Long-term trend and spatial pattern of PM2.5 induced premature mortality in China

Identification and Time Series Analysis of PM2.5 and O3 Associated Health Risk Prevention and Control Areas

Air pollution of PM2.5 and O3 is a global health concern. Traditional approaches for identifying air pollution control areas mainly relied on pollutant concentrations, neglecting population distribution and exposure. This study proposes a method to divide these areas from a health risk perspective, comparing their objectivity and rationality with the government-defined key regions. The results show that for PM2.5, the health risk population and average risk rates in the prevention and control areas were 0.993 million (0.1286%), 1.030 million (0.1283%), and 1.023 million (0.1202%) in 2010, 2015, and 2020, significantly higher than in the key areas: 0.778 million (0.1252%), 0.834 million (0.1278%), and 0.825 million (0.1212%). Similarly, for O3, the figures in the prevention and control areas were 0.096 million (0.01228%), 0.095 million (0.01243%), and 0.110 million (0.01316%), also higher than in the key areas: 0.0757 million (0.01218%), 0.078 million (0.01189%), and 0.090 million (0.01315%). Additionally, the Gini coefficients for PM2.5, O3, and overall health risks in the prevention and control areas were lower (0.182, 0.203, 0.284) compared to those in the key areas (0.207, 0.216, 0.292). This study provides a method for defining air pollution control regions based on health risks, offering significant insights for pollution zoning and prevention strategies.

PM2.5 concentration prediction using a whale optimization algorithm based hybrid deep learning model in Beijing, China

PM2.5 is a significant global atmospheric pollutant impacting visibility, climate, and public health. Accurate prediction of PM2.5 concentrations is critical for assessing air pollution risks and providing early warnings for effective management. This study proposes a novel hybrid machine learning model that combines the whale optimization algorithm (WOA) with a convolutional neural network (CNN), long short-term memory (LSTM), and an attention mechanism (AM) to predict daily PM2.5 concentrations. Tested with meteorological and air pollution daily data from 2014 to 2018, the WOA-CNN-LSTM-AM model demonstrates substantial improvements. It achieves MAE, RMSE, MBE, and R2 values of 14.29, 21.96, -0.23, and 0.93, respectively, showing a reduction in prediction errors by 39% compared to CNN and 34% compared to LSTM models. In the medium-term forecast, the accuracy of the hybrid model is 30%-54% over WOA-CNN-LSTM and 26%-39% over CNN-LSTM-AM. The R2 value decreases by 2.5% from the 1-day to 5-day forecast, maintaining high accuracy. SHAP analysis reveals that NO2 and CO are the primary drivers for PM2.5 predictions. This study provides a reliable tool for short and medium-term PM2.5 prediction and air pollution control.

National and provincial burden of disease attributable to fine particulate matter air pollution in China, 1990-2021: an analysis of data from the Global Burden of Disease Study 2021

BACKGROUND

Fine particulate matter (PM2·5) is the leading environmental risk factor for mortality and disability worldwide. We aimed to evaluate the temporal trend in, and spatial distribution of, the disease burden attributable to PM2·5 in China from 1990 to 2021.

METHODS

Based on the methodology framework and general analytical strategies applied in the Global Burden of Diseases, Injuries, and Risk Factors Study 2021, we calculated the numbers, age-standardised rates, and percentage of deaths and disability-adjusted life-years (DALYs) attributable to PM2·5 air pollution from 1990 to 2021 at the national and provincial level in China, by disease, sex, and age groups. Exposure to PM2·5, including ambient PM2·5 pollution and household PM2·5 pollution from solid fuels, was evaluated across 33 provincial administrative units in China.

FINDINGS

In 2021, 2·3 million (95% uncertainty interval [UI] 1·8-2·9) deaths and 46·7 million (36·6-59·7) DALYs could be attributable to PM2·5 pollution in China, accounting for 19·4% (16·0-23·6) of total deaths and 11·6% (9·4-14·1) of total DALYs. Of these, 1·9 million (95% UI 1·3-2·3) deaths and 37·8 million (26·3-46·5) DALYs resulted from ambient exposure, while 0·4 million (0·1-1·3) deaths and 8·9 million (1·5-27·8) DALYs were due to household exposure from solid fuel use. Stroke, ischaemic heart disease, and chronic obstructive pulmonary disease were the leading three causes. Two peaks in the burden were observed: in children aged younger than 5 years, and in people aged 70 years and older. The percentage of deaths and DALYs due to ambient PM2·5 was higher in men, while that due to household PM2·5 was higher in women. Geographically, the disease burden from ambient PM2·5 was higher in north and northwest China, while that from household PM2·5 was higher in southwest China. From 1990 to 2021, age-standardised death rates attributable to total PM2·5 decreased by 66·0% (95% UI 57·7-73·1) and those attributable to household PM2·5 decreased by 92·2% (76·6-98·7), with larger reductions observed in east and south China. By contrast, the disease burden related to ambient PM2·5 continued to increase and only began to decline in the past decade.

INTERPRETATION

Despite the decline in the disease burden attributable to total PM2·5 in China during 1990-2021, ambient PM2·5 remains a major contributor to mortality and disability. This study highlights considerable spatial heterogeneity across different provinces and provides valuable insights for developing geographically tailored strategies for PM2·5 control and public health promotion in China. Stricter control of ambient air pollution is needed in northern and northwestern regions, while promoting clean cooking energy is more urgently warranted in southwestern areas.

FUNDING

National Natural Science Foundation of China, National Key Research and Development Program of China, Shanghai Municipal Science and Technology Major Project, China Postdoctoral Science Foundation.

Trends and the Role of Gene-Environment Interactions in Idiopathic Membranous Nephropathy in Northern China

INTRODUCTION

Idiopathic membranous nephropathy (iMN) has become one of the most prevalent primary glomerular diseases, with a marked increase in prevalence over the past two decades in northern China. Fine particulate matter (PM2.5) is considered to be associated with this rising prevalence. In this study, we aimed to evaluate the trends of iMN in relation to improved air quality and conduct a cross-sectional study in Hebei province (northern China, near Beijing) to investigate the role of gene-environment interactions in its development.

METHODS

This study established two cohorts. Cohort 1 included 22,937 pathology reports from Peking University First Hospital (2002-2021) to assess iMN prevalence. Cohort 2 comprised 5,635 iMN patients from 11 cities in Hebei province (2009-2013). DNA samples from 374 iMN patients and 1,259 controls were genotyped for SNPs rs4664608 (PLA2R1) and rs2187668 (HLA-DQA1). Patients were stratified by air pollution risk levels. The annual percentage change (APC) and average annual percentage change were estimated using a joinpoint regression model. Gene-environment interactions were analyzed using logistic regression and epinet calculation.

RESULTS

In cohort 1, 5,586 patients with iMN were identified, representing 24.3% of the 22,937 patients from 2002 to 2021. The general population showed a significant increase in iMN proportion with an APC of +12.7% per year from 2002 to 2014 (95% CI: 10.3-17.5, p < 0.001), followed by a decline with an APC of -5.6% per year from 2014 to 2021 (95% CI: -9.6 to -2.6, p < 0.001). In Hebei province, the iMN frequency rose significantly with an APC of +17.6% per year from 2002 to 2016 (95% CI: 14.5-28.6, p < 0.001), peaking at 60%, and then declined with an APC of -5.5% per year from 2016 to 2021 (95% CI: -13.1 to -1.2, p = 0.02). Cohort 2 highlighted significant regional variation in iMN incidence across Hebei province. Geographic exposure to pollution was identified as an independent risk factor for iMN (RR: 1.49, 95% CI: 1.38-1.56, p < 0.001). Gene-environment interaction analysis revealed that patients with risk alleles in the PLA2R1 gene and exposure to risk environments had a markedly increased risk of developing iMN (odds ratio = 38.72, 95% CI: 11.95-125.46, p < 0.01).

CONCLUSION

The annual growth rate of iMN in northern China appears to be slowing down. Gene-environment interactions may have contributed to the previously observed increase in prevalence.

Exploring the mechanism of sesamin for the treatment of PM2.5-induced cardiomyocyte damage based on transcriptomics, network pharmacology and experimental verification

Introduction

Exposure to fine particulate matter (PM2.5) is known to be associated with cardiovascular diseases. Sesamin (Ses) is a natural phenolic compound found in sesame seeds and sesame oil. Ferroptosis is a novel mode of cell death characterised by iron-dependent lipid peroxidation. This study aims to explore whether PM2.5 can induce ferroptosis in H9C2 cells and to investigate the precise protective mechanism of Ses.

Methods

Based on transcriptomic data, PM2.5 may induce ferroptosis in cardiomyocytes. The ferroptosis inducer erastin and ferroptosis inhibitor ferrostatin-1 (Fer-1) were used to illustrate the mechanisms involved in PM2.5-induced H9C2 cell injury. Using network pharmacology, the pharmacological mechanism and potential therapy targets of Ses were explored for the treatment of PM2.5-induced cardiomyocyte injury. H9C2 cells were cultured and pretreated with Fer-1 or different concentrations of Ses, and then cardiomyocyte injury model was established using erastin or PM2.5. Indicators of oxidative responses, including total superoxide dismutase, reduced glutathione, glutathione peroxidase and malondialdehyde, were measured. The expression levels of ferroptosis-related proteins were determined through Western blot analysis.

