Estimating premature mortality attributable to PM2.5 exposure and benefit of air pollution control policies in China for 2020

Acute effect of particulate matter pollution on hospital admissions for stroke among patients with type 2 diabetes in Beijing, China, from 2014 to 2018

BACKGROUND

The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown.

METHODS

A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM_2.5) and inhalable particulate matter (PM₁₀) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends.

RESULTS

A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM_2.5 and PM₁₀ in relation to stroke admissions among T2D patients. A 10 μg/m³ increase in the four-day moving average of PM_2.5 and PM₁₀ was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m³ increase in PM_2.5 in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m³ increase in PM₁₀ in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke.

CONCLUSIONS

High particulate matter might be a risk factor for stroke among patients with T2D. PM_2.5 and PM₁₀ have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.

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.

Composition and exposure characteristics of PM2.5 on subway platforms and estimates of exposure reduction by protective masks

There is limited information on exposure to metallic constituents of fine particulate matter in subway stations. We characterized the concentrations and composition of airborne fine particulate pollution on six subway platforms in Nanjing, China in both summer and winter of 2019. A microenvironment exposure model was used to evaluate the concentrations of elements in fine particulate matter and the contribution of exposure duration (time spent in the subway station) to overall daily exposure of subway workers and commuters with and without the use of N95 respirators, surgical masks, and cotton masks. We found that airborne fine particulate pollution on station platforms was much higher than in an urban reference site of ambient air, and the same was true for metallic constituents of the particles, such as iron, copper, manganese, strontium, and vanadium. Subway workers were exposed to higher levels of these airborne metals than commuters. The average daily exposure concentration of fine particulate matter was 73.5 μg/m³ for subway workers and 61.8 μg/m³ for commuters, while the average daily exposure to iron was 15.5 μg/m³ for subway workers and 2.0 μg/m³ for commuters. Subway workers were exposed to iron, copper, manganese, and strontium/vanadium at levels approximately eight-fold, four-fold, three-fold, and two-fold greater than the exposure sustained by commuters, respectively. We calculated that wearing N95 respirators or surgical masks can reduce the exposure to these airborne metallic particles significantly for both subway workers and commuters. Overall, we estimate that personal exposure to airborne fine particulate matter on subway platforms can be reduced through the use of N95 respirators or properly fitting masks.

Ridership exceedance exposure risk: Novel indicators to assess PM2.5 health exposure of bike sharing riders

Identifying the fine particulate matter (PM_2.5) exposure risk for bicycle riders is crucial for promoting the development of theory and technology in transportation-related air pollution assessment as well as urban health planning. Previous studies have employed daily mean PM_2.5 concentrations and designed routes to evaluate air pollution exposure risk. However, because the daily mean PM_2.5 concentrations cannot fully illustrate the intra-day variations in PM_2.5, which are typically higher than daily mean values, the adverse effects of PM_2.5 concentrations remain underestimated. Moreover, the quantity and representativeness of monitoring samples make large spatial-scale and multi-temporal-scale analysis challenging. By defining hourly exceedance PM_2.5 concentration and sharing bicycle rider data, two novel indicators were proposed in our study: exceedance exposure risk of PM_2.5 for sharing bicycle riders (EPSR) and accumulative exceedance exposure risk of PM_2.5 for sharing bicycle riders (AEPSR). Standard deviation ellipse analysis was conducted to investigate the multi-temporal variation of ESPR and AEPSR. A geographically weighted regression model was applied to quantify the relationship between city function zones and exceedance PM_2.5 exposure risk for sharing bicycle riders. Results revealed that the mean values of EPSR and AEPSR during morning peak periods ranged between 0.109 min μg/m³ and 1.27 min μg/m³ and 6.83 min μg/m³ and 43.41 min μg/m³, respectively, whereas the mean values of EPSR and AEPSR during evening peak periods ranged between 0.19 min μg/m³ and 4.28 min μg/m³ and 14.67 min μg/m³ and 357.66 min μg/m³, respectively. This implied that sharing bicycle riders were exposed to higher PM_2.5-related risks during the evening than in the morning. When considering the accumulative effects, the average centers of the AEPSR moved to the north side as compared to the average centers of the EPSR. Expanding areas of EPSR shrunk by 20.25 km². This indicated that accumulative effects aggregated spatial clusters of exceedance PM_2.5 exposure risk for sharing bicycle riders more tightly to the north of the study areas. Spatiotemporal variation of EPSR and AEPSR led us to investigate the mechanism behind this phenomenon. Spatial associations between city function zones and EPSR and AEPSR showed that sharing bicycle riders experienced more severe exceedance PM_2.5 exposure risk around financial/corporations and leisure service areas, with R² values of 0.33 and 0.35, respectively. This spatial association tended to be more significant during the evening peak periods. By developing two novel indicators, the increasing health threats for bicycle riders caused by exceedance PM_2.5 were investigated in this study. The mechanism results should be included for developing mitigation strategies to alleviate the adverse effects of air pollution for public rider participators and achieving the goal of eco-health cities.

