Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter

Excess deaths and loss of life expectancy attributed to long-term NO2 exposure in the Chinese elderly

BACKGROUND

Evidence linking nitrogen dioxide (NO2) air pollution to life span of high-vulnerability older adults is extensively scarce in low- and middle-income countries. This study seeks to quantify mortality risk, excess deaths, and loss of life expectancy (LLE) associated with long-term exposure to NO2 among elderly individuals in China.

METHODS

A nationwide dynamic cohort of 20352 respondents ≥65 years old were enrolled from the China Longitudinal Health and Longevity Survey during 2005-2018. Residential exposures to NO2 and co-pollutants were assessed by well-validated spatiotemporal prediction models. A Cox regression model with time-dependent covariates was utilized to quantify the association of all-cause mortality with NO2 exposure, controlling for confounders such as demographics, lifestyle, health status, and ambient temperature. NO2-attributable deaths and LLE were evaluated for the years 2010 and 2020 based on the pooled NO2-mortality relation derived from multi-national cohort investigations. Decomposition analyses were conducted to dissociate net shift in NO2-related deaths between 2010 and 2020 into four primary contributing factors.

RESULTS

A total of 14313 deaths were recorded during follow-up of approximately 100 hundred person-years (median 3.6 years). We observed an approximately linear relationship (nonlinear P = 0.882) of NO2 exposure with all-cause death across a broad range from 6.6 to 95.7 μg/m3. Every 10-μg/m3 rise in yearly average NO2 concentration was linked to a hazard ratio (HR) of 1.045 (95% confidence interval [CI]: 1.031-1.059). In the updated meta-analysis of this study and 9 existing cohorts, we estimated a pooled HR of 1.043 (95% CI: 1.023-1.063) for each 10-μg/m3 growth in NO2. Reaching a 10-μg/m3 counterfactual target of NO2 concentration in China could avoid 0.33 (95% empirical CI: 0.19-0.49) million premature deaths and an LLE of 0.40 (95% empirical CI: 0.23-0.59) years in 2010, which greatly dropped to 0.24 (95% empirical CI: 0.14-0.36) million deaths and 0.21 (95% empirical CI: 0.12-0.31) years of LLE in 2020. The net fall in NO2-attributable deaths (-26.8%) between 2010 and 2020 was primarily driven by the declines in both NO2 concentration (-41.6%) and mortality rate (-27.1%) under population growth (+41.0%) and age structure transition (+0.9%).

CONCLUSIONS

Our findings provide national evidence for increased risk of premature death and loss of life expectancy attributed to later-life NO2 exposure among the elderly in China. In an accelerated aging society, strengthened clean air actions should be formulated to minimize the health burden and regional inequality in NO2-attributable mortality.

Cross-sectional analysis of socioeconomic drivers of PM2.5 pollution in emerging SAARC economies

Within the intricate interplay of socio-economic, natural and anthropogenic factors, haze pollution stands as a stark emblem of environmental degradation, particularly in the South Asian Association for Regional Cooperation (SAARC) region. Despite significant efforts to mitigate greenhouse gas emissions, several SAARC nations consistently rank among the world's most polluted. Addressing this critical research gap, this study employs robust econometric methodologies to elucidate the dynamics of haze pollution across SAARC countries from 1998 to 2020. These methodologies include the Pooled Mean Group (PMG) and Augmented Mean Group (AMG) estimator, Panel two-stage least squares (TSLS), Feasible Generalized Least Squares (FGLS) and Dumitrescu-Hurlin (D-H) causality test. The analysis reveals a statistically significant cointegrating relationship between PM2.5 and economic indicators, with economic development and consumption expenditure exhibiting positive associations and rainfall demonstrating a mitigating effect. Furthermore, a bidirectional causality is established between temperature and economic growth, both influencing PM2.5 concentrations. These findings emphasize the crucial role of evidence-based policy strategies in curbing air pollution. Based on these insights, recommendations focus on prioritizing green economic paradigms, intensifying forest conservation efforts, fostering the adoption of eco-friendly energy technologies in manufacturing and proactively implementing climate-sensitive policies. By embracing these recommendations, SAARC nations can formulate comprehensive and sustainable approaches to combat air pollution, paving the way for a healthier atmospheric environment for their citizens.

Bi-directional association between outdoor or social activities and cognitive function: do the PM2.5 exposure catalyze the detrimental inactivity-poor cognition cycle?

BACKGROUND

Previous research has shown that lack of leisure activities, either outdoor or social activities, impedes cognitive function. However, the interrelationship between poor cognition and deficient activities is understudied. In addition, whether exposure to air pollution, such as PM2.5, can accelerate the detrimental 'inactivity-poor cognition' cycle, is worthy of investigation.

METHODS

We used data from the 2008, 2011, 2014, and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We assessed the frequency of outdoor or social activities at each wave. The cognitive function was examined using a China-Modified Mini-mental State Examination. We estimated the residential exposure to fine particular matter (PM2.5) via a satellite-based model. We applied cross-lagged panel (CLP) model to examine the bi-directional relationship between outdoor or social activities and cognitive function. We then examined the effect of PM2.5 exposure with sequent cognitive function and activities using generalized estimation equation (GEE) model.

FINDINGS

Overall, we observed significant bi-directional associations between outdoor or social activities and cognitive function. Participants with better cognitive function in the last wave were more likely to engage in outdoor or social activities in the following wave (outdoor activities: β = 0.37, 95% CI [0.27,0.48], P < 0.01; social activities: β = 0.05, 95% CI [0.02,0.09] P < 0.01). Meanwhile, higher engagement in outdoor or social activities in the last wave was associated with more favorable cognitive function in the following wave (outdoor activities: β = 0.06, 95% CI [0.03,0.09], P < 0.01; social activities: β = 0.10, 95% CI [0.03,0.18], P < 0.01). Notably, an increase in PM2.5 exposure during the preceding year was significantly associated with a declining cognitive function (β = -0.05, 95% CI [-0.08,-0.03], P < 0.01), outdoor activities (β = -0.02, 95% CI [-0.04, -0.01], P < 0.01) and social activities (β = -0.02, 95% CI [-0.02, -0.01], P < 0.01) in the current year; the lagged effects of the PM2.5 exposure in the past year of the last wave on activities and cognitive function of the following wave were also observed.

INTERPRETATION

Our findings not only indicate the bi-directional links between the frequency of outdoor or social activities and cognitive function, but also report that PM2.5 exposure plays a role in catalyzing the detrimental inactivity-poor cognition cycle. Future research should investigate whether the policy-driven interventions, such as clean air policies, can break the unfavorable activity-cognition cycle, and thereby promoting health from the dual gains in leisure activities and cognition.

An Inflammatory Question? Prenatal Air Pollution, Childhood Allergic Rhinitis, and Healthy Fats

A study of more than 650 toddlers found that two polyunsaturated fatty acids were associated with fewer cases of allergic rhinitis (hay fever) in children who had been exposed prenatally to higher levels of PM2.5.

Urban health advantage and penalty in aging populations: a comparative study across major megacities in China

Background

Urban living is linked to better health outcomes due to a combination of enhanced access to healthcare, transportation, and human development opportunities. However, spatial inequalities lead to disparities, resulting in urban health advantages and penalties. Understanding the relationship between health and urban development is needed to generate empirical evidence in promoting healthy aging populations. This study provides a comparative analysis using epidemiological evidence across diverse major Chinese cities, examining how their unique urban development trajectories over time have impacted the health of their aging residents.

Methods

We tracked changes in air pollution (NO2, PM2.5, O3), green space (measured by NDVI), road infrastructure (ring road areas), and nighttime lighting over 20 years in six major cities in China. We followed a longitudinal cohort of 4992 elderly participants (average age 87.8 years) over 16,824 person-years. We employed Cox proportional hazard regression to assess longevity, assessing 14 variables, including age, sex, ethnicity, marital status, residence, household income, occupation, education, smoking, alcohol consumption, exercise, and points of interest (POI) count of medicine-related facilities, sports, and leisure service-related places, and scenic spots within a 5 km-radius buffer.

Findings

Geographic proximity to points of interest significantly improves survival. Elderly living in proximity of the POI-rich areas had a 34.6%-35.6% lower mortality risk compared to those in POI-poor areas, for the highest compared to the lowest quartile. However, POI-rich areas had higher air pollution levels, including PM2.5 and NO2, which was associated with a 21% and 10% increase in mortality risk for increase of 10 μg/m3, respectively. The benefits of urban living had higher effect estimates in monocentric cities, with clearly defined central areas, compared to polycentric layouts, with multiple satellite city centers.

Interpretation

Spatial inequalities create urban health advantages for some and penalties for others. Proximity to public facilities and economic activities is associated with health benefits, and may counterbalance the negative health impacts of lower green space and higher air pollution. Our empirical evidence show optimal health gains for age-friendly urban environments come from a balance of infrastructure, points of interest, green spaces, and low air pollution.

Funding

Natural Science Foundation of Beijing (IS23105), National Natural Science Foundation of China (82250610230, 72061137004), World Health Organization (2024/1463606-0), Research Fund Vanke School of Public Health Tsinghua University (2024JC002), Beijing TaiKang YiCai Public Welfare Foundation, National Key R&D Program of China (2018YFC2000400).

Emission characteristics and health effects of PM2.5 from vehicles in typical areas

Introduction

Vehicle emissions have become an important source of urban air pollution, and the assessment of air pollution emission characteristics and health effects caused by specific pollution sources can provide scientific basis for air quality management.