Results

Results demonstrate that PM2.5 induces ferroptosis in H9C2 cells and Ses exerts a protective effect by suppressing ACSL4-mediated ferroptosis.

Discussion

Overall, these findings elucidate a novel mechanism by which Ses ameliorates the detrimental effects of PM2.5 on cardiomyocytes.

Development of a Method to Determine the Environmental Burden of Diseases and an Application to Identify Factors Driving Changes in the Number of PM2.5-Related Deaths in China between 2000 and 2010

The attributable burden is codetermined by the exposure level and nontarget characteristics. However, the conventional method of health impact assessment based on preestablished exposure-response functions includes only a few well-known characteristics and thus is insufficient to capture the comprehensive variation. We aimed to develop a method to fuse health impact assessment with epidemiological analysis and to identify factors driving baseline risk. The method was applied to identify the factors underlying the change in the number of fine particulate matter (PM2.5) related deaths in China between 2000 and 2010. During the study period, the number of PM2.5-related deaths across mainland China increased by 0.62 (95% CI: 0.57, 0.69) million, with 0.65 (95% CI: 0.47, 0.91) million, 0.55 (95% CI: 0.39, 0.79) million, and 0.11 (95% CI: 0.06, 0.18) million deaths being associated with increased PM2.5 exposure, population aging, and growth in population size, respectively. However, economic growth, urbanization, improvement of welfare services, and improvement of hospital services resulted in 0.25 (95% CI: 0.15, 0.40) million, 0.16 (95% CI: 0.10, 0.27) million, 0.16 (95% CI: 0.09, 0.26) million, and 0.09 (95% CI: 0.05, 0.15) million fewer deaths, respectively. Results indicated that increased exposure was the major driver of the change in the number of PM2.5-related deaths, and economic growth was the main driver of increased resilience to air pollution.

Early-life air pollution and green space exposures as determinants of stunting among children under age five in Sub-Saharan Africa

BACKGROUND

Childhood malnutrition is a major public health issue in Sub-Saharan Africa (SSA) and 61.4 million children under the age of five years in the region are stunted. Although insight from existing studies suggests plausible pathways between ambient air pollution exposure and stunting, there are limited studies on the effect of different ambient air pollutants on stunting among children.

OBJECTIVE

Explore the effect of early-life environmental exposures on stunting among children under the age of five years.

METHODS

In this study, we used pooled health and population data from 33 countries in SSA between 2006 and 2019 and environmental data from the Atmospheric Composition Analysis Group and NASA's GIOVANNI platform. We estimated the association between early-life environmental exposures and stunting in three exposure periods - in-utero (during pregnancy), post-utero (after pregnancy to current age) and cumulative (from pregnancy to current age), using Bayesian hierarchical modelling. We also visualise the likelihood of stunting among children based on their region of residence using Bayesian hierarchical modelling.

RESULTS

The findings show that 33.6% of sampled children were stunted. In-utero PM2.5 was associated with a higher likelihood of stunting (OR = 1.038, CrI = 1.002-1.075). Early-life exposures to nitrogen dioxide and sulphate were robustly associated with stunting among children. The findings also show spatial variation in a high and low likelihood of stunting based on a region of residence.

IMPACT STATEMENT

This study explores the effect of early-life environmental exposures on child growth or stunting among sub-Saharan African children. The study focuses on three exposure windows - pregnancy, after birth and cumulative exposure during pregnancy and after birth. The study also employs spatial analysis to assess the spatial burden of stunted growth in relation to environmental exposures and socioeconomic factors. The findings suggest major air pollutants are associated with stunted growth among children in sub-Saharan Africa.

Projecting non-communicable diseases attributable to air pollution in the climate change era: a systematic review

OBJECTIVES

Climate change is a major global issue with significant consequences, including effects on air quality and human well-being. This review investigated the projection of non-communicable diseases (NCDs) attributable to air pollution under different climate change scenarios.

DESIGN

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 flow checklist. A population-exposure-outcome framework was established. Population referred to the general global population of all ages, the exposure of interest was air pollution and its projection, and the outcome was the occurrence of NCDs attributable to air pollution and burden of disease (BoD) based on the health indices of mortality, morbidity, disability-adjusted life years, years of life lost and years lived with disability.

DATA SOURCES

The Web of Science, Ovid MEDLINE and EBSCOhost databases were searched for articles published from 2005 to 2023.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

The eligible articles were evaluated using the modified scale of a checklist for assessing the quality of ecological studies.

DATA EXTRACTION AND SYNTHESIS

Two reviewers searched, screened and selected the included studies independently using standardised methods. The risk of bias was assessed using the modified scale of a checklist for ecological studies. The results were summarised based on the projection of the BoD of NCDs attributable to air pollution.

RESULTS

This review included 11 studies from various countries. Most studies specifically investigated various air pollutants, specifically particulate matter <2.5 µm (PM2.5), nitrogen oxides and ozone. The studies used coupled-air quality and climate modelling approaches, and mainly projected health effects using the concentration-response function model. The NCDs attributable to air pollution included cardiovascular disease (CVD), respiratory disease, stroke, ischaemic heart disease, coronary heart disease and lower respiratory infections. Notably, the BoD of NCDs attributable to air pollution was projected to decrease in a scenario that promotes reduced air pollution, carbon emissions and land use and sustainable socioeconomics. Contrastingly, the BoD of NCDs was projected to increase in a scenario involving increasing population numbers, social deprivation and an ageing population.

CONCLUSION

The included studies widely reported increased premature mortality, CVD and respiratory disease attributable to PM2.5. Future NCD projection studies should consider emission and population changes in projecting the BoD of NCDs attributable to air pollution in the climate change era.

PROSPERO REGISTRATION NUMBER

CRD42023435288.

The effect of fine particulate matter (PM2.5) pollution on health inequality: an intergenerational perspective

Air pollution poses a serious challenge to public health and simultaneously exacerbating regional & intergenerational health inequality. This research introduces PM2.5 pollution into the intergenerational health transmission model, and estimates its impact on health inequality in China using Ordered Logit Regression (OLR) and Multi-scale Geographically Weighted Regression (MGWR) model. The results indicate that PM2.5 pollution exacerbate the intergenerational health inequality, and its impacts show inconsistency across family income levels, parental health insurance status, and area of residence. Specifically, it is more difficult for offspring in low-income families to escape from the influence of unhealthy family to become upwardly mobile. Additionally, this health inequality is more significant in households in which at least one parent does not have health insurance. Moreover, the intergenerational solidification caused by PM2.5 pollution is higher in the east and lower in the west. Both the PM2.5 level and solidification effect are high in Beijing-Tianjin-Hebei region, Yangtze River Delta region and central areas of China, which is the focus of air pollution management. These findings suggest that more emphasis should be placed on family-based health promotion. In areas with high PM2.5 pollution levels, resources, subsidies and air pollution protection should be provided for less healthy families with lower incomes and no health insurance.

Impacts of ship emissions and sea-land breeze on urban air quality using chemical characterization, source contribution and dispersion model simulation of PM2.5 at Asian seaport

Fine particulate matter (PM2.5) emitted from marine transportation, bulk materials handling at the docks, and dust dispersion has garnered increased attention, particularly in the interface between port and urban areas. This study explored the inter-transport of PM2.5 between Kaohsiung Harbor and neighboring Metro Kaohsiung. Chemical analyses of PM2.5 samples from four sites include water-soluble ions, metallic elements, carbons, anhydrosugars, and organic acids to establish PM2.5's chemical fingerprints. The CALPUFF air dispersion model is employed to simulate the spatiotemporal distribution of PM2.5 in Kaohsiung Harbor and adjacent urban areas. A clear seasonal and diurnal variation of PM2.5 concentrations and chemical composition was observed in both harbor and urban areas. The high correlation of nighttime PM2.5 levels between the port and urban areas suggests inter-transport phenomena. Sea salt spray, ship emissions, secondary aerosols, and heavy fuel-oil boilers exhibit higher levels in the port area than in the urban area. In Metro Kaohsiung, mobile sources, fugitive dust, and waste incinerators emerge as major PM2.5 contributors. Furthermore, sea breeze significantly influences PM2.5 dispersion from Kaohsiung Harbor to Metro Kaohsiung, particularly in the afternoon. The average contribution of PM2.5 from ships' main engines in Kaohsiung Harbor ranges from 2.9% to 5.3%, while auxiliary engines contribute 3.8%-8.3% of PM2.5 in Metro Kaohsiung.

Modification of Food Allergy on the Associations between Early Life Exposure to Size-Specific Particulate Matter and Childhood Allergic Rhinitis

Previous studies have reported the association between particulate matter (PM) and childhood allergic rhinitis (AR). However, it is unclear whether food allergy (FA) modifies the PM-AR association. We aimed at evaluating the effect of the modification of FA on PM-AR association in preschool children. We adopted a cross-sectional study and conducted a questionnaire survey among preschool children aged 3-6 years in 7 cities in China from June 2019 to June 2020 to collect information on AR and FA. We used a combination of multilevel logistic regression and restricted cubic spline functions to quantitatively assess whether FA modifies the associations between size-specific PM exposure (1 × 1 km) and the risk of AR. The adjusted odds ratios (ORs) for AR among the children with FA as per a 10 μg/m3 increase in early life PM1, PM2.5, and PM10 were significantly higher than the corresponding ORs among the children without FA [e.g., OR: 1.58, 95% CI: (1.32, 1.90) vs 1.29, 95% CI: (1.18, 1.41), per 10 μg/m3 increase in PM1]. The interactions between FA and size-specific PM exposure and their effects on AR were statistically significant (all p-int < 0.001). FA, as an important part of the allergic disease progression, may modify the PM-AR association in preschool children.