Comprehensive and high-resolution emission inventory of atmospheric pollutants for the northernmost cities agglomeration of Harbin-Changchun, China: Implications for local atmospheric environment management

Using a bottom-up estimation method, a comprehensive, high-resolution emission inventory of gaseous and particulate atmospheric pollutants for multiple anthropogenic sectors with typical local sources has been developed for the Harbin-Changchun city agglomeration (HCA). The annual emissions for CO, NOx, SO₂, NH₃, VOC_S, PM_2.5, PM₁₀, BC and OC during 2017 in the HCA were estimated to be 5.82 Tg, 0.70 Tg, 0.34 Tg, 0.75 Tg, 0.81Tg, 0.67 Tg, 1.59 Tg, 0.12 Tg and 0.26 Tg, respectively. For PM₁₀ and SO₂, the emissions from industry processes were the dominant contributors representing 54.7% and 49.5%, respectively, of the total emissions, while 95.3% and 44.5% of the total NH₃ and NOx emissions, respectively, were from or associated with agricultural activities and transportation. Spatiotemporal distributions showed that most emissions (except NH₃) occurred in November to March and were concentrated in the central cities of Changchun and Harbin and the surrounding cities. Open burning of straw made an important contribution to PM_2.5 in the central regions of the northeastern plain during autumn and spring, while domestic coal combustion for heating purposes was significant with respect to SO₂ and PM_2.5 emissions during autumn and winter. Furthermore, based on Principal Component Analysis and Multivariable Linear Regression model, air temperature, relative humidity, electricity and energy consumption, and the urban and rural population were optimized to be representative indicators for rapidly assessing the magnitude of regional atmospheric pollutants in the HCA. Such indicators and equations were demonstrated to be useful for local atmospheric environment management.

Modelling Spatial Heterogeneity in the Effects of Natural and Socioeconomic Factors, and Their Interactions, on Atmospheric PM2.5 Concentrations in China from 2000–2015

In recent years, atmospheric PM2.5 pollution in China has become increasingly severe and exploring the relationships among its influencing factors is important in the prevention and control of air pollution. Although previous studies have identified complexity in variations in PM2.5 concentrations and recognized the interaction of multiple factors, little quantitative information is available on the evolution of the relationships among these factors, their spatial heterogeneity, and the multiscale interactions between them. In this study, geographical detector and multiscale geographically weighted regression models have been used to explore the multiscale interactions among natural and socioeconomic factors and PM2.5 concentration in China over the period 2000–2015. The results indicate that the relationship between natural factors and PM2.5 concentration is stronger than that for socioeconomic factors. The type of interaction between each factor is dominated by bivariate and nonlinear enhancement, exhibiting strong interactions between natural factors and anthropogenic factors. Although the effect of each factor on PM2.5 is complex, the relative influence of both human activities and social factors is shown to have gradually increased over time and population, agriculture, urbanization, and socioeconomic activities in general make important contributions to PM2.5. In addition, the scale of effects related to natural factors is smaller and more stable compared to the influence of human activities during the period 2000-2015. There are significant differences in the way natural factors and socioeconomic factors affect PM2.5, and there is strong non-stationarity of spatial relationships. Factors associated with topography, vegetation (NDVI), climate (temperature), natural sources, and agricultural activity are shown to be important determinants of PM2.5 across China and warrant significant attention in terms of managing atmospheric pollution. The study demonstrates that spatial differences in the direction, intensity, and scale of each factor should be accounted for to improve prevention and control measures and alleviate regional PM2.5 pollution.

