Air quality, metal(loid) sources identification and environmental assessment using (bio)monitoring in the former mining district of Salsigne (Orbiel valley, France).

The former mining district of Salsigne is situated in the Orbiel valley. Until the 20th century, it was the first gold mine in Europe and the first arsenic mine in the world. Rehabilitation has been performed during the 20 years that followed closure of the mines and factories, which led to the accumulation of storage of several million tons of waste in this valley. Nevertheless, a detailed description of the air quality of this area is still missing. The goal of the present study is to evaluate atmospheric contamination in the valley and identify the potential sources of this contamination. Active monitors (particulate matter samplers) and passive bioindicators (Tillandsia usneoides) were placed in strategic sites including remote areas. Over the year 2022, we assessed the air quality using microscopic and spectroscopic techniques, as well as environmental risk indicators to report the level of contamination. Results indicate that the overall air quality in the valley is good with PM10 levels in accordance with EU standards. Elemental concentrations in the exposed plants were lower than reported in the literature. Among the different sites studied, Nartau and La Combe du Saut, corresponding to waste storage and former mining industry sites, were the most affected. Chronic exposure over 1 year was highlighted for Fe, Ni, Cu, Pb, Sb and As. Pollution Load Index and Enrichment Factors, which provided valuable information to assess the environmental condition of the valley's air, suggested that dust and resuspension of anthropogenic materials were the principle sources for most of the elements. Finally, this study also highlights that using T. usneoides could be a convenient approach for biomonitoring of metal (loid)-rich particles in the atmosphere within a former mining area, for at least one year. These results in turn allow to better understand the effects of chronic exposure on the ecosystem.

Indoor sulfur dioxide prediction through air quality modeling and assessment of sulfur dioxide and nitrogen dioxide levels in industrial and non-industrial areas.

In this study, the levels of sulfur dioxide (SO2) and nitrogen dioxide (NO2) were measured indoors and outdoors using passive samplers in Tymar village (20 homes), an industrial area, and Haji Wsu (15 homes), a non-industrial region, in the summer and the winter seasons. In comparison to Haji Wsu village, the results showed that Tymar village had higher and more significant mean SO2 and NO2 concentrations indoors and outdoors throughout both the summer and winter seasons. The mean outdoor concentration of SO2 was the highest in summer, while the mean indoor NO2 concentration was the highest in winter in both areas. The ratio of NO2 indoors to outdoors was larger than one throughout the winter at both sites. Additionally, the performance of machine learning (ML) approaches: multiple linear regression (MLR), artificial neural network (ANN), and random forest (RF) were compared in predicting indoor SO2 concentrations in both the industrial and non-industrial areas. Factor analysis (FA) was conducted on different indoor and outdoor meteorological and air quality parameters, and the resulting factors were employed as inputs to train the models. Cross-validation was applied to ensure reliable and robust model evaluation. RF showed the best predictive ability in the prediction of indoor SO2 for the training set (RMSE = 2.108, MAE = 1.780, and R2 = 0.956) and for the unseen test set (RMSE = 4.469, MAE = 3.728, and R2 = 0.779) values compared to other studied models. As a result, it was observed that the RF model could successfully approach the nonlinear relationship between indoor SO2 and input parameters and provide valuable insights to reduce exposure to this harmful pollutant.

Confounder-dependent Bayesian mixture model: Characterizing heterogeneity of causal effects in air pollution epidemiology.

Several epidemiological studies have provided evidence that long-term exposure to fine particulate matter (pm2.5) increases mortality rate. Furthermore, some population characteristics (e.g., age, race, and socioeconomic status) might play a crucial role in understanding vulnerability to air pollution. To inform policy, it is necessary to identify groups of the population that are more or less vulnerable to air pollution. In causal inference literature, the group average treatment effect (GATE) is a distinctive facet of the conditional average treatment effect. This widely employed metric serves to characterize the heterogeneity of a treatment effect based on some population characteristics. In this paper, we introduce a novel Confounder-Dependent Bayesian Mixture Model (CDBMM) to characterize causal effect heterogeneity. More specifically, our method leverages the flexibility of the dependent Dirichlet process to model the distribution of the potential outcomes conditionally to the covariates and the treatment levels, thus enabling us to: (i) identify heterogeneous and mutually exclusive population groups defined by similar GATEs in a data-driven way, and (ii) estimate and characterize the causal effects within each of the identified groups. Through simulations, we demonstrate the effectiveness of our method in uncovering key insights about treatment effects heterogeneity. We apply our method to claims data from Medicare enrollees in Texas. We found six mutually exclusive groups where the causal effects of pm2.5 on mortality rate are heterogeneous.