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.

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.

Measuring the urban-rural and spatiotemporal heterogeneity of the drivers of PM2.5-attributed health burdens in China from 2008 to 2021 using high-resolution dataset

Urbanization has been considered a driver of PM2.5 pollution and the attributed health burden. This study systematically measured the spatiotemporal and urban-rural heterogeneity of PM2.5-attributed health burden drivers, including income, population, baseline mortality rate, and PM2.5 level. The results reveal the significantly positive contribution of disposable income and the periodical and urban-rural differentiation of population contribution to PM2.5-attributed health burden. The difference in driver performance due to socioeconomic development and urbanization stages might be an important determinant for different or even opposite results of previous studies. Policymaking for mitigating PM2.5-attributed health risk could incorporate the re-assessment and driver determination for PM2.5-attributed health burden into the construction and development plan from the overall urbanization perspective. The urbanization-perspective driver decomposition could be synergized with the flow analysis, equality evaluation, and policy benefit estimation to achieve further direction-determining and quantitative assessment of the urban-rural PM2.5 health risk management strategies.

Analysis of severe ozone-related human health and weather influence over China in 2019 based on a high-resolution dataset

Ozone pollution in 2019 in China is particularly severe posing a tremendous threat to the health of Chinese inhabitants. In this study, we constructed a more reliable and accurate 1-km gridded dataset for 2019 with as many sites as possible using the inverse distance weight interpolation method to analyze spatiotemporal ozone pollution characteristics and health burden attributed to ozone exposure from the perspective of different diseases and weather influence. The accuracy of this new dataset is higher than other public datasets, with the coefficient of determination of 0.84 and root-mean-square error of 8.77 ppb through the validation of 300 external sites which were never used for establishing retrieval methods by the datasets mentioned-above. The averaged MDA8 (the daily maximum 8 h average) ozone concentrations over China was 43.5 ppb, and during April-July, 83.9% of total grids occurred peak-month ozone concentrations. Overall, the highest averaged exceedance days (60 days) and population-weighted ozone concentrations (55.0 ppb) both concentrated in central-eastern China including 9 provinces (only 11.4% of the national territory); meanwhile, all-cause premature deaths attributable to ozone exposure reached up to 142,000 (54.9% of national total deaths) with higher deaths for cardiovascular and respiratory, and the provincial per capita premature mortality was 0.27~0.44‰. The six most polluted weather types in the central-eastern China are in order as follows: westerly (SW and W), cyclonic, northerly, and southerly (NW, N, and S) types, which accounts for approximately 73.2% of health burden attributed to daily ozone exposure and poses the greatest public health risk with mean daily premature deaths ranging from 466 to 610. Our findings could provide an effective support for regional ozone pollution control and public health management in China.

Short-term effect of particulate matter on lung function and impulse oscillometry system (IOS) parameters of chronic obstructive pulmonary disease (COPD) in Beijing, China

OBJECTIVE

This study aimed to evaluate the associations between particulate matter (PM), lung function and Impulse Oscillometry System (IOS) parameters in chronic obstructive pulmonary disease (COPD) patients and identity effects between different regions in Beijing, China.

METHODS

In this retrospective study, we recruited 1348 outpatients who visited hospitals between January 2016 and December 2019. Ambient air pollutant data were obtained from the central monitoring stations nearest the participants' residential addresses. We analyzed the effect of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM_2.5) exposure on lung function and IOS parameters using a multiple linear regression model, adjusting for sex, smoking history, education level, age, body mass index (BMI), mean temperature, and relative humidity .

RESULTS

The results showed a relationship between PM_2.5, lung function and IOS parameters. An increase of 10 µg/m³ in PM_2.5 was associated with a decline of 2.083% (95% CI: -3.047 to - 1.103) in forced expiratory volume in one second /predict (FEV₁%pred), a decline of 193 ml/s (95% CI: -258 to - 43) in peak expiratory flow (PEF), a decline of 0.932% (95% CI: -1.518 to - 0.342) in maximal mid-expiratory flow (MMEF); an increase of 0.732 Hz (95% CI: 0.313 to 1.148) in resonant frequency (F_res), an increase of 36 kpa/(ml/s) (95% CI: 14 to 57) in impedance at 5 Hz (Z₅) and an increase of 31 kpa/(ml/s) (95% CI: 2 to 54) in respiratory impedance at 5 Hz (R₅). Compared to patients in the central district, those in the southern district had lower FEV₁/FVC, FEV₁%pred, PEF, FEF_75%, MMEF, X₅, and higher F_res, Z₅ and R₅ (p < 0.05).

CONCLUSION

Short-term exposure to PM_2.5 was associated with reductions in lung function indices and an increase in IOS results in patients with COPD. The heavier the PM_2.5, the more severe of COPD.

Characteristics and sources of PM2.5-bound elements in Shanghai during autumn and winter of 2019: Insight into the development of pollution episodes

Elemental composition of PM_2.5 dispersed in the atmosphere has received increasing attention due to its health effect and catalytic activities. In this study, the characteristics and source apportionment of PM_2.5-bound elements were investigated using hourly measurements. K is the most abundant metal element, followed by Fe > Ca > Zn > Mn > Ba > Pb > Cu > Cd. With an average of 8.8 ± 4.1 ng m^-3, Cd was the only element whose pollution level exceeded the limits of Chinese standards and WHO guidelines. The concentrations of As, Se, and Pb doubled in December compared to November, indicating a large increase in coal consumption in winter. The enrichment factors of As, Se, Hg, Zn, Cu, Cd, and Ag were larger than 100, indicating that anthropogenic activities greatly affected them. Ship emissions, coal combustion, soil dust, vehicle emissions, and industrial emissions were identified as major sources of trace elements. In November, the pollution from coal burning and industrial activities was significantly reduced, demonstrating the remarkable achievement of coordinated control measures. For the first time, hourly measurements of PM_2.5-bound elements and secondary sulfate and nitrate were used to investigate the development of dust and PM_2.5 events. During a dust storm event, secondary inorganic salts, potentially toxic elements, and crustal elements sequentially reached peak concentrations, indicating different source origins and formation mechanisms. During the winter PM_2.5 event, the sustained increase of trace elements was attributed to the accumulation of local emissions, while regional transport was responsible for the explosive growth before the end of the event. This study highlights the important role of hourly measurement data in distinguishing local accumulation from regional and long-range transport.

Multi-component emission characteristics and high-resolution emission inventory of non-road construction equipment (NRCE) in China

With the continuous abatement of industries and vehicles in the past years in China, the comprehensive understanding and scientific control of non-road construction equipment (NRCE) may play an important role in alleviating PM_2.5 and O₃ pollution in the next stage. In this study, the emission rates of CO, HC, NOx, PM_2.5, CO₂ and the component profiles of HC and PM_2.5 from 3 loaders, 8 excavators and 4 forklifts under different operating conditions were tested for a systematic representation of NRCE emission characteristics. With the fusion of field tests, construction land types and population distributions, the NRCE emission inventory with a 0.1° × 0.1° resolution in nationwide and with a 0.01° × 0.01° resolution in Beijing-Tianjin-Hebei region (BTH) were established. The sample testing results suggested prominent differences in instantaneous emission rates and the composition characteristics among different equipment and under different operating modes. Generally, for NRCE, the dominant components are OC and EC for PM_2.5, and HC and olefin for OVOC. Especially, the proportion of olefins in idling mode is much higher than that in working mode. The measurement-based emission factors of various equipment exceeded the Stage III standard to varying degrees. The high-resolution emission inventory suggested that highly developed central and eastern areas, represented by BTH, showed the most prominent emissions in China. This study is a systematic representations of China's NRCE emissions, and the NRCE emission inventory establishment method with multiple data fusion has important methodological reference value for other emission sources.

Research of the impact of economic decline on air quality in Wuhan under COVID-19 epidemic

A novel economic impact model is proposed by this paper to analyze the impact of economic downturn on the air quality in Wuhan during the epidemic period, and to explore the effective solutions to improve the urban air pollution. The Space Optimal Aggregation Model (SOAM) is used to evaluate the air quality of Wuhan from January to April in 2019 and 2020. The analysis results show that the air quality of Wuhan from January to April 2020 is better than that of the same period in 2019, and it shows a gradually better trend. This shows that although the measures of household isolation, shutdown and production stoppage adopted during the epidemic period in Wuhan caused economic downturn, it objectively improved the air quality of the city. In addition, the impact of economic factors on PM2.5, SO2 and NO2 is 19%, 12% and 49% respectively calculated by the SOMA. This shows that industrial adjustment and technology upgrading for enterprises that emit a large amount of NO2 can greatly improve the air pollution situation in Wuhan. The SOMA can be extended to any city to analyze the impact of the economy on the composition of air pollutants, and it has extremely important application value at the level of industrial adjustment and transformation policy formulation.

