Size distribution, meteorological influence and uncertainty for source-specific risks: PM2.5 and PM10-bound PAHs and heavy metals in a Chinese megacity during 2011-2021

Assessing emission-driven changes in health risk of source-specific PM2.5-bound heavy metals by adjusting meteorological covariates

Heavy metals (HMs) in PM2.5 gain much attention for their toxicity and carcinogenic risk. This study evaluates the health risks of PM2.5-bound HMs, focusing on how meteorological conditions affect these risks against the backdrop of PM2.5 reduction trends in China. By applying a receptor model with a meteorological normalization technique, followed by health risk assessment, this work reveals emission-driven changes in health risk of source-specific HMs in the outskirt of Tianjin during the implementation of China' second Clean Air Action (2018-2020). Sources of PM2.5-bound HMs were identified, with significant contributions from vehicular emissions (on average, 33.4 %), coal combustion (26.3 %), biomass burning (14.1 %), dust (11.7 %), industrial boilers (9.7 %), and shipping emission and sea salt (4.7 %). The source-specific emission-driven health risk can be enlarged or dwarfed by the changing meteorological conditions over time, demonstrating that the actual risks from these source emissions for a given time period may be higher or smaller than those estimated by traditional assessments. Meteorology contributed on average 56.1 % to the interannual changes in source-specific carcinogenic risk of HMs from 2018 to 2019, and 5.6 % from 2019 to 2020. For the source-specific noncarcinogenic risk changes, the contributions were 38.3 % and 46.4 % for the respective periods. Meteorology exerts a more profound impact on daily risk (short-term trends) than on annual risk (long-term trends). Such meteorological impacts differ among emission sources in both sign and magnitude. Reduced health risks of HMs were largely from targeted regulatory measures on sources. Therefore, the meteorological covariates should be considered to better evaluate the health benefits attributable to pollution control measures in health risk assessment frameworks.

Probing the occurrence, sources and cancer risk assessment of polycyclic aromatic hydrocarbons in PM2.5 in a humid metropolitan city in China

Fifty-two consecutive PM2.5 samples from December 2021 to February 2022 (the whole winter) were collected in the center of Chongqing, a humid metropolitan city in China. These samples were analysed for the 16 USEPA priority polycyclic aromatic hydrocarbons (16 PAHs) to explore their composition and sources, and to assess their cancer risks to humans. The total concentrations of the 16 PAHs (ng m-3) ranged from 16.45 to 174.15, with an average of 59.35 ± 21.45. Positive matrix factorization (PMF) indicated that traffic emissions were the major source (42.4%), followed by coal combustion/industrial emission (31.3%) and petroleum leakage/evaporation (26.3%). The contribution from traffic emission to the 16 PAHs increased from 40.0% in the non-episode days to as high as 46.2% in the air quality episode during the sampling period. The population attributable fraction (PAF) indicates that when the unit relative risk (URR) is 4.49, the number of lung cancer cases per million individuals under PAH exposure is 27 for adults and 38 for seniors, respectively. It was 5 for adults and 7 for seniors, when the URR is 1.3. The average incremental lifetime cancer risk (ILCR) for children, adolescents, adults and seniors was 0.25 × 10-6, 0.23 × 10-6, 0.71 × 10-6, and 1.26 × 10-6, respectively. The results of these two models complemented each other well, and both implied acceptable PAH exposure levels. Individual genetic susceptibility and exposure time were identified as the most sensitive parameters. The selection and use of parameters in risk assessment should be further deepened in subsequent studies to enhance the reliability of the assessment results.

Potential toxic components in size-resolved particles and gas from residential combustion: Emission factor and health risk

Particulate matter (PM) from residential combustion is an existential threat to human health. Emission factors (EFs) of multiple potential toxic components (PTCs) in size-resolved PM and gas from eight residential fuel combustion were measured, and size distribution, gas/particle partitioning and health risks of the PTCs were investigated. Average EFs from clean coal and anthracite coal were PTEs (sum of EFs of 11 Potential Toxic Elements, 6.62 mg/kg fuels) > PAHs (sum of 22 Polycyclic Aromatic Hydrocarbons, 1.12 mg/kg) > OPAHs (sum of 5 Oxygenated Polycyclic Aromatic Hydrocarbons, 0.45 mg/kg) > PAEs (sum of 6 Phthalate Esters, 0.11 mg/kg) > NPAHs (sum of 14 Nitropolycyclic Aromatic Hydrocarbons, 16.84 μg/kg) > OPEs (sum of 7 Organophosphate Esters, 7.57 μg/kg) > PCBs (sum of 6 Polychorinated Biphenyls, 0.07 μg/kg), which were 2-3 and 1-2 orders of magnitude lower than the EFs of PTCs (except PTEs) from bituminous coal and biomass. Most PAHs, OPAHs and NPAHs, which may mainly originate from chemical reactions, showed similar size distributions and averagely 85 % concentrated in PM1. PTEs, PAEs, OPEs and PCBs generated from the release from raw fuels may have a higher proportion, so their size distributions were more complex and varied with combustion temperature, volatility of compounds, binding mode of the raw fuels, and so on. In addition, clean coal and high-quality anthracite coal could reduce the health risks from the potential organic toxic components, but also reveal the stumbling block of PTEs in risk control.