All-Cause Mortality Risk and Attributable Deaths Associated with Long-Term Exposure to Ambient PM2.5 in Chinese Adults

Several recent studies in China have associated raised mortality risks with chronic exposure to ambient PM_2.5. However, cohort evidence covering general populations and more homogeneous regions is extensively scarce. We conceived a nationwide perspective cohort study from 2010 through 2018, by enrolling 30 946 adult men and women aged 16-110 years from 25 provincial regions in mainland China. Cox proportional hazards models with time-varying exposures were adopted to quantify longitudinal association of PM_2.5 exposure with all-cause mortality. A total of 1762 death events occurred during a median follow-up of 8.1 years. Participants were exposed to a broad range of annual mean PM_2.5 concentrations (2.4-112 μg/m³), with an average estimate of 47.5 μg/m³. A 10-μg/m³ increase in annual average of PM_2.5 exposure was associated with an hazard ratio of 1.055 (95% confidence interval: 1.022-1.088, p < 0.001) for all-cause mortality. We estimated totally 2.68 million deaths attributable to ambient PM_2.5 in 2015, yielding a remarkable reduction of 36.7 thousand compared to the estimate in 2010 (2.72 million deaths). This study added nationally representative evidence regarding concentration-response function for long-term PM_2.5-mortality association in Chinese adults, which may significantly contribute to national and global assessments of PM_2.5-attributable death burden.

Overviewing the air quality models on air pollution in Sichuan Basin, China

Most developing countries in the world face the common challenges of reducing air pollution and advancing the process of sustainable development, especially in China. Air pollution research is a complex system and one of the main methods is through numerical simulation. The air quality model is an important technical method, it allows researchers to better analyze air pollutants in different regions. In addition, the SCB is a high-humidity and foggy area, and the concentration of atmospheric pollutants is always high. However, research on this region, one of the four most polluted regions in China, is still lacking. Reviewing the application of air quality models in the SCB air pollution has not been reported thoroughly. To fill these gaps, this review provides a comprehensive narration about i) The status of air pollution in SCB; ii) The application of air quality models in SCB; iii) The problems and application prospects of air quality models in the research of air pollution. This paper may provide a theoretical reference for the prevention and control of air pollution in the SCB and other heavily polluted areas in China and give some¹inspirations for air pollution forecast in other countries with complex terrain.

Improving Human Health in China Through Alternative Energy

In this study, we estimate the health benefits of more stringent alternative energy goals and the costs of reducing coal-fired power plant pollution in China projected in 2030. One of our two overarching alternative energy goals was to estimate the health benefits of complete elimination of coal energy, supplemented by natural gas and renewables. The second was a policy scenario similar to the U.S. 2013 Climate Action Plan (CAP), which played a pivotal role leading up to the 2015 Paris Climate Agreement. We used the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model created by the International Institute for Applied Systems Analysis for our model simulations. We found that 17,137–24,220 premature deaths can be avoided if coal energy is completely replaced by alternative energy, and 8,693–9,281 premature deaths can be avoided if coal energy is replaced by alternatives in a CAP-like scenario. A CAP-like scenario using emission-controls in coal plants costs $11–18 per person. Reducing coal energy in China under a CAP-like scenario would free up $9.4 billion in the annual energy budget to spend on alternatives, whereas eliminating the cost of coal energy frees up $32 billion. This study's estimates show that more stringent alternative energy targets in China are worth the investment in terms of health.

