Estimation of PM2.5 mortality burden in China with new exposure estimation and local concentration-response function

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

Background

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

Methods

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

Results

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

Conclusion

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

Associations between short-term exposure to fine particulate matter and acute myocardial infarction: A case-crossover study

BACKGROUND

Previous studies evaluated the impact of particle matters (PM) on the risk of acute myocardial infarction (AMI) based on local registries.

HYPOTHESIS

This study aimed to evaluate possible short term effect of air pollutants on occurrence of AMI based on a specific case report sheet that was designed for this purpose.

METHODS

AMI was documented among 982 patients who referred to the emergency departments in Tehran, Iran, between July 2017 to March 2019. For each patient, case period was defined as 24 hour period preceding the time of emergency admission and referent periods were defined as the corresponding time in 1, 2, and 3 weeks before the admission. The associations of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2 .5 ) and particulate matter with an aerodynamic diameter ≤10 μm (PM10 ) with AMI were analyzed using conditional logistic regression in a case-crossover design.

RESULT

Increase in PM2.5 and PM10 was significantly associated with the occurrence of AMI with and without adjustment for the temperature and humidity. In the adjusted model each 10 μg/m3 increase of PM10 and PM2.5 in case periods was significantly associated with increase myocardial infarction events (95% CI = 1.041-1.099, OR = 1.069 and 95% CI = 1.073-1.196, and OR = 1.133, respectively). Subgroup analysis showed that increase in PM10 did not increase AMI events in diabetic subgroup, but in all other subgroups PM10 and PM2 .5 concentration showed positive associations with increased AMI events.

CONCLUSION

Acute exposure to ambient air pollution was associated with increased risk of AMI irrespective of temperature and humidity.

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

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

What Factors Dominate the Change of PM2.5 in the World from 2000 to 2019? A Study from Multi-Source Data

As the threat to human life and health from fine particulate matter (PM2.5) increases globally, the life and health problems caused by environmental pollution are also of increasing concern. Understanding past trends in PM2.5 and exploring the drivers of PM2.5 are important tools for addressing the life-threatening health problems caused by PM2.5. In this study, we calculated the change in annual average global PM2.5 concentrations from 2000 to 2020 using the Theil-Sen median trend analysis method and reveal spatial and temporal trends in PM2.5 concentrations over twenty-one years. The qualitative and quantitative effects of different drivers on PM2.5 concentrations in 2020 were explored from natural and socioeconomic perspectives using a multi-scale geographically weighted regression model. The results show that there is significant spatial heterogeneity in trends in PM2.5 concentration, with significant decreases in PM2.5 concentrations mainly in developed regions, such as the United States, Canada, Japan and the European Union countries, and conversely, significant increases in PM2.5 in developing regions, such as Africa, the Middle East and India. In addition, in regions with more advanced science and technology and urban management, PM2.5 concentrations are more evenly influenced by various factors, with a more negative influence. In contrast, regions at the rapid development stage usually continue their economic development at the cost of the environment, and under a high intensity of human activity. Increased temperature is known as the most important factor for the increase in PM2.5 concentration, while an increase in NDVI can play an important role in the reduction in PM2.5 concentration. This suggests that countries can achieve good air quality goals by setting a reasonable development path.

Association between ambient cold exposure and mortality risk in Shandong Province, China: Modification effect of particulate matter size

Introduction

Numerous studies have reported the modification of particulate matters (PMs) on the association between cold temperature and health. However, it remains uncertain whether the modification effect may vary by size of PMs, especially in Shandong Province, China where the disease burdens associated with cold temperature and PMs are both substantial. This study aimed to examine various interactive effects of cold exposure and ambient PMs with diameters ≤1/2.5 μm (PM1 and PM2.5) on premature deaths in Shandong Province, China.

Methods

In the 2013-2018 cold seasons, data on daily mortality, PM1 and PM2.5, and weather conditions were collected from the 1822 sub-districts of Shandong Province. A time-stratified case-crossover study design was performed to quantify the cumulative association between ambient cold and mortality over lag 0-12 days, with a linear interactive term between temperature and PM1 and PM2.5 additionally added into the model.

Results

The mortality risk increased with temperature decline, with the cumulative OR of extreme cold (-16.9°C, the 1st percentile of temperature range) being 1.83 (95% CI: 1.66, 2.02), compared with the minimum mortality temperature. The cold-related mortality risk was 2.20 (95%CI: 1.83, 2.64) and 2.24 (95%CI: 1.78, 2.81) on high PM1 and PM2.5 days, which dropped to 1.60 (95%CI: 1.39, 1.84) and 1.60 (95%CI: 1.37, 1.88) on low PM1 and PM2.5 days. PM1 showed greater modification effect for per unit concentration increase than PM2.5. For example, for each 10?g/m3 increase in PM1 and PM2.5, the mortality risk associated with extreme cold temperature increased by 7.6% (95% CI: 1.3%, 14.2%) and 2.6% (95% CI: -0.7%, 5.9%), respectively.

Discussion

The increment of smaller PMs' modification effect varied by population subgroups, which was particularly strong in the elderly aged over 75 years and individuals with middle school education and below. Specific health promotion strategies should be developed towards the greater modification effect of smaller PMs on cold effect.

Mathematical modeling in the health risk assessment of air pollution-related disease burden in China: A review

This review paper covers an overview of air pollution-related disease burden in China and a literature review on the previous studies which have recently adopted a mathematical modeling approach to demonstrate the relative risk (RR) of air pollution-related disease burden. The associations between air pollution and disease burden have been explored in the previous studies. Therefore, it is necessary to quantify the impact of long-term exposure to ambient air pollution by using a suitable mathematical model. The most common way of estimating the health risk attributable to air pollution exposure in a population is by employing a concentration-response function, which is often based on the estimation of a RR model. As most of the regions in China are experiencing rapid urbanization and industrialization, the resulting high ambient air pollution is influencing more residents, which also increases the disease burden in the population. The existing RR models, including the integrated exposure-response (IER) model and the global exposure mortality model (GEMM), are critically reviewed to provide an understanding of the current status of mathematical modeling in the air pollution-related health risk assessment. The performances of different RR models in the mortality estimation of disease are also studied and compared in this paper. Furthermore, the limitations of the existing RR models are pointed out and discussed. Consequently, there is a need to develop a more suitable RR model to accurately estimate the disease burden attributable to air pollution in China, which contributes to one of the key steps in the health risk assessment. By using an updated RR model in the health risk assessment, the estimated mortality risk due to the impacts of environment such as air pollution and seasonal temperature variation could provide a more realistic and reliable information regarding the mortality data of the region, which would help the regional and national policymakers for intensifying their efforts on the improvement of air quality and the management of air pollution-related disease burden.

