Health burden attributable to ambient PM2.5 in China

Particle-ozone complex pollution under diverse synoptic weather patterns in the Yangtze River Delta region: Synergistic relationships and the effects of meteorology and chemical compositions

There is considerable academic interest in the particle-ozone synergistic relationship (PO) between fine particulate matter (PM2.5) and ozone (O3). Using various synoptic weather patterns (SWPs), we quantitatively assessed the variations in the PO, which is relevant to formulating policies aimed at controlling complex pollution in the air. First, based on one-year sampling data from March 2018 to February 2019, the SWPs classification of the Yangtze River Delta (YRD) was conducted using the sum-of-squares technique (SS). Five dominant SWPs can be found in the YRD region, including the Aleutian low under SWP1 (occurring 45 % of the year), a tropical cyclone under SWP2 (21 %), the tropical cyclone and western Pacific Subtropical High (WPSH) under SWP3 (15.4 %), the WPSH under SWP4 (6.9 %), and a continental high pressure under SWP5 (3.1 %). The phenomenon of a "seesaw" between PM2.5 and O3 concentrations exhibited significant spatial heterogeneity, which was influenced by meteorological mechanisms. Second, the multi-linear regression (MLR) model and the partial correlation (PCOR) analysis were employed to quantify the effects of dominant components and meteorological factors on the PO. Meteorological variables could collectively explain only 33.0 % of the PM2.5 variations, but 58.0 % for O3. O3 promoted each other with low concentrations of PM2.5 but was inhibited by high concentrations of PM2.5. High relative humidity (RH) was conducive to the generation of PM2.5 secondary components and enhanced the radiative effects of aerosols and the negative correlation of PO. In addition, attention should be paid to assessing the combined effects of precursor levels, weather, and chemical reactions on the particle-ozone complex pollution. The control of O3 pollutants should be intensified in summer, while the focus should be on reducing PM2.5 pollutants in winter. Prevention and control measures need to reflect the differences in weather conditions and pollution characteristics, with a focus on RH and secondary components of PM2.5.

Contribution of greenness, air pollution, and residential food environment to excess gestational weight gain: A cross-sectional study in Wuhan, China

OBJECTIVES

Our goal was to explore how greenness, air pollution, and residential food environment were linked to excessive gestational weight gain (EGWG), and to estimate their combined effects on this condition.

METHOD

This cross-sectional analysis included 51,507 pregnant women from the Wuhan Maternal and Child Health Management Information System between 2016 and 2019. Generalized linear mixed regression models were employed to explore the relationships between greenness, air pollution, residential food environmental exposure, and EGWG; and the combined effects were further estimated by cluster analysis and principal components analysis.

RESULT

We only found a significant association between convenience store density within the 250 m buffer zone (OR = 1.03 and 95% CI: 1.01,1.05) and EGWG. In terms of air pollution, sulfur dioxide(SO2), particulate matter with a diameter of 10 μm or less(PM10), and particulate matter with a diameter of 2.5 μm or less(PM2.5) were substantially correlated with a higher prevalence of EGWG and higher GWG, with (OR = 1.16 and 95% CI: 1.12,1.21; OR = 1.12 and 95% CI: 1.08,1.16; OR = 1.17 and 95% CI: 1.14,1.21, respectively) per interquartile range(IQR) increase. Cluster analysis revealed the presence of three clusters representing urban exposures. In contrast to urban environment clusters characterized by favourable conditions, those exhibiting elevated air pollution levels, high-density residential food environment and low levels of greenness were found to have increased odds of EGWG (OR = 1.10, 95% CI: 1.03, 1.19).

CONCLUSION

This study emphasizes that exposure to elevated air pollution, high-density residential neighbourhood food environments, and low levels of greenness is a neighbourhood obesogenic environment for pregnant women.

Health risks and sources of trace elements and black carbon in PM2.5 from 2019 to 2021 in Beijing

A comprehensive health risk assessment of PM2.5 is meaningful to understand the current status and directions regarding further improving air quality from the perspective of human health. In this study, we evaluated the health risks of PM2.5 as well as highly toxic inorganic components, including heavy metals (HMs) and black carbon (BC) based on long-term observations in Beijing from 2019 to 2021. Our results showed that the relative risks of chronic obstructive pulmonary disease, lung cancer, acute lower respiratory tract infection, ischemic heart disease, and stroke decreased by 4.07%-9.30% in 2020 and 2.12%-6.70% in 2021 compared with 2019. However, they were still at high levels ranging from 1.26 to 1.77, in particular, stroke showed the highest value in 2021. Mn had the highest hazard quotient (HQ, from 2.18 to 2.56) for adults from 2019 to 2021, while Ni, Cr, Pb, As, and BC showed high carcinogenic risks (CR > 1.0×10-6) for adults. The HQ values of Mn and As and the CR values of Pb and As showed constant or slight upwards trends during our observations, which is in contrast to the downward trends of other HMs and PM2.5. Mn, Cr, and BC are crucial toxicants in PM2.5. A significant shrink of southern region sourcesof HMs and BCshrank suggests the increased importance of local sources. Industry, dust, and biomass burning are the major contributors to the non-carcinogenic risks, while traffic emissions and industry are the dominant contributors to the carcinogenic risks in Beijing.

Exosomal miR-196b secreted from bronchial epithelial cells chronically exposed to low-dose PM2.5 promotes invasiveness of adjacent and lung cancer cells

Fine particulate matter (PM2.5) is a risk factor for pulmonary diseases and lung cancer, and inhaled PM2.5 is mainly deposited in the bronchial epithelium. In this study, we investigated the effect of long-term exposure to low-dose PM2.5 on BEAS-2B cells derived from the normal bronchial epithelium. BEAS-2B cells chronically exposed to a concentration of 5 µg/ml PM2.5 for 30 passages displayed the phenotype promoting epithelial-mesenchymal transition (EMT) and cell invasion. Cellular internalization of exosomes (designated PM2.5 Exo) extracted from BEAS-2B cells chronically exposed to low-dose PM2.5 promoted cell invasion in vitro and metastatic potential in vivo. Hence, to identify the key players driving phenotypic alterations, we analyzed microRNA (miRNA) expression profiles in PM2.5 Exo. Five miRNAs with altered expression were selected: miRNA-196b-5p, miR-135a-2-5p, miR-3117-3p, miR-218-5p, and miR-497-5p. miR-196b-5p was the most upregulated in both BEAS-2B cells and isolated exosomes after PM2.5 exposure. In a functional validation study, genetically modified exosomes overexpressing a miR-196b-5p mimic induced an enhanced invasive phenotype in BEAS-2B cells. Conversely, miR-196b-5p inhibition diminished the PM2.5-enhanced EMT and cell invasion. These findings indicate that exosomal miR-196b-5p may be a candidate biomarker for predicting the malignant behavior of the bronchial epithelium and a therapeutic target for inhibiting PM2.5-triggered pathogenesis.

Two Decades of Air Pollution Health Risk Assessment: Insights From the Use of WHO's AirQ and AirQ+ Tools

Objectives

We evaluated studies that used the World Health Organization's (WHO) AirQ and AirQ+ tools for air pollution (AP) health risk assessment (HRA) and provided best practice suggestions for future assessments.

Methods

We performed a comprehensive review of studies using WHO's AirQ and AirQ+ tools, searching several databases for relevant articles, reports, and theses from inception to Dec 31, 2022.

Results

We identified 286 studies that met our criteria. The studies were conducted in 69 countries, with most (57%) in Iran, followed by Italy and India (∼8% each). We found that many studies inadequately report air pollution exposure data, its quality, and validity. The decisions concerning the analysed population size, health outcomes of interest, baseline incidence, concentration-response functions, relative risk values, and counterfactual values are often not justified, sufficiently. Many studies lack an uncertainty assessment.

Conclusion

Our review found a number of common shortcomings in the published assessments. We suggest better practices and urge future studies to focus on the quality of input data, its reporting, and associated uncertainties.

Exploring the link between ambient PM2.5 concentrations and respiratory diseases in the elderly: a study in the Muang district of Khon Kaen, Thailand

The impact of air pollution is a major public health concern. However, there are few studies on the correlation between PM2.5 and respiratory infections. This study aimed to determine a link between PM2.5 and respiratory diseases among the elderly in Thailand. The data source for this study consisted of 43 electronic files from the Khon Kaen Provincial Health Office covering years 2020 and 2021 and surveyed a total of 43,534 people. The generalized linear mixed model (GLMM) was used to determine the adjusted odds ratio (AOR), and 95 % CI. We found that exposure to PM2.5 concentrations (in 10 μg m-3 increments) was associated with respiratory diseases (AOR: 3.98; 95 % CI [1.53-10.31]). Respondents who are male, aged less than 80 years, single, self-employed, or working as contractors, have a body mass index (BMI) not equal to the standard, have NCDs (hypertension, diabetes mellitus, and cardiovascular disease), are smokers, live in sub-districts where more than 5 % of the land is planted to sugarcane, or live in close proximity to a biomass power plant were at significantly higher risk of developing respiratory diseases (p<0.05). Therefore, environmental factors including ambient PM2.5 concentrations, the proportion of sugarcane plantation areas, and biomass power plants impact the occurrence of respiratory diseases among the elderly. Also, demographic factors and NCDs are serious issues. Systematic approaches to reducing PM2.5 levels in industrial and agricultural sectors are necessary for both the general population and vulnerable groups, including the elderly and NCD patients.