Concentration, composition, and exposure contributions of fine particulate matter on subway concourses in China

Concentrations of airborne metal-rich particles are typically higher on subway platforms and in subway tunnels than in ambient air. The subway concourse is an area of direct air exchange with both platforms and the outside environment, but few researchers have measured the concentrations and composition of fine particles on subway concourses. We characterized the concentrations and composition of fine particles on six subway concourses in Nanjing, China in both summer and winter. We used a respiration rate-adjusted microenvironment exposure model to estimate the contribution of a 6-h work period to daily mean exposure to fine particulate matter of subway workers and compared the estimate with those for general indoor and outdoor workers. We found that particle concentrations were typically higher on the station concourses than in ambient air. The most abundant elements composing the particles were Fe, S, Ca, Si, and K in both subway concourses and reference ambient air, but their contents varied greatly between indoor and outdoor air. The indoor/outdoor ratios of Fe, Cu, and Mn were highest, and subway workers were disproportionately exposed to these three metals. The mean daily exposure dose to Fe was 44.8 μg for subway workers, approximately five times the exposure dose of indoor and outdoor workers. Daily exposure doses of Cu, Mn, V, Sr, As, Co, Sn, and Cr were also higher for subway workers. The quality of indoor air at subway stations is therefore of occupational health concern and strategies should be formulated to reduce worker exposure.

Present cum future of SARS-CoV-2 virus and its associated control of virus-laden air pollutants leading to potential environmental threat - A global review

The world is presently infected by the biological fever of COVID-19 caused by SARS-CoV-2 virus. The present study is mainly related to the airborne transmission of novel coronavirus through airway. Similarly, our mother planet is suffering from drastic effects of air pollution. There are sufficient probabilities or evidences proven for contagious virus transmission through polluted airborne-pathway in formed aerosol molecules. The pathways and sources of spread are detailed along with the best possible green control technologies or ideas to hinder further transmission. The combined effects of such root causes and unwanted outcomes are similar in nature leading to acute cardiac arrest of our planet. To maintain environmental sustainability, the prior future of such emerging unknown biological hazardous air emissions is to be thoroughly researched. So it is high time to deal with the future of hazardous air pollution and work on its preventive measures. The lifetime of such an airborne virus continues for several hours, thus imposing severe threat even during post-lockdown phase. The world waits eagerly for the development of successful vaccination or medication but the possible outcome is quite uncertain in terms of equivalent economy distribution and biomedical availability. Thus, risk assessments are to be carried out even during the post-vaccination period with proper environmental surveillance and monitoring. The skilled techniques of disinfection, sanitization, and other viable wayouts are to be modified with time, place, and prevailing climatic conditions, handling the pandemic efficiently. A healthy atmosphere makes the earth a better place to dwell, ensuring its future lifecycle.

The Effect of Different Cleaning Methods on Needles for Assessing the Atmospheric Heavy Metal Retention Capacity of Three Coniferous Trees

Urban air pollution has received increasing attention in recent years. To investigate the interaction between several heavy metal elements and the degree of atmospheric pollution, the leaves of three evergreen tree species—Chinese juniper (Juniperus chinensis L.), dragon juniper (Juniperus chinensis L. ‘Kaizuca’), and cedar (Cedrus deodara (Roxb. ex D.Don) G.Don)—were collected from main road intersections in the urban area of Tianjin, China. Two different treatments—water washing (WW) and ethanol washing (EW)—were used, and the contents of Cu, Mn, Cd, and Zn were measured in both washed and unwashed (UW) leaves. It was found that the heavy metal contents within Chinese juniper and dragon juniper were ranked as Mn > Zn > Cu > Cd, and the metal accumulation index (MAI) value was higher for dragon juniper. For the three plants, water washed off 5.36% to 58.58% of the total heavy metals in the needles, while ethanol washed off 16.08% to 71.60% of the total. Both washes were more effective for Cu, Zn, and Cd, and especially for the element Cd. Ethanol could clean off 38.64% to 71.60% of the total Cd from the leaves. Ethanol had a better elution effect compared to water, and the trend of the Cd content in the leaves of the three plants showed a change after the use of different washing methods, which suggests that the water washing may have masked the real difference.