A benefit allocation model for the joint prevention and control of air pollution in China: In view of environmental justice

The benefit allocation of fair and justice is an inevitable guarantee for the long-term operation of the joint prevention and control of air pollution (JPCAP). The ignorance of interest demands of various governance subjects in the existing benefit allocation mechanism results in the widespread "free rider" behavior in the joint control and unsatisfactory effects of JPCAP. Given this, it is imperative to build a reasonable benefit allocation model. The innovation of this paper is proposing a benefit allocation model of JPCAP to achieve the symmetry between control costs and benefits based on environmental justice. The control objectives and total benefits of JPCAP are calculated through the adjustment of optimal removal rates. The interest demands of various control subjects and benefit compensation scheme are clarified by adopting an improved Shapley method, which comprehensively considers factors affecting environmental justice. An empirical analysis is conducted on SO₂ governance in Beijing-Tianjin-Hebei (BTH) and its surrounding areas. The results show that the benefit allocation model based on environmental justice can not only accurately evaluate the benefits of joint control, but also effectively achieve the symmetry between control costs and benefits. This study provides a scientific and reasonable theoretical basis for the benefit allocation of SO₂ control and can be extended to the researches and practices of other air pollutants control.

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

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

Influence of Spatial Resolution on Satellite-Based PM2.5 Estimation: Implications for Health Assessment

Satellite-based PM2.5 estimation has been widely used to assess health impact associated with PM2.5 exposure and might be affected by spatial resolutions of satellite input data, e.g., aerosol optical depth (AOD). Here, based on Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD in 2020 over the Yangtze River Delta (YRD) and three PM2.5 retrieval models, i.e., the mixed effects model (ME), the land-use regression model (LUR) and the Random Forest model (RF), we compare these model performances at different spatial resolutions (1, 3, 5 and 10 km). The PM2.5 estimations are further used to investigate the impact of spatial resolution on health assessment. Our cross-validated results show that the model performance is not sensitive to spatial resolution change for the ME and LUR models. By contrast, the RF model can create a more accurate PM2.5 prediction with a finer AOD spatial resolution. Additionally, we find that annual population-weighted mean (PWM) PM2.5 concentration and attributable mortality strongly depend on spatial resolution, with larger values estimated from coarser resolution. Specifically, compared to PWM PM2.5 at 1 km resolution, the estimation at 10 km resolution increases by 7.8%, 22.9%, and 9.7% for ME, LUR, and RF models, respectively. The corresponding increases in mortality are 7.3%, 18.3%, and 8.4%. Our results also show that PWM PM2.5 at 10 km resolution from the three models fails to meet the national air quality standard, whereas the estimations at 1, 3 and 5 km resolutions generally meet the standard. These findings suggest that satellite-based health assessment should consider the spatial resolution effect.

Particulate matter in COPD pathogenesis: an overview

Chronic obstructive pulmonary disease (COPD) is a progressive lung disorder with substantial patient burden and leading cause of death globally. Cigarette smoke remains to be the most recognised causative factor behind COPD pathogenesis. Given the alarming increase in prevalence of COPD amongst non-smokers in recent past, a potential role of air pollution particularly particulate matter (PM) in COPD development has gained much attention of the scientists. Indeed, several epidemiological studies indicate strong correlation between airborne PM and COPD incidence/exacerbations. PM-induced oxidative stress seems to be the major player in orchestrating COPD inflammatory cycle but the exact molecular mechanism(s) behind such a process are still poorly understood. This may be due to the complexity of multiple molecular pathways involved. Oxidative stress-linked mitochondrial dysfunction and autophagy have also gained importance and have been the focus of recent studies regarding COPD pathogenesis. Accordingly, the present review is aimed at understanding the key molecular players behind PM-mediated COPD pathogenesis through analysis of various experimental studies supported by epidemiological data to identify relevant preventive/therapeutic targets in the area.

Coordinated health effects attributable to particulate matter and other pollutants exposures in the North China Plain

Hebei Province, located in the North China Plain (NCP) and encircling Beijing and Tianjin, has been suffering from severe air pollution. The monthly average fine particulate matter (PM_2.5) concentration was up to 276 μg/m³ in Hebei Province, which adversely affects human health. However, few studies evaluated the coordinated health impact of exposure to PM (PM_2.5 and PM₁₀) and other key air pollutants (SO₂, NO₂, CO, and surface ozone (O₃)). In this study, we systematically analyzed the health risks (both mortality and morbidity) due to multiple air pollutants exposures in Hebei Province. The economic loss associated with these health consequences was estimated using the value of statistical life (VSL) and cost of illness (COI) methods. Our results show the health burden and economic loss attributable to multiple ambient air pollutants exposures in Hebei Province is substantial. In 2017, the total premature mortality from multiple air pollutants exposures in Hebei Province was 69,833 (95% CI: 55,549-83,028), which was 2.9 times higher than that of the Pearl River Delta region (PRD). Most of the potential economic loss (79.65%) was attributable to premature mortality from air pollution. The total economic loss due to the health consequences of multiple air pollutants exposures was 175.16 (95% CI: 134.61-224.61) billion Chinese Yuan (CNY), which was 4.92% of Hebei Province's annual gross domestic product (GDP). Thus, the adverse health effects and economic loss caused by exposure to multiple air pollutants should be seriously taken into consideration. To alleviate these damages, Hebei's government ought to establish more stringent measures and regulations to better control air pollution.

Coconut Oil Alleviates the Oxidative Stress-Mediated Inflammatory Response via Regulating the MAPK Pathway in Particulate Matter-Stimulated Alveolar Macrophages