Influence of Urbanization on the Spatial Distribution of Associations Between Air Pollution and Mortality in Beijing, China

This study investigated the influence of urbanization on the intra-city spatial distribution of associations between air pollution and mortality in Beijing, China. First, we utilized the generalized additive model to establish the exposure-response associations of PM2.5, O3, with nonaccidental and cardiorespiratory mortality between urban and suburban areas. Second, we assessed district-specific air pollution-related mortality and analyzed how these associations were affected by the degree of urbanization. Finally, we analyzed the changes in air pollution-related mortality before and after the enforcement of the Air Pollution Prevention and Control Action Plan (referred to as the Action Plan). The effect estimates of PM2.5 for nonaccidental mortality were 0.20% (95% CI: 0.12-0.28) in urban areas and 0.46% (95% CI: 0.35-0.58) in suburban areas per 10 μg/m3 increase in PM2.5 concentrations. The corresponding estimates of O3 were 0.13% (95% CI: -0.04-0.29) in urban areas and 0.34% (95% CI: 0.12-0.56) in suburban areas per 10 μg/m3 increase in O3 concentrations; however, the difference between the estimates of O3 in urban and suburban areas was not statistically significant. The district-specific results suggested that the estimated risks increased along with urban vulnerability levels for the effects of PM2.5. Implementing the Action Plan reduced the mortality risks of PM2.5, but the risks of O3 increased in some districts. However, the difference in the estimates between the pre- and post-emission reductions was not statistically significant. Our study indicated that populations living in less urbanized areas are more vulnerable to the adverse effects of air pollution in Beijing, particularly for PM2.5.

Analysis of Pollution Characteristics and Emissions Reduction Measures in the Main Cotton Area of Xinjiang

With cotton production in Xinjiang increasing annually, the impact on the environment of agricultural waste produced to improve production has been reflected. This study selected Bozhou of Xinjiang, the main cotton producing region in northern Xinjiang, as the research object, and collected hourly concentration data of six pollutants from 2017 to 2021, and analyzed the spatial and temporal distribution characteristics of each pollutant. At the same time, Morlet wavelet analysis was used to further analyze the variation period of PM_2.5 (PM particles with aerodynamic diameters less than 2.5 μm) concentration. The Weather Research and Forecasting model coupled with the Community Multiscale Air Quality (WRF-CMAQ) model was used to evaluate the emissions reduction measures for the most polluted month. The results showed that the concentration of particulate matter (PM particles with aerodynamic diameters less than 2.5 μm and 10 μm) decreased from the southern mountains to the north; moreover, the concentrations of CO (carbon monoxide), NO₂ (nitrogen dioxide), and SO₂ (sulfur dioxide) in the suburbs were higher than those in the urban center. The concentration of O₃ (Ozone) was the highest in summer, while the concentrations of other pollutants were high in autumn and winter. Under the time scale of a = 13, 24, PM_2.5 had significant periodic fluctuation. The health risk values of PM_2.5 and PM₁₀ in this study were within the scope of the United States Environmental Protection Agency (USEPA) criteria, but it is still necessary to keep a close watch on them. In the context of emissions reduction measures, agricultural sources reduced by 20%, residential sources by 40%, industrial sources by 20%, and transportation sources by 20%; no change in the power source remains. Under these conditions, the daily average value of each pollutant met the first level of the national ambient air quality standard. The research results provide a reference for the local government to formulate heavy pollution emissions reduction policies.

Pretreatment with rosavin attenuates PM2.5-induced lung injury in rats through antiferroptosis via PI3K/Akt/Nrf2 signaling pathway

Inflammation and oxidative stress caused by fine particulate matter (PM2.5) increase the incidence and mortality rates of respiratory disorders. Rosavin is the main chemical component of Rhodiola plants, which exerts anti-oxidative and antiinflammatory effects. In this research, the potential therapeutic effect of rosavin was investigated by the PM2.5-induced lung injury rat model. Rats were instilled with PM2.5 (7.5 mg/kg) suspension intratracheally, while rosavin (50 mg/kg, 100 mg/kg) was delivered by intraperitoneal injection before the PM2.5 injection. It was observed that rosavin could prevent lung injury caused by PM2.5. PM2.5 showed obvious ferroptosis-related ultrastructural alterations, which were significantly corrected by rosavin. The pretreatment with rosavin downregulated the levels of tissue iron, malondialdehyde, and 4-hydroxynonenal, and increased the levels of glutathione. The expression of nuclear factor E2-related factor 2 (Nrf2) was upregulated by rosavin, together with other ferroptosis-related proteins. RSL3, a specific ferroptosis agonist, reversed the beneficial impact of rosavin. The network pharmacology approach predicted the activation of rosavin on the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway. LY294002, a potent PI3K inhibitor, decreased the upregulation of Nrf2 induced by rosavin. In conclusion, rosavin prevented lung injury induced by PM2.5 stimulation and suppressed ferroptosis via upregulating PI3K/Akt/Nrf2 signaling pathway.

Potential impact of industrial transfer on PM2.5 and economic development under scenarios oriented by different objectives in Guangdong, China

For sustainable regional development, industrial transfer is an important trend that will potentially change the spatial and temporal pattern of air pollution and economic development. Aiming to better regulate industrial transfer and guide policy-making, this study proposes an assessment framework for industrial transfer that combines precise enterprise data, GIS technology and a 3-D air quality model. Taking Guangdong Province as an example, this study simulates the redistribution of 4015 high-pollution and high-energy-consumption (double-high) enterprises in the Pearl River Delta (PRD) to surrounding areas, and the potential impact on air quality is further evaluated. Three mutually independent transfer scenarios with different objectives are designed-ENV (ENVironment), ENT (ENTerprise), and GOV (GOVernment)-which aim to maximize benefits from the standpoint of the residents of Guangdong, the enterprises themselves, and local governments, respectively. Results show that Western Guangdong (WG), Northern Guangdong (NG), and Eastern Guangdong (EG) would be the primary transfer-in regions under the ENV, ENT, and GOV scenarios due to different resource endowment. Controlled by the different scenarios, the redistribution of enterprises presented different characteristics regarding the transport of pollutant emissions and economic added value between the PRD and surrounding areas. The average concentration of PM_2.5 and the related population-weighted concentrations (PWC) showed a slight decrease over the PRD (-0.75 to -0.62 μg/m³ and -0.35 to -0.49 μg/m³ per person) but increased dramatically in surrounding areas under the three scenarios (0.46-7.68 μg/m³ and 0.07-4.44 μg/m³ per person). The transfer of double-high enterprises could potentially decrease the industrial fossil fuel consumption intensity (fossil energy consumption per unit of industrial GDP) of most of the cities while exacerbating pollution intensity (concentration of PM_2.5 per unit of industrial GDP), reflecting the huge gap in the regional industrial development pattern in Guangdong Province at this stage, and illustrating the importance of emission control of these enterprises for improvement of regional air quality in the future. The research perspective on industrial transfer proposed in this study could provide a reference for future studies.

Avoidable mortality due to long-term exposure to PM2.5 in Colombia 2014-2019

OBJECTIVE

To compare estimates of spatiotemporal variations of surface PM_2.5 concentrations in Colombia from 2014 to 2019 derived from two global air quality models, as well as to quantify the avoidable deaths attributable to the long-term exposure to concentrations above the current and projected Colombian standard for PM_2.5 annual mean at municipality level.

METHODS

We retrieved PM_2.5 concentrations at the surface level from the ACAG and CAMSRA global air quality models for all 1,122 municipalities, and compare 28 of them with available concentrations from monitor stations. Annual mortality data 2014-2019 by municipality of residence and pooled effect measures for total, natural and specific causes of mortality were used to calculate the number of annual avoidable deaths and years of potential life lost (YPLL) related to the excess of PM_2.5 concentration over the current mean annual national standard of 25 µg/m³ and projected standard of 15 µg/m³.

RESULTS

Compared to surface data from 28 municipalities with monitoring stations in 2019, ACAG and CAMSRA models under or overestimated annual mean PM_2.5 concentrations. Estimations from ACAG model had a mean bias 1,7 µg/m³ compared to a mean bias of 4,7 µg/m³ from CAMSRA model. Using ACAG model, estimations of total nationally attributable deaths to PM_2.5 exposure over 25 and 15 µg/m³ were 142 and 34,341, respectively. Cardiopulmonary diseases accounted for most of the attributable deaths due to PM_2.5 excess of exposure (38%). Estimates of YPLL due to all-cause mortality for exceeding the national standard of 25 µg/m³ were 2,381 years.

CONCLUSION

Comparison of two global air quality models for estimating surface PM_2.5 concentrations during 2014-2019 at municipality scale in Colombia showed important differences. Avoidable deaths estimations represent the total number of deaths that could be avoided if the current and projected national standard for PM_2.5 annual mean have been met, and show the health-benefit of the implementation of more restrictive air quality standards.

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.

Air Pollution and Corporate Green Financial Constraints: Evidence from China's Listed Companies

This paper aims to investigate how air pollution may affect corporate green financial constraints. We assume that poor air quality can enhance the pressure of governments on environmental protection, which creates easier access to financing for firms' green investments and transitions, especially in emerging markets. Using a sample of Chinese-listed companies, we find that the level of green financial constraints is reduced when air quality deteriorates. This effect is more obvious in regions with stronger local government influence or fewer formal environmental regulations. To manage potential self-selection and endogeneity issues, fixed effects (FE), two-stage least squares (2SLS) with instrumental variables (IV), and propensity-score matching (PSM) approaches are used to verify the validity of our results. We link air pollution and financial constraints of green investment, and we fill a literature gap by considering whether the environment can have an impact on corporate green transformation. In the channel analysis, we identify that debt could be an important mechanism through which firms derive fewer green financial constraints. Our findings indicate that air pollution can be a crucial factor restricting corporate green investment and transformation, and managers in the context of emerging markets should be more attentive to green financing.