Air pollution and cause-specific mortality: A comparative study of urban and rural areas in China

Air pollution increases the risks of all-cause mortality, cardiovascular mortality and respiratory mortality across China. However, the urban-rural differences in the associations between air pollution and mortality have not been clearly identified. In this study, a distributed lag nonlinear model was used to examine whether the air pollutants-mortality associations vary between urban and rural areas. Then, we used logistic regression analyses to evaluate the air pollutants-mortality relations. Also, generalized additive models were simulated to evaluate the nonlinear curves. Our results showed that the relative risks of air pollution-related mortality were generally higher in rural areas, where PM_2.5 pollution was the dominant factor (p-value < 0.05). Mortality risks for all-cause, cardiovascular and respiratory will increase when average annual PM_2.5 concentrations exceed approximately 38 μg/m³, 41 μg/m³ and 41 μg/m³, respectively, all of which exceed the annual Grade II standards. In urban areas, PM_10-2.5 and NO₂ were associated with mortality (p-value < 0.05). We proposed some area-specific strategies for controlling the NO₂ pollution and PM_10-2.5 pollution in urban areas and the PM_2.5 pollution in rural areas to eliminate the gaps. Our findings identify that rural residents are more sensitive to air pollution than urban residents in China, and this result challenges previous assumptions about the more adverse effects of urbanization on residents' health in developing countries.

Infrastructure policy and public health: Evidence from OECD countries

When making infrastructure policies, decision makers insufficiently consider negative consequences for the environment or health. This lack of multi-sectorial awareness in policymaking triggers poor public health outcomes. To illustrate this issue, this interdisciplinary work presents evidence for the association of road infrastructure investment (as infrastructure policy) with the incidences of deaths due to transport accidents, chronic obstructive pulmonary disease, and pneumonia using nationally aggregated data from the Organisation for Economic Co-operation and Development for 27 countries over an 18-year period (1995-2012). We conduct an explorative analysis using descriptive statistics and fixed-effects panel-data regression models that include the interaction of the policy variable with the Environmental Policy Stringency Index, which proxies the awareness of negative consequences of policies. We show that countries which never achieved a score of 3 or higher for the Environmental Policy Stringency Index had higher levels of standardized death rates. This is supported by Pearson's correlation coefficients and by the results of t-tests for deaths due to transport accidents. Following the fixed-effects analysis, we find that an increase in road infrastructure investment of 1% of gross domestic product is associated, on average, with about three additional deaths per 100,000 population due to transport accidents and about 18 fewer deaths per 100,000 population due to chronic obstructive pulmonary disease using standardized death rates. A one unit increase in the Environmental Policy Stringency Index is related to about 7 fewer deaths per 100,000 population due to chronic obstructive pulmonary diseases. Marginal effects of the interaction of road infrastructure investment and the Environmental Policy Stringency Index are significant for standardized death rates due to transport accidents and chronic obstructive pulmonary disease. Multi-sectorial awareness in infrastructure policy mediates health effects for deaths due to transport accidents and chronic obstructive pulmonary disease.

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.