Global quantification of emerging and legacy per- and polyfluoroalkyl substances in indoor dust: Levels, profiles and human exposure.

This study investigated the occurrence and distribution of per- and polyfluoroalkyl substances (PFASs) in house dust samples from six regions across four continents. PFASs were detected in all indoor dust samples, with total median concentrations ranging from 17.3 to 197 ng/g. Among the thirty-one PFAS analytes, eight compounds, including emerging PFASs, exhibited high detection frequencies in house dust from all six locations. The levels of PFASs varied by region, with higher concentrations found in Adelaide (Australia), Tianjin (China), and Carbondale (United States, U.S.). Moreover, PFAS composition profiles also differed among regions. Dust from Australia and the U.S. contained high levels of 6:2 fluorotelomer phosphate ester (6:2 diPAP), while perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) were predominant in other regions. Furthermore, our results indicate that socioeconomic factors impact PFAS levels. The assessment of human exposure through dust ingestion and dermal contact indicates that toddlers may experience higher exposure levels than adults. However, the hazard quotients of PFASs for both toddlers and adults were below one, indicating significant health risks are unlikely. Our study highlights the widespread occurrence of PFASs in global indoor dust and the need for continued monitoring and regulation of these chemicals.

[Pollution Characteristics, Source, and Health Risk Assessment of Metal Elements in PM2.5 Between Winter and Spring in Zhengzhou].

A total of 18 metal elements in ambient PM2.5 in Zhengzhou were continuously determined using an online heavy metal observation instrument in January and April, 2021, and the changes in element concentrations were analyzed. Metal elements were traced via enrichment factors, positive matrix factorization (PMF), and a characteristic radar chart. The US EPA health risk assessment model was used to assess the health risks of heavy metals, and the backward trajectory method and the concentration-weighted trajectory (CWT) method were used to evaluate the potential source regions of health risks. The results showed that the element concentrations were higher in spring, and the sum of Fe, Ca, Si, and Al concentrations accounted for 89.8% and 87.5% of the total element concentrations in winter and spring, respectively. Cd was enriched significantly, which was related to human activities. The concentrations of Pb, Se, Zn, Ni, Sb, and K in winter and Cr, Ni, Fe, Mn, V, Ba, Ca, K, Si, and Al in spring increased with the increasing pollution level. The results of PMF and the characteristic radar chart showed that the main sources of metal elements in winter and spring were industry, crust, motor vehicles, and mixed combustion, with industry and mixed combustion pollution occurring more often in winter and crust pollution occurring more often in spring. Significant non-carcinogenic risks existed in both winter and spring with more severe health risks in winter, and Mn caused significant non-carcinogenic risks. The health risks in winter were mainly influenced by Zhengzhou and surrounding cities and long-distance transport in the northwest, and the health risks in spring were mainly influenced by Zhengzhou and surrounding cities.

[Spatial and Temporal Distribution Characteristics of Ozone Concentration and Health Benefit Assessment in the Beijing-Tianjin-Hebei Region from 2015 to 2020].

To evaluate the spatial and temporal distribution characteristics of ambient ozone (O3) in the Beijing-Tianjin-Hebei (BTH) Region, the land use regression (LUR) model and random forest (RF) model were used to simulate the ambient O3 concentration from 2015 to 2020. Meanwhile, all-cause, cardiovascular, and respiratory mortalities as well as economic losses attributed to O3 were also estimated. The results showed that upward trends with fluctuation were observed for ambient O3 concentration, mortalities, and economic losses attributable to O3 exposure in the BTH Region from 2015 to 2020. The areas with high O3 concentration and great changes were concentrated in the central and southwestern regions, whereas the concentration in the northern region was low, and the change degree was small. The spatial distribution of the mortalities was also consistent with the spatial distribution of O3 concentration. From 2015 to 2020, the economic losses regarding all-cause mortality and cardiovascular mortality increased in 13 cities of the BTH Region, whereas the economic losses of respiratory mortality decreased in 4 cities in the BTH Region. The results indicated that the priority areas for O3 control were not uniform. Specifically, Beijing, Tianjin, Hengshui, and Xingtai were vital areas for O3 pollution control in the BTH Region. Differentiated control measures should be adopted based on the characteristics of these target areas to decline O3 concentration and reduce health impacts and economic losses associated with O3 exposure.