Associations between long-term exposure to air pollution, diabetes, and hypertension in metropolitan Iran: an ecologic study

Epidemiological studies on air pollution, diabetes, and hypertension conflict. This study examined air pollution, diabetes, and hypertension in adults in 11 metropolitan areas of Iran (2012-2016). Local environment departments and the Tehran Air Quality Control Company provided air quality data. The VIZIT website and Stepwise Approach to Chronic Disease Risk Factor Surveillance study delivered chronic disease data. Multiple logistic regression and generalized estimating equations evaluated air pollution-related diabetes and hypertension. In Isfahan, Ahvaz, and Tehran, PM2.5 was linked to diabetes. In all cities except Urmia, Yasuj, and Yazd, PM2.5 was statistically related to hypertension. O3 was connected to hypertension in Ahvaz, Tehran, and Shiraz, whereas NO2 was not. BMI and gender predict hypertension and diabetes. Diabetes, SBP, and total cholesterol were correlated. Iran's largest cities' poor air quality may promote diabetes and hypertension. PM2.5 impacts many cities' outcomes. Therefore, politicians and specialists have to control air pollution.

PM2.5-induced DNA oxidative stress in A549 cells and regulating mechanisms by GST DNA methylation and Keap1/Nrf2 pathway

Fine particulate matter (PM2.5) increases the risks of lung cancer. Epigenetics provides a new toxicology mechanism for the adverse health effects of PM2.5. However, the regulating mechanisms of PM2.5 exposure on candidate gene DNA methylation changes in the development of lung cancer remain unclear. Abnormal expression of the glutathione S transferase (GST) gene is associated with cancer. However, the relationship between PM2.5 and DNA methylation-mediated GST gene expression is not well understood. In this study, we performed GST DNA methylation analysis and GST-related gene expression in human A549 cells exposed to PM2.5 (0, 50, 100 µg/mL, from Taiyuan, China) for 24 h (n = 4). We found that PM2.5 may cause DNA oxidative damage to cells and the elevation of GSTP1 promotes cell resistance to reactive oxygen species (ROS). The Kelch-1ike ECH-associated protein l (Keap1)/nuclear factor NF-E2-related factor 2 (Nrf2) pathway activates the GSTP1. The decrease in the DNA methylation level of the GSTP1 gene enhances GSTP1 expression. GST DNA methylation is associated with reduced levels of 5-methylcytosine (5mC), DNA methyltransferase 1 (DNMT1), and histone deacetylases 3 (HDAC3). The GSTM1 was not sensitive to PM2.5 stimulation. Our findings suggest that PM2.5 activates GSTP1 to defend PM2.5-induced ROS and 8-hydroxy-deoxyguanosine (8-OHdG) formation through the Keap1/Nrf2 signaling pathway and GSTP1 DNA methylation.

Exploring the Burden of PM2.5-Related Deaths and Economic Health Losses in Beijing

Air pollution is one of the major global public health challenges. Using annual fine particulate matter (PM2.5) concentration data from 2016 to 2021, along with the global exposure mortality model (GEMM), we estimated the multi-year PM2.5-pollution-related deaths divided by different age groups and diseases. Then, using the VSL (value of statistical life) method, we assessed corresponding economic losses and values. The number of deaths attributed to PM2.5 in Beijing in 2021 fell by 33.74 percent from 2016, while health economic losses would increase by USD 4.4 billion as per capita disposable income increases year by year. In 2021, the average annual concentration of PM2.5 in half of Beijing's municipal administrative districts is less than China's secondary ambient air quality standard (35 μg/m3), but it can still cause 48,969 deaths and corresponding health and economic losses of USD 16.31 billion, equivalent to 7.9 percent of Beijing's GDP. Therefore, it is suggested that more stringent local air quality standards should be designated to protect public health in Beijing.

Existence of typical winter atmospheric circulation patterns leading to high PM2.5 concentration days in East Asia

Understanding the atmospheric circulation patterns responsible for severe air pollution events in East Asia is important because East Asia is one of the most polluted regions in the world, particularly during the boreal winter (December-January-February). Here, by conducting GEOS-Chem simulation with fixed anthropogenic emission sources, we found that there exist three typical atmospheric circulation patterns conducive to leading to high concentrations of particulate matter with a diameter less than or equal to 2.5 μm (PM2.5) in East Asia. These atmospheric circulation patterns are characterized by weakened horizontal winds, which allows PM2.5 to accumulate, and by enhanced relative humidity, which can favor secondary formation of PM2.5. The occurrence of these atmospheric circulation patterns is associated with increased sea ice cover over the Barents Sea and heavy precipitation over the tropical western Indian Ocean. The existence of these atmospheric circulation patterns among typical atmospheric circulation patterns indicates high PM2.5 days in East Asia are unavoidable given current level of anthropogenic emissions in the region. This conclusion indicates that sustained efforts to reduce anthropogenic emission sources in East Asia should be warranted to avoid high PM2.5 days.

Ambient fine particulate matter is associated with daily outpatient visits for ankylosing spondylitis: A time-series analysis in Beijing, China

Exposure to ambient fine particulate matter (PM2.5) has a great impact on human body's immune system, but the correlation between PM2.5 and ankylosing spondylitis has not yet been clarified. We extracted 58,600 outpatient visits for ankylosing spondylitis from the Beijing Medical Claim Data for Employees database from 2010 to 2017. The percentage of outpatient visits following PM2.5 concentrations was estimated using generalized additive models with Poisson connections. Increase by 10 μ g/m3, PM2.5 is associated with daily outpatient visits for ankylosing spondylitis. In this test, the average concentration of PM2.5 was 86.8 ± 74.3 μ g/m3. For every 10 μg/m3 increase in PM2.5 concentration, there was a 0.34% (95% CI, 0.26-0.42%) increase in the risk of patients who visited the doctor on the same day. Females and younger patients were most susceptible to the impact of PM2.5 exposure (P＜0.05). This study revealed the relationship between exposure to PM2.5 and ankylosing spondylitis, and future research can further confirm this finding and explore the potential mechanisms.

Air-Liquid Interface Microfluidic Monitoring Sensor Platform for Studying Autophagy Regulation after PM2.5 Exposure

Undoubtedly, a deep understanding of PM2.5-induced tumor metastasis at the molecular level can contribute to improving the therapeutic effects of related diseases. However, the underlying molecular mechanism of fine particle exposure through long noncoding RNA (lncRNA) regulation in autophagy and, ultimately, lung cancer (LC) metastasis remains elusive; on the other hand, the related monitoring sensor platform used to investigate autophagy and cell migration is lacking. Herein, this study performed an air-liquid interface microfluidic monitoring sensor (AIMMS) platform to analyze human bronchial epithelial cells after PM2.5 stimulation. The multiomics analysis [RNA sequencing (RNA-seq) on lncRNA and mRNA expressions separately] showed that MALAT1 was highly expressed in the PM2.5 treatment group. Furthermore, RNA-seq analysis demonstrated that autophagy-related pathways were activated. Notably, the main mRNAs associated with autophagy regulation, including ATG4D, ATG12, ATG7, and ATG3, were upregulated. Inhibition or downregulation of MALAT1 inhibited autophagy via the ATG4D/ATG12/ATG7/ATG3 pathway after PM2.5 exposure and ultimately suppressed LC metastasis. Thus, based on the AIMMS platform, we found that MALAT1 might become a promising therapeutic target. Furthermore, this low-cost AIMMS system as a fluorescence sensor integrated with the cell-monitor module could be employed to study LC migration after PM2.5 exposure. With the fluorescence cell-monitoring module, the platform could be used to observe the migration of LC cells and construct the tumor metastasis model. In the future, several fluorescence probes, including nanoprobes, could be used in the AIMMS platform to investigate many other biological processes, especially cell interaction and migration, in the fields of toxicology and pharmacology.