Evaluating the meteorological normalized PM2.5 trend (2014-2019) in the "2+26" region of China using an ensemble learning technique

In recent years, implementation of aggressive and strict clean air policies has resulted in significant decline in observed PM_2.5 concentration in the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas (i.e., the "2 + 26" region). To eliminate the effects of interannual and seasonal meteorological variation, and to evaluate the effectiveness of emission abatement policies, we applied a boosted regression tree model to remove confounding meteorological factors. Results showed that the annual average PM2.5 concentration normalized by meteorology for the "2 + 26" region declined by 38% during 2014-2019 (i.e., from 96 to 60 μg/m³); however, the BTH region exhibited the most remarkable decrease in PM_2.5 concentration (i.e., a 60% reduction). Certain seasonal trend in normalized PM_2.5 level remained for four target subregions owing to the effects of anthropogenic emissions in autumn and winter. Although strong interannual variations of meteorological conditions were unfavorable for pollutant dispersion during the heating seasons of 2016-2018, the aggressive abatement policies were estimated to have contributed to reductions in normalized PM_2.5 concentration of 19%, 10%, 19%, and 17% in the BTH, Henan, Shandong, and Shanxi subregions, respectively. Our study eliminated the meteorological contribution to concentration variation and confirmed the effectiveness of the implemented clean air policies.

Distribution characteristics and policy-related improvements of PM2.5 and its components in six Chinese cities

This study presents the distribution characteristics and possible sources of fine particulate matter (PM_2.5) and its components, as well as policy-related pollution reduction in the Chinese cities of Jinan, Shijiazhuang (SJZ), Chengdu, Wuxi, Wuhan, and Harbin (HRB). PM_2.5 samples were collected using mid-volume samplers during the autumn of 2017 in all six cities. The samples were analyzed to determine the ambient PM_2.5 compositions, including the concentrations of water-soluble inorganic ions (WSIIs), carbonaceous aerosols, and elements concentrations. The chemical ratios of organic carbon to elemental carbon and nitrate to sulfate as well as the enrichment factors of elements were calculated to establish the possible sources of PM_2.5 in all six cities. The highest PM_2.5 concentration was 152 μg/m³ in SJZ, while the lowest concentration was 47 μg/m³ in HRB. During the sampling period in these six cities, the PM_2.5 concentrations exceeded the World Health Organization recommended daily average air quality guidelines by 2.4-6.1 times, and WSIIs, carbonaceous aerosols, and elements accounted for 31.8%-61.6%, 9.8%-35.1%, and 0.9%-2.5% of the PM_2.5, respectively. In 2013, the Chinese government formulated the Air Pollution Prevention and Control Action Plan (APPCAP) for controlling air pollution, and effective measures have been implemented since then. Compared with previous studies conducted during 2009-2013 before the implementation of the APPCAP, the concentrations of PM_2.5 and most of its components decreased to varying degrees, and large changes in the chemical ratios of PM_2.5 components were observed. These results indicate that PM_2.5 sources vary among these six cities and that China has improved the ambient air quality in these cities through the implementation of air pollution control policies. The APPCAP have achieved considerable results in continuously reducing pollution concentrations, although the air pollution concentrations observed in this study remain high compared with those of other countries.

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.

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

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

Regional transport in Beijing-Tianjin-Hebei region and its changes during 2014-2017: The impacts of meteorology and emission reduction

Emissions of air pollutants have been dramatically reduced in the Beijing-Tianjin-Hebei (BTH) region of China during 2014-2017. However, impacts of emission reduction on regional air quality are not well quantified. This study evaluates the impacts of emission reduction and inter-annual meteorological conditions on regional air pollution transport in BTH region by employing Community Multiscale Air Quality model embedded with the Integrated Source Apportionment Model (CMAQ-ISAM). Results suggest that the regional transport contributed 32.5%-68.4% of total PM_2.5 mass concentrations and 52.4%-83.2% of sulfate, nitrate and ammonium in 2017. During 2014-2017, the annual averaged PM_2.5 concentrations in BTH region decreased by 33%, of which the decrease of local emissions, inter-regional transport and transport from outside the BTH region contributed for 47%, 25%, and 28%, respectively. Emission reductions (91%) mitigate not only the impacts of local sources, but also influence the regional transport with similar magnitude, demonstrating the effectiveness of multiple regional joint controls. The variation of meteorology contributes only 9% to the decrease of PM_2.5 in BTH, with higher contributions from the change of regional transport compared to local sources since the regional transport is more sensitive to the meteorology variation. The impacts of meteorological variations are considerable, with over 20% on the relative changes of local and regional contributions, and up to 40% on regional transport in spring and winter. Therefore, more strengthened regional joint air pollution control is suggested in winter and spring for this region.