Methods

In this paper, vehicle PM2.5 pollution in typical urban agglomerations of China (the Beijing-Tianjin-Hebei urban agglomeration (BTHUA), the triangle of the Central China urban agglomeration (TCCUA) and the Chengdu-Chongqing urban agglomeration (CCUA)) were used as research samples to evaluate the emission characteristics, health effects and economic losses of vehicle PM2.5 pollution based on the emission inventory, air quality model and exposure-response function from 2010 to 2020.

Results

The results indicated that PM2.5 emissions from vehicles in the three urban agglomerations during 2010-2020 first showed an upward yearly trend and then showed a slow decrease in recent years. Heavy-duty trucks and buses are the main contribution vehicles of PM2.5, and the contribution rates of light-duty vehicles to PM2.5 is increasing year by year. The contribution rate of PM2.5 in Beijing decreased significantly. In addition to capital cities and municipalities directly under the central Government, the emission of pollutants in other cities cannot be ignored. The evaluation results of the impact of PM2.5 pollution from vehicles on population health show that: the number of each health endpoint caused by PM2.5 pollution from vehicles in the BTHUA and CCUA showed an overall upward trend, while the TCCUA showed a downward trend in recent years. Among them, PM2.5 pollution from vehicles in the three major urban agglomerations cause about 78,200 (95% CI: 20,500-138,800) premature deaths, 122,800 (95% CI: 25,600-220,500) inpatients, and 628,400 (95% CI: 307,400-930,400) outpatients and 1,332,400 (95% CI: 482,700-2,075,600) illness in 2020. The total health economic losses caused by PM2.5 pollution from vehicles in the three major urban agglomerations in 2010, 2015 and 2020 were 68.25 billion yuan (95% CI: 21.65-109.16), 206.33 billion yuan (95% CI: 66.20-326.20) and 300.73 billion yuan (95% CI: 96.79-473.16), accounting for 0.67% (95% CI: 0.21-1.07%), 1.19% (95% CI: 0.38%-1.88%) and 1.21% (95% CI: 0.39%-1.90%) of the total GDP of these cities.

Discussion

Due to the differences in vehicle population, PM2.5 concentration, population number and economic value of health terminal units, there are differences in health effects and economic losses among different cities in different regions. Among them, the problems of health risks and economic losses were relatively prominent in Beijing, Chengdu, Chongqing, Tianjin and Wuhan.

How far can air pollution affect tourism in China? Evidence from panel unconditional quantile regressions

Previous studies provide empirical evidence for the connection between air pollution and tourism. However, many of them take the nexus as a linear one. It remains unexplored whether any thresholds are required for the nexus to materialize. This study systematically investigates whether PM2.5 concentrations-an essential indicator of air pollution-affect tourism in China at various tourism development levels. We analyze 284 Chinese cities from 2008 to 2018 using the Unconditional Quantile Regression method. Our statistical results reveal that air pollution positively influences tourism (regarding tourist visits and tourism revenue) in areas with low tourism development levels. However, a complex correlation between air pollution and tourism emerges when tourism development has reached a certain level. The correlation is initially negative, then positive, and finally disappears. But, the overall correlation remains negative. The effects of the interaction between air pollution and tourism resources on tourism are inverted U-shaped, implying that tourism resources can mitigate the negative effects of air pollution on tourism only when tourism development has reached a certain level. Based on the above findings, the associated policy implications are discussed.

Secondary inorganic aerosols and aerosol acidity at different PM2.5 pollution levels during winter haze episodes in the Sichuan Basin, China

Wintertime fine particle (PM2.5) pollution remains to be perplexing air quality problems in many parts of China. In this study, PM2.5 compositions and aerosol acidity at different pollution levels at an urban cite in the southwest China's Sichuan Basin were investigated during a sustained winter haze episode. Organic matter was the most abundant component of PM2.5, followed by nitrate, sulfate and ammonium. Shares of organic aerosol in PM2.5 mass decreased with the elevated PM2.5 levels, while the enhancements of sulfate and secondary organic aerosol were much less than that of nitrate and ammonium during heavy pollution with increased ratios of nitrate to sulfate, implying a significant role of nitrate in the haze formation. Results also suggest the nighttime chemistry might contribute substantially to the formation of nitrate under severe pollutions. The daily average aerosol pH showed a decreasing trend with the elevated levels of PM2.5, and this increased aerosl acidity was mainly due to the fast rising secondary inorganic aerosol (SIA) concentration, with the increase in hydronium ion concentration in air (Hair+) surpassing the dilution effect of elevated aerosol liquid water content (LWC). Thermodynamic model calculations revealed that the air environment was NH3-rich with total NHx (NH3 + NH4+) greater than required NHx, and the aerosol pH exponentially declined with the decreasing excess NHx (p < 0.01). This study demonstrated that under air stagnation and NH3-rich environment during winter, the raised relative humidity (RH) would lead to an increase in LWC and thereby facilitate the aqueous chemistry processes with the neutralization capacity of NH3 to form sulfate and nitrate, which would further increase the LWC and lower the pH. This self-amplifying SIA formation might be crucial to the severe PM2.5 pollution and haze events during winter, and therefore cutting both NOx and NH3 emissions would benefit stopping the self-amplification.

Potentially toxic elements and lead isotopic signatures in the 10 μm fraction of urban dust: Environmental risk enhanced by resuspension of contaminated soils

In urban environments, soils are a sink of pollutants and might become a source of contamination, as they commonly display potentially toxic elements (PTE) concentrations above the legislative limits. Particularly, the inhalable fraction of soils (<10 μm) is enriched in PTE compared to bulk soils (BS). The enrichment makes these particles an environmental hazard because of their susceptibility to resuspension and their potential contribution to road dust (RD) and atmospheric particulate matter (PM10) pollution. To gain a better insight into urban contamination dynamics we studied the BS, the resuspended <10 μm fraction of BS (Res-BS) and RD (Res-RD) in a European historically industrialized and densely populated city. Compared to BS, the Res-BS and Res-RD showed higher PTE concentrations and a higher variability for most of the elements. Lead was the only PTE showing similar concentrations in all the matrices, suggesting shared sources and redistribution pathways within the city. Chemometric elaborations identified Res-BS as a transition between BS and Res-RD or, rather, a Res-RD precursor. Also, Pb was confirmed to be ubiquitous in all the media. In all the matrices, Pb isotopic signatures were investigated and compared with PM10 fingerprints from the same city. The anthropogenic isotopic signature in Res-BS and Res-RD was evident, and samples belonging to neighboring sites showed comparable isotopic ratios. The Res-BS appeared as a key driver for Pb distribution within the city both in Res-RD and in PM10. These results demonstrate the intimate interaction between urban environmental compartments (soil, road dust and PM10), and the active contribution of fine soil fractions to anthropogenic pollution, with relevant policy implications in urban areas since soils were found to contribute directly to air pollution.

A comprehensive review of the development of land use regression approaches for modeling spatiotemporal variations of ambient air pollution: A perspective from 2011 to 2023

Land use regression (LUR) models are widely used in epidemiological and environmental studies to estimate humans' exposure to air pollution within urban areas. However, the early models, developed using linear regressions and data from fixed monitoring stations and passive sampling, were primarily designed to model traditional and criteria air pollutants and had limitations in capturing high-resolution spatiotemporal variations of air pollution. Over the past decade, there has been a notable development of multi-source observations from low-cost monitors, mobile monitoring, and satellites, in conjunction with the integration of advanced statistical methods and spatially and temporally dynamic predictors, which have facilitated significant expansion and advancement of LUR approaches. This paper reviews and synthesizes the recent advances in LUR approaches from the perspectives of the changes in air quality data acquisition, novel predictor variables, advances in model-developing approaches, improvements in validation methods, model transferability, and modeling software as reported in 155 LUR studies published between 2011 and 2023. We demonstrate that these developments have enabled LUR models to be developed for larger study areas and encompass a wider range of criteria and unregulated air pollutants. LUR models in the conventional spatial structure have been complemented by more complex spatiotemporal structures. Compared with linear models, advanced statistical methods yield better predictions when handling data with complex relationships and interactions. Finally, this study explores new developments, identifies potential pathways for further breakthroughs in LUR methodologies, and proposes future research directions. In this context, LUR approaches have the potential to make a significant contribution to future efforts to model the patterns of long- and short-term exposure of urban populations to air pollution.

Particulate Matter Air Pollution is a Significant Risk Factor for Cardiovascular Disease

Air pollution is responsible worldwide for 9-12 million deaths annually. The major contributor to air pollution is particulate matter ≤2.5 µg per cubic meter of air (PM2.5) from vehicles, industrial emissions, and wildfire smoke. United States ambient air standards recommend annual average PM2.5 concentrations of ≤12 μg/m³ while European standards allow an average annual PM2.5 concentration of ≤20 μg/m3. However, significant PM2.5 cardiovascular and pulmonary health risks exist below these concentrations. Chronic PM2.5 exposure significantly increases major cardiovascular and pulmonary event risks in Americans by 8 to more than 20% for each 10-μg/m3 increase in PM2.5. PM2.5-induced increases in lipid peroxidation, induction of vascular inflammation and endothelial cell injury initiate and propagate respiratory diseases, coronary and carotid atherosclerosis. PM2.5 can cause atherosclerotic vascular plaque rupture and myocardial infarction and stroke by activating metalloproteinases. This article discusses PM2.5 effects on the cardiovascular and pulmonary systems, specific PM2.5 pathophysiologic mechanisms contributing to cardiopulmonary disease, and preventive measures to limit the cardiovascular and pulmonary effects of PM2.5.