Exposure to particulate matter (PM) is related to various respiratory diseases, and this affects the respiratory immune system. Alveolar macrophages (AMs), which are defenders against pathogens, play a key role in respiratory inflammation through cytokine production and cellular interactions. Coconut oil demonstrates antioxidant and anti-inflammatory properties, and it is consumed worldwide for improved health. However, reports on the protective effects of coconut oil on the PM-induced respiratory immune system, especially in AMs, are limited. In this study, we generated artificial PM (APM) with a diameter approximately of 30 nm by controlling the temperature, and compared its cytotoxicity with diesel exhaust particles (DEP). We also investigated the antioxidant and anti-inflammatory effects of coconut oil in APM− and DEP−stimulated AMs, and the underlying molecular mechanisms. Our results showed that APM and DEP had high cytotoxicity in a dose-dependent manner in AMs. In particular, APM or DEP at 100 μg/mL significantly decreased cell viability (p < 0.05) and significantly increased oxidative stress markers such as reactive oxygen species (p < 0.01); the GSSH/GSH ratio (p < 0.01); and cytokine production, such as tumor necrosis factor-α (p < 0.001), interleukin (IL)-1β (p < 0.001), and IL-6 (p < 0.001). The expression of the genes for chemokine (C-X-C motif) ligand-1 (p < 0.05) and monocyte chemoattractant protein-1 (p < 0.001); and the proteins toll-like receptor (TLR) 4 (p < 0.01), mitogen-activated protein kinase (MAPK), and c-Jun N-terminal kinase (p < 0.001), p38 (p < 0.001); and extracellular receptor-activated kinase (p < 0.001), were also upregulated by PM. These parameters were reversed upon treatment with coconut oil in APM− or DEP−stimulated AMs. In conclusion, coconut oil can reduce APM− or DEP−induced inflammation by regulating the TLR4/MAPK pathway in AMs, and it may protect against adverse respiratory effects caused by PM exposure.

Composition and sources of particulate matter in the Beijing-Tianjin-Hebei region and its surrounding areas during the heating season

This paper aimed to analyze the composition and pollution sources of particulate matter (PM) in the Beijing-Tianjin-Hebei region and its surrounding areas (henceforth the BTH region) during the heating season to support the mitigation and control of regional air pollution. Manual monitoring data from the China National Environmental Monitoring Network for Atmospheric PM in the BTH region were collected and analyzed during the 2016 and 2018 heating seasons. The positive definite matrix factor analysis (PMF) model was used to analyze the PM sources in BTH cities during the heating season. The main PM components were organic matter (OM), nitrate (NO₃^-), sulfate (SO₄^2-) and ammonium salt (NH₄⁺). Direct emission sources have decreased since 2016, indicating the effectiveness of governmental controls on these sources; however, secondary pollution showed an increasing trend, suggesting control measures should be strengthened. Daily regional average concentrations of OM, SO₄^2-, NH₄⁺, elemental carbon (EC), chloride (Cl^-) and trace elements all showed similar trends. When air quality worsened, the concentrations of the main PM components increased, but trends of change varied among components. In 2018, concentrations of OM and chloride were highest in the Taihang Mountains, and NO₃ concentrations were highest in Anyang, Hebi, Jiaozuo and Xinxiang. The SO₄^2- concentration was highest in the southern section of the Taihang Mountains. The NH₄⁺ and EC concentrations were generally highest in the central and southern regions. The concentration of crustal substances was highest in some cities in the north and central parts of the BTH region. In the 2018 heating season, the pollution level of five transmission channels showed an increasing trend in the Northwest, Southeast, Yanshan, South and Taihang Mountain channels. These findings provide a scientific basis for the continued management of atmospheric PM pollution.

Spatiotemporal variations of air pollution and population exposure in Shandong Province, eastern China, 2014-2018

To clarify the characteristics and interannual variation of air pollution since the implementation of China's clean air actions, hourly in situ measurements of six gaseous and particulate criteria pollutants at 100 sites in Shandong Province were studied during 2014-2018. General decreasing trends in the concentrations of PM_2.5, PM₁₀, NO₂, SO₂, and CO were observed, while O₃ increased continuously. In 2018, the annual average PM_2.5, PM₁₀, NO₂, SO₂, and CO concentration in Shandong was 50, 100, 35, 16 μg m^-3, and 1.5 mg m^-3, representing decreases of 39%, 30%, 24%, 73%, and 35% from 2014, respectively. These decreases occurred throughout the province. Seven "2 + 26" cities (in Beijing-Tianjin-Hebei and its surrounds) in western Shandong had higher average concentrations and greater reductions than other areas. In contrast, O₃ concentration rose, with occurrences of the 90^th percentile of all daily maximum 8-h averages increasing by 12% from 159 to 181 μg m^-3, during 2014-2018. From May to September, O₃ pollution dominated as the sole primary pollutant on non-attainment days, and PM_2.5 contributed to more than 90% of polluted days in wintertime months. Population exposures were investigated based on high-resolution monitoring data and population distribution, and high exposure to pollution was displayed. The population-weighted exposure to PM_2.5 in Shandong was 50 μg m^-3, a decrease of 33%. Eighty-nine percentage of the provincial population was exposed to PM_2.5 > 35 μg m^-3, while for 99.2% of population in the seven "2 + 26" cities, PM_2.5 exposure exceeded 50 μg m^-3.

Isoprenoid emissions from natural vegetation increased rapidly in eastern China

An accurate local biogenic volatile organic compound (BVOC) emission inventory in Shandong Province is crucial for air pollution control in Shandong and the Beijing-Tianjin-Hebei region, China. We estimated the multi-year isoprenoid emissions from natural vegetation in Shandong Province at a spatial resolution of 4 km × 4 km using the MEGAN2.1 model. A new vegetation classification with 23 plant species/types was developed, and emission factors were determined based on the most detailed and localized investigation and statistics. Isoprene, monoterpene, and sesquiterpene emissions in 2018 were 325.6, 18.2, and 7.9 Gg (mass of carbon), respectively. β-Pinene, α-pinene, ocimene, farnescene, and caryophyllene were the dominant monoterpenes and sesquiterpenes. Broadleaf trees contributed the most to total emissions, particularly poplar, which had the highest emission rates. Wheat also had higher emissions owing to its large coverage. Isoprenoid emissions displayed an inverted "U" pattern when plotted against the months and peaked in summer. Emissions were concentrated in the western and southeastern areas with emission intensities of >10 ton/grid, including Dezhou, Liaocheng, and Rizhao cities. During 1981-2018, isoprenoid emissions experienced a rapid increase from 12.0 to 351.7 Gg, at a rate of 11.20 Gg/yr. Isoprene had the highest enhancement rate of 10.72 Gg/yr. The most rapid increase was observed in the northwestern cities Dezhou and Liaocheng, and the southeastern cities Rizhao, at an average rate of >100 kg/yr, even >500 kg/yr in some areas. The high emissions and their continued increase should be considered when studying the prevention and control of regional air pollution and making policies in China.

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

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

Environmental and Genetic Determinants of Major Chronic Disease in Beijing-Tianjin-Hebei Region: Protocol for a Community-Based Cohort Study

Introduction: Personal lifestyle and air pollution are potential risk factors for major non-communicable diseases (NCDs). However, these risk factors have experienced dramatic changes in the Beijing–Tianjin–Hebei (BTH) region in recent years, and few cohorts have focused on identifying risk factors for major NCDs in this specific region. The current study is a large, prospective, long-term, population-based cohort study that investigated environmental and genetic determinants of NCDs in BTH areas. The results of this study may provide scientific support for efforts to develop health recommendations for personalized prevention.