Direct and indirect consumption activities drive distinct urban-rural inequalities in air pollution-related mortality in China

Household consumption in China is associated with substantial PM2.5 pollution, through activities directly (i.e., fuel use) and/or indirectly (i.e., consumption of goods and services) causing pollutant emissions. Urban and rural households exhibit different consumption preferences and living areas, thus their contributions to and suffering from air pollution could differ. Assessing this contrast is crucial for comprehending the environmental impacts of the nation's ongoing urbanization process. Here we quantify Chinese urban and rural households' contributions to ambient PM2.5 pollution and the health risks they suffer from, by integrating economic, atmospheric, and health models and/or datasets. The national premature deaths related to long-term exposure to PM2.5 pollution contributed by total household consumption are estimated to be 1.1 million cases in 2015, among which 56% are urban households and 44% are rural households. For pollution contributed indirectly, urban households, especially in developed provinces, tend to bear lower mortality risks compared with the portions of deaths or pollution they contribute. The opposite results are true for direct pollution. With China's rapid urbanization process, without adequate reduction in emission intensity, the increased indirect pollution-associated premature deaths could largely offset that avoided by reduced direct pollution, and the indirect pollution-associated urban-rural inequalities might become severer. Developing pollution mitigation strategies from both production and consumption sides could help with reducing pollution-related mortality and associated urban-rural inequality.

L.acidophilus participates in intestinal inflammation induced by PM2.5 through affecting the Treg/Th17 balance

Particulate matter with aerodynamic diameters of ≤2.5 μm (PM2.5) is associated with multiple organ damage, among which the influence of PM2.5 on the gastrointestinal system has been a recent focus of attention. In this study, four different types of PM2.5 exposure models are established to determine the occurrence of PM2.5 induced intestinal inflammation. In view of the abnormal expression of lymphocytes detected in the model and the well-known fact that the intestine is the largest immune organ, we focused on the intestinal immune system. A combined regulatory T cell (Treg) transplantation experiment demonstrated that PM2.5 induced intestinal inflammation by affecting the imbalance of regulatory T cell/T helper cell 17 (Treg/Th17). Since the intestine has the highest microbial content, and the results of the 16S rDNA third-generation sequencing analysis further revealed that the abundance of Lactobacillus_acidophilus (L.acidophilus) decreased significantly after PM2.5 exposure. The following mechanism study confirmed that L.acidophilus participated in an imbalance of Treg/Th17. Moreover, L.acidophilus supplementation successfully alleviated intestinal inflammation by regulated regulating the balance of Treg/Th17 under the background of PM2.5 exposure. Hence, this is a potential method to protect against intestinal inflammation induced by PM2.5.

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.

Concentration identification and endpoint-oriented health risk assessments on a broad-spectrum of organic compounds in atmospheric fine particles: A sampling experimental study in Beijing, China

Understanding the complicate chemical components in atmospheric fine particulate matter (PM2.5) helps policy makers for pollutants control track progress and identify disparities in overall health risks. However, till now, information on accurate component detection, source identification, and effect-oriented risk assessment is scarce, especially for the simultaneous analysis of a broad-spectrum of compounds. In this study, a high-throughput target method was employed to distinguish the occurrence and characteristics of 152 chemicals: phthalate esters (PAEs), organophosphate esters (OPEs), carboxylic acid esters (CAEs), nitrophenols (NPs), nitrogen heterocyclic compounds (NHCs), per- and poly-fluoroalkyl substances (PFASs), triclosan and its derivatives (TCSs), and organosulfates (OSs) in ambient PM2.5 collected from Beijing, China. Detection frequencies of 77 targeted compounds were >50 %. Total concentrations of all compounds ranged from 33.1 to 745 ng/m3. The median concentration of ∑PAEs (108 ng/m3) was the highest, followed by ∑CAEs (12.2 ng/m3) and ∑NPs (10.1 ng/m3). Organophosphate diesters (di-OPEs) and TCSs were reported for the first time in ambient PM2.5. The pollutants mainly originated from the local industrial production, release of building materials, and environmental degradation of parent compounds. Based on absorption, distribution, metabolism, excretion, and toxicity (ADMET)-oriented risk evaluations, we found that bis (2-ethylhexyl) phthalate, diisobutyl phthalate, dibutyl phthalate, and di (2-ethylhexyl) adipate have high health risks. Additionally, the high oxidative stress potential of 4-nitrocatechol and the strong blood-brain barrier penetration potential of triclosan cannot be ignored. Our study will facilitate the evaluations of specific health outcomes and mechanisms of pollutants, and suggestion of pollutants priority control to reduce human health hazards caused by atmospheric particles.

Decoding the effect of demographic factors on environmental health based on city-level PM2.5 pollution in China

Although considerable health effects are gained from air quality improvement action plans implemented in China recently, they may have been amplified or offset due to the complexity and uncertainty of the changing demographic factors. In this study, we developed a framework for analyzing the effects of demographic factors on environmental health effects, focusing on three aspects: population scale, age structure, and spatial distribution. We quantified the above three effects by investigating how the health endpoint changed by the three demographic factors, based on a strategy of counterfactual and step-by-step relaxing hypothesis. We found that the increasing population scale and population aging caused 44,279 to 292,442 premature deaths, which offset the health effect of air quality improvement efforts for China. The change in population spatial distribution, in general, has little impact on the health effects of air quality improvement. Furthermore, the three effects are distributed unevenly across regions, especially the spatial distribution effect. Considering the widespread effect of demographic factors, PM2.5 concentration should be further reduced, and the aged population and mega-cities should be targeted for managing air quality in a cost-effective manner.

The effect of haze pollution on rural-to-urban migrants' long-term residence intentions

Severe haze pollution in China threatens human health, and its negative effect hampers rural-to-urban migrants' settlement intentions in destination cities. Using the 2017 China Migrants Dynamic Survey Data (CMDS), the satellite data of PM2.5, and city-level data, this study investigates the impact of haze pollution on rural migrants, long-term residence intentions in Chinese context with IV-probit model, and mediating effect model. Overall, we find an inverted U-shaped relationship between the level of haze pollutants and rural migrants' long-term settlement intentions. Robustness check using multi-measures and thermal inversion as the instrumental variable supports this conclusion. The mediating effect model shows haze pollution plays its role through two opposite mechanisms: signal effect and health effect. When the size of signal effect is larger than health effect, rural migrants are inclined to settle down in their host cities; otherwise, they show lower settlement willingness. The turning point appears when PM2.5 concentration reaches 38.5 μg/m3; migrants have the highest long-term residence intentions. Currently, the national average PM2.5 concentration is 40.98 μg/m3, indicating that China is at the stage where the health effect of haze pollution holds a dominant position. Haze pollution has heterogeneous impacts on migrants' residence intentions. From the individual level, the younger generation, female, and higher-educated migrants have a higher tolerance for polluted air. From the city level, migrants who work in the city with 5 to 10 million dwellers have the highest long-term residence intention and are less sensitive to haze pollution. Thus, we propose stringent environmental regulations and more inclined public service policies to migrants.

Specific analysis of PM2.5-attributed disease burden in typical areas of Northwest China

Background

Frequent air pollution events in Northwest China pose a serious threat to human health. However, there is a lack of specific differences assessment in PM2.5-related disease burden. Therefore, we aimed to estimate the PM2.5-related premature deaths and health economic losses in this typical northwest region, taking into account disease-specific, age-specific, and region-specific factors.

Methods

We utilized the WRF-Chem model to simulate and analyze the characteristics and exposure levels of PM2.5 pollution in Gansu Province, a typical region of Northwest China. Subsequently, we estimated the premature mortality and health economic losses associated with PM2.5 by combining the Global Exposure Mortality Model (GEMM) and the Value of a Statistical Life (VSL).

Results

The results suggested that the PM2.5 concentrations in Gansu Province in 2019 varied spatially, with a decrease from north to south. The number of non-accidental deaths attributable to PM2.5 pollution was estimated to be 14,224 (95% CI: 11,716-16,689), accounting for 8.6% of the total number of deaths. The PM2.5-related health economic loss amounted to 28.66 (95% CI: 23.61-33.63) billion yuan, equivalent to 3.3% of the regional gross domestic product (GDP) in 2019. Ischemic heart disease (IHD) and stroke were the leading causes of PM2.5-attributed deaths, contributing to 50.6% of the total. Older adult individuals aged 60 and above accounted for over 80% of all age-related disease deaths. Lanzhou had a higher number of attributable deaths and health economic losses compared to other regions. Although the number of PM2.5-attributed deaths was lower in the Hexi Corridor region, the per capita health economic loss was higher.

Conclusion

Gansu Province exhibits distinct regional characteristics in terms of PM2.5 pollution as well as disease- and age-specific health burdens. This highlights the significance of implementing tailored measures that are specific to local conditions to mitigate the health risks and economic ramifications associated with PM2.5 pollution.