Surrounding greenness is associated with lower risk and burden of low birth weight in Iran

The nexus between prenatal greenspace exposure and low birth weight (LBW) remains largely unstudied in low- and middle-income countries (LMICs). We investigated a nationwide retrospective cohort of 4,021,741 live births (263,728 LBW births) across 31 provinces in Iran during 2013-2018. Greenness exposure during pregnancy was assessed using satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). We estimated greenness-LBW associations using multiple logistic models, and quantified avoidable LBW cases under scenarios of improved greenspace through counterfactual analyses. Association analyses provide consistent evidence for approximately L-shaped exposure-response functions, linking 7.0-11.5% declines in the odds of LBW to each 0.1-unit rise in NDVI/EVI with multiple buffers. Assuming causality, 3931-5099 LBW births can be avoided by achieving greenness targets of mean NDVI/EVI, amounting to 4.4-5.6% of total LBW births in 2015. Our findings suggest potential health benefits of improved greenspace in lowering LBW risk and burden in LMICs.

Redox and inflammatory mechanisms linking air pollution particulate matter with cardiometabolic derangements

Air pollution is the largest environmental risk factor for disease and premature death. Among the different components that are present in polluted air, fine particulate matter below 2.5 μm in diameter (PM2.5) has been identified as the main hazardous constituent. PM2.5 mainly arises from fossil fuel combustion during power generation, industrial processes, and transportation. Exposure to PM2.5 correlates with enhanced mortality risk from cardiovascular diseases (CVD), such as myocardial infarction and stroke. Over the last decade, it has been increasingly suggested that PM2.5 affects CVD already at the stage of risk factor development. Among the multiple biological mechanisms that have been described, the interplay between oxidative stress and inflammation has been consistently highlighted as one of the main drivers of pulmonary, systemic, and cardiovascular effects of PM2.5 exposure. In this context, PM2.5 uptake by tissue-resident immune cells in the lung promotes oxidative and inflammatory mediators release that alter tissue homeostasis at remote locations. This pathway is central for PM2.5 pathogenesis and might account for the accelerated development of risk factors for CVD, including obesity and diabetes. However, transmission and end-organ mechanisms that explain PM2.5-induced impaired function in metabolic active organs are not completely understood. In this review, the main features of PM2.5 physicochemical characteristics related to PM2.5 ability to induce oxidative stress and inflammation will be presented. Hallmark and recent epidemiological and interventional studies will be summarized and discussed in the context of current air quality guidelines and legislation, knowledge gaps, and inequities. Lastly, mechanistic studies at the intersection between redox metabolism, inflammation, and function will be discussed, with focus on heart and adipose tissue alterations. By offering an integrated analysis of PM2.5-induced effects on cardiometabolic derangements, this review aims to contribute to a better understanding of the pathogenesis and potential interventions of air pollution-related CVD.

Uncertainty Reduction and Environmental Justice in Air Pollution Epidemiology: The Importance of Minority Representation

Ambient air pollution is an increasing threat to society, with rising numbers of adverse outcomes and exposure inequalities worldwide. Reducing uncertainty in health outcomes models and exposure disparity studies is therefore essential to develop policies effective in protecting the most affected places and populations. This study uses the concept of information entropy to study tradeoffs in mortality uncertainty reduction from increasing input data of air pollution versus health outcomes. We study a case scenario for short-term mortality from particulate matter (PM2.5) in North Carolina for 2001-2016, employing a case-crossover design with inputs from an individual-level mortality data set and high-resolution gridded data sets of PM2.5 and weather covariates. We find a significant association between mortality and PM2.5, and the information tradeoffs indicate that a 10% increase in mortality information reduces model uncertainty three times more than increased resolution of the air pollution model from 12 to 1 km. We also find that Non-Hispanic Black (NHB) residents tend to live in relatively more polluted census tracts, and that the mean PM2.5 for NHB cases in the mortality model is significantly higher than that of Non-Hispanic White cases. The distinct distribution of PM2.5 for NHB cases results in a relatively higher information value, and therefore faster uncertainty reduction, for new NHB cases introduced into the mortality model. This newfound influence of exposure disparities in the rate of uncertainty reduction highlights the importance of minority representation in environmental research as a quantitative advantage to produce more confident estimates of the true effects of environmental pollution.

Tracing the plasma kallikrein-kinin system-activating component in the atmospheric particulate matter with different origins

Atmospheric particulate matter (PM) perturbs hematological homeostasis by targeting the plasma kallikrein-kinin system (KKS), causing a cascade of zymogen activation events. However, the causative components involved in PM-induced hematological effects are largely unknown. Herein, the standard reference materials (SRMs) of atmospheric PM, including emissions from the diesel (2975), urban (1648a), and bituminous coal (2693), were screened for their effects on plasma KKS activation, and the effective constituent contributing to PM-induced KKS activation was further explored by fraction isolation and chemical analysis. The effects of three SRMs on KKS activation followed the order of 2975 > 1648a > 2693, wherein the fractions of 2975 isolated by acetone and water, together with the insoluble particulate residues, exerted significant perturbations in the hematological homeostasis. The soot contents in the SRMs and corresponding isolated fractions matched well with their hematological effects, and the KKS activation could be dependent on the soot surface oxidation degree. This study, for the first time, uncovered the soot content in atmospheric PM with different origins contributed to the distinct effects on plasma KKS activation. The finding would be of utmost importance for the health risk assessment on inhaled airborne fine PM, given its inevitable contact with human circulatory system.

Reversal of trends in global fine particulate matter air pollution

Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 μg/m3) to a peak in 2011 (38.9 μg/m3) and decreased steadily afterwards (34.7 μg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.

The challenge of population aging for mitigating deaths from PM2.5 air pollution in China

Estimating the health burden of air pollution against the background of population aging is of great significance for achieving the Sustainable Development Goal 3.9 which aims to substantially reduce the deaths and illnesses from air pollution. Here, we estimated spatiotemporal changes in deaths attributable to PM2.5 air pollution in China from 2000 to 2035 and examined the drivers. The results show that from 2019 to 2035, deaths were projected to decease 15.4% (6.6%-20.7%, 95% CI) and 8.4% (0.6%-13.5%) under the SSP1-2.6 and SSP5-8.5 scenario, respectively, but increase 10.4% (5.1%-20.5%) and 18.1% (13.0%-28.3%) under SSP2-4.5 and SSP3-7.0 scenarios. Population aging will be the leading contributor to increased deaths attributable to PM2.5 air pollution, which will counter the positive gains achieved by improvements in air pollution and healthcare. Region-specific measures are required to mitigate the health burden of air pollution and this requires long-term efforts and mutual cooperation among regions in China.

Association of Fine Particulate Matter and Its Components with Macrosomia: A Nationwide Birth Cohort Study of 336 Chinese Cities

To examine the associations between macrosomia risk and exposure to fine particulate matter (PM2.5) and its chemical components during pregnancy, we collected birth records between 2010 and 2015 in mainland China from the National Free Preconception Health Examination Project and used satellite-based models to estimate concentrations of PM2.5 mass and five main components, namely, black carbon (BC), organic carbon (OC), nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+). Associations between macrosomia risk and prenatal exposure to PM2.5 were examined by logistic regression analysis, and the sensitive subgroups were explored by stratified analyses. Of the 3,248,263 singleton newborns from 336 cities, 165,119 (5.1%) had macrosomia. Each interquartile range increase in concentration of PM2.5 during the entire pregnancy was associated with increased risk of macrosomia (odds ratio (OR) = 1.18; 95% confidence interval (CI), 1.17-1.20). Among specific components, the largest effect estimates were found on NO3- (OR = 1.36; 95% CI, 1.35-1.38) followed by OC (OR = 1.23; 95% CI, 1.22-1.24), NH4+ (OR = 1.22; 95% CI, 1.21-1.23), and BC (OR = 1.21; 95% CI, 1.20-1.22). We also that found boys, women with a normal or lower prepregnancy body mass index, and women with irregular or no folic acid supplementation experienced higher risk of macrosomia associated with PM2.5 exposure.

Global PM2.5 Prediction and Associated Mortality to 2100 under Different Climate Change Scenarios

Ambient fine particulate matter (PM_2.5) has severe adverse health impacts, making it crucial to reduce PM_2.5 exposure for public health. Meteorological and emissions factors, which considerably affect the PM_2.5 concentrations in the atmosphere, vary substantially under different climate change scenarios. In this work, global PM_2.5 concentrations from 2021 to 2100 were generated by combining the deep learning technique, reanalysis data, emission data, and bias-corrected CMIP6 future climate scenario data. Based on the estimated PM_2.5 concentrations, the future premature mortality burden was assessed using the Global Exposure Mortality Model. Our results reveal that SSP3-7.0 scenario is associated with the highest PM_2.5 exposure, with a global concentration of 34.5 μg/m³ in 2100, while SSP1-2.6 scenario has the lowest exposure, with an estimated of 15.7 μg/m³ in 2100. PM_2.5-related deaths for individuals under 75 years will decrease by 16.3 and 10.5% under SSP1-2.6 and SSP5-8.5, respectively, from 2030s to 2090s. However, premature mortality for elderly individuals (>75 years) will increase, causing the contrary trends of improved air quality and increased total PM_2.5-related deaths in the four SSPs. Our results emphasize the need for stronger air pollution mitigation measures to offset the future burden posed by population age.