The dynamics of cardiovascular and respiratory deaths attributed to long-term PM2.5 exposures in global megacities

Exposure to ambient fine particulate matter (PM_2.5) air pollution is a significant driver of premature deaths. We estimate the number of cardiovascular and respiratory (CR) premature deaths attributed to long-term exposure to PM_2.5 in 33 global megacities based on long-term remotely sensed observations from 2000 to 2019. Our analysis uses high-resolution (0.01 degree) PM_2.5 concentration data and cause-specific integrated exposure-response (IER) functions developed for the Global Burden of Disease Project. From 2000 to 2019, PM_2.5-related CR death rates per 1000 people increased in 6 of 33 megacities, decreased in 9, and remained constant in 18 megacities. The increase in PM_2.5-related CR mortality in 11 megacities located in South and East Asia during the period 2000-2019 can be attributed to the increases in PM_2.5 concentrations. All 33 megacities could avoid 30,248 (9 %), 62,989 (20 %), 128,457 (40 %), 198,462 (62 %) and all of the estimated 322,515 CR deaths attributed to PM_2.5 pollution in 2019 if they were to attain the World Health Organization's four interim PM_2.5 targets (IT-1, IT-2, IT-3, and IT-4) and the new air quality guideline (AQG), respectively. Major improvements in air quality are needed to reduce the number of CR deaths attributed to PM_2.5 in South and East Asia, in addition to ny reductions that would likely follow shifts in the population structures of these megacities moving forward.

Associations of Early-Life Exposure to Submicron Particulate Matter With Childhood Asthma and Wheeze in China

IMPORTANCE

Exposure to particulate matter (PM) has been associated with childhood asthma and wheeze. However, the specific associations between asthma and PM with an aerodynamic equivalent diameter of 1 μm or less (ie, PM1), which is a contributor to PM2.5 and potentially more toxic than PM2.5, remain unclear.

OBJECTIVE

To investigate the association of early-life (prenatal and first year) exposure to size-segregated PM, including PM1, PM1-2.5, PM2.5, PM2.5-10, and PM10, with childhood asthma and wheeze.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study was based on a questionnaire administered between June 2019 and June 2020 to caregivers of children aged 3 to 6 years in 7 Chinese cities (Wuhan, Changsha, Taiyuan, Nanjing, Shanghai, Chongqing, and Urumqi) as the second phase of the China, Children, Homes, Health study.

EXPOSURES

Exposure to PM1, PM1-2.5, PM2.5, PM2.5-10, and PM10 during the prenatal period and first year of life.

MAIN OUTCOMES AND MEASURES

The main outcomes were caregiver-reported childhood asthma and wheeze. A machine learning-based space-time model was applied to estimate early-life PM1, PM2.5, and PM10 exposure at 1 × 1-km resolution. Concentrations of PM1-2.5 and PM2.5-10 were calculated by subtracting PM1 from PM2.5 and PM2.5 from PM10, respectively. Multilevel (city and child) logistic regression models were applied to assess associations.

RESULTS

Of 29 418 children whose caregivers completed the survey (15 320 boys [52.1%]; mean [SD] age, 4.9 [0.9] years), 2524 (8.6%) ever had wheeze and 1161 (3.9%) were diagnosed with asthma. Among all children, 18 514 (62.9%) were breastfed for more than 6 months and 787 (2.7%) had parental history of atopy. A total of 22 250 children (75.6%) had a mother with an educational level of university or above. Of the 25 422 children for whom information about cigarette smoking exposure was collected, 576 (2.3%) had a mother who was a current or former smoker during pregnancy and 7525 (29.7%) had passive household cigarette smoke exposure in early life. Early-life PM1, PM2.5, and PM10 exposure were significantly associated with increased risk of childhood asthma, with higher estimates per 10-μg/m3 increase in PM1 (OR, 1.55; 95% CI, 1.27-1.89) than in PM2.5 (OR, 1.14; 95% CI, 1.03-1.26) and PM10 (OR, 1.11; 95% CI, 1.02-1.20). No association was observed between asthma and PM1-2.5 exposure, suggesting that PM1 rather than PM1-2.5 contributed to the association between PM2.5 and childhood asthma. There were significant associations between childhood wheeze and early-life PM1 exposure (OR, 1.23; 95% CI, 1.07-1.41) and PM2.5 exposure (OR, 1.08; 95% CI, 1.01-1.16) per 10-μg/m3 increase in PM1 and PM2.5, respectively.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, higher estimates were observed for the association between PM with smaller particles, such as PM1, vs PM with larger particles and childhood asthma. The results suggest that the association between PM2.5 and childhood asthma was mainly attributable to PM1.

Environmental Status and Human Health: Evidence from China

In recent years, there have been growing concerns about the environment and its effect on human health. In this paper, we measure human health by mortality. Firstly, we use the method of deviation decomposition to investigate the different changes of mortality in eastern, central and western regions of China. Secondly, we study the linearity and nonlinearity between environmental status and mortality by semi-parametric additive panel model. Following is the primary conclusions obtained in the study: (1) There exists a big mortality gap among different regions; the gap is mainly dominated by the inter-regional difference; the mortality of the middle region increases heavily; the western region becomes a major source of mortality differences. (2) Mortality decreased with the increase of urban green area. On the other hand, the higher the environmental pollution index, the higher the mortality rate. (3) The environmental pollution index, urban green area, number of licensed (assistant) physicians per thousand and the per capita GDP can affect mortality in a nonlinear way.

Assessment of long-term particulate nitrate air pollution and its health risk in China

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO₃⁻) concentration remains high or even increases at monitoring sites despite the total PM_2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO₃⁻ concentration across China due to the lack of a PM_2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO₃⁻, thereby understanding the disease burden associated with long-term NO₃⁻ exposure in China. Our results show that existing air pollution control policies are effective, but increased NO₃⁻ of traffic emissions offset reduced NO₃⁻ of industrial emissions. In 2018, the national mean mortality burden attributable to NO₃⁻ was as high as 0.68 million, indicating that targeted regulations are needed to control NO₃⁻ pollution in China.

•

We build a NO₃⁻ model using machine learning techniques incorporating satellite data

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We estimate spatiotemporal variations of NO₃⁻ concentration in China from 2005–2018

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In 2018, the national mean mortality burden attributable to NO₃⁻ was about 0.68 million

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Targeted regulations on vehicle emissions are needed to control NO₃⁻ pollution in China

Mortality burden due to long-term exposure to ambient PM2.5 above the new WHO air quality guideline based on 296 cities in China

OBJECTIVE

Quantifying the spatial and socioeconomic variation of mortality burden attributable to particulate matters with aerodynamic diameter ≤ 2.5 µm (PM2.5) has important implications for pollution control policy. This study aims to examine the regional and socioeconomic disparities in the mortality burden attributable to long-term exposure to ambient PM2.5 in China.

METHODS

Using data of 296 cities across China from 2015 to 2019, we estimated all-cause mortality (people aged ≥ 16 years) attributable to the long-term exposure to ambient PM2.5 above the new WHO air quality guideline (5 µg/m3). Attributed fraction (AF), attributed deaths (AD), attributed mortality rate (AMR) and total value of statistical life lost (VSL) by regional and socioeconomic levels were reported.

RESULTS

Over the period of 2015-2019, 17.0% [95% confidence interval (CI): 7.4-25.2] of all-cause mortality were attributable to long-term exposure to ambient PM2.5, corresponding to 1,425.2 thousand deaths (95% CI: 622.4-2,099.6), 103.5/105 (95% CI: 44.9-153.3) AMR, and 1006.9 billion USD (95% CI: 439.8-1483.4) total VSL per year. The AMR decreased from 120.5/105 (95% CI: 52.9-176.6) to 92.7/105 (95% CI:39.9-138.5) from 2015 to 2019. The highest mortality burden was observed in the north region (annual average AF = 24.2%, 95% CI: 10.8-35.1; annual average AMR = 137.0/105, 95% CI: 60.9-198.5). The highest AD and economic loss were observed in the east region (annual average AD = 390.0 thousand persons, 95% CI: 170.3-574.6; annual total VSL = 275.6 billion USD, 95% CI: 120.3-406.0). Highest AMR was in the cities with middle level of GDP per capita (PGDP)/urbanization. The majority of the top ten cities of AF, AMR and VSL were in high and middle PGDP/urbanization regions.

CONCLUSION

There were significant regional and socioeconomic disparities in PM2.5 attributed mortality burden among Chinese cities, suggesting differential mitigation policies are required for different regions in China.