Characterization of VOC emissions and health risk assessment in the plastic manufacturing industry.

Volatile organic compounds (VOCs) significantly contribute to ozone pollution formation, and many VOCs are known to be harmful to human health. Plastic has become an indispensable material in various industries and daily use scenarios, yet the VOC emissions and associated health risks in the plastic manufacturing industry have received limited attention. In this study, we conducted sampling in three typical plastic manufacturing factories to analyze the emission characteristics of VOCs, ozone formation potential (OFP), and health risks for workers. Isopropanol was detected at relatively high concentrations in all three factories, with concentrations in organized emissions reaching 322.3 µg/m3, 344.8 µg/m3, and 22.6 µg/m3, respectively. Alkanes are the most emitted category of VOCs in plastic factories. However, alkenes and oxygenated volatile organic compounds (OVOCs) exhibit higher OFP. In organized emissions of different types of VOCs in the three factories, alkenes and OVOCs contributed 22.8%, 67%, and 37.8% to the OFP, respectively, highlighting the necessity of controlling them. The hazard index (HI) for all three factories was less than 1, indicating a low non-carcinogenic toxic risk; however, there is still a possibility of non-cancerous health risks in two of the factories, and a potential lifetime cancer risk in all of the three factories. For workers with job tenures exceeding 5 years, there may be potential health risks, hence wearing masks with protective capabilities is necessary. This study provides evidence for reducing VOC emissions and improving management measures to ensure the health protection of workers in the plastic manufacturing industry.

Assessment of the health impacts of air pollution exposure in East African countries.

The health effects of air pollution remain a public concern worldwide. Using data from the Global Burden of Disease 2019 report, we statistically analyzed total mortality, disability-adjusted life years (DALY), and years of life lost (YLL) attributable to air pollution in eight East African countries between 1990 and 2019. We acquired ambient ozone (O3), PM2.5 concentrations and household air pollution (HAP) from the solid fuel from the State of Global Air report. The multilinear regression model was used to evaluate the predictability of YLLs by the air pollutants. We estimated the ratio rate for each health burden attributable to air pollution to compare the country's efforts in the reduction of air pollution health burden. This study found that the total number of deaths attributable to air pollution decreased by 14.26% for 30 years. The drop came from the reduction of 43.09% in mortality related to Lower Respiratory tract Infection (LRI). However, only five out of eight countries managed to decrease the total number of deaths attributable to air pollution with the highest decrease observed in Ethiopia (40.90%) and the highest increase in Somalia (67.49%). The linear regression model showed that HAP is the pollutant of the most concern in the region, with a 1% increase in HAP resulting in a 31.06% increase in regional YLL (R2 = 0.93; p < 0.05). With the increasing ground-level ozone, accompanied by the lack of adequate measures to reduce particulate pollutants, the health burdens attributable to air pollution are still a threat in the region.

Ambient air concentrations of plant protection products: Data collection for the combined air concentration database and associated risk assessment.

CropLife Europe collected literature values from monitoring studies measuring air concentrations of Plant Protection Products (PPPs) that may be inhaled by humans located in rural areas but not immediately adjacent to PPP applications. The resulting "Combined Air Concentration Database" (CACD) was used to determine whether air concentrations of PPPs reported by the French "Agency for Food, Environmental and Occupational Health & Safety" (ANSES) are consistent with those measured by others to increase confidence in values of exposure to humans. The results were put into risk assessment context. Results show that 25-90% of samples do not contain measurable PPP concentrations. Measured respirable fractions were below EU default air concentrations used for risk assessment for resident exposure by the European Food Safety Authority. All measured exposures in the CACD were also below established toxicological endpoints, even when considering the highest maximum average reported concentrations and very conservative inhalation rates. The highest recorded air concentration was for prosulfocarb (0.696 µg/m³ measured over 48 h) which is below the EFSA default limit of 1 µg/m³ for low volatility substances. In conclusion, based on the CACD, measured air concentrations of PPPs are significantly lower than EFSA default limits and relevant toxicological reference values.

Household air pollution and attributable burden of disease in rural China: A literature review and a modelling study.