Methods: About 36,000 participants 18 years or older would be obtained by multistage, stratified cluster sampling from five cities for the baseline assessment. Participants underwent seven examinations primarily targeting respiratory and circulatory system function and filled out questionnaires regarding lifestyle behavior, pollutant exposure, medical and family history, medication history, and psychological factors. Biochemistry indicators and inflammation markers were tested, and a biobank was established. Participants will be followed up every 2 years. Genetic determinants of NCDs will be demonstrated by using multiomics, and risk prediction models will be constructed using machine learning methods based on a multitude of environmental exposure, examination data, biomarkers, and psychosocial and behavioral assessments. Significant spatial and temporal differentiation is well-suited to demonstrating the health determinants of NCDs in the BTH region, which may facilitate public health strategies with respect to disease prevention and survivorship-related aspects.

Short and long term exposure to air pollution increases the risk of ischemic heart disease

Previous studies have suggested an increased risk of ischemic heart disease related to air pollution. This study aimed to explore both the short-term and long-term effects of air pollutants on the risk of ischemic heart disease after adjusting for meteorological factors. The Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2013 was used. Overall, 2155 participants with ischemic heart disease and 8620 control participants were analyzed. The meteorological data and air pollution data, including SO₂ (ppm), NO₂ (ppm), O₃ (ppm), CO (ppm), and particulate matter (PM)₁₀ (μg/m³), were analyzed using conditional logistic regression. Subgroup analyses were performed according to age, sex, income, and region of residence. One-month exposure to SO₂ was related to 1.36-fold higher odds for ischemic heart disease (95% confidence interval [95% CI] 1.06–1.75). One-year exposure to SO₂, O₃, and PM₁₀ was associated with 1.58- (95% CI 1.01–2.47), 1.53- (95% CI 1.27–1.84), and 1.14 (95% CI 1.02–1.26)-fold higher odds for ischemic heart disease. In subgroup analyses, the ≥ 60-year-old group, men, individuals with low income, and urban groups demonstrated higher odds associated with 1-month exposure to SO₂. Short-term exposure to SO₂ and long-term exposure to SO_2, O₃, and PM₁₀ were related to ischemic heart disease.

Premature mortality attributable to PM2.5 pollution in China during 2008-2016: Underlying causes and responses to emission reductions

Long-term exposure to fine particulate matter (PM_2.5) poses a great threat to public health in China. To this end, the Chinese government promulgated the Air Pollution Prevention and Control Action Plan (the Action Plan) in 2013. However, the health benefits of the Action Plan have not been well explained. In this paper, the underlying causes of changes in premature mortality attributable to PM_2.5 pollution and the response of this mitigation policy in China were explored using sensitivity analysis. The simulated annual average PM_2.5 concentration reduced by 24.9% over mainland China from 2008 to 2016. Subsequently, national premature mortality would decrease by 14.4% from 1.14 million (95% CI: 0.54, 1.55) in 2008 to 0.98 million (95% CI: 0.44, 1.38) in 2016. Specifically, premature mortality reduced by 209,600 cases (-18.3%) owing to PM_2.5 reduction during 2008-2016, of which 188,500 cases were from 2014 to 2016 due to the Action Plan in 2013. Note that the health benefits were limited when compared with air quality improvements, mainly due to that the IER functions have a stable curve at higher concentration intervals. Meanwhile, premature mortality would have increased by 14.2% from 2008 to 2016 owing to demographic changes, substantially weakening the impact of the decrease in PM_2.5 and baseline mortality. The effectiveness of China's new air pollution mitigation policy was proved through the research. However, considering the non-linear response of mortality to PM_2.5 changes and the aggravation of demography trends, stronger emission control steps should be further taken to protect public health in China.

The long-term trend of PM2.5-related mortality in China: The effects of source data selection

Quantification of PM_2.5 exposure and associated mortality is critical to inform policy making. Previous studies estimated varying PM_2.5-related mortality in China due to the usage of different source data, but rarely justify the data selection. To quantify the sensitivity of mortality assessment to source data, we first constructed state-of-the-art PM_2.5 predictions during 2000-2018 at a 1-km resolution with an ensemble machine learning model that filled missing data explicitly. We also calibrated and fused various gridded population data with a geostatistical method. Then we assessed the PM_2.5-related mortality with various PM_2.5 predictions, population distributions, exposure-response functions, and baseline mortalities. We found that in addition to the well documented uncertainties in the exposure-response functions, missingness in PM_2.5 prediction, PM_2.5 prediction error, and prediction error in population distribution resulted to a 40.5%, 25.2% and 15.9% lower mortality assessment compared to the mortality assessed with the best-performed source data, respectively. With the best-performed source data, we estimated a total of approximately 25 million PM_2.5-related mortality during 2001-2017 in China. From 2001 to 2017, The PM_2.5 variations, growth and aging of population, decrease in baseline mortality led to a 7.8% increase, a 42.0% increase and a 24.6% decrease in PM_2.5-related mortality, separately. We showed that with the strict clean air policies implemented in 2013, the population-weighted PM_2.5 concentration decreased remarkably at an annual rate of 4.5 μg/m³, leading to a decrease of 179 thousand PM_2.5-related deaths nationwide during 2013-2017. The mortality decrease due to PM_2.5 reduction was offset by the population growth and aging population.