Assessment of PM2.5-related health effects: A comparative study using multiple methods and multi-source data in China

In China, PM_2.5 pollution has caused extensive death and economic loss. Thus, an accurate assessment of the spatial distribution of these losses is crucial for delineating priority areas for air pollution control in China. In this study, we assessed the PM_2.5 exposure-related health effects according to the integrated exposure risk function and non-linear power law (NLP) function in 338 prefecture-level cities in China by utilizing online monitoring data and the PM_2.5 Hindcast Database (PHD). Our results revealed no significant difference between the monitoring data and PHD (p value = 0.66 > 0.05). The number of deaths caused by PM_2.5-related Stroke (cerebrovascular disease), ischemic heart disease, chronic obstructive pulmonary disease, and lung cancer at the national level estimated through the NLP function was 0.27 million (95% CI: 0.06-0.50), 0.23 million (95% CI: 0.08-0.38), 0.31 million (95% CI: 0.04-0.57), and 0.31 million (95% CI: 0.16-0.40), respectively. The total economic cost at the national level in 2016 was approximately US$80.25 billion (95% CI: 24.46-132.25). Based on a comparison of Z statistics, we propose that the evaluation results obtained using the NLP function and monitoring data are accurate. Additionally, according to scenario simulations, Beijing, Chongqing, Tianjin, and other cities should be priority areas for PM_2.5 pollution control to achieve considerable health benefits. Our statistics can help improve the accuracy of PM_2.5-related health effect assessments in China.

Assessing the impact of green nudges on ozone concentration: Evidence from China's night refueling policy

Ozone (O₃) pollution poses health risks and premature mortality, and gas stations are one of the largest sources of urban volatile organic compounds (VOCs, the main precursor to O₃). This paper investigates whether the government's call for night refueling, which can be regarded as a green nudge, can guide changes in consumer behavior and consequently improve environmental quality. Using a difference-in-differences (DID) estimation and weekly monitoring site air quality panel data, we analyze the effect of the Night Refueling Preferential Policy on O₃ concentrations. We find that the policy can reduce O₃ concentrations by 10% by encouraging consumers to refuel at night. The reduction in O₃ has brought great benefits to human health, leading to a 4-5‰ reduction in non-accidental mortality and a 6-8‰ reduction in cardiovascular mortality in Jiangsu province. The economic benefits of this policy would be approximately 62-189 billion Chinese Yuan (CNY) if it were implemented nationwide. The findings of this study suggest that the government can influence consumer behavior to promote environmental quality.

A stochastic exposure model integrating random forest and agent-based approaches: Evaluation for PM2.5 in Jiangsu, China

This research proposes an Activity Pattern embedded Air Pollution Exposure Model (AP2EM), based on survey data of when, where, and how people spend their time and indoor/outdoor ratios for microenvironments. AP2EM integrates random forest and agent-based approaches to simulate the stochastic exposure to outdoor fine particulate matter (PM_2.5) along with indoor and in-vehicle PM_2.5 of outdoor origin. The R² of the linear regression between the model's calculations and personal measurement was 0.65, which was more accurate than the commonly-used aggregated exposure (AE) model and the outdoor exposure (OE) model. The population-weighted PM_2.5 exposure estimated by the AP2EM was 36.7 μg/m³ in Jiangsu, China, during 2014-2017. The OE model overestimated exposure by 54.0%, and the AE model underestimated exposure by 6.5%. These misestimate reflect ignorance of traditional studies on effects posed from time spent indoors (~85%) and doing low respiratory rate activities (~93%), problems of biased sampling, and neglecting low probability events. The proposed AP2EM treats activity patterns of individuals as chains and uses stochastic estimates to model activity choices, providing a more comprehensive understanding of human activity and exposure characteristics. Overall, the AP2EM is applicable for other air pollutants in different regions and benefits China's air pollution control policy designs.

Potential years of life lost due to PM2.5-bound toxic metal exposure: Spatial patterns across 60 cities in China

To clarify the spatial patterns of disease burden caused by toxic metals in fine particulate matter (PM_2.5) across China, annual concentration levels of typical toxic metals in PM_2.5 over 60 cities of China were retrieved. Then, potential years of life lost (PYLL) attributable to toxic metal (As, Cd, Cr (VI), Mn, and Ni) exposure was calculated from health risk assessments and lifetable estimates. The results show that Cr(VI) and As were the most polluted metals and greatly exceeded the recommended annual values in the National Ambient Air Quality Standard of China. PYLL for each death (mean ± standard deviation) of 19.8 ± 4.5 years was observed for lung cancer, followed closely by COPD and pneumonia. Furthermore, the PYLL rate (years per 100,000 people) attributable to exposure to these toxic metals was 457 (male: 505, female: 402) years for different cities; therein, Cr(VI) contributed the highest PYLL among these toxic metals, with a proportion of 72.7% (male: 75.3%, female: 69.5%), followed by As of 16.4% (male: 13.8%, female: 19.8%). The concentration level and PYLL both showed large spatial variability, of which the top-ranking cities were observed to be affected by well-developed metal-related industries and coal-powered industrial sectors.

Spatiotemporal trends in life expectancy and impacts of economic growth and air pollution in 134 countries: A Bayesian modeling study

Life expectancy (LE) varies across countries in space and time, and economic growth and air pollution are two important influence factors to LE. This study mainly aims to investigate spatiotemporal trends in LE in 134 countries from 1960 to 2016 by using Bayesian spatiotemporal modeling. Further, the relations between per capita gross domestic product (GDP_pc) and population-weighted fine particulate matter (pwPM_2.5) and LE are investigated from a global perspective from 1998 to 2016 by using the Bayesian regression model. The results illustrated the heterogeneity of spatiotemporal trends in LE globally. Specifically, Africa and South-East Asia show much lower LE levels, and the Americas, European, and Western Pacific exhibit a relatively higher LE level compared to the overall level. The countries with low overall levels of LE show a relatively stronger upward trend than the overall upward trend and vice versa. In addition, this study demonstrates that the spatial differences in effects of influence factors on LE in the six WHO regions in the 134 countries. Africa shows the highest positive regression coefficient of GDP_pc and lowest negative regression coefficient of pwPM_2.5 on LE than other regions in the world. Furthermore, it shows the complexity of the interaction between economic growth and air pollution on LE across six WHO regions. Our findings suggest the public policies to reduce the health damage caused by air pollution, especially in Africa, Eastern Mediterranean, and Europe where the pwPM_2.5 negatively affect the LE benefits from economic growth.

Spatial Distribution of PM2.5-Related Premature Mortality in China

PM2.5 is a major component of air pollution in China and has a serious threat to public health. It is very important to quantify spatial characteristics of the health effects caused by outdoor PM2.5 exposure. This study analyzed the spatial distribution of PM2.5 concentration (45.9 μg/m3 national average in 2016) and premature mortality attributed to PM2.5 in cities at the prefectural level and above in China in 2016. Using the Global Exposure Mortality Model (GEMM), the total premature mortality in China was estimated to be 1.55 million persons, and the per capita mortality was 11.2 per 10,000 persons in the year 2016, resulting in higher estimates compared to the integrated exposure-response model. We assessed the premature mortality attributed to PM2.5 through common diseases, including ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and lower respiratory infections (LRI). The premature mortality due to IHD and CEV accounted for 68.5% of the total mortality, and the per capita mortality (per 10,000 persons) for all ages due to IHD was 3.86, the highest among diseases. For the spatial distribution of disease-specific premature mortality, the top two highest absolute numbers of premature mortality associated with IHD, CEV, LC, and LRI, respectively, were found in Chongqing and Beijing. In 338 cities of China, we have found a significant positive spatial autocorrelation of per capita premature mortality, indicating the necessity of coordinated regional governance for an efficient control of PM2.5.

Long-term health impact of PM2.5 under whole-year COVID-19 lockdown in China

The health impact of changes in particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5) pollution associated with the COVID-19 lockdown has aroused great interest, but the estimation of the long-term health effects is difficult because of the lack of an annual mean air pollutant concentration under a whole-year lockdown scenario. We employed a time series decomposition method to predict the monthly PM_2.5 concentrations in urban cities under permanent lockdown in 2020. The premature mortality attributable to long-term exposure to ambient PM_2.5 was quantified by the risk factor model from the latest epidemiological studies. Under a whole-year lockdown scenario, annual mean PM_2.5 concentrations in cites ranged from 5.4 to 68.0 μg m^-3, and the national mean concentration was reduced by 32.2% compared to the 2015-2019 mean. The Global Exposure Mortality Model estimated that 837.3 (95% CI: 699.8-968.4) thousand people in Chinese cities would die prematurely from illnesses attributable to long-term exposure to ambient PM_2.5. Compared to 2015-2019 mean levels, 140.2 (95% CI: 122.2-156.0) thousand premature deaths (14.4% of the annual mean deaths from 2015 to 2019) attributable to long-term exposure to PM_2.5 were avoided. Because PM_2.5 concentrations were still high under the whole-year lockdown scenario, the health benefit is limited, indicating that continuous emission-cutting efforts are required to reduce the health risks of air pollution. Since a similar scenario may be achieved through promotion of electric vehicles and the innovation of industrial technology in the future, the estimated long-term health impact under the whole year lockdown scenario can establish an emission-air quality-health impact linkage and provide guidance for future emission control strategies from a health protection perspective.