A cross-sectional analysis of ambient fine particulate matter (PM2.5) exposure and haemoglobin levels in children aged under 5 years living in 36 countries

Low haemoglobin (Hb) concentrations and anaemia in children have adverse effects on development and functioning, some of which may have consequences in later life. Exposure to ambient air pollution is reported to be associated with anaemia, but there is little evidence specific to low- and middle-income countries (LMICs), where childhood anaemia prevalence is greatest. We aimed to determine if long-term ambient fine particulate matter (≤2.5 μm in aerodynamic diameter [PM_2.5]) exposure was associated with Hb levels and the prevalence of anaemia in children aged <5 years living in 36 LMICs. We used Demographic and Health Survey data, collected between 2010 and 2019, which included blood Hb measurements. Satellite-derived estimates of annual average PM_2.5 was the main exposure variable, which was linked to children's area of residence. Anaemia was defined according to standard World Health Organization guidelines (Hb < 11 g/dL). The association of PM_2.5 with Hb levels and anaemia prevalence was examined using multivariable linear and logistic regression models, respectively. We examined whether the effects of ambient PM_2.5 were modified by a child's sex and age, household wealth index, and urban/rural place of residence. Models were adjusted for relevant covariates, including other outdoor pollutants and household cooking fuel. The study included 154,443 children, of which 89,904 (58.2%) were anaemic. The country-level prevalence of anaemia ranged from 15.8% to 87.9%. Mean PM_2.5 exposure was 33.0 (±21.6) μg/m³. The adjusted model showed that a 10 μg/m³ increase in annual PM_2.5 concentration was associated with greater odds of anaemia (OR = 1.098 95% CI: 1.087, 1.109). The same increase in PM_2.5 was associated with a decrease in average Hb levels of 0.075 g/dL (95% CI: 0.081, 0.068). There was evidence of effect modification by household wealth index and place of residence, with greater adverse effects in children from lower wealth quintiles and children in rural areas. Exposure to annual PM_2.5 was cross-sectionally associated with decreased blood Hb levels, and greater risk of anaemia, in children aged <5 years living in 36 LMICs.

Assessment of Regional Differences in the Implementation of the Air Pollution Prevention and Control Action Plan in China

Air pollution is still an important risk factor that endangers the health of Chinese people, leading the government to implement a series of policies to address air pollution. This study takes the Air Pollution Prevention and Control Action Plan (APPCAP) proposed in 2013 as the object and uses the combined data set of China's 2000-2019 economic panel data and PM_2.5 remote sensing data to analyse the implementation effect of the policy by the multiperiod difference-in-differences method, considering regional heterogeneity. The results show that the implementation of the APPCAP significantly reduced the PM_2.5 concentration in China, and the effect was stronger in the Yangtze River Delta region. Future governance policies should further consider local characteristics and determine pollution control goals and measures according to local conditions.

Interaction between home and community-based services and PM2.5 on cognition: A prospective cohort study of Chinese elderly

PM_2.5 and home and community-based services (HCBSs) had been shown to affect cognition, but the evidence on their joint effects was limited. Aimed to study the joint effects of HCBSs and PM_2.5 on cognition, we utilized the follow-up data of participants in the Chinese Longitudinal Health Longevity Survey (CLHLS) who were 65 years of age or older and had normal cognitive function at baseline for the 2008-2018, 2011-2018, and 2014-2018 waves. 16,954, 9,765, and 7192 participants from each of these three waves were initially recruited, respectively. The PM_2.5 concentration data of each province in China from 2008 to 2018 was obtained from the Atmospheric Composition Analysis Group. Participants were asked what kind of HCBSs were available in their community. The cognitive status of the participants was evaluated by the Chinese version of Mini-Mental State Examination (CMMSE). We applied the Cox proportional hazard regression model to investigate the joint effects of HCBSs and PM_2.5 on cognition and further stratified the analysis according to HCBSs. Hazard ratio (HR) and 95% confidence interval (95% CI) were calculated based on Cox models. During a median follow-up period of 5.2 years, 911 (8.8%) participants with normal baseline cognitive function developed cognitive impairment. Compared to participants without HCBSs and exposed to the highest level of PM_2.5, those with HCBSs and exposed to the lowest level of PM_2.5 had a significantly reduced risk of developing cognitive impairment (HR = 0.428, 95% CI: 0.303-0.605). The results from the stratified analysis revealed that the detrimental effect of PM_2.5 on cognition was more pronounced in participants without HCBSs (HR = 3.44, 95% CI: 2.18-5.41) compared with those with HCBSs (HR = 1.42, 95% CI: 0.77-2.61). HCBSs may attenuate the harmful impact of PM_2.5 on cognitive status in the elderly Chinese and the government should further promote the application of HCBSs.

Ambient Air Pollution and All-Cause and Cause-Specific Mortality in an Analysis of Asian Cohorts

INTRODUCTION

Much of what is currently known about the adverse effects of ambient air pollution comes from studies conducted in high-income regions, with relatively low air pollution levels. The aim of the current project is to examine the relationship between exposure to ambient air pollution (as predicted from satellite-based models) and all-cause and cause-specific mortality in several Asian cohorts.

METHODS

Cohorts were recruited from the Asia Cohort Consortium (ACC). The geocoded residences of participants were assigned levels of ambient particulate material with aerodynamic diameter of 2.5 μm or less (PM2.5) and nitrogen dioxide (NO2) utilizing global satellite-derived models and assigned for the year of enrollment (or closest available year). The association between ambient exposure and mortality was established with Cox proportional hazard models, after adjustment for common confounders. Both single- and two-pollutant models were generated. Model robustness was evaluated, and hazard ratios were calculated for each cohort separately and combined via random effect meta-analysis for pooled risk estimates.

RESULTS

Six cohort studies from the ACC participated: the Community-based Cancer Screening Program (CBCSCP, Taiwan), the Golestan Cohort Study (Iran), the Health Effects for Arsenic Longitudinal Study (HEALS, Bangladesh), the Japan Public Health Center-based Prospective Study (JPHC), the Korean Multi-center Cancer Cohort Study (KMCC), and the Mumbai Cohort Study (MCS, India). The cohorts represented over 340,000 participants.

Mean exposures to PM2.5 ranged from 8 to 58 μg/m3. Mean exposures to NO2 ranged from 7 to 23 ppb. For PM2.5, a positive, borderline nonsignificant relationship was observed between PM2.5 and cardiovascular mortality. Other relationships with PM2.5 tended toward the null in meta-analysis. For NO2, an overall positive relationship was observed between exposure to NO2 and all cancers and lung cancer. A borderline association between NO2 and nonmalignant lung disease was also observed. The findings within individual cohorts remained consistent across a variety of subgroups and alternative analyses, including two-pollutant models.

CONCLUSIONS

In a pooled examination of cohort studies across Asia, ambient PM2.5 exposure appears to be associated with an increased risk of cardiovascular mortality and ambient NO2 exposure is associated with an increased cancer (and lung cancer) mortality. This project has shown that satellite-derived models of pollution can be used in examinations of mortality risk in areas with either incomplete or missing air pollution monitoring.

Public perceptions of vehicular traffic emissions on health risk in Lagos metropolis Nigeria: A critical survey

The perception and behavior of the public is key in reducing Traffic-related air pollution health burdens which has become an increasingly alarming problem in many cities across the globe. The study assessed the perception of the public about vehicle traffic emissions and the health hazard associated with them in Lagos, Nigeria using structured questionnaires. Multivariate statistical analysis and structural equation modeling were performed to determine the factors that were associated with the participant's perception of traffic air pollution and the health risks it presents. The findings revealed the majority (78.9%) of the respondents were aware of the haze air pollution from vehicles and its adverse effects on health. The regression model showed a significant relationship between age, education status, employment status, road proximity, vehicle ownership and air pollution awareness (P < 0.05). However, the structural equation model SEM revealed that age, gender, marital status, education, employment status, and road proximity showed statistical significance (p < 0.05) and indicated a linear relationship to vehicular emissions perception. The findings suggest the need to increase public education for all ages and especially for roadside residents on the effects of prolonged exposure and long-term effects of transport-related air pollution and associated risk. The result is applicable in many developing cities, especially in Sub-Saharan Africa.

Long term spatiotemporal trends and health risk assessment of remotely sensed PM2.5 concentrations in Nigeria

PM_2.5 is an important indicator reflecting air quality variations. Currently, environmental pollution related issues have become more severe that significantly threaten human health. The current study is an attempt to analyze the spatio-dynamic characteristics of PM_2.5 in Nigeria based on the directional distribution and trend clustering analysis from 2001 to 2019. The results indicated that PM_2.5 concentration increased in most of the Nigerian states, particularly in mid-northern and southern states. The lowest PM_2.5 concentration in Nigeria is even beyond the interim target-1 (35 μg/m³) of the WHO. During the study period, the average PM_2.5 concentration increased at a growth rate of 0.2 μg/m³/yr from 69 μg/m³ to 81 μg/m³. The growth rate varied from region to region. Kano, Jigawa, Katsina, Bauchi, Yobe, and Zamfara experienced the fastest growth rate of 0.9 μg/m³/yr with 77.9 μg/m³ mean concentration. The median center of the national average PM_2.5 moved toward the north indicating the highest PM_2.5 concentration in northern states. The Saharan desert dust is the dominant source of PM_2.5 in northern areas. Moreover, agricultural practices and deforestation activities along with low rainfall increase desertification and air pollution in these regions. Health risks increased in most of the mid-northern and southern states. The extent of ultra-high health risk (UHR) areas corresponding to the 8×10⁴-7.3×10⁶ μg⋅person/m³ increased from 1.5% to 2.8%. Mainly Kano, Lagos, Oyo, Edo, Osun, Ekiti, southeastern Kwara, Kogi, Enugu, Anambra, Northeastern Imo, Abia, River, Delta, northeastern Bayelsa, Akwa Ibom, Ebonyi, Abuja, Northern Kaduna, Katsina, Jigawa, central Sokoto, northeastern Zamfara, central Borno, central Adamawa, and northwestern Plateau are under UHR areas.