Household air pollution prevails in rural residences across China, yet a comprehensive nationwide comprehending of pollution levels and the attributable disease burdens remains lacking. This study conducted a systematic review focusing on elucidating the indoor concentrations of prevalent household air pollutants-specifically, PM2.5, PAHs, CO, SO2, and formaldehyde-in rural Chinese households. Subsequently, the premature deaths and economic losses attributable to household air pollution among the rural population of China were quantified through dose-response relationships and the value of statistical life. The findings reveal that rural indoor air pollution levels frequently exceed China's national standards, exhibiting notable spatial disparities. The estimated annual premature mortality attributable to household air pollution in rural China amounts to 966 thousand (95% CI: 714-1226) deaths between 2000 and 2022, representing approximately 22.2% (95% CI: 16.4%-28.1%) of total mortality among rural Chinese residents. Furthermore, the economic toll associated with these premature deaths is estimated at 486 billion CNY (95% CI: 358-616) per annum, constituting 0.92% (95% CI: 0.68%-1.16%) of China's GDP. The findings quantitatively demonstrate the substantial disease burden attributable to household air pollution in rural China, which highlights the pressing imperative for targeted, region-specific interventions to ameliorate this pressing public health concern.

Health assessment of emerging persistent organic pollutants (POPs) in PM2.5 in northern and central Taiwan.

Over the last two decades, Taiwan has effectively diminished atmospheric concentrations of polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) through the adept utilization of advanced technologies and the implementation of air pollution control devices. Despite this success, there exists a dearth of data regarding the levels of other PM2.5-bound organic pollutants and their associated health risks. To address this gap, our study comprehensively investigates the spatial and seasonal variations, potential sources, and health risks of PCDD/Fs, Polychlorinated biphenyls (PCBs), and Polychlorinated naphthalene (PCNs) in Northern and Central Taiwan. Sampling collections were conducted at three specific locations, including six municipal waste incinerators in Northern Taiwan, as well as a traffic and an industrial site in Central Taiwan. As a result, the highest mean values of PM2.5 (20.3-39.6 µg/m3) were observed at traffic sites, followed by industrial sites (14.4-39.3 µg/m3), and the vicinity of the municipal waste incinerator (12.4-29.4 µg/m3). Additionally, PCDD/Fs and PCBs exhibited discernible seasonal fluctuations, displaying higher concentrations in winter (7.53-11.9 and 0.09-0.12 fg I-TEQWHO/m3) and spring (7.02-13.7 and 0.11-0.16 fg I-TEQWHO/m3) compared to summer and autumn. Conversely, PCNs displayed no significant seasonal variations, with peak values observed in winter (0.05-0.10 fg I-TEQWHO/m3) and spring (0.03-0.08 fg I-TEQWHO/m3). Utilizing a Positive Matrix Factorization (PMF) model, sintering plants emerged as the predominant contributors to PCDD/Fs, constituting 77.9% of emissions. Woodchip boilers (68.3%) and municipal waste incinerators (21.0%) were identified as primary contributors to PCBs, while municipal waste incinerators (64.6%) along with a secondary copper and a copper sludge smelter (22.1%) were the principal sources of PCNs. Moreover, the study specified that individuals aged 19-70 in Northern Taiwan and those under the age of 12 years in Central Taiwan were found to have a significantly higher cancer risk, with values ranging from 9.26 x 10-9-1.12 x 10-7 and from 2.50 x 10-8-2.08 x 10-7respectively.

Laboratory and field evaluation of a low-cost optical particle sizer.

Low-cost sensors are widely used to collect high-spatial-resolution particulate matter data that traditional reference monitoring devices cannot. In addition to the mass concentration, the number concentration and size distribution are also fundamental in determining the origin and hazard level of particulate pollution. Therefore, low-cost optical sensors have been improved to establish optical particle sizers (OPSs). In this study, a low-cost OPS, the Nova SDS029, is introduced, and it is evaluated in comparison to two reference instruments-the GRIMM 11-D and the TSI 3330. We first tested the sizing accuracy using polystyrene latex spheres. Then, we assessed the mass and number size distribution accuracy in three application scenarios: indoor smoking, ambient air quality, and mobile monitoring. The evaluations suggest that the low-cost SDS029 rivals research-grade optical sizers in many aspects. For example, (1) the particle diameters obtained with the SDS029 are close to the reference instruments (usually < 10%) in the 0.3-5 µm range; (2) the number of particles and mass concentration are highly correlated (r ≥ 0.99) with the values obtained with the reference instruments; and (3) the SDS029 slightly underestimates the number concentration, but the derived PM2.5 values are closer to monitoring station than the reference instruments. The successful application of the SDS029 in multiple scenarios suggests that a plausible particle size distribution can be obtained in an easy and cost-efficient way. We believe that low-cost OPSs will increasingly be used to map the sources and risk levels of particles at the city scale.