Meteorology-driven PM2.5 interannual variability over East Asia

Atmospheric fine particulate matter (PM2.5) is a human health risk factor, but its ambient concentration depends on both precursor emissions and meteorology. While emission reductions are used to set PM2.5-related health policies, the effect of meteorology is often overlooked. To explore this aspect, we examined PM2.5 interannual variability (IAV) associated with meteorological parameters using the long-term simulation from the Community Earth System Model (CESM1), a global climate-chemistry model, with fixed emissions. The results are subsequently contrasted with the MERRA-2 reanalysis dataset, which inherently considers emission and meteorology effects. Over continental East Asia, the CESM1 domain-average PM2.5 IAV is 6.7 %, mainly attributed to humidity, precipitation, and ventilation variation. The grid-cell PM2.5 IAVs over southern East China are larger, up to 12 % due to the more substantial influence of El Niño-induced meteorological anomalies. Under such climate extreme, sub-regional PM2.5 concentration may occasionally exceed WHO air quality guideline levels despite the compliance of the long-term mean. The simulated PM2.5 IAV over continental East Asia is ~25 % of that derived from the MERRA-2 data, which highlights the influence of both emission and meteorology-driven variations and trends inherent in the latter. Although emission-driven variability is significant to PM2.5 IAV, in remote areas downwind of major source regions in East Asia, North America, and Western Europe, the MERRA-2 data revealed that meteorological variations contributed more to PM2.5 IAV than emission variations. Thus, when setting policies for complying with the WHO PM2.5-related air quality guideline levels, the highest annual PM2.5 associated with climate extremes should be considered instead of that based on average climate conditions.

Application of TCN-biGRU neural network in [Formula: see text] concentration prediction

Fine particulate matter ([Formula: see text]) poses a significant threat to human life and health, and therefore, accurately predicting [Formula: see text] concentration is critical for controlling air pollution. Two improved types of recurrent neural networks (RNNs), the long short-term memory (LSTM) and gated recurrent unit (GRU), have been widely used in time series data prediction due to their ability to capture temporal features. However, both degrade into random guessing as the time length increases. In order to enhance the accuracy of [Formula: see text] concentration prediction and address the issue of random guessing in RNNs neural networks, this study introduces a TCN-biGRU neural network model. This model is a hybrid prediction approach based on combining temporal convolutional networks (TCN) and bidirectional gated recurrent units (bi-GRU). TCN extracts higher-level feature information from longer time series data of [Formula: see text] concentrations, while bi-GRU captures features from past and future data to achieve more accurate predictive outcomes. This case study utilizes data from monitoring stations in Beijing in 2021 for conducting [Formula: see text] prediction experiments. The TCN-biGRU model achieves an average absolute error, root mean square error, and [Formula: see text] of 4.20, 7.71, and 0.961 in its predictive outcomes. When compared to the predictive outcomes of individual LSTM, GRU, and bi-GRU models, it is evident that the TCN-biGRU model exhibits smaller errors and superior predictive performance.

Computational and experimental assessment of health risks of fine particulate matter in Nanjing and Yangzhou, China

Fine particulate matter (PM2.5) is a major air pollutant in most cities of China, and poses great health risks to local residents. In this study, the health effects of PM2.5 in Nanjing and Yangzhou were compared using computational and experimental methods. The global exposure mortality model (GEMM), including the results of a cohort study in China, was used to estimate the disease-related risks. Premature mortality attributable to PM2.5 exposure were markedly higher in Nanjing than that in Yangzhou at comparable levels of PM2.5 (8191 95% CI, 6975-9994 vs. 6548 95% CI, 5599-8049 in 2015). However, the baseline mortality rate was on a country-level and the age distribution was on a province-level, traditional estimation method could not accurately represent the health burdens of PM2.5 on a city-level. We proposed a refined calculation method which based on the actual deaths of each city and the disease death rates. Conversely, similar concentrations of PM2.5 exposure resulted in higher actual deaths per million population in Yangzhou (1466 95% CI, 1266-1746) than that in Nanjing (1271 95% CI, 1098-1514). Health risks of PM2.5 are associated with the generation of reactive oxygen species, among which hydroxyl radial (·OH) is the most reactive one. We then collected these PM2.5 samples and quantified the induced ·OH. Consistently, average ·OH concentration in 2015 was higher in Yangzhou than that in Nanjing, again indicating that PM2.5 in Yangzhou was more toxic. The combination of computational and experimental methods demonstrated the complex relationship between health risks and PM2.5 concentrations. The refined estimation method could help us better estimate and interpret the risks caused by PM2.5 exposure on a city-level.

Estimating the geographical patterns and health risks associated with PM2.5-bound heavy metals to guide PM2.5 control targets in China based on machine-learning algorithms

PM2.5 is the main component of haze, and PM2.5-bound heavy metals (PBHMs) can induce various toxic effects via inhalation. However, comprehensive macroanalyses on large scales are still lacking. In this study, we compiled a substantial dataset consisting of the concentrations of eight PBHMs, including As, Cd, Cr, Cu, Mn, Ni, Pb and Zn, across different cities in China. To improve prediction accuracy, we enhanced the traditional land-use regression (LUR) model by incorporating emission source-related variables and employing the best-fitted machine-learning algorithm, which was applied to predict PBHM concentrations, analyze geographical patterns and assess the health risks associated with metals under different PM2.5 control targets. Our model exhibited excellent performance in predicting the concentrations of PBHMs, with predicted values closely matching measured values. Noncarcinogenic risks exist in 99.4% of the estimated regions, and the carcinogenic risks in all studied regions of the country are within an acceptable range (1 × 10-5-1 × 10-6). In densely populated areas such as Henan, Shandong, and Sichuan, it is imperative to control the concentration of PBHMs to reduce the number of patients with cancer. Controlling PM2.5 effectively decreases both carcinogenic and noncarcinogenic health risks associated with PBHMs, but still exceed acceptable risk level, suggesting that other important emission sources should be given attention.

Lower Airway Dysbiosis Augments Lung Inflammatory Injury in Mild-to-Moderate Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is associated with high morbidity, mortality, and healthcare costs. Cigarette smoke is a causative factor; however, not all heavy smokers develop COPD. Microbial colonization and infections are contributing factors to disease progression in advanced stages. Objectives: We investigated whether lower airway dysbiosis occurs in mild-to-moderate COPD and analyzed possible mechanistic contributions to COPD pathogenesis. Methods: We recruited 57 patients with a >10 pack-year smoking history: 26 had physiological evidence of COPD, and 31 had normal lung function (smoker control subjects). Bronchoscopy sampled the upper airways, lower airways, and environmental background. Samples were analyzed by 16S rRNA gene sequencing, whole genome, RNA metatranscriptome, and host RNA transcriptome. A preclinical mouse model was used to evaluate the contributions of cigarette smoke and dysbiosis on lower airway inflammatory injury. Measurements and Main Results: Compared with smoker control subjects, microbiome analyses showed that the lower airways of subjects with COPD were enriched with common oral commensals. The lower airway host transcriptomics demonstrated differences in markers of inflammation and tumorigenesis, such as upregulation of IL-17, IL-6, ERK/MAPK, PI3K, MUC1, and MUC4 in mild-to-moderate COPD. Finally, in a preclinical murine model exposed to cigarette smoke, lower airway dysbiosis with common oral commensals augments the inflammatory injury, revealing transcriptomic signatures similar to those observed in human subjects with COPD. Conclusions: Lower airway dysbiosis in the setting of smoke exposure contributes to inflammatory injury early in COPD. Targeting the lower airway microbiome in combination with smoking cessation may be of potential therapeutic relevance.

China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment

Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.

PM2.5 promotes apoptosis of alveolar epithelial cells via targeting ROS/p38 signaling pathway and thus leads to emphysema in mice

BACKGROUND

The aim of this study was to uncover the ability of PM2.5 exposure to induce apoptosis in alveolar epithelial cells by stimulating excessive production of reactive oxygen species (ROS), thus activating p38 to result in emphysema in mice.

METHODS

Male BALB/c mice with 6-8-week-old were exposed to 200 TPM mg/L PM2.5 for 12 weeks. Lung tissues of mice were harvested after sacrifice. Hematoxylin and eosin staining was conducted for observing alveolar structure change. Protein levels of p-p38 and p38, as well as ROS level in mouse liver tissues were determined. A549 cells were exposed to different doses of PM2.5, followed by ROS detection, protein level detection of p-p38 and p38, and apoptosis determination. After transfection of si-p38, protein level of clv-caspase3 and apoptotic rate in PM2.5-exposed A549 cells were assessed.

RESULTS

After 12-week exposure to PM2.5, enlarged alveolar space, elevated ROS level in lung tissues and activated p38 were observed in mice. In PM2.5-exposed A549 cells, ROS level, p-p38 expression and apoptotic rate were dose-dependently enhanced. The antioxidant NAC reversed the above changes in PM2.5-exposed A549 cells. Silence of p38 reversed the enhanced clv-claspase3 level and apoptotic rate in PM2.5-exposed A549 cells.