The Silver Lining of COVID-19: Estimation of Short-Term Health Impacts Due to Lockdown in the Yangtze River Delta Region, China

The outbreak of COVID-19 in China has led to massive lockdowns in order to reduce the spread of the epidemic and control human-to-human transmission. Subsequent reductions in various anthropogenic activities have led to improved air quality during the lockdown. In this study, we apply a widely used exposure-response function to estimate the short-term health impacts associated with PM_2.5 changes over the Yangtze River Delta (YRD) region due to COVID-19 lockdown. Concentrations of PM_2.5 during lockdown period reduced by 22.9% to 54.0% compared to pre-lockdown level. Estimated PM_2.5-related daily premature mortality during lockdown period is 895 (95% confidential interval: 637-1,081), which is 43.3% lower than pre-lockdown period and 46.5% lower compared with averages of 2017-2019. According to our calculation, total number of avoided premature death aassociated with PM_2.5 reduction during the lockdown is estimated to be 42.4 thousand over the YRD region, with Shanghai, Wenzhou, Suzhou (Jiangsu province), Nanjing, and Nantong being the top five cities with largest health benefits. Avoided premature mortality is mostly contributed by reduced death associated with stroke (16.9 thousand, accounting for 40.0%), ischemic heart disease (14.0 thousand, 33.2%), and chronic obstructive pulmonary disease (7.6 thousand, 18.0%). Our calculations do not support or advocate any idea that pandemics produce a positive note to community health. We simply present health benefits from air pollution improvement due to large emission reductions from lowered human and industrial activities. Our results show that continuous efforts to improve air quality are essential to protect public health, especially over city-clusters with dense population.

Prenatal exposure to residential PM2.5 and anogenital distance in infants at birth: A birth cohort study from Shanghai, China

Fine particulate matter (PM_2.5) is believed to be one of the most hazardous air pollution with a ubiquitous presence. Animal studies have reported the association between prenatal exposure to traffic pollutant (not exclusively including PM_2.5) and reproductive development in male offspring. However, the effects of prenatal exposure to PM_2.5 on reproductive health in children are still unknown. The present study was based on the Shanghai-Minhang Birth Cohort Study (S-MBCS). A total of 876 pregnant women and their infants were included. Infants' anogenital distance (AGD, the distance from the anus to the genitals; AGDap [anus-penis] and AGDas [anus-scrotum] for boys, and AGDac [anus-clitoris] and AGDaf [anus-fourchette] for girls) were measured at birth. PM_2.5 concentrations during pregnancy were estimated using satellite based modeling approach. Multiple linear regression analysis and multiple informant model were conducted to examine the associations between prenatal exposure to PM_2.5 (pre μg/m³) and offspring's AGDs (mm). In order to minimize the misclassification of exposure, a sensitivity analysis restricted to mothers being off work during pregnancy was performed. In multiple linear regression models, we found that prenatal exposure to PM_2.5 during the 1^st and 3^rd trimesters was associated with shorter AGDs. In multiple informant model, similar patterns were found, and statistically significant reductions were observed in AGDap (β=-0.278, 95%CI: -0.343∼-0.212), AGDac (β=-0.188, 95%CI: -0.247∼-0.130) and AGDaf (β= -0.163, 95%CI: -0.238∼-0.088) with PM_2.5 exposure during the 1^st trimester, and AGDap (β=-0.201, 95%CI: -0.247∼-0.155), AGDas (β=-0.158, 95%CI: -0.198∼-0.117), AGDac (β=-0.128, 95%CI: -0.167∼-0.089) and AGDaf (β = -0.144, 95%CI: -0.194∼-0.094) with PM_2.5 exposure during the 3^rd trimester. The sensitivity analysis restricted to women being off work during pregnancy showed similar results. PM_2.5 exposure during the 1^st and 3^rd trimesters was associated with shortened AGDs in offspring at birth. Our findings provide preliminary evidence that prenatal exposure to PM_2.5 might be associated with the reproductive development of offspring.