Prenatal exposure to ambient PM2.5 and its chemical constituents and child intelligence quotient at 6 years of age

There are limited studies on the associations between prenatal exposure to constituents of fine particulate matter (PM_2.5) and children's intelligence quotient (IQ). Our study aimed to explore the associations between prenatal PM_2.5 and its six constituents and the IQ levels of 6-year-old children. We included 512 mother-child pairs. We used a satellite-based modelling framework to estimate prenatal PM_2.5 and its six constituents (ammonium, sulfate, nitrate, organic carbon, soil dust, and black carbon). We assessed the children's IQ using the short form of the Wechsler Intelligence Scale. Perceptual Reasoning Index (PRI), Verbal Comprehension Index (VCI), and Full Scale IQ (FSIQ) scores were computed. The multiple informant model (MIM) was applied to explore the trimester specific effects of PM_2.5 and its six constituents' exposure on children's PRI, VCI, and FSIQ. To examine whether the duration of breastfeeding and physical activity (PA) could modify the effects of PM_2.5 on children's IQ, we stratified the analyses according to the duration of breastfeeding (≤6 and >6 months) and time of outdoor activities after school (≤2 and >2 h/week). The first trimester PM_2.5 and its five constituents' exposures were inversely associated with FSIQ [β = -1.34, 95 % confidence interval [CI] (-2.71, 0.04) for PM_2.5] and PRI [β = -2.18, 95 %CI (-3.80, -0.57) for PM_2.5] in children. The associations were magnified among boys and those with less outdoor activities or shorter breastfeeding duration. Our results indicate that prenatal PM_2.5 and several of its main constituents' exposure may disrupt cognitive development in children aged 6 years. More PA and longer breastfeeding duration may alleviate the detrimental effects of prenatal PM_2.5 exposure on children's cognitive function.

Quantitative estimation of the PM2.5 removal capacity and influencing factors of urban green infrastructure

Long-term exposure to PM_2.5 (fine particulate matter with an aerodynamic diameter <2.5 μm) could cause great harm to human health and sustainable development. It remains a challenge to estimate the long-term PM_2.5 removal capacity of nature-based green infrastructure in urban areas. In this paper, the annual PM_2.5 removal capacity of urban green infrastructure (UGI) from 2000 to 2019 in Shenyang was estimated based on the PM2.5 dry deposition model. The spatial heterogeneity of annual PM_2.5 removal capacity were detected Sen-MK test and local spatial autocorrelations analysis. Then the effects of landscape patterns and socioeconomic variables on PM_2.5 removal capacity were explored based on linear regression model. The results illustrated that the PM_2.5 removal capacity of UGI increased significantly from 2000 to 2019 in Shenyang, with the amount of PM_2.5 removal, PM_2.5 removal flux and removal rate increasing by 20.64 Mg/a, 0.0258 g/m²/a, and 0.377 %/a, respectively. The PM_2.5 removal capacity of UGI exhibited spatial heterogeneity in the study area. Specifically, the regions experiencing the increase in PM_2.5 removal capacity of UGI accounted for majority of the old urban area of Shenyang City during the study period; the lower PM_2.5 removal capacity clustered in the center urban area, in which high density impervious surfaces distributed, while the higher PM_2.5 removal capacity mainly gathered in the area with large scale green space; PM_2.5 removal capacity were significantly higher in urban functional zones with a high proportion of green spaces. The landscape metrics representing fragmentation and shape complexity positively affected the annual PM_2.5 removal flux and removal rate, while the aggregation metrics had significantly negative correlations with the PM_2.5 removal flux and removal rate. Moreover, it was also found that population density and GDP negatively affected the PM_2.5 removal capacity of UGI. This study provides a methodological reference and some new insights for future urban landscape planning and air pollution purification.

Environmental Regulation in Evolution and Governance Strategies

Environmental regulation faces theoretical and practical research challenges on global scale, due to differences such as language and policy environment. Research reflects the beneficial exploration of scholars, policymakers, and enterprises in the cognitive and behavioural norms of economic development, environmental protection, and social governance. This study demonstrated that the relevant research is motivated by the enaction of environmental regulations and discussed the influence of relevant research on the evolution of environmental regulations. Under the assumption that environmental regulations are consistent with related research, this study used 9185 papers in the field of environmental regulation from 2000 to 2019 to construct a research network panorama and explored the development and revelation of environmental regulation. The results revealed that environmental regulation research is motivated by the introduction of policies, and regulation is influenced by research evolution with the path of 'competitiveness-technological change-innovation.' In addition, after the twenty-first session of the Conference of the Parties (COP21), the number of studies increased significantly, with the USA in the leading position in the research field. Furthermore, governance strategies were inspired by real events, including the increasing concern with climate change, regional research preferences, and the promotion of information disclosure. These results suggest that environmental governors should focus on climate change, localisation, and mechanisms of information disclosure.

Long-term fine particular exposure and incidence of frailty in older adults: findings from the Chinese Longitudinal Healthy Longevity Survey

BACKGROUND

The association between fine particular matter (PM2.5) and frailty is less studied, and the national burden of PM2.5-related frailty in China is unknown.

OBJECTIVE

To explore the association between PM2.5 exposure and incident frailty in older adults, and estimate the corresponding disease burden.

DESIGN

Chinese Longitudinal Healthy Longevity Survey from 1998 to 2014.

SETTING

Twenty-three provinces in China.

SUBJECTS

A total of 25,047 participants aged ≥65-year-old.

METHODS

Cox proportional hazards models were performed to evaluate the association between PM2.5 and frailty in older adults. A method adapted from the Global Burden of Disease Study was used to calculate the PM2.5-related frailty disease burden.

RESULTS

A total of 5,733 incidents of frailty were observed during 107,814.8 person-years follow-up. A 10 μg/m3 increment of PM2.5 was associated with a 5.0% increase in the risk of frailty (Hazard Ratio = 1.05, 95% confidence interval = [1.03-1.07]). Monotonic, but non-linear exposure-response, relationships of PM2.5 with risk of frailty were observed, and slopes were steeper at concentrations >50 μg/m³. Considering the interaction between population ageing and mitigation of PM2.5, the PM2.5-related frailty cases were almost unchanged in 2010, 2020 and 2030, with estimations of 664,097, 730,858 and 665,169, respectively.

CONCLUSIONS

This nation-wide prospective cohort study showed a positive association between long-term PM2.5 exposure and frailty incidence. The estimated disease burden indicated that implementing clean air actions may prevent frailty and substantially offset the burden of population ageing worldwide.

A cross-sectional analysis of long-term exposure to ambient air pollution and cognitive development in children aged 3-4 years living in 12 low- and middle-income countries

Exposure to ambient air pollution may affect cognitive functioning and development in children. Unfortunately, there is little evidence available for low- and middle-income countries (LMICs), where air pollution levels are highest. We analysed the association between exposure to ambient fine particulate matter (≤2.5 μm [PM_2.5]) and cognitive development indicators in a cross-sectional analysis of children (aged 3-4 years) in 12 LMICs. We linked Demographic and Health Survey data, conducted between 2011 and 2018, with global estimates of PM_2.5 mass concentrations to examine annual average exposure to PM_2.5 and cognitive development (literacy-numeracy and learning domains) in children. Cognitive development was assessed using the United Nations Children's Fund's early child development indicators administered to each child's mother. We used multivariable logistic regression models, adjusted for individual- and area-level covariates, and multi-pollutant models (including nitrogen dioxide and surface-level ozone). We assessed if sex and urban/rural status modified the association of PM_2.5 with the outcome. We included 57,647 children, of whom, 9613 (13.3%) had indicators of cognitive delay. In the adjusted model, a 5 μg/m³ increase in annual all composition PM_2.5 was associated with greater odds of cognitive delay (OR = 1.17; 95% CI: 1.13, 1.22). A 5 μg/m³ increase in anthropogenic PM_2.5 was also associated with greater odds of cognitive delay (OR = 1.05; 95% CI: 1.00, 1.10). These results were robust to several sensitivity analyses, including multi-pollutant models. Interaction terms showed that urban-dwelling children had greater odds of cognitive delay than rural-dwelling children, while there was no significant difference by sex. Our findings suggest that annual average exposure to PM_2.5 in young children was associated with adverse effects on cognitive development, which may have long-term consequences for educational attainment and health.

Manufacturing agglomeration, urban form, and haze pollution

Manufacturing agglomeration promotes rapid economic development while also causing severe environmental pollution. This paper investigates the impact and mechanism of manufacturing agglomeration on haze pollution from the Chinese city level. Furthermore, we discuss the moderating effect and threshold effect of the three urban forms of urban external shape complexity, urban compactness, and urban fragmentation on the relationship between the two. The result shows the following: (1) The aggregation of the manufacturing industry presents an inverted U-shaped characteristic of promoting first and then inhibiting haze pollution in China's overall, eastern and central regions. (2) The complexity of the city's external shape and the city's fragmentation has a positive moderating effect on the relationship between manufacturing agglomeration and haze pollution. And urban fragmentation shows a negative moderating effect on the relationship between the two when the level of manufacturing agglomeration is on the right side of the inverted U-shaped curve. (3) The urban form shows a significant double threshold characteristic for haze pollution, increasing the complexity of the city's external shape and the city's fragmentation. The agglomeration of manufacturing shows the characteristics of first inhibiting and then promoting haze pollution. As urban compactness increases, the inhibitory effect of manufacturing agglomeration on haze pollution increases.

Haze and inbound tourism: Empirical evidence from China

The impact of climate change on tourism has always been an important topic for research in the field of international tourism, and haze has been widely recognized as the primary negative factor affecting the development of inbound tourism in China. In this study, we first conduct a theoretical analysis of the mechanism through which haze influences the tourism industry, and then we empirically analyze the impact on China's inbound tourism using surface particulate matter (PM2.5) concentrations as a proxy for haze, based on provincial panel data from 1998 to 2016. The empirical results show that haze not only has an inhibitory effect on inbound tourism, but also significantly reduces the average length of stay of international tourists. In addition, while there are significant regional differences in the crowding-out effect of haze pollution on inbound tourism, the effect varies depending on the origin of inbound tourists, exhibiting the greatest negative impact on inbound tourism from Taiwan and the smallest from foreign countries. Our research highlights that haze pollution can led to the change of human tourism behavior which enrich the literature on tourism and haze.