CONCLUSIONS

PM2.5 exposure elevates ROS level in lung tissues, and activates p38, thus leading to apoptosis of alveolar epithelial cells. PM2.5 finally results in the development of emphysema in mice.

Assessment of the Negative Impact of Urban Air Pollution on Population Health Using Machine Learning Method

This study focuses on assessing the level of morbidity among the population of Almaty, Kazakhstan, and investigating its connection with atmospheric air pollution using machine learning algorithms. The use of these algorithms is aimed at analyzing the relationship between air pollution levels and the state of public health, as well as the correlations between COVID-19 infection and the development of respiratory diseases. This study analyzes the respiratory diseases of the population of Almaty and the level of air pollution as a result of suspended particles for the period of 2017-2022. The study includes recommendations to reduce harmful emissions into the atmosphere using machine learning methods. The results of the study show that air pollution is a critical factor affecting the increase in the number of diseases of the respiratory system. The study recommends taking measures to reduce air pollution and improve air quality in order to prevent the development of chronic respiratory diseases. The study offers recommendations to industrial enterprises, traffic management organizations, thermal power plants, the Department of Environmental Protection, and local executive bodies in order to reduce respiratory diseases among the population.

Chronic and acute health effects of PM2.5 exposure and the basis of pollution control targets

Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.

Impact analysis of meteorological variables on PM2.5 pollution in the most polluted cities in China

With the continuous promotion of urbanization in China, air pollution problems have become increasingly prominent in recent years. Various factors, such as emissions, meteorology, and physical and chemical reactions, jointly affect the severity of PM_2.5 pollution to a large extent. This study selected five meteorological variables (planetary boundary layer height (PBLH), wind speed (WS), temperature(T), water vapor mixing ratio(Q), and precipitation (PCP)) for perturbation, and 21 different scenarios were set up. In this study, the effects of changes in a single meteorological variable on the pollutants produced in the area were represented by subtracting the baseline scenario (i.e., without perturbation of meteorological variables) simulated in January 2017 separately from each post-disturbance scenario. The results showed that Handan (HD) has the highest annual mean PM_2.5 concentration of 85.75 μg/m³ in 2017, while all cities in study area exceeded the secondary concentration limit of urban atmospheric particulate matter. The correlation coefficient (R) between the simulation values of models and the actual monitoring values ranges from 0.41 to 0.74, indicating good model performance and acceptable simulation errors. PBLH (±10%-±20%), WS(±10%-±20%), and PCP(±10%-±20%) all showed a single adverse effect among the five meteorological variables, meaning that a reduction in these three factors led to an increase in PM_2.5 concentrations. However, T (±1 K-±1.5 K) and Q (±10%-±20%) could indicate a positive impact under certain conditions. From the sensitivity calculations of single meteorological variables, it is clear that WS, PBLH, and PCP show a highly linear trend in all cities at the 0.01 level of significance. The hypothesis that T changes linearly in 10 cities in the study area is valid, while for Q, the hypothesis that Q changes linearly only occurs in Shijiazhuang and Baoding. When different meteorological variables are disturbed, there are significant spatial differences in the main affected areas of PM_2.5 concentrations. By discussing the impact of meteorological variable disturbance on air quality in critically polluted cities in China, this study identified the meteorological variables that can substantially affect PM_2.5 concentration. The more complex T and Q should be considered when formulating relevant emission measures.

Tracing the sources of PM2.5-related health burden in China

Fine particulate matter (PM2.5) poses a major environmental risk to human health. We estimated PM2.5-related premature deaths in 30 Chinese provinces in 2020 using an integrated exposure response model based on monitored concentrations and obtained regional and sectoral contributions based on the atmospheric transport of the atmospheric transport contribution matrix. From the perspective of regional- and sectoral-scale effects, the results revealed that 740,140 [95% confidence interval (CI):646,538-839,968] premature deaths were related to PM2.5 in 2020, mainly in East (30%), Central (18%), and North (15%) China. Manufacturing activity was found to be the major cause of PM2.5-related premature deaths, accounting for over 50% of the deaths. From the perspective of the interregional atmospheric transport effect, although local emissions were the major source of PM2.5-related premature deaths in all regions, non-local emissions contributed approximately 30%. The overall trend in the net atmospheric transport direction was from north to south. In particular, the Guangdong, Guangxi, and Hainan provinces of South China received contributions of more than 40% from non-local provinces, mainly from the East and Central China. Combined with economic data, the regions and sectors with the highest PM2.5-related premature deaths per unit output or consumption include the manufacturing and household sectors in North and Northeast China and transportation, agriculture, and electricity in Central China. Therefore, from the perspective of the above three impacts, although the potential impact of PM2.5 pollution on health in China has decreased with the decrease in PM2.5 concentration in the past decade owing to strict air pollution control, the central and northern parts of China are still the key areas requiring air pollution control. The health impacts of air pollution associated with the rapid development of China's manufacturing industry in the post-pandemic era cannot be ignored.

Assessment of health risk and burden of disease induced by exposure to benzene, toluene, ethylbenzene, and xylene in the outdoor air in Tehran, Iran

The health risk and burden of disease induced by exposure to benzene, toluene, ethylbenzene, and xylene (BTEX) in the outdoor air in Tehran, 2019 were assessed based on the data of five fixed stations with weekly BTEX measurements. The non-carcinogenic risk, carcinogenic risk, and disease burden from exposure to BTEX compounds were determined by hazard index (HI), incremental lifetime cancer risk (ILCR), and disability-adjusted life year (DALY), respectively. The average annual concentrations of benzene, toluene, ethylbenzene, and xylene in the outdoor air in Tehran were 6.59, 21.62, 4.68, and 20.88 μg/m³, respectively. The lowest seasonal BTEX concentrations were observed in spring and the highest ones occurred in summer. The HI values of BTEX in the outdoor air in Tehran by district ranged from 0.34 to 0.58 (less than one). The average ILCR values of benzene and ethylbenzene were 5.37 × 10^-5 and 1.23 × 10^-5, respectively (in the range of probable increased cancer risk). The DALYs, death, DALY rate (per 100,000 people) and death rate (per 100,000 people) induced by BTEX exposure in the outdoor air in Tehran were determined to be 180.21, 3.51, 2.07, and 0.04, respectively. The five highest attributable DALY rates in Tehran by district were observed in the districts 10 (2.60), 11 (2.43), 17 (2.41), 20 (2.32), and 9 (2.32), respectively. The corrective measures such as controlling road traffic and improving the quality of vehicles and gasoline in Tehran could reduce the burden of disease from BTEX along with the health effects of other outdoor air pollutants.

PM2.5 promotes pulmonary fibrosis by mitochondrial dysfunction

Pulmonary fibrosis is known as an incurable lung disorder with irreversible progression of chronic injury, myofibroblast proliferation, extracellular matrix (ECM) accumulation, and tissue scarring. Atmospheric particulate matter 2.5 (PM_2.5 ) is implicated as a risk factor of several diseases, especially lung diseases such as pulmonary fibrosis. The molecular mechanism which participates PM_2.5 -induced pulmonary fibrosis in type II alveolar cells (AEII) has yet to be determined. Our results proved that short- and long-term exposure to PM_2.5 significantly stimulated epithelial-mesenchymal transition (EMT) activity in AEII cells, according to, changes in gene signature analyzed by RNA-seq and cell morphology. Furthermore, Gene Ontology (GO) enrichment analysis also suggested that mitochondrial dysfunction was related to progression of pulmonary fibrosis in AEII after PM_2.5 exposure. We observed a marked decline in mitochondria membrane potential (MMP), as well as fragmented mitochondria, in AEII cells exposed to PM_2.5 , which suggests that energy metabolism is suppressed after PM_2.5 exposure. We also confirmed that PM_2.5 exposure could influence the expression levels of Mfn1, Mfn2, and Drp1 in AEII. Pretreatment of mitochondrial fusion promoter M1 was able to reverse mitochondrial dysfunction as well as EMT in AEII. These data suggested the key role of mitochondrial fragmentation in AEII, which was induced by PM_2.5 exposure, and participated pathogenesis of pulmonary fibrosis. Finally, we investigated the response of lung tissue exposed to PM_2.5 in vivo. The data indicated that the lung tissue exposed to PM_2.5 obviously induced collagen accumulation. Moreover, IHC results revealed that PM_2.5 enhanced Drp1 expression but suppressed Mfn1 and Mfn2 expression in lung tissue. The current study provides novel insight of pulmonary fibrosis caused by PM_2.5 exposure.