Effects of China's current Air Pollution Prevention and Control Action Plan on air pollution patterns, health risks and mortalities in Beijing 2014-2018

Beijing is one of the most polluted cities in the world. However, the "Air Pollution Prevention and Control Action Plan" (APPCAP), introduced since 2013 in China, has created an unprecedented drop in pollution concentrations for five major pollutants, except O₃, with a significant drop in mortalities across most parts of the city. To assess the effects of APPCAP, air pollution data were collected from 35 sites (divided into four types, namely, urban, suburban, regional background, and traffic) in Beijing, from 2014 to 2018 and analyzed. Simultaneously, health-risk based air quality index (HAQI) and district-specific pollution (PM_2.5 and O₃) attributed mortality were calculated for Beijing. The results show that the annual PM_2.5 concentration exceeded the Chinese national ambient air quality standard Grade II (35 μg/m³) in all sites, ranging from 88.5 ± 77.4 μg/m³ for the suburban site to 98.6 ± 89.0 μg/m³ for the traffic site in 2014, but was reduced to 50.6 ± 46.6 μg/m³ for the suburban site, and 56.1 ± 47.0 μg/m³ for the regional background in 2018. O₃ was another most important pollutant that exceeded the Grade II standard (160 μg/m³) for a total of 291 days. It peaked at 311.6 μg/m³ in 2014 for the urban site and 290.6 μg/m³ in 2018 in the suburban site. APPCAP led to a significant reduction in PM_2.5, PM₁₀, NO₂, SO₂ and CO concentrations by 7.4, 8.1, 2.4, 1.9 and 80 μg/m³/year respectively, though O₃ concentration was increased by 1.3 μg/m³/year during the five-years. HAQI results suggest that during the high pollution days, the more vulnerable groups, such as the children, and the elderly, should take additional precautions, beyond the recommendations currently put forward by Beijing Municipal Environmental Monitoring Center (BJMEMC). In 2014, PM_2.5 and O₃ attributed to 29,270 and 3,030 deaths respectively, though in 2018 their mortalities were reduced by 5.6% and 18.5% respectively. The highest mortality was observed in Haidian and Chaoyang districts, two of the most densely populated areas in Beijing. Beijing's air quality has seen a dramatic improvement over the five-year period, which can be attributable to the implementation of APPCAP and the central government's determination, with significant drops in the mortalities due to PM_2.5 and O₃ in parallel. To further improve air quality in Beijing, more stringent regulatory measures should be introduced to control volatile organic compounds (VOCs) and reduce O₃ concentrations. Consistent air pollution control interventions will be needed to ensure long-term prosperity and environmental sustainability in Beijing, China's most powerful city. This study provides a robust methodology for analyzing air pollution trends, health risks and mortalities in China. The crucial evidence generated forms the basis for the governments in China to introduce location-specific air pollution policy interventions to further reduce air pollution in Beijing and other parts of China. The methodology presented in this study can form the basis for future fine-grained air pollution and health risk study at the city-district level in China.

Specific differences and responses to reductions for premature mortality attributable to ambient PM2.5 in China

Although recent assessments have quantified the impact of ambient PM_2.5 on public health in China, air quality managers would benefit from assessing specific differences in premature mortality and its responses to air quality improvement. Using PM_2.5 data simulated by an observation-fused air quality model and an integrated exposure-response model for the full range of PM_2.5, we determined the premature mortality attributable to ambient PM_2.5 across mainland China in 2016. Overall, the total number of PM_2.5-related deaths nationwide was 1.31 million, of which lung cancer, chronic obstructive pulmonary disease, ischemic heart disease, and stroke represented 0.13, 0.13, 0.42, and 0.62 million, respectively. Per capita PM_2.5-related mortality in China was 95 per 100,000 person-years, and that of elderly people aged ≥75 years (1166 deaths per 100,000) was much higher than that of young people aged 25-44 years (11 deaths per 100,000). Additionally, there were significant spatial differences in premature deaths, which mainly occurred in regions with high PM_2.5 levels or/and population density. Halving deaths across mainland China required an average of 63% reduction of PM_2.5 nationwide and a decrease by 73% in high concentration regions exceeding 70 μg/m³ and 19% in low concentration locales below 10 μg/m³. Moreover, reducing PM_2.5 to the WHO interim target I (IT-1) of 35 μg/m³ would only result in a 12.6% reduction in premature mortality, while a more exacting standard (reducing PM_2.5 to 10 μg/m³) would avoid 73.0% of mortality. In particular, there is a large potential for reducing the high PM_2.5-related mortality in heavily polluted locales. In conclusion, to further reduce premature mortality across mainland China, targets stricter than the IT-1 and tight policies to improve air quality and protect public health are necessary, especially for vulnerable groups such as the elderly and patients with cardio-cerebrovascular diseases, particularly in areas with high premature mortality.

Incorporating Health Cobenefits in Decision-Making for the Decommissioning of Coal-Fired Power Plants in China

China's coal-fired power industry urgently needs deep decarbonization to meet the challenge of climate change. Regional air quality improvement and the health benefits can motivate efforts to achieve low-carbon goals. However, the health cobenefit per amount of carbon reduction may vary drastically across power plant units. The strategy of targeting more health cobenefits has been considered in designing an efficient carbon mitigation pathway, whereas this issue has not been analyzed at the unit level. In this study, an indicator called health benefit by carbon reduction (H/C) was constructed for each power unit to assess the relative potential of obtaining health cobenefits. The results reveal that the distribution of H/C values among units is extremely uneven: the first 1, 5, and 20% of the total carbon emission contributed to nearly 20, 40, and 70%, respectively, of the total health effects. The additional health benefits from H/C optimization were evaluated, and the decommissioning pathway of China's coal-fired power industry for achieving more health benefits was explored.

Understanding global PM2.5 concentrations and their drivers in recent decades (1998-2016)

The threat of fine particulate matter (PM2.5) is increasing globally. Tackling this issue requires an accurate understanding of its trends and drivers. In this study, global risk regions of PM2.5 concentrations during 1998-2016 were spatiotemporally derived. Time series analysis was conducted in the spatial relationship between PM2.5 and three socio-environmental drivers: population, urban ratio, and vegetation greenness that can cause changes in the concentration of PM2.5. "High Risk" areas were widely distributed in India and China. In India and sub-Saharan Africa, the increased overall population was strongly correlated with PM2.5 concentrations. Urban ratio increased in both developed and developing countries. A "decoupling" phenomenon occurred in developed countries, where urban expansion continued while PM2.5 concentrations decreased. Vegetation greenness and PM2.5 were strongly correlated in High Risk zones. Although urban expansion and population growth generally reduce vegetation greenness, developed countries reduced PM2.5 while maintaining greenness, whereas developing countries increased PM2.5 with decreasing greenness significantly in High Risk regions. Ultimately, economic and national growth should occur without increasing PM2.5 concentrations. Recent cases from Europe and the eastern United States demonstrate that this is possible, depending on the development pathway.

County-level variation in the long-term association between PM2.5 and lung cancer mortality in China

INTRODUCTION

The relative risk (RR) of long-term exposure to PM_2.5 in lung cancer mortality (LCM) may vary spatially in China. However, previous studies applying global regression have been unable to capture such variation. We aimed to employ a geographically weighted Poisson regression (GWPR) to estimate the RRs of LCM among the elderly (≥65 years) related to long-term exposure to PM_2.5 and the LCM attributable to PM_2.5 at the county level in China.