The impact of air pollution on physical disability in a middle-aged and older Chinese population using regression discontinuity design

Emerging evidence has shown the association between ambient air pollution exposure and comorbid chronic diseases, which can subsequently impair physical function. However, less is known about the causal and contextual effect of air pollution on physical disability. Using data from the China Health and Retirement Longitudinal Study (CHARLS), this study employs a geographical regression discontinuity design based on the Huai River Policy to estimate the impact of ambient air pollution on physical disability in activities of daily living (ADL) in China. We find that a 10 μg/m³ increase in particulate matter [particulate matter smaller than 10 μm (PM₁₀)] leads to a 5.4% increase in the incidence of physical disability among middle-aged and older adults. This result is robust to using alternative measurement of key variables, different bandwidths and polynomial functions, and adjustment for a set of sociodemographic covariates. Stroke might be one of the potential pathological pathways linking air pollution and physical disability, with a 10 μg/m³ increase in PM₁₀ leading to a 4.7% increase in the incidence of stroke. In heterogeneity analyses, we find that older adults, males, urban residents, and people with lower socioeconomic status are more vulnerable to air pollution. These results contribute to the limited evidence on the causal and contextual effect of air pollution on physical health, and further provide policy implications for air quality control and health protection for vulnerable populations.

Understanding Anthropogenic PM2.5 Concentrations and Their Drivers in China during 1998-2016

Air pollution poses serious challenges for human health and wellbeing. It also affects atmospheric visibility and contributes to climate change. As social and economic processes have increased, anthropogenic PM_2.5 pollution caused by intensive human activities has led to extremely severe air pollution. Spatiotemporal patterns and drivers of anthropogenic PM_2.5 concentrations have received increasing attention from the scientific community. Nonetheless, spatiotemporal patterns and drivers of anthropogenic PM_2.5 concentrations are still inadequately understood. Based on a time series of remotely sensed anthropogenic PM_2.5 concentrations, this study analyzed the spatiotemporal patterns of this crucial pollutant in China from 1998 to 2016 using Sen's slope estimator and the Mann-Kendall trend model. This, in combination with grey correlation analysis (GCA), was used to reveal the socioeconomic factors influencing anthropogenic PM_2.5 concentrations in eastern, central, and western China from 1998 to 2016. The results were as follows: (1) the average annual anthropogenic concentration of PM_2.5 in China increased quickly and reached its peak value in 2007, then remained stable in the following years; (2) only 63.30 to 55.09% of the land area reached the threshold value of 15 μg/m³ from 1998 to 2016; (3) regarding the polarization phenomenon of anthropogenic PM_2.5 concentrations existing in eastern and central China, the proportion of gradient 1 (≤15 μg/m³) gradually decreased and gradient 3 (≥35 μg/m³) gradually increased; and (4) the urbanization level (UR), population density (PD), and proportion of secondary industry to gross domestic product (SI) were the dominant socioeconomic factors affecting the formation of anthropogenic PM_2.5 concentrations in eastern, central, and western China, independently. The improvements in energy consumption per gross domestic product (EI) have a greater potential for mitigating anthropogenic PM_2.5 emissions in central and western China. These findings allow an interpretation of the spatial distribution of anthropogenic PM_2.5 concentrations and the mechanisms influencing anthropogenic PM_2.5 concentrations, which can help the Chinese government develop effective abatement strategies.

Spatiotemporal Evolution and Drivers of Total Health Expenditure across Mainland China in Recent Years

A substantially growing health expenditure has become an important global issue. Thus, how and why health expenditure is rising should be urgently investigated in systematic research. The Bayesian space-time model and the Bayesian least absolute shrinkage and selection operator (LASSO) model were employed in this study to investigate the spatiotemporal trends and influence patterns of total health expenditure per capita (THEPC) and total health expenditure (THEE) as a share of the gross domestic product (GDP) on the Chinese mainland from 2009 to 2018. The spatial distribution of THEE as a share of GDP in mainland China has shaped a distinct geographical structure with the characteristic of 'west high/east low'. Its local increasing trends formed a geographical structure that exhibited a 'north high/south low' feature. The heterogeneity of the influence patterns of health expenditure was observed from east to west across China. Natural environmental factors, such as air pollution and green coverage, along with changes in dietary structures, have increasingly influenced the growth of health expenditures.

Exposure to ultrafine particles and the incidence of asthma in children: A population-based cohort study in Montreal, Canada

Asthma is the most prevalent chronic respiratory disease in children. The role of ultrafine particles (UFPs) in the development of the disease remains unclear. We used a population-based birth cohort to evaluate the association between prenatal and childhood exposure to low levels of ambient UFPs and childhood-onset asthma.

Methods

The cohort included all children born and residing in Montreal, Canada, between 2000 and 2015. Children were followed for asthma onset from birth until <13 years of age. Spatially resolved annual mean concentrations of ambient UFPs were estimated from a land use regression model. We assigned prenatal exposure according to the residential postal code at birth. We also considered current exposure during childhood accounting for time-varying residence location. We estimated hazard ratios (HRs) using Cox proportional hazards models adjusted for age, sex, neighborhood material and social deprivation, calendar year, and coexposure to ambient nitrogen dioxide (NO₂) and fine particles (PM_2.5).

Results

The cohort included 352,966 children, with 30,825 children developing asthma during follow-up. Mean prenatal and childhood UFP exposure were 24,706 particles/cm³ (interquartile range [IQR] = 3,785 particles/cm³) and 24,525 particles/cm³ (IQR = 3,427 particles/cm³), respectively. Both prenatal and childhood UFP exposure were not associated with childhood asthma onset in single pollutant models (HR per IQR increase of 0.99 [95% CI = 0.98, 1.00]). Estimates of association remained similar when adjusting for coexposure to ambient NO₂ and PM_2.5.

Conclusion

In this population-based birth cohort, childhood asthma onset was not associated with prenatal or childhood exposure to low concentrations of UFPs.

Assessment of spatiotemporal changes of ecological environment quality of the Yangtze River Delta urban agglomeration in China based on MRSEI

The Ecological Environment Quality (EEQ) is an important foundation for the sustainable development of society and economy. To assess the spatiotemporal changes of the EEQ in the Yangtze River Delta Urban Agglomeration (YRDUA), we selected MODIS images of 2001, 2006, 2011, 2016 and 2021 to construct the Modified Remote Sensing Ecological Index (MRSEI) based on Google Earth Engine (GEE) platform and Principal Component Analysis (PCA). Then, we evaluated the spatiotemporal changes and spatial autocorrelation of the EEQ in the YRDUA. The results showed that: the EEQ of the YRDUA was improved from 2001 to 2011, deteriorated from 2011 to 2016, and improved from 2016 to 2021. The overall EEQ of the YRDUA was at moderate or excellent level, and the EEQ in the south was better than that in the north. The EEQ of the southern cities in the study area was better and more stable, while that of the northern cities was relatively poor and changes relatively drastic. The EEQ of the YRDUA was mainly unchanged and improved from 2001 to 2021. The regions with improved EEQ were mainly distributed in the north and west, while those with deteriorated EEQ were mainly distributed in the east and south. The EEQ of the YRDUA was improved gradually from 2001 to 2006, and relatively stable from 2006 to 2011. From 2011 to 2016, the changes were drastic and the EEQ deteriorated greatly; while from 2016 to 2021, the EEQ of the YRDUA was improved, and the area of ecological deterioration was significantly reduced. From 2001 to 2021, the Globalmoran’s I value ranged from 0.838 ~ 0.918. In the past 20 years, NS area in the YRDUA accounted for the highest proportion, while the HH aggregation was mainly distributed in the southern part of the YRDUA, while LL aggregation was mainly distributed in the northern part, indicated that the EEQ in the southern part was better than that in the northern part. This study provides a promising approach to assess the spatiotemporal changes of EEQ in urban areas, which is crucial to formulate the ecosystem protection policies and sustainable development strategies of YRDUA.

Particulate matter of air pollution may increase risk of kidney failure in IgA nephropathy

IgA nephropathy (IgAN) is characterized by deposition of galactose-deficient IgA1 (Gd-IgA1) in glomerular mesangium associated with mucosal immune disorders. Since environmental pollution has been associated with the progression of chronic kidney disease in the general population, we specifically investigated the influence of exposure to fine particulate matter less than 2.5 μm in diameter (PM2.5) on IgAN progression. Patients with biopsy-proven primary IgAN were recruited from seven Chinese kidney centers. PM2.5 exposure from 1998 to 2016 was derived from satellite aerosol optical depth data and a total of 1,979 patients with IgAN, including 994 males were enrolled. The PM2.5 exposure levels for patients from different provinces varied but, in general, the PM2.5 exposure levels among patients from the north were higher than those among patients from the south. The severity of PM2.5 exposure in different regions was correlated with regional kidney failure burden. In addition, each 10 μg/m³ increase in annual average concentration of PM2.5 exposure before study entry (Hazard Ratio, 1.14; 95% confidence interval, 1.06-1.22) or time-varying PM2.5 exposure after study entry (1.10; 1.01-1.18) were associated with increased kidney failure risk after adjustment for age, gender, estimated glomerular filtration rate, urine protein, uric acid, hemoglobin, mean arterial pressure, Oxford classification, glucocorticoid and renin-angiotensin system blocker therapy. The associations were robust when the time period, risk factors of cardiovascular diseases or city size were further adjusted on the basis of the above model. Thus, our results suggest that PM2.5 is an independent risk factor for kidney failure in patients with IgAN, but these findings will require validation in more diverse populations and other geographic regions.