Is model-estimated PM2.5 exposure equivalent to station-observed in mortality risk assessment? A literature review and meta-analysis.

Model-estimated air pollution exposure assessments have been extensively employed in the evaluation of health risks associated with air pollution. However, few studies synthetically evaluate the reliability of model-estimated PM2.5 products in health risk assessment by comparing them with ground-based monitoring station air quality data. In response to this gap, we undertook a meticulously structured systematic review and meta-analysis. Our objective was to aggregate existing comparative studies to ascertain the disparity in mortality effect estimates derived from model-estimated ambient PM2.5 exposure versus those based on monitoring station-observed PM2.5 exposure. We conducted searches across multiple databases, namely PubMed, Scopus, and Web of Science, using predefined keywords. Ultimately, ten studies were included in the review. Of these, seven investigated long-term annual exposure, while the remaining three studies focused on short-term daily PM2.5 exposure. Despite variances in the estimated Exposure-Response (E-R) associations, most studies revealed positive associations between ambient PM2.5 exposure and all-cause and cardiovascular mortality, irrespective of the exposure being estimated through models or observed at monitoring stations. Our meta-analysis revealed that all-cause mortality risk associated with model-estimated PM2.5 exposure was in line with that derived from station-observed sources. The pooled Relative Risk (RR) was 1.083 (95% CI: 1.047, 1.119) for model-estimated exposure, and 1.089 (95% CI: 1.054, 1.125) for station-observed sources (p = 0.795). In conclusion, most model-estimated air pollution products have demonstrated consistency in estimating mortality risk compared to data from monitoring stations. However, only a limited number of studies have undertaken such comparative analyses, underscoring the necessity for more comprehensive investigations to validate the reliability of these model-estimated exposure in mortality risk assessment.

Relationships between long-term exposure to major PM2.5 constituents and outpatient visits and hospitalizations in Guangdong, China.

Ambient fine particulate matter (PM2.5) has attracted considerable attention due to its crucial role in the rising global disease burden. Evidence of health risks associated with exposure to PM2.5 and its major constituents is important for advancing hazard assessments and air pollution emission policies. We investigated the relationship between exposure to major constituents of PM2.5 and outpatient visits as well as hospitalizations in Guangdong Province, China, where 127 million residents live in a severe PM2.5 pollution environment. An approach that integrates the generalized weighted quantile sum (gWQS) regression with the difference-in-differences (DID) approach was used to assess the overall mixture effects and relative contributions of each constituent. We observed significant associations between long-term exposure to the mixture of PM2.5 constituents (WQS index) and outpatient visits (IR%, percentage increases in risk per unit WQS index increase:1.73, 95%CI: 1.72, 1.74) as well as hospitalizations (IR%:5.15, 95%CI: 5.11, 5.20). Black carbon (weight: 0.34) and nitrate (weight: 0.60) respectively exhibited the highest contributions to outpatient visits and hospitalizations. The overall mixture effects on outpatient visits and hospitalizations were higher with increased summer air temperatures (IR%: 7.54, 95%CI: 7.33, 7.74 and IR%: 9.55, 95%CI: 8.36, 10.75, respectively) or decreased winter air temperatures (IR%: 1.88, 95%CI: 1.68, 2.08 and IR%: 4.87, 95%CI: 3.73, 6.02, respectively). Furthermore, the overall mixture effects on outpatient visits and hospitalizations were significantly higher in populations with higher socioeconomic status (P < 0.01). It's crucial to address the primary sources of nitrate precursor substances and black carbon (mainly traffic-related and industrial-related air pollutants) and consider the complex interaction effects between air temperature and PM2.5 in the context of climate change. Of particular concern is the need to prioritize healthcare demands in economically disadvantaged regions and to address the health inequalities stemming from the uneven distribution of healthcare resources and PM2.5 pollution.

Assessing the 2023 Canadian wildfire smoke impact in Northeastern US: Air quality, exposure and environmental justice.