METHODS

We obtained annual LCM in the elderly between 2013 and 2015 from the National Death Surveillance. We linked annual mean concentrations of PM_2.5 between 2000 and 2004 with LCM using GWPR model at 148 counties across mainland China, adjusting for smoking and socioeconomic covariates. We used county-specific GWPR models to estimate annual average LCM in the elderly between 2013 and 2015 attributable to PM_2.5 exposure between 2000 and 2004.

RESULTS

The magnitude of the association between long-term exposure to PM_2.5 and LCM varied with county. The median of county-specific RRs of LCM among elderly men and women was 1.52 (range: 0.90, 2.40) and 1.49 (range: 0.88, 2.56) for each 10 μg/m³ increment in PM_2.5, respectively. The RRs were positively significant (P < 0.05) at 95% (140/148) of counties among both elderly men and women. Higher RRs of PM_2.5 among elderly men were located at Southwest and South China, and higher RRs among elderly women were located at Northwest, Southwest, and South China. There were 99,967 and 54,457 lung cancer deaths among elderly men and women that could be attributed to PM_2.5, with the attributable fractions of 31.4% and 33.8%, respectively.

CONCLUSIONS

The relative importance of long-term exposure to PM_2.5 in LCM differed by county. The results could help the government design tailored and efficient interventions. More stringent PM_2.5 control is urgently needed to reduce LCM in China.

Substantial changes in PM2.5 pollution and corresponding premature deaths across China during 2015-2019: A model prospective

Long-term exposure to the ambient fine particulate matter (PM_2.5) is the major public health risk factor in China. Several past studies have assessed premature mortalities associated with PM_2.5 in China at varying levels of temporal and spatial scales using different methodological approaches. However, recently developed global exposure mortality model [GEMM NCD + LRI and GEMM 5-COD] provides a much more sophisticated methodology in capturing mortality due to PM_2.5-exposure than the commonly accepted integrated exposure-response (IER) model, which this study applied to China. This study provides a comparative assessment of the excess long-term PM_2.5-attributed nonaccidental deaths as well as cause-specific deaths for 349 cities in mainland China during five years (from 2015 to 2019) and compares the results with the spatial resolution scale of 0.1° × 0.1° across overall China. The results demonstrate that the national annual average PM_2.5 concentration declined from 51.9 ± 18.2 μg/m³ in 2015 to 39.0 ± 13.2 μg/m³ in 2019, and the overall annual negative trend was around -3.1 ± 2.2 μg/m³/year [-5.6 ± 3.4%/year] across China. Consequently, the number of PM_2.5-related deaths decreased by 383 thousand [95% CI: 331-429] to 1755 thousand [95% Confidence Interval: 1470-2025; GEMM NCD + LRI]; 315 thousand [95% CI: 227-370] to 1380 thousand [95% CI: 948-1740; GEMM 5-COD] and 125 thousand [95% CI: 64-140] to 876 thousand [95% CI: 394-1262; IER] in 2019, derived from the pre-established models (GEMM and IER). The estimate PM_2.5-attributed death with a spatial resolution of 0.1° × 0.1° was 2419 thousand [95% CI: 2041-2771; GEMM NCD + LRI], 1918 thousand [95% CI: 1333-2377; GEMM 5-COD] and 1162 thousand [95% CI: 534-1611; IER] in 2015, which is about 11-16% higher value than the city-level health risk assessment study. The estimated deaths by GEMM NCD + LRI and GEMM 5-COD were 104% and 61% higher than the estimated by IER, highlighting that total premature mortalities associated with PM_2.5 were substantially left behind based on the pre-existing model. The "other noncommunicable diseases" mortality, which IER method doesn't account for, was 375 thousand in 2019, 68 thousand less than in 2015. Such significant mortality was previously overlooked in estimation methods, which should now be considered for the air pollution-related policy development in China. The high number of premature deaths in central and northern parts of China, calls for the need for the Government to quickly impose even more stringent and effective pollution control measures.

Exposure to urban particulate matter and its association with human health risks

Human health and environmental risks are increasing following air pollution associated with vehicular and industrial emissions in which particulate matter is a constituent. The purpose of this review was to assess studies on the health effects and mortality induced by particles published for the last 15 years. The literature survey indicated the existence of strong positive associations between fine and ultrafine particles' exposure and cardiovascular, hypertension, obesity and type 2 diabetes mellitus, cancer health risks, and mortality. Its exposure is also associated with increased odds of hypertensive and diabetes disorders of pregnancy and premature deaths. The ever increasing hospital admission and mortality due to heart failure, diabetes, hypertension, and cancer could be due to long-term exposure to particles in different countries. Therefore, its effect should be communicated for legal and scientific actions to minimize emissions mainly from traffic sources.

Temporal variations in ambient air quality indicators in Shanghai municipality, China

Official data on daily PM_2.5, PM₁₀, SO₂, NO₂, CO, and maximum 8-h average O₃ (O₃_8h) concentrations from January 2015 to December 2018 were evaluated and air pollution status and dynamics in Shanghai municipality were examined. Factors affecting air quality, including meteorological factors and socio-economic indicators, were analyzed. The main findings were that: (1) Overall air quality status in Shanghai municipality has improved and number of days meeting 'Chinese ambient air quality standards' (CAAQS) Grade II has increased. (2) The most frequent major pollutant in Shanghai municipality is O₃ (which exceeded the standard on 110 days in 2015, 84 days in 2016, 126 days in 2017, 113 days in 2018), followed by PM_2.5 (120days in 2015, 104 days in 2016, 67 days in 2017, 61 days in 2018) and NO₂ (50 days in 2015, 67 days in 2016, 79 days in 2017, 63 days in 2018). (3) PM_2.5 pollution in winter and O₃ pollution in summer are the main air quality challenges in Shanghai municipality. (4) Statistical analysis suggested that PM_2.5, PM₁₀, SO₂ and NO₂ concentrations were significantly negatively associated with precipitation (Prec) and atmosphere temperature (T) (p < 0.05), while the O₃ concentration was significantly positively associated with Prec and T (p < 0.05). Lower accumulation of PM, SO₂, NO₂, and CO and more serious O₃ pollution were revealed during months with higher temperature and more precipitation in Shanghai. The correlation between the socio-economic factors and the air pollutants suggest that further rigorous measures are needed to control PM_2.5 and that further studies are needed to identify O₃ formation mechanisms and control strategies. The results provide scientific insights into meteorological factors and socio-economic indicators influencing air pollution in Shanghai.