Association of long-term particulate matter exposure with all-cause mortality among patients with ovarian cancer: A prospective cohort

BACKGROUND

Evidence of the association between particles with a diameter of 2.5 μm or less (PM_2.5) in long term and ovarian cancer (OC) mortality is limited.

METHODS

This prospective cohort study analyzed data collected between 2015 and 2020 from 610 newly diagnosed OC patients, aged 18-79 years. The residential average PM_2.5 concentrations 10 years before the date of OC diagnosis were assessed by random forest models at a 1 km × 1 km resolution. Cox proportional hazard models fully adjusted for the covariates (including age at diagnosis, education, physical activity, kitchen ventilation, FIGO stage, and comorbidities) and distributed lag non-linear models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) of PM_2.5 and all-cause mortality of OC.

RESULTS

During a median follow-up of 37.6 months (interquartile: 24.8-50.5 months), 118 (19.34 %) deaths were confirmed among 610 OC patients. One-year PM_2.5 exposure levels before OC diagnosis was significantly associated with an increase in all-cause mortality among OC patients (single-pollutant model: HR = 1.22, 95 % CI: 1.02-1.46; multi-pollutant models: HR = 1.38, 95 % CI: 1.10-1.72). Furthermore, during 1 to 10 years prior to diagnosis, the lag-specific effect of long-term PM_2.5 exposure on the all-cause mortality of OC had a risk increase for lag 1-6 years, and the exposure-response relationship was linear. Of note, significant interactions between several immunological indicators as well as solid fuel use for cooking and ambient PM_2.5 concentrations were observed.

CONCLUSION

Higher ambient PM_2.5 concentrations were associated with an increased risk of all-cause mortality among OC patients, and there was a lag effect in long-term PM_2.5 exposure.

MitoQ ameliorates PM2.5-induced pulmonary fibrosis through regulating the mitochondria DNA homeostasis

Pulmonary fibrosis is a severe pulmonary disease, and may related to PM_2.5 exposure. Our study aims to explore the pathogenesis of PM_2.5-induced pulmonary fibrosis, and MitoQ protective effect in this process. Our results find that inflammatory cells aggregation and pulmonary fibrosis in mice lung after PM_2.5 exposure. Moreover, Collagen I/III overproduction, EMT and TGF-β1/Smad2 pathway activation in mice lung and BEAS-2B after PM_2.5 exposure. Fortunately, these changes were partially ameliorated after MitoQ treatment. Meanwhile, severe oxidative stress, mitochondrial homeostasis imbalance, overproduction of 8-oxoG (7,8-dihydro-8-oxoguanine), as well as the inhibition of SIRT3/OGG1 pathway have founded in mice lung or BEAS-2B after PM_2.5 exposure, which were alleviated by MitoQ treatment. Collectively, our study found that oxidative stress, especially mitochondrial oxidative stress participates in the PM_2.5-induced pulmonary fibrosis, and MitoQ intervention had a protective effect on this progress. Moreover, mitochondrial DNA homeostasis might participate in the pulmonary fibrosis caused by PM_2.5 exposure. Our study provides a novel pathogenesis of PM_2.5-caused pulmonary fibrosis and a possible targeted therapy for the pulmonary diseases triggered by PM_2.5.

Association between exposure to ambient PM2.5 and the health status in the mobile population from 338 cities in China

There are limited studies investigating the relationship between exposure to PM_2.5 and the health status among the mobile population. A cross-sectional analysis was performed in a nationally representative sample (2017 China Migrants Dynamic Survey data) consisting of 169,469 mobile population. The ordered logistic regression model was used to examine the association between PM_2.5 and the health status in mobile population. Stratified analyses were performed to identify whether the association varied across gender, age group, and regions in China. Overall, every 10 μg/m³ increment in annual average PM_2.5 was associated with increased risk of poor self-reported health (OR = 1.021, 95% CI: 1.012-1.030). Mobile population aged 31-49 years and living in the central region suffers the highest PM_2.5-associated health risk (OR = 1.030, 95% CI: 1.019-1.042; OR = 1.095, 95% CI: 1.075-1.116). Our study suggests that PM_2.5 exposure was associated with an increased risk of poor self-reported health in mobile population, particularly among the population aged 31-49 years and people living in the central region of China. Policymakers should pay more attention to the vulnerable mobile population to tackle the health burden of ambient air pollution.

Changes in healthy effects and economic burden of PM2.5 in Beijing after COVID-19

The COVID-19 lockdown had a positive control effect on urban air quality. However, this effect remains uncertain after the epidemic enters regular management, and furthermore, only limited data are available regarding urban PM_2.5 (aerodynamic diameter ≤ 2.5μm) under the impact of the epidemic. We used daily ambient PM_2.5 concentration data in Beijing to compare and analyze the changes in urban PM_2.5 concentrations before and after the COVID-19 epidemic and to estimate the healthy effects and economic burden associated with PM_2.5 before and after the epidemic. The study found that COVID-19 has a significant impact on the urban environmental PM_2.5 concentration, which is manifested by the decrease in the PM_2.5 concentration in Beijing during the epidemic by 27.8%. Exposure-response models estimated 56.443 (95% CI: 43.084-69.893) thousand people die prematurely in Beijing during the COVID-19 epidemic attributed to long-term PM_2.5 exposure, with a 13.3% decrease in the number of premature deaths year-on-year. The total healthy economic losses attributable to PM_2.5 in Beijing during the COVID-19 epidemic were 35.76 (95% CI: 28.41-42.44) billion yuan, with a per capita loss of 816.8 yuan. Strict control measures throughout the COVID-19 epidemic had a positive impact on air quality in Beijing, with a decrease in both premature deaths and economic healthy losses attributable to fine particles. This paper helps to enrich and expand the research on the impact of COVID-19 on the urban environment and provides a basis for formulating policies related to air quality improvement in the post-epidemic era.

Associations between air pollutants and hospital admissions for chronic obstructive pulmonary disease in Jinan: potential benefits from air quality improvements

Evidence between air pollution and chronic obstructive pulmonary disease (COPD) is inconsistent and limited in China. In this study, we aim to examine the associations between air pollutants and hospital admissions for COPD, hoping to provide practical advice for prevention and control of COPD. Hospital admissions for COPD were collected from a Grade-A tertiary hospital in Jinan from 2014 to 2020. A generalized additive model (GAM) was used to examine the associations between air pollutants and hospital admissions for COPD. Stratified analysis was also conducted for gender, age (20-74 and ≥75 years), and season (warm and cold). The avoidable number of COPD hospital admissions was calculated when air pollutants were controlled under national and WHO standards. Over the study period, a total of 4,012 hospital admissions for COPD were recorded. The daily hospital admissions of COPD increased by 2.36% (95%CI: 0.13-4.65%) and 2.39% (95%CI: 0.19-4.65%) for per 10 μg/m³ increase of NO₂ and SO₂ concentrations at lag2, respectively. There was no statistically significant difference in health effects caused by increased concentrations of PM_2.5, PM₁₀, CO, and O₃. The health effects of increased SO₂ concentration were stronger in women, the ≥75 years old people and the cold season. About 2 (95%CI: 0-3), 64 (95%CI: 4-132) and 86 (95%CI: 6-177) COPD admissions would be avoided when the SO₂ concentration was controlled below the NAAQS-II (150 μg/m³), NAAQS-I (50 μg/m³), and WHO's AQG2021 standard (40 μg/m³), respectively. These findings suggest that short-term exposure to NO₂ and SO₂ was associated with increased risks of daily COPD admissions, especially for females and the elderly. The control of SO₂ and NO₂ under the national and WHO standards could avoid more COPD admissions and obtain greater health benefits.

Effects of shared governance and cost redistribution on air pollution control: a study of game theory-based cooperation

This study seeks cost-effective strategies for PM2.5 reduction to generate insights into minimizing pollution abatement costs subject to different scenarios. This study theorizes that the cooperation of PM2.5 abatement has potential gains for participants and develop an empirical way to compare the costs and efficiency of PM2.5 abatement involving the variation of environmental conditions. This study revises the cooperative game model in the context of threshold effects using data obtained from the Beijing-Tianjin-Hebei metropolitan cluster in China. In general, the results support the key assertion that cooperation in the metropolitan cluster plays a vital role in optimizing the efficiency and costs of PM2.5 abatement. In addition to extending the application of the revised model, this study provides a way to estimate the costs and the mitigation benefits of meeting the pollution targets for each coparticipant and take the scenario of multiparty cooperation into account as well as the scenarios involving other types of pollutants. The empirical findings have important policy implications for regional shared governance, decentralization, and resource reallocation. Economic incentive-based shared governance and cost reallocation work better than traditional regulations.