Assessment of the effects of straw burning bans in China: Emissions, air quality, and health impacts

Open biomass burning (OBB) plays an important role in air pollution and climate change by releasing short-term but intensive amounts of particulate matter and gaseous air pollutants. During past years, policies with respect to prohibition on open straw burning have been issued in China in order to mitigate the air pollution problems and the effectiveness of these straw burning bans in different regions remains to be evaluated. In this study, open crop straw burning (OCSB) emissions during 2010-2018 were analyzed based on a commonly used emission inventory with high spatial and temporal resolution. High emissions concentrated over Northeast China (31.8% of national total PM_2.5 emissions in 2018), East China (24.0%), and North China (16.6%). Simulations based on an integrated meteorology-air quality modeling system and an exposure-response function show that OCSB emissions could increase monthly PM_2.5 concentration by as much as 10 μg/m³ during burning seasons in Northeast China and were associated with 4741 premature deaths in 2018. Spatial heterogeneities were observed with respect to the trends of OCSB emissions during 2010-2018. In East China, North China, and Central China, OCSB emissions showed a general declining trend since 2013 while an opposing increasing trend was observed in Northeast China with peak emissions in 2017. Comparing 2013 (before intensive implementation of straw burning bans) and 2018 (after), national total PM_2.5 emissions from OCSB activities decreased by 46.9%, ranging from -14.1% to +70% depending on the specific regions. Northeast China is the only region that showed higher OCSB emissions in 2018 compared to 2013, probably associated with the relatively delayed implementation of the straw burning bans. Avoided number of premature deaths due to reduced OCSB emissions was estimated to be 4256 on a national scale, with most health benefits gained in East and Central China. Results from this study demonstrate the importance of OCSB contribution to PM_2.5 concentrations and spatial heterogeneities exist in terms of the effectiveness of the straw burning bans in reducing OCSB emissions and gained health benefits.

Particulate Matter and Premature Mortality: A Bayesian Meta-Analysis

BACKGROUND

We present a systematic review of studies assessing the association between ambient particulate matter (PM) and premature mortality and the results of a Bayesian hierarchical meta-analysis while accounting for population differences of the included studies.

METHODS

The review protocol was registered in the PROSPERO systematic review registry. Medline, CINAHL and Global Health databases were systematically searched. Bayesian hierarchical meta-analysis was conducted using a non-informative prior to assess whether the regression coefficients differed across observations due to the heterogeneity among studies.

RESULTS

We identified 3248 records for title and abstract review, of which 309 underwent full text screening. Thirty-six studies were included, based on the inclusion criteria. Most of the studies were from China (n = 14), India (n = 6) and the USA (n = 3). PM_2.5 was the most frequently reported pollutant. PM was estimated using modelling techniques (22 studies), satellite-based measures (four studies) and direct measurements (ten studies). Mortality data were sourced from country-specific mortality statistics for 17 studies, Global Burden of Disease data for 16 studies, WHO data for two studies and life tables for one study. Sixteen studies were included in the Bayesian hierarchical meta-analysis. The meta-analysis revealed that the annual estimate of premature mortality attributed to PM_2.5 was 253 per 1,000,000 population (95% CI: 90, 643) and 587 per 1,000,000 population (95% CI: 1, 39,746) for PM₁₀.

CONCLUSION

253 premature deaths per million population are associated with exposure to ambient PM_2.5. We observed an unstable estimate for PM₁₀, most likely due to heterogeneity among the studies. Future research efforts should focus on the effects of ambient PM₁₀ and premature mortality, as well as include populations outside Asia. Key messages: Ambient PM_2.5 is associated with premature mortality. Given that rapid urbanization may increase this burden in the coming decades, our study highlights the urgency of implementing air pollution mitigation strategies to reduce the risk to population and planetary health.

Co-benefits of carbon and pollution control policies on air quality and health till 2030 in China

Facing the dual challenges of climate change and air pollution, China has made great efforts to explore the co-control strategies for the both. We assessed the benefits of carbon and pollution control policies on air quality and human health, with an integrated framework combining an energy-economic model, an air quality model and a concentration-response model. With a base year 2015, seven combined scenarios were developed for 2030 based on three energy scenarios and three end-of-pipe control ones. Policy-specific benefits were then evaluated, indicated by the reduced emissions, surface concentrations of major pollutants, and premature deaths between scenarios. Compared to the 2030 baseline scenario, the nationwide PM_2.5- and O₃-related mortality was expected to decline 23% or 289 (95% confidence interval: 220-360) thousand in the most stringent scenario, and three quarters of the avoided deaths were attributed to the end-of-pipe control measures. Provinces in heavily polluted and densely populated regions would benefit more from carbon and pollution control strategies. The population fractions with PM_2.5 exposure under the national air quality standard (35 μg/m³) and WHO guideline (10 μg/m³) would be doubled from 2015 to 2030 (the most stringent scenario), while still very few people would live in areas with the WHO guideline achieved for O₃ (100 μg/m³). Increased health impact of O₃ suggested a great significance of joint control of PM_2.5 and O₃ in future policy-making.

Recent trends in premature mortality and health disparities attributable to ambient PM2.5 exposure in China: 2005-2017

In the past decade, particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) has reached unprecedented levels in China and posed a significant threat to public health. Exploring the long-term trajectory of the PM_2.5 attributable health burden and corresponding disparities across populations in China yields insights for policymakers regarding the effectiveness of efforts to reduce air pollution exposure. Therefore, we examine how the magnitude and equity of the PM_2.5-related public health burden has changed nationally, and between provinces, as economic growth and pollution levels varied during 2005-2017. We derive long-term PM_2.5 exposures in China from satellite-based observations and chemical transport models, and estimate attributable premature mortality using the Global Exposure Mortality Model (GEMM). We characterize national and interprovincial inequality in health outcomes using environmental Lorenz curves and Gini coefficients over the study period. PM_2.5 exposure is linked to 1.8 (95% CI: 1.6, 2.0) million premature deaths over China in 2017, increasing by 31% from 2005. Approximately 70% of PM_2.5 attributable deaths were caused by stroke and IHD (ischemic heart disease), though COPD (chronic obstructive pulmonary disease) and LRI (lower respiratory infection) disproportionately affected poorer provinces. While most economic gains and PM_2.5-related deaths were concentrated in a few provinces, both gains and deaths became more equitably distributed across provinces over time. As a nation, however, trends toward equality were more recent and less clear cut across causes of death. The rise in premature mortality is due primarily to population growth and baseline risks of stroke and IHD. This rising health burden could be alleviated through policies to prevent pollution, exposure, and disease. More targeted programs may be warranted for poorer provinces with a disproportionate share of PM_2.5-related premature deaths due to COPD and LRI.

Determinant Powers of Socioeconomic Factors and Their Interactive Impacts on Particulate Matter Pollution in North China

Severe air pollution has significantly impacted climate and human health worldwide. In this study, global and local Moran’s I was used to examine the spatial autocorrelation of PM_2.5 pollution in North China from 2000–2017, using data obtained from Atmospheric Composition Analysis Group of Dalhousie University. The determinant powers and their interactive effects of socioeconomic factors on this pollutant are then quantified using a non-linear model, GeoDetector. Our experiments show that between 2000 and 2017, PM_2.5 pollution globally increased and exhibited a significant positive global and local autocorrelation. The greatest factor affecting PM_2.5 pollution was population density. Population density, road density, and urbanization showed a tendency to first increase and then decrease, while the number of industries and industrial output revealed a tendency to increase continuously. From a long-term perspective, the interactive effects of road density and industrial output, road density, and the number of industries were amongst the highest. These findings can be used to develop the effective policy to reduce PM_2.5 pollution, such as, due to the significant spatial autocorrelation between regions, the government should pay attention to the importance of regional joint management of PM_2.5 pollution.

Impacts of implementing Healthy Building guidelines for daily PM2.5 limit on premature deaths and economic losses in urban China: A population-based modeling study

Given a large fraction of people's exposure to urban PM_2.5 occur indoors, reducing indoor PM_2.5 levels may offer a more feasible and immediate way to save substantial lives and economic losses attributable to PM_2.5 exposure. We aimed to estimate the premature mortality and economic loss reductions associated with achieving the newly established Chinese indoor air guideline and a few hypothetical indoor PM_2.5 guideline values. We used outdoor PM_2.5 concentrations from 1497 monitoring sites in 339 Chinese cities in 2015, coupled with a steady-state mass balance model, to estimate indoor concentrations of outdoor-infiltrated PM_2.5. Using province-specific time-activity patterns for urban residents, we estimated outdoor and indoor exposures to PM_2.5 of outdoor origin. We then proceeded to use localized census-based concentration-response models and the value of statistical life estimates to calculate premature deaths and economic losses attributable to PM_2.5 exposure across urban China. Finally, we estimated potentially avoidable mortality and corresponding economic losses by meeting the current 24-hour based guideline and various hypothetical indoor limits for PM_2.5. In 2015 in urban areas of mainland China, the city-specific annual mean outdoor and indoor PM_2.5 concentrations ranged 9-108 μg/m³ and 5-56 μg/m³, respectively. Indoor exposures contributed 62%-91% daily and 68%-83% annually to the total time-weighted exposures. The potential reductions in total deaths and economic losses for the scenario in which daily indoor concentrations met the current guideline of 75 μg/m³, 37.5 μg/m³, and 25 μg/m³ were 16.9 (95% CI: 0.7-62.1) thousand, 87.7 (95% CI: 9.7-197.7) thousand, and 165.5 (95% CI: 30.8-304.0) thousand, respectively. The corresponding reductions in economic losses were 5.7 (95% CI: 0.2-34.8) billion, 29.4 (95% CI: 2.4-109.6) billion, and 55.2 (95% CI: 7.7-168.0) billion US Dollars, respectively. Deaths and economic losses would be reduced exponentially within the range of 0-75 μg/m³ for hypothetical indoor PM_2.5 limits. The findings demonstrate the effectiveness of reducing indoor concentrations of outdoor-originated PM_2.5 in saving substantial lives and economic losses in China. The analysis provides quantitative evidence to support the implementation of an indoor air quality guideline or standard for PM_2.5.