Application of cell-based biological bioassays for health risk assessment of PM2.5 exposure in three megacities, China

The determination of PM_2.5-induced biological response is essential for understanding the adverse health risk associated with PM_2.5 exposure. In this study, we conducted cell-based bioassays to measure the toxic effects of PM_2.5 exposure, including cytotoxicity, oxidative stress, genotoxicity and inflammatory response. The concentration-response relationship was analyzed by benchmark dose (BMD) modeling and the BMDL₁₀ was used to estimate the biological potency of PM_2.5 exposure. PM_2.5 samples were collected from three typical megacities of China (Beijing, BJ; Wuhan, WH; Guangzhou, GZ) in typical seasons (winter and summer). The total PM, water-soluble fractions (WSF), and organic extracts (OE) were prepared and subjected to examination of toxic effects. The biological potencies for cytotoxicity, oxidative stress and genotoxicity were generally higher in winter samples, while the inflammatory potency of PM_2.5 was higher in summer samples. The relative health risk (RHR) was determined by integration of the biological potencies and the cumulative exposure level, and the ranks of RHR were BJ-W > WH-W > BJ-S > WH-S > GZ-W > GZ-S. Notably, we note that different PM_2.5 compositions were associated with distinct biological effects, and the health effects distribution of PM_2.5 varied in regions and seasons. These findings demonstrate that the approach of integrated cell-based bioassays could be used for the evaluation of health effects of PM_2.5 exposure.

PM2.5-Related Health Economic Benefits Evaluation Based on Air Improvement Action Plan in Wuhan City, Middle China

On the basis of PM_2.5 data of the national air quality monitoring sites, local population data, and baseline all-cause mortality rate, PM_2.5-related health economic benefits of the Air Improvement Action Plan implemented in Wuhan in 2013–2017 were investigated using health-impact and valuation functions. Annual avoided premature deaths driven by the average concentration of PM_2.5 decrease were evaluated, and the economic benefits were computed by using the value of statistical life (VSL) method. Results showed that the number of avoided premature deaths in Wuhan are 21,384 (95% confidence interval (CI): 15,004 to 27,255) during 2013–2017, due to the implementation of the Air Improvement Action Plan. According to the VSL method, the obtained economic benefits of Huangpi, Wuchang, Hongshan, Xinzhou, Jiang’an, Hanyang, Jiangxia, Qiaokou, Jianghan, Qingshan, Caidian, Dongxihu, and Hannan District were 8.55, 8.19, 8.04, 7.39, 5.78, 4.84, 4.37, 4.04, 3.90, 3.30, 2.87, 2.42, and 0.66 billion RMB (1 RMB = 0.1417 USD On 14 October 2019), respectively. These economic benefits added up to 64.35 billion RMB (95% CI: 45.15 to 82.02 billion RMB), accounting for 4.80% (95% CI: 3.37% to 6.12%) of the total GDP of Wuhan in 2017. Therefore, in the process of formulating a regional air quality improvement scheme, apart from establishing hierarchical emission-reduction standards and policies, policy makers should give integrated consideration to the relationship between regional economic development, environmental protection and residents’ health benefits. Furthermore, for improving air quality, air quality compensation mechanisms can be established on the basis of the status quo and trends of air quality, population distribution, and economic development factors.

Impact of Environmental Regulations on Environmental Quality and Public Health in China: Empirical Analysis with Panel Data Approach

Achieving high-quality environmental development through environmental regulations and thus enhancing public health is a goal of the Chinese government. Based on the panel data of 30 Chinese provinces from 1998 to 2017, this study demonstrates the co-benefits of environmental regulations on air quality, water, and public health through a panel Granger causality model and mediation effect model. The findings indicate that environmental regulations have a Granger causal effect on public health costs and air and water pollution. Furthermore, the results from the mediation effect model suggest that waste gas treatment could improve air quality, thus reducing public health costs; wastewater treatments could not only reduce public health costs through improvement of the water environment but also increase social welfare. Additionally, air pollution exhibits a greater negative externality impact on health than water pollution. Thus, environmental regulation policies should pay more attention to air pollution control. The findings of this study indicate that environmental regulations have a significant co-benefit on high-quality environmental development and public health.

Trends of outdoor air pollution and the impact on premature mortality in the Pearl River Delta region of southern China during 2006-2015

Severe air pollution in the Pearl River Delta (PRD) region of southern China has increased attention of both the scientific community and policy makers. Air quality data collected at the PRD Regional Air Quality Monitoring Network during 2006-2015 were analyzed for assessing the effectiveness of pollution control measures and for estimating the trends of premature mortality attributable to ambient PM_2.5 and O₃. Statistically significant decreasing trends were detected for PM_2.5 (-1.74 to -1.83 μg m^-3 yr^-1), PM₁₀ (-2.70 to -2.78 μg m^-3 yr^-1), NO (-0.61 to -0.74 μg m^-3 yr^-1), NO₂ (-1.20 to -1.22 μg m^-3 yr^-1), and SO₂ (-3.46 to -4.01 μg m^-3 yr^-1), while an increasing trend was found for O₃ (0.70-0.86 μg m^-3 yr^-1) during the study period. The findings demonstrate the effectiveness of control measures implemented in the last decade for primary pollutants and also indicate the challenges for controlling secondary pollutants. The PM_2.5-related premature deaths varied little, e.g., from 40.6 thousand deaths in 2006 to 40.4 thousand deaths in 2015, due to the two contrasting factors, i.e., the decreased PM_2.5 concentration and increased population. The increases in both O₃ concentration and exposed population resulted in a significant rising trend for the O₃-related premature deaths, which increased from 2.7 thousand deaths in 2006 to 4.5 thousand deaths in 2015, at a rate of 165 deaths yr^-1. Consistent with the spatial distribution of air pollution and population density, high levels of premature deaths from PM_2.5 and O₃ were located in the central PRD including Guangzhou, Foshan, Dongguan, and Shenzhen. Decreasing PM_2.5 concentration is the most effective way in reducing the regional mortality burden from air pollution in the near future. Besides controlling primary emissions of PM_2.5, reducing VOCs emissions is also important for limiting atmospheric oxidizing capacity and associated secondary PM_2.5 formation.