The Canadian wildfires in June 2023 significantly impacted the northeastern United States, particularly in terms of worsened air pollution and environmental justice concerns. While advancements have been made in low-cost sensor deployments and satellite observations of atmospheric composition, integrating dynamic human mobility with wildfire PM2.5 exposure to fully understand the environmental justice implications remains underinvestigated. This study aims to enhance the accuracy of estimating ground-level fine particulate matter (PM2.5) concentrations by fusing chemical transport model outputs with empirical observations, estimating exposures using human mobility data, and evaluating the impact of environmental justice. Employing a novel data fusion technique, the study combines the Weather Research and Forecasting model with Chemistry (WRF-Chem) outputs and surface PM2.5 measurements, providing a more accurate estimation of PM2.5 distribution. The study addresses the gap in traditional exposure assessments by incorporating human mobility data and further investigates the spatial correlation of PM2.5 levels with various environmental and demographic factors from the US Environmental Protection Agency (EPA) Environmental Justice Screening and Mapping Tool (EJScreen). Results reveal that despite reduced mobility during high PM2.5 levels from wildfire smoke, exposure for both residents and individuals on the move remains high. Regions already burdened with high environmental pollution levels face amplified PM2.5 effects from wildfire smoke. Furthermore, we observed mixed correlations between PM2.5 concentrations and various demographic and socioeconomic factors, indicating complex exposure patterns across communities. Urban areas, in particular, experience persistent high exposure, while significant correlations in rural areas with EJScreen factors highlight the unique vulnerabilities of these populations to smoke exposure. These results advocate for a comprehensive approach to environmental health that leverages advanced models, integrates human mobility data, and addresses socio-demographic disparities, contributing to the development of equitable strategies against the growing threat of wildfires.

Modeling assessment of air pollution control measures and COVID-19 pandemic on air quality improvements over Greater Bay Area of China.

A remarkable progress has been made toward the air quality improvements over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 2017 to 2020. In this study, for the first time, the emission reductions of regional control measures together with the COVID-19 pandemic were considered simultaneously into the development of the GBA's emission inventories for the years of 2017 and 2020. Based on these collective emission inventories, the impacts of control measures, meteorological variations together with temporary COVID-19 lockdowns on the five major air quality index pollutants (SO2, NO2, PM2.5, PM10, and O3, excluding CO) were evaluated using the WRF-CMAQ and SMAT-CE model attainment assessment tool over the GBA region. Our results revealed that control measures in the Pearl River Delta (PRD) region affected significantly the GBA, resulting in pollutant reductions ranging from 48 % to 64 %. In contrast, control measures in Hong Kong and Macao contributed to pollutant reductions up to 10 %. In PRD emission sectors, stationary combustion, on-road, industrial processes and dust sectors stand out as the primary contributors to overall air quality improvements. Moreover, the COVID-19 pandemic during period I (Jan 23-Feb 23) led to a reduction of NO2 concentration by 7.4 %, resulting in a negative contribution (disbenefit) for O3 with an increase by 2.4 %. Our findings highlight the significance of PRD control measures for the air quality improvements over the GBA, emphasizing the necessity of implementing more refined and feasible manageable joint prevention and control policies.

Source analysis and health risk assessment of polycyclic aromatic hydrocarbon (PAHs) in total suspended particulate matter (TSP) from Bengbu, China.

The polycyclic aromatic hydrocarbon (PAH) concentrations in total suspended particulate matter (TSP) samples collected from October, 2021 to September, 2022 were analyzed to clarify the pollution characteristics and sources of 16 PAHs in the atmospheric TSP in Bengbu City. The ρ(PAHs) concentrations ranged from 1.71 to 43.85 ng/m3 and higher concentrations were detected in winter, followed by spring, autumn, and summer. The positive matrix factorization analysis revealed that, in spring and summer, PAH pollution was caused mainly by industrial emissions, gasoline and diesel fuel combustion, whereas in autumn and winter, it was coal, biomass and natural gas combustion. The cluster and potential source factor analyses showed that long-range transport was a significant factor. During spring, autumn, and winter, the northern and northwestern regions had a significant impact, whereas the coastal area south of Bengbu had the greatest influence in summer. The health risk assessment revealed that the annual total carcinogenic equivalent concentration values for PAHs varied from 0.0159 to 7.437 ng/m3, which was classified as moderate. Furthermore, the annual incremental lifetime cancer risk values ranged from 1.431 × 10-4 to 3.671 × 10-3 for adults and from 6.823 × 10-5 to 1.749 × 10-3 for children, which were higher than the standard.

