Cd and Cu. According to the Geo-accumulation index and potential ecological risk index, Cd was priority control pollutant. Moreover, 55.0% of the road dust samples reached heavily polluted level, and 52.86% of the samples were at high ecological risk levels. These results illustrated that HM contamination was serious and universal in the road dust of Anyang. The occurrences of HMs were allocated to traffic emissions, natural sources, industrial activities and agricultural activities with contribution rates of 35.4%, 6.0%, 41.6% and 17.0%, respectively. Except for Zn in the gastric phase, all other HMs had relatively low bioaccessibilities in the gastrointestinal system, usually less than 20%. The bioaccessibilities of most HMs were higher in the gastric phase, except for Cr, Ni and Cu, which remained higher in the intestinal phase. The non-carcinogenic risk and carcinogenic risk were remarkably reduced when considering the HM bioaccessibilities in the gastrointestinal system, especially for adults. The outcomes of this paper are valuable for understanding HM contamination in road dust and highlight the importance of risk assessment for populations living in the fourth- and fifth-tier cities.

Fine particulate matter (PM2.5) trends from land surface changes and air pollution policies in China during 1980-2020

High levels of fine particulate matter (PM_2.5) pose a severe air pollution challenge in China. Both land use changes and anthropogenic emissions can affect PM2.5 concentrations. Only a few studies have addressed the long-term impact of land surface changes on PM2.5 in China. We conducted a comprehensive analysis of PM_2.5 trends over China using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) during 1980-2020. The monthly mean PM_2.5 concentrations of MERRA-2 were evaluated across mainland China against independent surface measurements from 2013 to 2020, showing a good agreement. For the trend analysis, China was subdivided into six regions based on land use and ambient aerosols types. Our results indicate an overall significant PM_2.5 increase over China during 1980-2020 with major changes in-between. Notwithstanding continued urbanization and associated anthropogenic activities, the PM_2.5 reversed to a downward trend around 2007 over most regions except for the part of China that is most affected by desert dust. Statistical analysis suggests that PM_2.5 trends during 1980-2010 were associated with urban expansion and deforestation over eastern and southern China. The trend reversal around 2007 is mainly attributed to Chinese air pollution control measures. A multiple linear regression analysis reveals that PM_2.5 variability is linked to soil moisture and vegetation. Our results suggest that land use and land cover changes as well as pollution controls strongly influenced PM_2.5 trends and that drought conditions affect PM_2.5 particularly over desert and forest regions of China. This work contributes to a better understanding of the changes in PM_2.5 over China.