Air Purifier Intervention to Remove Indoor PM2.5 in Urban China: A Cost-Effectiveness and Health Inequality Impact Study

Using air purifiers is an intervention to reduce exposure to fine particulate matter (PM_2.5) for health benefits. We performed a comprehensive simulation in urban China to estimate the cost-effectiveness of long-term use of air purifiers to remove indoor PM_2.5 from indoor and ambient air pollution in five intervention scenarios (S1-S5), where the indoor PM_2.5 targets were 35, 25, 15, 10, and 5 μg/m³, respectively. In scenarios S1 to S5, 5221 (95% uncertainty interval: 3886-6091), 6178 (4554-7242), 8599 (6255-10,109), 11,006 (7962-13,013), and 14,990 (10,888-17,610) thousand disability-adjusted-life-years (DALYs) can be avoided at the cost of 201 (199-204), 240 (238-243), 364 (360-369), 522 (515-530), and 921 (905-939) billion Chinese Yuan (CNY), respectively. A high disparity in per capita health benefits and costs was observed by city, which expanded with the decrease of the indoor PM_2.5 target. The net benefits of using purifiers in cities varied across scenarios. Cities with a lower ratio of annual average outdoor PM_2.5 concentration to gross domestic product (GDP) per capita tended to achieve higher net benefits in the scenario with a lower indoor PM_2.5 target. Controlling ambient PM_2.5 pollution and developing the economy can reduce the inequality in air purifier use across China.

Intrinsic atmospheric circulation patterns associated with high PM2.5 concentration days in South Korea during the cold season

Based on observation data and a novel K-mean clustering method, we investigated whether intrinsic atmospheric circulation patterns are related with the occurrence of high particulate matter (PM) concentration days (diameters less than or equal to 2.5 μm (PM_2.5)), in Seoul, South Korea, during the cold season (December to March). A simple composite map shows that weak horizontal and vertical ventilation over the Korean Peninsula can cause high PM_2.5 concentration (High_PM_2.5) days. Also, atmospheric circulations are quite different between one day of High_PM_2.5 and periods longer than two days. We also found that two intrinsic atmospheric circulation patterns in Asia, which were obtained by adopting K-mean clustering to the daily 850 hPa geopotential height anomalies for 2005-2020, were associated with High_PM_2.5 days. These results indicate that High_PM_2.5 days in Seoul, South Korea, occur as a result of intrinsic atmospheric circulation patterns, therefore, they are unavoidable unless the anthropogenic emission sources over the Korean Peninsula, East Asia, or both are reduced. In addition, these two intrinsic atmospheric circulation patterns are more prominent for periods longer than two days while there are no favorable intrinsic atmospheric circulation patterns to induce one day of High_PM_2.5, which indicates that a single day of High_PM_2.5 tends to occur by a stochastic atmospheric circulation rather than the intrinsic atmospheric circulation patterns.

Ozone exposure and health risks of different age structures in major urban agglomerations in People's Republic of China from 2013 to 2018

High concentration of surface ozone (O₃) will cause health risks to people. In order to analyze the spatiotemporal characteristics of O₃ and assess O₃ exposure and health risks for different age groups in China, we applied multiple methods including standard deviation ellipse, spatial autocorrelation, and exposure-response functions. Results show that O₃ concentrations increased in 64.5% of areas in China from 2013 to 2018. The central plain urban agglomeration (CPU), Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD) witnessed the greatest incremental rates of O₃ by 16.7%, 14.3%, and 13.1%. Spatially, the trend of O₃ shows a significant positive autocorrelation, and high trend values primarily in central and east China. The proportion of the total population exposed to high O₃ (above 160 μg/m³) increased annually. Compared to 2013, the proportion of the young, adult, and old populations exposed to high O₃ increased to different extents in 2018 by 26.8%, 29.6%, and 27.2%, respectively. The extent of population exposure risk areas in China expanded in size, particularly in north and east China. The total premature respiratory mortalities attributable to long-term O₃ exposure in six urban agglomerations were about 177,000 in 2018 which has increased by 16.4% compared to that in 2013. Among different age groups, old people are more vulnerable to O₃ pollution, so we need to strengthen their relevant health protection of them.

Changes in PM2.5-related health burden in China's poverty and non-poverty areas during 2000-2020: A health inequality perspective

China suffers from severe PM_2.5 pollution that has resulted in a huge health burden. Such PM_2.5-related health burden has long been suspected to differ between China's poverty-stricken areas (PAs) and non-poverty-stricken areas (NPAs). Yet, evidence-based examination of this long-held belief, which is critical as a barrier of environmental injustice to advancing China's sustainability, is still missing. Here our study shows that the PM_2.5 pollution is more serious in China's NPAs than PAs-with their annual averages being respectively 54.83 μg/m³ and 43.63 μg/m³-causing higher premature mortality in the NPAs. Compared to economic inequality, China's total PM_2.5-related premature mortality was relatively evenly distributed during 2000-2015 across regions of varying levels of gross domestic product (GDP) per capita but increased slightly in 2015-2020 owing to the dramatic change in age structure. The elderly population increased by 31 %. PM_2.5-related premature deaths were more severe for populations of low socioeconomic status, and such environmental health inequalities could be amplified by population aging. Additionally, population migration from China's PAs to developed cities contributed to 638, 779, 303, 954, and 896 premature deaths in 2000, 2005, 2010, 2015, and 2020, respectively. Changes in the age structure (53 %) and PM_2.5 concentration (28 %) had the greatest impact on premature deaths, followed by changes in population (12 %) and baseline mortality (8 %). The contribution rate of changes in the age structure and PM_2.5 concentration was higher in PAs than in NPAs. Our findings provide insight into PM_2.5-related premature death and environmental inequality, and may inform more equitable clean air policies to achieve China's sustainable development goals.

Characteristics, sources of volatile organic compounds, and their contributions to secondary air pollution during different periods in Beijing, China

Continuous measurements of volatile organic compounds (VOCs), ozone (O₃), fine particulate matter (PM_2.5), and related parameters were conducted between April 2020 and March 2021 in Beijing, China, to characterize potential sources of VOCs and their impacts on secondary organic aerosols (SOAs) and O₃ levels. The annual average mixing ratio of VOCs was 17.4 ± 10.1 ppbv, with monthly averages ranging from 11.6 to 25.2 ppbv. According to the empirical kinetic modeling approach (EKMA), O₃ formation during O₃ season was "VOCs-limited", while it was in a "transition" regime during O₃ pollution episodes. In the O₃ season, higher ozone formation potential (OFP) of m/p-xylene, o-xylene, toluene, isopentane, and n-butane were evident during O₃ pollution episodes, in line with the increasing contributions of solvent usage and coating, as well as gasoline evaporation to OFP obtained through a matrix factorization model (PMF). Aromatics contributed the most to the secondary organic aerosol formation potential (SOAFP). In the non-O₃ season, the contribution of vehicle exhaust to SOAFP elevated on hazy days, thereby revealing the importance of traffic-derived VOCs for PM_2.5 pollution. Our results indicate that the prior control of different VOC sources should vary by season, thereby facilitating the synergistic control of O₃ and PM_2.5 in Beijing.

Effect of urban form on PM2.5 concentrations in urban agglomerations of China: Insights from different urbanization levels and seasons

Planned urban form has become an important strategy to improve air quality in urban agglomerations (UAs), especially pollution due to PM_2.5, but the influencing mechanisms are not yet clear. This study explores the relationship between four metrics of urban form (size, fragmentation, shape, and dispersion) as determined by analysis of remotely sensed images at 30-m resolution and PM_2.5 concentrations in 19 Chinese UAs. The influence of level of urban development and season is examined. Five control variables, including population density, temperature, precipitation, wind speed, and the normalized difference vegetation index (NDVI) are selected for use in multiple linear regression models. Size, fragmentation, and shape of urban form, but not dispersion, were found to have significant effects on PM_2.5 concentrations of different urbanization-level UAs. Urban size and fragmentation have stronger impacts on PM_2.5 concentrations in UAs with lower urbanization levels while urban shape has a greater impact in higher-level UAs. In terms of seasonal variation in all UAs, urban form is more pronouncedly associated with PM_2.5 concentrations during spring and autumn than summer and winter. Urban size and fragmentation are positively associated with PM_2.5 concentrations whereas urban shape and dispersion are on the contrary. The relationships between urban form and PM_2.5 uncovered here underscore the importance of urban planning as a tool to minimize PM_2.5 pollution. Specifically, local government should encourage polycentric urban form with lower fragmentation in urban agglomerations. UAs with lower urbanization levels should control the disordered expansion of construction land and higher-level UAs should promote the mix of green land and construction land. Moreover, measures to control air pollution from anthropogenic activities in spring, autumn and winter are likely to be more effective in decreasing PM_2.5 concentrations in UAs.