Land use regression for spatial distribution of urban particulate matter (PM10) and sulfur dioxide (SO2) in a heavily polluted city in Northeast China

Particulate material 10 μm (PM₁₀) and sulfur dioxide (SO₂) are representative air pollutants in Northeast China and may contribute more to the morbidity of respiratory and cardiovascular disease than may other pollutants. Up to now, there have been few studies on the relation between health effect and air pollution by PM₁₀ and SO₂ in Northeast China, which may be due to the lack of a model for determination of air pollution exposure. For the first time, we used daily concentration data and influencing factors (different type of land use, road length and population density, and weather conditions as well) to develop land use regression models for spatial distribution of PM₁₀ and SO₂ in a central city in Northeast China in both heating and non-heating months. The final models of SO₂ and PM₁₀ estimation showed good performance (heating months: R² = 0.88 for SO₂, R² = 0.88 for PM₁₀; non-heating months: R² = 0.79 for SO₂; R² = 0.87 for PM₁₀). Estimated concentrations of air pollutants were more affected by population density in heating seasons and land use area in non-heating seasons. We used the land use regression (LUR) models developed to predict pollutant levels in nine districts in Shenyang and conducted a correlation analysis between air pollutant levels and hospital admission rates for childhood asthma. There were high associations between asthma hospital admission rates and air pollution levels of SO₂ and PM₁₀, which indicated the usability of the LUR models and the need for more concern about the health effects of SO₂ and PM₁₀ in Northeast China. This study may contribute to epidemiological research on the relation between air pollutant exposure and typical chronic disease in Northeast China as well as providing the government with more scientific recommendations for air pollution prevention.

Characteristics of cohort studies of long-term exposure to PM2.5: a systematic review

This study systematically reviewed all the cohort studies investigating the relationship between long-term exposure to PM_2.5 and any health outcome until February 2018. We searched ISI Web of Knowledge, Pubmed, and Scopus databases for peer-reviewed journal research articles published in English. We only extracted the results of the single-pollutant main analysis of each study, excluding the effect modifications and sensitivity analyses. Out of the initial 9523 articles, 203 articles were ultimately included for analysis. Based on the different characteristics of studies such as study design, outcome, exposure assessment method, and statistical model, we calculated the number and relative frequency of analyses with statistically significant and insignificant results. Most of the studies were prospective (84.8%), assessed both genders (66.5%), and focused on a specific age range (86.8%). Most of the articles (78.1%) had used modeling techniques for exposure assessment of cohorts' participants. Among the total of 317 health outcomes, the most investigated outcomes include mortality due to cardiovascular disease (6.19%), all causes (5.48%), lung cancer (4.00%), ischemic heart disease (3.50%), and non-accidental causes (3.50%). The percentage of analyses with statistically significant results were higher among studies that used prospective design, mortality as the outcome, fixed stations as exposure assessment method, hazard ratio as risk measure, and no covariate adjustment. We can somehow conclude that the choice of right characteristics for cohort studies can make a difference in their results.

Value Assessment of Health Losses Caused by PM2.5 in Changsha City, China

With the advancement of urbanization, the harm caused to human health by PM2.5 pollution has been receiving increasing attention worldwide. In order to increase public awareness and understanding of the damage caused by PM2.5 in the air and gain the attention of relevant management departments, Changsha City is used as the research object, and the environmental quality data and public health data of Changsha City from 2013 to 2017 are used. All-cause death, respiratory death, cardiovascular death, chronic bronchitis, and asthma were selected as the endpoints of PM2.5 pollution health effects, according to an exposure-response coefficient, Poisson regression model, and health-impact-assessment-related methods (the Human Capital Approach, the Willingness to Pay Approach, and the Cost of Illness Approach), assessing the health loss and economic loss associated with PM2.5. The results show that the pollution of PM2.5 in Changsha City is serious, which has resulted in extensive health hazards and economic losses to local residents. From 2013 to 2017, when annual average PM2.5 concentrations fell to 10 μg/m3, the total annual losses from the five health-effect endpoints were $2788.41 million, $2123.18 million, $1657.29 million, $1402.90 million, and $1419.92 million, respectively. The proportion of Gross Domestic Product (GDP) in the current year was 2.69%, 1.87%, 1.34%, 1.04% and 0.93%, respectively. Furthermore, when the concentration of PM2.5 in Changsha City drops to the safety threshold of 10 μg/m3, the number of affected populations and health economic losses can far exceed the situation when it falls to 35 μg/m3, as stipulated by the national secondary standard. From 2013 to 2017, the total loss under the former situation was 1.48 times, 1.54 times, 1.86 times, 2.25 times, and 2.33 times that of the latter, respectively. Among them, all-cause death and cardiovascular death are the main sources of health loss. Taking 2017 as an example, when the annual average concentration dropped to 10 μg/m3, the health loss caused by deaths from all-cause death and cardiovascular disease was 49.16% of the total loss and 35.73%, respectively. Additionally, deaths as a result of respiratory disease, asthma, and chronic bronchitis contributed to 7.31%, 7.29%, and 0.51% of the total loss, respectively. The research results can provide a reference for the formulation of air pollution control policies based on health effects, which is of great significance for controlling air pollution and protecting people's health.

Incidence and mortality for respiratory cancer and traffic-related air pollution in São Paulo, Brazil

BACKGROUND

Multiple lines of evidence have associated exposure to ambient air pollution with an increased risk of respiratory malignancies. However, there is a dearth of evidence from low-middle income countries, including those within South America, where the social inequalities are more marked.

OBJECTIVES

To quantify the association between exposures to traffic related air pollution and respiratory cancer incidence and mortality within São Paulo, Brazil. Further, we aim to investigate the role of socioeconomic status (SES) upon these outcomes.

METHODS

Cancer incidence between 2002 and 2011 was derived from the population-based cancer registry. Mortality data (between 2002 and 2013) was derived from the Municipal Health Department. A traffic density database and an annual nitrogen dioxide (NO₂) land use regression model were used as markers of exposure. Age-adjusted Binomial Negative Regression models were developed, stratifying by SES and gender.

RESULTS

We observed an increased rate of respiratory cancer incidence and mortality in association with increased traffic density and NO₂ concentrations, which was higher among those regions with the lowest SES. For cancer mortality and traffic exposure, those in the most deprived region, had an incidence rate ratio (IRR) of 2.19 (95% CI: 1.70, 2.82) when comparing the highest exposure centile (top 90%) to the lowest (lowest 25%). By contrast, in the least deprived area, the IRR for the same exposure contrast was.1.07 (95% CI: 0.95, 1.20). For NO₂ in the most deprived regions, the IRR for cancer mortality in the highest exposed group was 1.44 (95% CI: 1.10, 1.88) while in the least deprived area, the IRR for the highest exposed group was 1.11 (95% CI: 1.01, 1.23).

CONCLUSIONS

Traffic density and NO₂ were associated with an increased rate of respiratory cancer incidence and mortality in São Paulo. Residents from poor regions may suffer more from the impact of traffic air pollution.