Effects of prenatal exposure to PM2.5 and its composition on cognitive and motor functions in children at 12 months of age: The Shanghai Birth Cohort Study

BACKGROUND

Prenatal fine particulate matter (PM_2.5) exposure has been linked to infant cognitive and motor functions, but the effects of PM_2.5 chemical composition remain unclear.

OBJECTIVES

We aimed to explore the associations of prenatal PM_2.5 and its composition exposure with infant cognitive and motor functions.

METHODS

We studied 2,435 mother-infant pairs in the Shanghai Birth Cohort Study. PM_2.5 and its seven compositions [primary particles (black carbon, mineral dust and sea salts) and secondary particles (NH₄⁺, NO₃^-, SO₄^2- and organic matter)] during thethreetrimesters ofpregnancy were retrieved from the V4.CH.03 product developed by using a combined geoscience-statistical method. At the 12-month-old follow-up, infant cognitive and motor functions in five domains were assessed using the Ages and Stages Questionnaire (ASQ). We used multivariable linear regressions to estimate the effects of PM_2.5 and its composition on the ASQ scores, for all infants and stratifying by sex and breastfeeding duration.

RESULTS

PM_2.5 exposure was negatively associated with gross motor, problem-solving and personal-social scores for all infants. PM_2.5 compositions were inversely associated with ASQ scores in all five domains, and the effects of different compositions varied across domains. Specifically, all compositions except organic matter were correlated with lower problem-solving scores [e.g., ( [Formula: see text]  =  - 10.79, 95 % CI: -17.40, -4.18) ∼ ( [Formula: see text]  =  - 4.68, 95 % CI: -7.84, -1.53); for each 10 μg/m³ increase in PM_2.5 compositions during the third trimester]. Primary and some secondary particles (organic matter, NO₃^-) were related to lower gross motor scores. Secondary particles were also inversely associated with communication (organic matter and NO₃^-), fine motor (NH₄⁺, NO₃^-, SO₄^2-) and personal-social (NH₄⁺) scores. Additionally, boys and infants breastfed for < 6 months appeared to be more susceptible.

CONCLUSIONS

We found negative associations of PM_2.5 and its compositions with infant cognitive and motor functions over a range of domains, especially the problem-solving domain.

Exploring the association between resource dependence and haze pollution in China: the mediating effect of green technology innovation

Haze pollution has been addressed in extensive studies over the last few years. However, the relationship between resource dependence and haze pollution has not been fully investigated. This study focuses on addressing this problem while considering the mediating role of green technology innovation. A panel dataset of 263 prefecture-level cities in China from 2005 to 2018 is used for the analysis. The results show the following: (1) the two-way fixed-effect model reveals that resource dependence contributes significantly to haze pollution, and this finding remains robust across a series of robustness tests. (2) A mediation analysis indicates that resource dependence is unfavorable for green technology innovation, indirectly affecting the alleviation of haze pollution. (3) The results of panel threshold regression suggest that green technology innovation promotes haze reduction in the weak and medium resource dependence stages, whereas this optimization effect disappears in the strong resource dependence stage due to rebound effects. (4) The results of regional heterogeneity demonstrate that the positive effects of resource dependence on haze pollution exist in eastern and western China but not in central China. Based on these results, policy implications are given to reduce haze pollution.

Spatial and temporal variations in PM2.5 and associated health risk assessment in Saudi Arabia using remote sensing

Air pollutants, especially ambient particulate matter (PM_2.5), detrimentally impact human health and cause premature deaths. The dynamic characteristics and associated health risks of PM_2.5 are analyzed based on the standard deviational ellipse (SDE) and trend analysis in Saudi Arabia (SAU) from 1998 to 2018 by utilizing recently updated satellite-derived PM_2.5 concentrations (V4.GL.03). The outcomes show that the national average PM_2.5 concentration increased from 28 μg/m³ to 45 μg/m³ with a growth rate of 2.3 μg/m³/year. The center of median PM_2.5 concentrations moved to the southeast over the years studied due to the presence of vast sandy deserts, sand dunes, a busy port, and coastal and industrial areas in this region. The areas of SAU that experienced PM_2.5 concentrations above 35 μg/m³ increased from 20% to 70%. The rapid-fast growth (RFG) class acquired from the unsupervised classification has the fastest growth rate of 2.5 μg/m³/yr, occurring in southeastern SAU, namely Ash-Sharqiyah, Ar-Riyad, and Najran. It covered ∼27% of the total area of SAU over the study period. Whereas, the slow growth (SG) class with a less than 0.2 μg/m³/yr growth rate covered 12% of the total area of SAU, distributed in northwestern regions. The extent of extremely-high risk areas corresponding to greater than 1 × 10³ μg·person/m³ increased from 4% to 11%, particularly in Makkah, Central Al-Madinah, and western Asir, Jizan, mid-eastern Najran, Al-Quassim, and mid-eastern Ar-Riyad and Ash Sharqiyah.

Do anthropogenic and natural factors elevate the haze pollution in the South Asian countries? Evidence from long-term cointegration and VECM causality estimation

Anthropogenic and natural factors lead to substantial environmental degradation. This shift is aligned with the country's overall development, resulting in high demand for energy resources and a dramatic shift in human activities that contribute to haze pollution. Some of the countries in the South Asian region are ranked between one and twenty on the list of countries with the highest levels of PM2.5 pollution. The member countries have taken many steps to tackle global warming, but concern about haze pollution was found limited. Moreover, very little research was conducted on haze pollution, which led us to conduct this research in this region. This study used the panel data from 1998 to 2018 and a set of econometric models like long-term cointegrating relationship, fully modified ordinary least squares, and vector error-correction model Granger causality tests to examine the major drivers like anthropogenic and natural factors that might elevate haze pollution. Furthermore, our empirical results depict that (1) there is a long-term cointegrating relation between haze and the factors studied. (2) Energy consumption, urbanisation, and economic growth are the primary drivers of environmental degradation. (3) Rainfall has the most substantial influence on reducing haze pollution. The study concluded that (a) if the countries continue to develop at the same pace, all factors studied will continue to drive haze pollution to rise. (b) A decrease in PM2.5 pollution requires improvements in regional rainfall through vegetation, reducing reliance on fossil fuel-based energy sources, and increasing environmental education. (c) Slowing down the drive for urbanisation would not be cost-effective in reducing haze pollution in the region in the short run. Thus, reducing haze by adjusting the factors studied would not be easy in the short run and require the careful adoption of long-term policies.

Impact of dust accumulation on the physiological functioning of selected herbaceous plants of Delhi, India

Plants are now widely recognized for their potential role in improving the air quality by dispersion and deposition of atmospheric dust particles. However, suspended dust particles negatively affect plant growth and physiological development. The present study aims to assess the amount of dust accumulation on the leaf surface and to evaluate the effect of foliar dust on leaf gas exchange parameters, photosynthetic pigment, and metabolite content of five roadside herbaceous plant species (Amaranthus viridis, Achyranthes aspera, Acalypha indica, Parthenium hysterophorus, Trianthema portulacastrum). Two sites (site I and site II) were selected that differed in their surrounding anthropogenic activities and dust pollution levels. Results showed that the average amount of dust accumulated on the leaf surface was significantly greater in plants grown at the polluted site. Among the five species examined, the highest amount of foliar dust load was observed for A. aspera (0.49 mg cm-2). Dust accumulation caused substantial changes in plant physiology as indicated by the significant decline in chlorophyll content, photosynthetic rate, stomatal conductivity, and transpiration rate in plants grown at the polluted site. Moreover, an increase in antioxidant activity, total ascorbate, and metabolite content, responsible for maintaining plant defense, was higher in plants at polluted site. Biochemical response of the individual plants studied was variable, which suggests that different plants adopted different mechanisms to cope with the stress induced by dust particles.

Spatial Autocorrelation and Temporal Convergence of PM2.5 Concentrations in Chinese Cities

Scientific study of the temporal and spatial distribution characteristics of haze is important for the governance of haze pollution and the formulation of environmental policies. This study used panel data of the concentrations of particulate matter sized < 2.5 μm (PM2.5) in 340 major cities from 1999 to 2016 to calculate the spatial distribution correlation by the spatial analysis method and test the temporal convergence of the urban PM2.5 concentration distribution using an econometric model. It found that the spatial autocorrelation of PM2.5 seemed positive, and this trend increased over time. The yearly concentrations of PM2.5 were converged, and the temporal convergence fluctuated under the influence of specific historical events and economic backgrounds. The spatial agglomeration effect of PM2.5 concentrations in adjacent areas weakened the temporal convergence of PM2.5 concentrations. This paper introduced policy implications for haze prevention and control.