Air Pollution Prediction with Multi-Modal Data and Deep Neural Networks

Air pollution is becoming a rising and serious environmental problem, especially in urban areas affected by an increasing migration rate. The large availability of sensor data enables the adoption of analytical tools to provide decision support capabilities. Employing sensors facilitates air pollution monitoring, but the lack of predictive capability limits such systems’ potential in practical scenarios. On the other hand, forecasting methods offer the opportunity to predict the future pollution in specific areas, potentially suggesting useful preventive measures. To date, many works tackled the problem of air pollution forecasting, most of which are based on sequence models. These models are trained with raw pollution data and are subsequently utilized to make predictions. This paper proposes a novel approach evaluating four different architectures that utilize camera images to estimate the air pollution in those areas. These images are further enhanced with weather data to boost the classification accuracy. The proposed approach exploits generative adversarial networks combined with data augmentation techniques to mitigate the class imbalance problem. The experiments show that the proposed method achieves robust accuracy of up to 0.88, which is comparable to sequence models and conventional models that utilize air pollution data. This is a remarkable result considering that the historic air pollution data is directly related to the output—future air pollution data, whereas the proposed architecture uses camera images to recognize the air pollution—which is an inherently much more difficult problem.

Long-term exposure to PM2.5 and Children's lung function: a dose-based association analysis

Background

The current literature is still not consist regarding the effect of long-term exposure to PM2.5 and children’s lung function, partly due to inadequate or inaccurate exposure assessment. In this study, we aim to investigate the associations between long-term exposure to PM2.5, estimated as average daily dose (ADD), and lung function in school-age children.

Methods

We recruited 684 participants of 7–12 years old from the city of Lanzhou located in northwestern China. Participants underwent spirometric tests for lung function and responded to a questionnaire survey. Detailed information about individual air exposure and personal information were collected, including length of school hours, home address, age, gender, etc. Combining the spatial distribution of PM2.5 concentrations in the past 5 years and individual time-activity data, we estimated annual ADD for 5 years preceding the lung function tests and 5-year average ADD, respectively. We used multiple linear regression models to examine the associations between ADD values and lung function, controlling for a range of individual-level covariates.

Results

The 5-year average ADD among all the participants was 50.5 µg/kg-d, with higher values estimated for children living in the urban area than the suburban area, for boys than girls, and for children whose parents received a lower education attainment. We found that a 1 μg/kg-d increment in ADD of PM2.5 was associated with a 10.49 mL (95% CI: −20.47, −0.50) decrease in forced vital capacity (FVC) and a 7.68 mL (95% CI: −15.80, −0.44) decrease in forced exploratory volume in 1 second (FEV₁). Among the annual ADDs estimated for the preceding 5 years, the immediate past year prior to lung function measurement had the greatest effect on lung function. The effect was greater in girls than in boys. We found no associations between annual exposure of PM2.5 (instead of ADD) and lung function when defined concentration was used as an exposure variable.

Conclusions

Long-term PM2.5 exposure, when estimated as exposure dose averaged over a year or longer, was associated with statistically significant reductions in FVC and FEV1 in children of elementary-school age. Future studies may consider the use of individual-level dose estimates (as opposed to exposure concentrations) to improve the dose-response assessment.

Health impacts of long-term ozone exposure in China over 2013-2017

Increasing ozone concentrations are becoming a severe problem for air pollution in China and have an adverse impact on human health. Here we evaluate premature deaths attributable to long-term exposure to ambient ozone in China between 2013 and 2017 with an air quality model at 5 km resolution and the latest estimates of the relative risk to health. We use a modified inverse distance weighting method to bias-correct the key model-simulated ozone metrics. We find that on a 5-year average basis there are 186,000 (95% Confidence Interval: 129,000-237,000) respiratory deaths and 125,000 (42,000-204,000) cardiovascular deaths attributable to ozone exposure. Sichuan exhibits the largest per capita respiratory mortality (0.31‰) among all provinces. We find that there are 73,000 (51,000-93,000) premature respiratory deaths in urban areas, accounting for 39% of total deaths. Between 2013 and 2017 the population-weighted annual average maximum daily 8-h average ozone (AMDA8) and premature respiratory deaths increased by 14% and 31%, respectively, at a national level. Changes in precursor emissions explain most of these increases, with differences in meteorology accounting for 21% and 16% respectively. Interannual variations in population-weighted ozone and premature respiratory deaths at a provincial level are much larger than those at a national level, particularly in northern, central and eastern China. These findings emphasize that ozone should be an important focus of future air quality policies in China, and tighter controls of precursor emissions are urgently needed.

Spatiotemporal variability in long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across the Yangtze River Delta (YRD) region over 2010-2016: A multistage approach

The Yangtze River Delta region (YRD) is one of the most densely populated regions in the world, and is frequently influenced by fine particulate matter (PM_2.5). Specifically, lung cancer mortality has been recognized as a major health burden associated with PM_2.5. Therefore, this study developed a multistage approach 1) to first create dasymetric population data with moderate resolution (1 km) by using a random forest algorithm, brightness reflectance of nighttime light (NTL) images, a digital elevation model (DEM), and a MODIS-derived normalized difference vegetation index (NDVI), and 2) to apply the improved population dataset with a MODIS-derived PM_2.5 dataset to estimate the association between spatiotemporal variability of long-term population exposure to PM_2.5 and lung cancer mortality attributable to PM_2.5 across YRD during 2010-2016 for microscale planning. The created dasymetric population data derived from a coarse census unit (administrative unit) were fairly matched with census data at a fine spatial scale (street block), with R² and RMSE of 0.64 and 27,874.5 persons, respectively. Furthermore, a significant urban-rural difference of population exposure was found. Additionally, population exposure in Shanghai was 2.9-8 times higher than the other major cities (7-year average: 192,000 μg·people/m³·km²). More importantly, the relative risks of lung cancer mortality in high-risk areas were 28%-33% higher than in low-risk areas. There were 12,574-14,504 total lung cancer deaths attributable to PM_2.5, and lung cancer deaths in each square kilometer of urban areas were 7-13 times higher than for rural areas. These results indicate that moderate-resolution information can help us understand the spatiotemporal variability of population exposure and related health risk in a high-density environment.

The 17-y spatiotemporal trend of PM2.5 and its mortality burden in China

Investigations on the chronic health effects of fine particulate matter (PM_2.5) exposure in China are limited due to the lack of long-term exposure data. Using satellite-driven models to generate spatiotemporally resolved PM_2.5 levels, we aimed to estimate high-resolution, long-term PM_2.5 and associated mortality burden in China. The multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) at 1-km resolution was employed as a primary predictor to estimate PM_2.5 concentrations. Imputation techniques were adopted to fill in the missing AOD retrievals and provide accurate long-term AOD aggregations. Monthly PM_2.5 concentrations in China from 2000 to 2016 were estimated using machine-learning approaches and used to analyze spatiotemporal trends of adult mortality attributable to PM_2.5 exposure. Mean coverage of AOD increased from 56 to 100% over the 17-y period, with the accuracy of long-term averages enhanced after gap filling. Machine-learning models performed well with a random cross-validation R ² of 0.93 at the monthly level. For the time period outside the model training window, prediction R ² values were estimated to be 0.67 and 0.80 at the monthly and annual levels. Across the adult population in China, long-term PM_2.5 exposures accounted for a total number of 30.8 (95% confidence interval [CI]: 28.6, 33.2) million premature deaths over the 17-y period, with an annual burden ranging from 1.5 (95% CI: 1.3, 1.6) to 2.2 (95% CI: 2.1, 2.4) million. Our satellite-based techniques provide reliable long-term PM_2.5 estimates at a high spatial resolution, enhancing the assessment of adverse health effects and disease burden in China.

The impact of prenatal exposure to PM2.5 on childhood asthma and wheezing: a meta-analysis of observational studies

With the accelerated pace of economic development and modernization, air pollution has become one of the most focused public health problems. However, the impact of particulate matter exposure during pregnancy on childhood asthma and wheezing remains controversial. We performed this meta-analysis to explore the relationship between prenatal exposure to PM2.5 and childhood asthma and wheezing. Candidate papers were searched on PubMed, Web of Science, Embase, and Cochrane Library before July 15, 2019. The main characteristics of the included studies were extracted, and the quality was evaluated by the Newcastle-Ottawa Scale (NOS). A sensitivity analysis was performed to assess the impact of individual studies on the combined effects. The Egger and Begg tests were conducted to examine the publication bias. Nine studies were included in the final analysis. Prenatal exposure to PM2.5 significantly increased the risk of childhood asthma and wheezing (OR = 1.06, 95% CI 1.02-1.11; per 5 μg/m3). Maternal exposure was more strongly related to childhood asthma and wheezing before age 3 (OR = 1.15, 95% CI 1.00-1.31; per 5 μg/m3) than after (OR = 1.04, 95% CI 1.00-1.09; per 5 μg/m3). Children in developed countries showed more severe effects (OR = 1.14, 95% CI 1.02-1.27; per 5 μg/m3). Children who were born to mothers with higher levels of prenatal exposure were at higher risk of asthma and wheezing (OR = 1.07, 95% CI 1.02-1.13; per 5 μg/m3). This meta-analysis indicated that the impact of PM2.5 on childhood asthma and wheezing begins as early as utero, so regulating pollutant emission standards and strengthening prenatal protection are crucial to maternal and child health.