A city-level dataset of heavy metal emissions into the atmosphere across China from 2015-2020

The absence of nationwide distribution data regarding heavy metal emissions into the atmosphere poses a significant constraint in environmental research and public health assessment. In response to the critical data deficiency, we have established a dataset covering Cr, Cd, As, and Pb emissions into the atmosphere (HMEAs, unit: ton) across 367 municipalities in China. Initially, we collected HMEAs data and covariates such as industrial emissions, vehicle emissions, meteorological variables, among other ten indicators. Following this, nine machine learning models, including Linear Regression (LR), Ridge, Bayesian Ridge (Bayesian), K-Neighbors Regressor (KNN), MLP Regressor (MLP), Random Forest Regressor (RF), LGBM Regressor (LGBM), Lasso, and ElasticNet, were assessed using coefficient of determination (R2), root-mean-square error (RMSE) and Mean Absolute Error (MAE) on the testing dataset. RF and LGBM models were chosen, due to their favorable predictive performance (R2: 0.58-0.84, lower RMSE/MAE), confirming their robustness in modelling. This dataset serves as a valuable resource for informing environmental policies, monitoring air quality, conducting environmental assessments, and facilitating academic research.

Distribution and source identification of polycyclic aromatic hydrocarbons (PAHs) with PCA-MLR and PMF methods in the topsoil of Chengdu at SW, China

In spite of extensive studies on the features of polycyclic aromatic hydrocarbons (PAHs) as typical persistent organic pollutants (POPs) in cities, lack of understanding on the distribution and source characteristics of PAHs in big city with basin climate that can easily accelerate the pollution. Therefore, we sampled and analyzed PAHs from forty-five topsoil samples evenly distributed in Chengdu and the data shows that: (1) concentrations of ∑16PAHs in the study area ranged from 88.56 to 4448.34 ng/g, with a mean value of 739.07 ng/g, which is a lower level compared to similar cities, the distribution and proportion of LMW-PAHs show that the migration of pollution is blocked by the topography of the basin; (2) principal component analysis-multiple linear regression (PCA-MLR) and positive matrix factorization (PMF) indicated that combustion of fossil fuels and biomass is the most important source of PAHs in Chengdu; (3) the toxic equivalency factors of benzo[a]pyrene indicated a low risk of ∑16PAHs in all areas in Chengdu; (4) the inherited lifetime carcinogenic risk (ILCR) showed a relatively low level of potential risk in the region, while female inhabitants in several regions seem to suffer from higher health risks. Overall, our case study of PAHs in the topsoil at Chengdu city at SW China indicates that the PCA-MLR analysis is useful to identify the source of PAHs in the urban region with complicated pollution source.

Heavy vehicles' non-exhaust exhibits competitive contribution to PM2.5 compared with exhaust in port and nearby areas

Heavy port transportation networks are increasingly considered as significant contributors of PM2.5 pollution compared to vessels in recent decades. In addition, evidence points to the non-exhaust emission of port traffic as the real driver. This study linked PM2.5 concentrations to varied locations and traffic fleet characteristics in port area through filter sampling. The coupled emission ratio-positive matrix factorisation (ER-PMF) method resolves source factors by avoiding direct overlap from collinear sources. In the port central and entrance areas, freight delivery activity emissions including vehicle exhaust and non-exhaust particles, as well as induced road dust resuspension, accounted for nearly half of the total contribution (42.5%-49.9%). In particular, the contribution of non-exhaust from denser traffic with high proportion of trucks was competitive and equivalent to 52.3% of that from exhaust. Backward trajectory statistical models further interpreted the notably larger-scale coverage of non-exhaust emissions in the port's central area. The distribution of PM2.5 were interpolated within the scope of the port and nearby urban areas, displaying the potential contribution of non-exhaust within 1.15 μg/m3-4.68 μg/m3, slightly higher than the urban detections reported nearby. This study may provide useful insights into the increasing percentage of non-exhaust from trucks in ports and nearby urban areas and facilitate supplementary data collection on Euro-VII type-approval limit settings.