Probabilistic human health risk assessment of PCDD/Fs near municipal solid-waste incinerator using Monte Carlo analysis coupled with triangular fuzzy numbers.

PCDD/Fs are dioxins produced by waste incineration and pose risks to human health. We aimed to detail the health risks of airborne and soil PCDD/Fs near a municipal solid-waste incinerator (MSWI) for the surrounding population and develop a new model that improves upon existing methods. Thus, we conducted field sampling and then investigated a MSWI in the Pearl River Delta (2016-2018). Our results showed that the carcinogenic and non-carcinogenic risk values of PCDD/Fs exposed to residents in nearby areas were acceptable, with hazard index (HI) values lower than 1.0 and a total carcinogenic risk lower than 1.0E-6. Notably, the results raised concerns regarding higher non-carcinogenic risks in children than in adults. Comparative analysis of the frequency accumulation diagram, accumulated probability risk, and the absolute value of error (δ) between the 95% confidence interval (CI) and the 90% CI of the Monte Carlo stochastic simulation-triangular fuzzy number (MCSS-TFN) and the MCSS model, respectively, demonstrated that the MCSS-TFN exhibited less uncertainty than the MCSS model, regardless of the health risk value of PCDD/Fs in ambient air or in soil. This observation underscores the superiority of the MCSS-TFN model over other models in assessing the health risks associated with PCDD/Fs in situations with limited data. Our new method overcomes the limited dataset size and high uncertainty in assessing the health risks of dioxin substances, providing a more comprehensive understanding of their associated health risks than MCSS models.

Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors.

Exposure scenario and receptor behavior significantly affect PM2.5 exposure quantity of persons and resident groups, which in turn influenced indoor or outdoor air quality & health management. An Internet of Things (IoT) system, EnvironMax+, was developed to accurately and conveniently assess residential dynamic PM2.5 exposure state. A university community "QC", as the application area, was divided into four exposure scenarios and five groups of residents. Low-cost mobile sensors and indoor/outdoor pollution migration (IOP) models jointly estimated multi-scenario real-time PM2.5 concentrations. Questionnaire was used to investigate residents' indoor activity characteristics. Mobile application (app) "Air health management (AHM)" could automatic collect residents' activity trajectory. At last, multi-scenario daily exposure concentrations of each residents-group were obtained. The results showed that residential exposure scenario was the most important one, where residents spend about 60 % of their daily time. Closing window was the most significant behavior affecting indoor contamination. The annual average PM2.5 concentration in the studied scenarios: residential scenario (RS) < public scenario (PS) < outdoor scenario (OS) < catering scenario (CS). Except for CS, the outdoor PM2.5 in other scenarios was higher than indoor by 5-10 µg/m3. The multi-scenario population weighted annual average exposure concentration was 37.1 µg/m3, which was 78 % of the annual average outdoor concentration. The exposure concentration of 5 groups: cooks > outdoor workers > indoor workers > students > the elderly, related to their daily activity time proportion in different exposure scenario.

Advancing nuanced pollution control: Local improvements and spatial spillovers of policies on key enterprises.

This paper examines the impact of air pollution control policies targeting key polluting enterprises, highlighting a strategic shift towards precision pollution control that concentrates on high-emission, high-risk businesses. The paper explores the efficacy of these policies and their potential spatial spillover effects, utilizing panel data from 259 Chinese cities from 2013 to 2021. Employing the difference-in-differences (DID) model and spatial Durbin model, the study analyzes both the direct local effects and the broader spatial consequences of these regulatory measures on air quality. The findings indicate a significant reduction in air pollutant concentrations in urban areas, attributing this improvement to factors such as industrial restructuring, increased investment in science and technology, and economic growth. Spatial econometric analysis further reveals a substantial positive correlation in air quality among Chinese cities. However, estimates of the spillover effect indicate that while such policies successfully reduce pollution locally, they could unintentionally degrade air quality in adjacent areas. The study highlights the need for nuanced policy strategies to mitigate unintended spatial spillovers and enhance overall effectiveness. It recommends tailored policies that integrate environmental and socioeconomic objectives, national and regional coordination for consistent enforcement, technology-driven compliance strategies, and incentives for sustainable enterprise practices.