The "Pollution Halo" Effect of FDI: Evidence from the Chinese Sichuan-Chongqing Urban Agglomeration

In this paper, panel data from nineteen key cities in the Sichuan-Chongqing urban agglomeration from 2003 to 2016 were used as the study sample. Using the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model, the effect of foreign direct investment (FDI) on particulate matter (PM_2.5) pollution and its action mechanism in the Sichuan-Chongqing urban agglomeration were considered for both socioeconomic and natural factors. The results showed that the "pollution halo" hypothesis of FDI in the Sichuan-Chongqing urban agglomeration has been supported. There are significant positive spatial spillover effects of PM_2.5 pollution in this urban agglomeration, and the introduction of FDI is conducive to alleviating PM_2.5 pollution in the urban agglomeration. Similar to the "inverted U" curve proposed by the environmental Kuznets curve (EKC) hypothesis, there was a significant "inverted U" curve relationship between PM_2.5 pollution and economic growth in the Sichuan-Chongqing urban agglomeration. However, there was a significant "U"-type curve relationship between the urbanization degree and the PM_2.5 concentration, which indicates that the current urbanization mode may aggravate the pollution degree of PM_2.5 in the urban agglomeration in the long term. Furthermore, the two natural factors of annual average temperature and annual precipitation play an important role in PM_2.5 pollution and spatial spillover effect in the Sichuan-Chongqing urban agglomeration. Economic development and rationalization of the industrial structure are the main ways by which FDI affects PM_2.5 pollution in the urban agglomeration. The research conclusions of this study can be of great practical significance to optimize the regional industrial layout, control PM_2.5 pollution, and establish a sustainable development policy system in the Sichuan-Chongqing urban agglomeration.

Acute exposure to air pollutants increase the risk of acute glaucoma

Background

Ambient air pollution is related to the onset and progression of ocular disease. However, the effect of air pollutants on the acute glaucoma remains unclear.

Objective

To investigate the effect of air pollutants on the incidence of acute glaucoma (acute angle closure glaucoma and glaucomatocyclitic crisis) among adults.

Methods

We conducted a time-stratified case-crossover study based on the data of glaucoma outpatients from January, 2015 to Dec, 2021 in Shanghai, China. A conditional logistic regression model combined with a polynomial distributed lag model was applied for the statistical analysis. Each case serves as its own referent by comparing exposures on the day of the outpatient visit to the exposures on the other 3–4 control days on the same week, month and year. To fully capture the delayed effect of air pollution, we used a maximum lag of 7 days in main model.

Results

A total of 14,385 acute glaucoma outpatients were included in this study. We found exposure to PM_2.5, PM₁₀, nitrogen dioxide (NO₂) and carbon monoxide (CO) significantly increased the odds of outpatient visit for acute glaucoma. Wherein the odds of acute glaucoma related to PM_2.5 and NO₂ were higher and more sustained, with OR of 1.07 (95%CI: 1.03–1.11) and 1.12 (95% CI: 1.08–1.17) for an IQR increase over lag 0–3 days, than PM₁₀ and CO over lag 0–1 days (OR:1.03; 95% CI: 1.01–1.05; OR: 1.04; 95% CI: 1.01–1.07).

Conclusions

This case-crossover study provided first-hand evidence that air pollutants, especially PM_2.5 and NO₂, significantly increased risk of acute glaucoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14078-9.

Mortality Associated with Ambient PM2.5 Exposure in India: Results from the Million Death Study

BACKGROUND

Studies on the extent to which long-term exposure to ambient particulate matter (PM) with aerodynamic diameter ≤2.5μm (PM2.5) contributes to adult mortality in India are few, despite over 99% of Indians being exposed to levels that the World Health Organization (WHO) considers unsafe.

OBJECTIVE

We conducted a retrospective cohort study within the Million Death Study (MDS) to provide the first-ever quantification of national mortality from exposure to PM2.5 in India from 1999 to 2014.

METHODS

We calculated relative risks (RRs) by linking a total of ten 3-y intervals of satellite-based estimated PM2.5 exposure to deaths 3 to 5 y later in over 7,400 small villages or urban blocks covering a total population of 6.8 million. We applied using a model-based geostatistical model, adjusted for individual age, sex, and year of death; smoking prevalence, rural/urban residency, area-level female illiteracy, languages, and spatial clustering and unit-level variation.

RESULTS

PM2.5 exposure levels increased from 1999 to 2014, particularly in central and eastern India. Among 212,573 deaths at ages 15-69 y, after spatial adjustment, we found a significant RR of 1.09 [95% credible interval (CI): 1.04, 1.14] for stroke deaths per 10-μg/m3 increase in PM2.5 exposure, but no significant excess for deaths from chronic respiratory disease and ischemic heart disease (IHD), all nonaccidental causes, and total mortality (after excluding stroke). Spatial adjustment attenuated the RRs for chronic respiratory disease and IHD but raised those for stroke. The RRs were consistent in various sensitivity analyses with spatial adjustment, including stratifying by levels of solid fuel exposure, by sex, and by age group, addition of climatic variables, and in supplementary case-control analyses using injury deaths as controls.

DISCUSSION

Direct epidemiological measurements, despite inherent limitations, yielded associations between mortality and long-term PM2.5 inconsistent with those reported in earlier models used by the WHO to derive estimates of PM2.5 mortality in India. The modest RRs in our study are consistent with near or null mortality effects. They suggest suitable caution in estimating deaths from PM2.5 exposure based on MDS results and even more caution in extrapolating model-based associations of risk derived mostly from high-income countries to India. https://doi.org/10.1289/EHP9538.

A new hybrid prediction model of PM2.5 concentration based on secondary decomposition and optimized extreme learning machine

As air pollution worsens, the prediction of PM2.5 concentration becomes increasingly important for public health. This paper proposes a new hybrid prediction model of PM2.5 concentration based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), amplitude-aware permutation entropy (AAPE), variational mode decomposition improved by marine predators algorithm (MPA-VMD), and extreme learning machine optimized by chimp optimization algorithm (ChOA-ELM), named CEEMDAN-AAPE-MPA-VMD-ChOA-ELM. Firstly, CEEMDAN is used to decompose the original data, and AAPE is used to quantify the complexity of all IMF components. Secondly, MPA-VMD is used to decompose the IMF component with the maximum AAPE. Lastly, ChOA-ELM is used to predict all IMF components, and all prediction results are reconstructed to obtain the final prediction results. The proposed model combines the advantages of secondary decomposition technique, feature analysis, and optimization algorithm, which can predict PM2.5 concentration accurately. PM2.5 concentrations at hourly intervals collected from March 1, 2021, to March 31, 2021, in Shanghai and Shenyang, China, are used for experimental study and DM test. The experimental results in Shanghai show that the RMSE, MAE, MAPE, and R2 of the proposed model are 1.0676, 0.7685, 0.0181, and 0.9980 respectively, which is better than all comparison models at 90% confidence level. In Shenyang, the RMSE, MAE, MAPE, and R2 of the proposed model are 1.4399, 1.1258, 0.0389, and 0.9976, respectively, which is better than all comparison models at 95% confidence level.

The life expectancy benefits on respiratory diseases gained by reducing the daily concentration of particulate matter to attain different air quality standard targets: findings from a 5-year time-series study in Tianjin, China

The short-term effects of particulate matter (PM) on years of life lost (YLL) have been confirmed by several studies; however, little attention has been paid to the effects of PM on life expectancy from respiratory diseases (RD), especially at the city level. A generalized additive model (GAM) was used to assess the associations between daily PM and YLL of the RD and chronic obstructive pulmonary diseases (COPD) in Tianjin from 2015 to 2019. Then the daily avoidable YLL, attributable fraction, and potential life expectancy benefits (PLEB) of RD and COPD by reducing the daily concentration of PM_2.5 and PM₁₀ to attain the Chinese and World Health Organization (WHO) air quality standard targets were estimated during 2015-2019. The stratified analyses by gender were also conducted. A total of 18279 RD and 7767 COPD deaths were included in this study. Per 10 μg/m³ increments in PM_2.5 and PM₁₀ at lag1 were significantly associated with 0.83(95%CI: 0.11, 1.55) years and 0.57(95%CI: 0.06, 1.08) years increasing in YLL of total RD and 0.48 (95%CI: 0.07, 0.90) years and 0.30 (95%CI: 0.01, 0.60) years increasing in YLL of total COPD. If the daily PM_2.5 and PM₁₀ concentrations decreased to attain the Chinese and WHO air quality standard targets, 0.06-0.39 years PLEB due to total RD and 0.08-0.53 years PLEB due to COPD could be gained. And more PLEB on RD could be gained by decreasing the daily PM concentrations to attain the WHO air quality standard targets than that of attaining the Chinese air quality standard targets. These evidence-based findings emphasize the importance of the Chinese PM-related guideline updating and may have implications for PM-related policy-making.

Visible, near-infrared dual-polarization lidar based on polarization cameras: system design, evaluation and atmospheric measurements

A visible, near-infrared (VIS-NIR) dual-polarization lidar technique employing laser diodes and polarization cameras has been designed and implemented for all-day unattended field measurements of atmospheric aerosols. The linear volume depolarization ratios (LVDR) and the offset angles can be retrieved from four-directional polarized backscattering signals at wavelengths of 458 nm and 808 nm without additional optical components and sophisticated system adjustments. Evaluations on the polarization crosstalk of the polarization camera and the offset angle have been performed in detail. A rotating linear polarizer (RLP) method based on the Stokes-Mueller formalism has been proposed and demonstrated for measuring extinction ratios of the polarization camera, which can be used to eliminate the polarization crosstalk between different polarization signals. The offset angles can be online measured with a precision of 0.1°, leading to negligible measurement errors on the LVDR. One-month statistical analysis revealed a small temporal variation of the offset angles, namely -0.13°±0.07° at 458 nm and 0.33°±0.09° at 808 nm, indicating good system stability for long-term measurement. Atmospheric measurements have been carried out to verify the system performance and investigate aerosol optical properties. The spectral characteristics of the aerosol extinction coefficient, the color ratio, the linear particle polarization ratio (LPDR) and the ratio of LPDR were retrieved and evaluated based on one-month continuous atmospheric measurements, from which different types of aerosols can be classified. The promising results showed great potential of employing the VIS-NIR dual-polarization lidar in characterizing aerosol optical properties, discriminating aerosol types and analyzing long-range aerosol transportation.