Analyzing the socioeconomic determinants of PM2.5 air pollution at the global level

Since PM2.5 pollution has jeopardized public health, the research on how ambient fine particulate matter (PM2.5) concentrations are influenced has been increasingly important for the implementation of regional PM2.5 concentration reduction. This study analyzed the socioeconomic determinants of PM2.5 air pollution of 132 countries/economies. It was found that the main inhibitor for the PM2.5 air pollution is the emission intensity (EmI), which is measured by the PM2.5 emission when a united of energy is consumed, in every income level of countries, while the energy intensity (EnI) is the second inhibitor. Meanwhile, economic output (EO) was the largest driving factor on the PM2.5 concentrations, while population (P) growth was the second. Overall, the national employment rate (Emp) showed very little impact on the countries. This study also analyzed the income-based variation in the effects of the five factors on PM2.5 concentration changes: overall, the effects of the determinants all decreased with the rise of income levels, i.e., both the inhibiting effects of PM2.5 EmI and EnI and driving effects of EO and P performed stronger in lower-income countries than higher-income ones. Regarding the income-based variation of the determinants, this study also discussed the policy implications, such as adopting technologies on reducing PM2.5 intensity and EnI, transferring the EO from the manufacturing industry to the service industry, and international organizations on public health and environmental protection should provide targeted strategies, guidelines, and other assistances to lower-income countries as both driving and inhibiting factors performed more influential on their PM2.5 concentration changes.

Effects of green spaces on alleviating mortality attributable to PM2.5 in China

Increasing research suggested that green spaces are associated with many health benefits, but evidence for the quantitative relationship between green spaces and mortality attributable to particulate matter with an aerodynamic diameter of 2.5 μm or less (PM_2.5) is limited. We collected disease-specific mortality and PM_2.5 data for a period of 4 years (2015-2018) along with green space data for an 8-year duration (2010-2017) in 31 provincial-level administrative regions of China. First, this study used the Integrated Exposure-Response model to estimate the mortality of four diseases attributable to PM_2.5, including chronic obstructive pulmonary diseases (COPD), lung cancer (LC), ischemic heart disease (IHD), and cerebrovascular disease (CBVD). Then we performed linear regression and mixed-effects model to investigate the counteracting effect of green spaces on death caused by PM_2.5 exposure. The differences in impacts among the Eastern, Central, and Western regions were explored using stratified analysis. The most significant results from linear regression analysis indicated that per 100 km² of green spaces increase, there was a decreased total mortality (10^-5) (COPD, LC, IHD, and CBVD) attributable to PM_2.5 by - 4.012 [95% confidence interval (CI): - 5.535, - 2.488], while the reduction by mixed-linear regression analysis was - 2.702/10⁵ (95% CI =  - 3.645, - 1.759). Of all hysteresis analyses, the effect estimates (β) at lag3 and lag4 were the largest. The effect of green spaces was more advantageous when targeting CBVD and the Eastern region. We found a negative correlation between green space exposure and mortality attributable to PM_2.5, which can provide further support for city planners, government personnel, and others to build a healthier city and achieve national health goals.

Surface ozone pollution in China: Trends, exposure risks, and drivers

Introduction

Within the context of the yearly improvement of particulate matter (PM) pollution in Chinese cities, Surface ozone (O₃) concentrations are increasing instead of decreasing and are becoming the second most important air pollutant after PM. Long-term exposure to high concentrations of O₃ can have adverse effects on human health. In-depth investigation of the spatiotemporal patterns, exposure risks, and drivers of O₃ is relevant for assessing the future health burden of O₃ pollution and implementing air pollution control policies in China.

Methods

Based on high-resolution O₃ concentration reanalysis data, we investigated the spatial and temporal patterns, population exposure risks, and dominant drivers of O₃ pollution in China from 2013 to 2018 utilizing trend analysis methods, spatial clustering models, exposure-response functions, and multi-scale geographically weighted regression models (MGWR).

Results

The results show that the annual average O₃ concentration in China increased significantly at a rate of 1.84 μg/m³/year from 2013 to 2018 (160 μg/m³) in China increased from 1.2% in 2013 to 28.9% in 2018, and over 20,000 people suffered premature death from respiratory diseases attributed to O₃ exposure each year. Thus, the sustained increase in O₃ concentrations in China is an important factor contributing to the increasing threat to human health. Furthermore, the results of spatial regression models indicate that population, the share of secondary industry in GDP, NOx emissions, temperature, average wind speed, and relative humidity are important determinants of O₃ concentration variation and significant spatial differences are observed.

Discussion

The spatial differences of drivers result in the spatial heterogeneity of O₃ concentration and exposure risks in China. Therefore, the O₃ control policies adapted to various regions should be formulated in the future O₃ regulation process in China.

Effect of long-term exposure to PM2.5 on the risk of type 2 diabetes and arthritis in type 2 diabetes patients: Evidence from a national cohort in China

BACKGROUND

It remains unclear whether type 2 diabetes and the complication of arthritis are causally related to the PM_2.5 pollutant. Therefore, we aimed to investigate the associations of long-term PM_2.5 exposure with type 2 diabetes and with arthritis in type 2 diabetes patients.

MATERIALS AND METHODS

This study used data from the China Health and Retirement Longitudinal Survey (CHARLS) implemented during 2011-2018. The associations were analyzed by Cox proportional hazards regression models, and the population-attributable fraction (PAF) was calculated to assess the burden of type 2 diabetes and arthritis-attributable to PM_2.5.

RESULTS

A total of 21,075 participants were finally included, with 19,121 analyzed for PM_2.5 and type 2 diabetes risk and 12,427 analyzed for PM_2.5 and arthritis risk, of which 1,382 with newly-diagnosed type 2 diabetes and 1,328 with arthritis during the follow-up. Overall, each 10 μg/m³ increment in PM_2.5 concentration was significantly associated with an increase in the risk of type 2 diabetes (HR = 1.26, 95 %CI1.22 to 1.31), and the PAF of type 2 diabetes attributable to PM_2.5 was 13.54 %. In type 2 diabetes patients, each 10 μg/m³ increment in PM_2.5 exposure was associated with an increase in arthritis (HR = 1.42, 95 %CI: 1.28 to 1.57), and the association was significantly greater than that (H = 1.23, 95 %CI: 1.19 to 1.28) in adults without type 2 diabetes. The PAFs of arthritis-attributable to PM_2.5 in participants with and without type 2 diabetes were 18.54 % and 10.69 %, respectively.

CONCLUSION

Long-term exposure to PM_2.5 may increase the risk of type 2 diabetes and make type 2 diabetes patients susceptible to arthritis.

Air pollution-induced health impacts and health economic losses in China driven by US demand exports

Understanding how trade between regions or countries drives the transfer of air pollution has attracted considerable interest recently, but few studies have explored the various transfer pathways or evaluated economic losses due to the health impact of such air pollution. Here, we assess the air pollutant emissions and related health impacts and economic losses in China caused by export trade due to US demand by combining the linked multi-regional input-output (MRIO) model, GEOS-Chem model, integrated exposure-response model, and the willingness to pay method. We show that the air pollutant emissions embedded in China's export due to the US demand reached 5792.38 Kt in 2012 (2.48% of the total), which includes direct exports of intermediate (40.27%) and final (33.61%) products and indirect exports of intermediate products via domestic provinces (16.43%, domestic spillover) and other countries (9.69%, foreign spillover). The resulting increase in PM_2.5 (<2.8 μg m^-3) leads to additional 27,963 deaths in 30 provinces, with a higher death toll in coastal areas and the corresponding economic loss was higher in more developed regions and reached USD 2.08 billion. This study highlights the region-different air pollution and health impacts in China embedded in the US-demand trade, and provides a framework for the analysis of health and economic losses hidden in global trade, particularly between developing and developed countries.

Population Aging Driven Slowdown in the Reduction of Economic Cost-Attributed to PM2.5 Pollution after 2013 in China

Since seniors are more susceptible to ambient fine particulate matter (PM2.5), the high economic cost to protect the aged population from PM2.5 exposure is expected. Significant efforts have been made in China to mitigate PM2.5 since 2013 under the Air Pollution Prevention and Control Action (APPCA) Plan, which remarkably reduced PM2.5 contamination and its associated economic and health burdens. However, to what extent population aging could influence the economic benefits from the APPCA Plan is unclear. Here, we estimate five driving factors contributing to the economic cost of mortality attributable to PM2.5 pollution. The results show that the economic cost attributed to PM2.5 pollution increased from 1980 to 2013 and decreased from 2013 to 2019 in China, benefiting from the APPCA Plan. Since 2013, population aging becomes the most significant positive driver that almost offsets declining economic cost from significantly declining PM2.5. Rapid aging has become an enormous burden to PM2.5-associated health and economic loss. Our findings suggest that we should further improve air quality and enhance health care for the elderly population.