Outdoor Health Risk of Atmospheric Particulate Matter at Night in Xi'an, Northwestern China

The deterioration of air quality via anthropogenic activities during the night period has been deemed a serious concern among the scientific community. Thereby, we explored the outdoor particulate matter (PM) concentration and the contributions from various sources during the day and night in winter and spring 2021 in a megacity, northwestern China. The results revealed that the changes in chemical compositions of PM and sources (motor vehicles, industrial emissions, coal combustion) at night lead to substantial PM toxicity, oxidative potential (OP), and OP/PM per unit mass, indicating high oxidative toxicity and exposure risk at nighttime. Furthermore, higher environmentally persistent free radical (EPFR) concentration and its significant correlation with OP were observed, suggesting that EPFRs cause reactive oxygen species (ROS) formation. Moreover, the noncarcinogenic and carcinogenic risks were systematically explained and spatialized to children and adults, highlighting intensified hotspots to epidemiological researchers. This better understanding of day-night-based PM formation pathways and their hazardous impact will assist to guide measures to diminish the toxicity of PM and reduce the disease led by air pollution.

Spatiotemporal variation and influencing factors of air pollution in Anhui Province

Anhui Province locates in the Yangtze River Delta region. The spatial difference between the north and the south is significant, and the air quality is improved over time. Studying the spatial and temporal changes of air pollution and its influencing factors for the coordinated control of air pollutants in the Yangtze River Delta region is significant. This study used the annual and monthly average data of six pollutants, PM_2.5, PM₁₀, O₃, NO₂, SO₂, and CO, in Anhui Province and various cities from 2015 to 2021 and analyzed the spatiotemporal change characteristics using Excel and GIS software. Meanwhile, this paper used the SPSS correlation analysis method to analyze the correlation between pollutants and meteorological factors and analyzed the impact of economic development and environmental protection policies. The results are shown below. (1) The concentrations of SO₂, NO₂, and CO showed an overall downward trend at an interannual level. Meanwhile, the concentrations of PM₁₀ and PM_2.5 first increased slowly before 2017 and then declined, while the concentrations of O₃ increased significantly before 2018 and then declined slowly. On a monthly scale, O₃ presented an M-shaped change, while the other five pollutants basically presented a U-shaped change mode. The top monthly pollutants in each city followed the order of PM_2.5, O₃, PM₁₀, and NO₂. (2) PM_2.5 and PM₁₀ showed apparent characteristics of high concentrations in the north and low concentrations in the south in space. There were no significant differences in NO₂, SO₂, and CO pollution between the north and the south in space, and the differences in spatial pollution among cities were reduced significantly. (3) Five pollutants (SO₂, NO₂, PM₁₀, PM_2.5, and CO) except O₃ were positively correlated, and the degree of correlation was correlated, strongly correlated, and above. However, five pollutants were negatively correlated with O₃. The temperature had the most significant impact of negative correlation on five pollutants except for O₃. The sunshine duration had the most significant impact on O₃. (4) Economic growth and environmental protection policies in Anhui Province have positively affected environmental governance.

The effects of air pollution, meteorological parameters, and climate change on COVID-19 comorbidity and health disparities: A systematic review

Air pollutants, especially particulate matter, and other meteorological factors serve as important carriers of infectious microbes and play a critical role in the spread of disease. However, there remains uncertainty about the relationship among particulate matter, other air pollutants, meteorological conditions and climate change and the spread of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), hereafter referred to as COVID-19. A systematic review was conducted using PRISMA guidelines to identify the relationship between air quality, meteorological conditions and climate change, and COVID-19 risk and outcomes, host related factors, co-morbidities and disparities. Out of a total of 170,296 scientific publications screened, 63 studies were identified that focused on the relationship between air pollutants and COVID-19. Additionally, the contribution of host related-factors, co-morbidities, and health disparities was discussed. This review found a preponderance of evidence of a positive relationship between PM_2.5, other air pollutants, and meteorological conditions and climate change on COVID-19 risk and outcomes. The effects of PM_2.5, air pollutants, and meteorological conditions on COVID-19 mortalities were most commonly experienced by socially disadvantaged and vulnerable populations. Results however, were not entirely consistent, and varied by geographic region and study. Opportunities for using data to guide local response to COVID-19 are identified.