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.

Public health benefits of optimizing urban industrial land layout - The case of Changsha, China

In China, ambient fine particulate matter (PM_2.5) causes a large health burden and raises specific concerns for policymakers. However, assessments of the health effects associated with air pollution from industrial land layouts remain inadequate. This study established a comprehensive assessment framework to quantify the health and economic impacts of PM_2.5 exposure at different industrial geographical locations. This framework aims to optimize the spatial distribution of industrial emissions to achieve the lowest public health costs in Changsha, a representative industrial city in China. Health effects were estimated by applying the integrated exposure-response model and a long-range pollution dispersion model (CALPUFF). The value of statistical life (VSL) was used to monetize health outcomes. It was found that implementing an optimal industrial land layout can yield considerable social and financial benefits. Compared with the current industrial space layout, in 2030, the averted contribution by Changsha's industrial sector to PM_2.5-related mortality and corresponding economic losses will be 60.8% and 0.69 billion US dollars (USD), respectively. The results of optimization analyses highlighted that population density and emission location are significant factors affecting the health burden. This method can identify the optimal geographical allocation of industrial land with minimal expected health and economic burden. These results will also provide policymakers with a measurable assessment of health risks related to industrial spatial planning and the associated health costs to enhance the effectiveness of efforts to improve air quality.

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.

Impact of the ‘13th Five-Year Plan’ Policy on Air Quality in Pearl River Delta, China: A Case Study of Haizhu District in Guangzhou City Using WRF-Chem

Due to increasingly stringent control policy, air quality has generally improved in major cities in China during the past decade. However, the standards of national regulation and the World Health Organization are yet to be fulfilled in certain areas (in some urban districts among the cities) and/or certain periods (during pollution episode event). A further control policy, hence, has been issued in the 13th Five-Year Plan (2016–2020, hereafter 13th FYP). It will be of interest to evaluate the air quality before the 13th FYP (2015) and to estimate the potential air quality by the end of the 13th FYP (2020) with a focus on the area of an urban district and the periods of severe pollution episodes. Based on observation data of major air pollutants, including SO2 (sulphur dioxide), NO2 (nitrogen dioxide), CO (carbon monoxide), PM10 (particulate matter with aerodynamic diameter equal to or less than 10 μm), PM2.5 (particulate matter with aerodynamic diameter equal to or less than 2.5 µm) and O3 (Ozone), the air quality of Haizhu district [an urban district in the Pearl River Delta (PRD), China] in 2015 suggested that typical heavy pollution occurred in winter and the hot season, with NO2 or PM2.5 as the key pollutants in winter and O3 as the key pollutant in the hot season. We also adopted a state-of-the-art chemical transport model, the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), to predict the air quality in Haizhu District 2020 under different scenarios. The simulation results suggested that among the emission control scenarios, comprehensive measures taken in the whole of Guangzhou city would improve air quality more significantly than measures taken just in Haizhu, under all conditions. In the urban district, vehicle emission control would account more than half of the influence of all source emission control on air quality. Based on our simulation, by the end of the 13th FYP, it is noticeable that O3 pollution would increase, which indicates that the control ratio of volatile organic compounds (VOCs) and nitrogen oxides (NOx) may be unsuitable and therefore should be adjusted. Our study highlights the significance of evaluating the efficacy of current policy in reducing the air pollutants and recommends possible directions for further air pollution control for urban areas during the 13th FYP.

Air pollution and chronic obstructive pulmonary disease

There is considerable epidemiological evidence indicating that air pollution has adverse effects on human health and is closely related to respiratory diseases, including chronic obstructive pulmonary disease (COPD). These effects, which can be divided into short- and long-term effects, can manifest as an exacerbation of existing symptoms, impaired lung function, and increased hospitalization and mortality rates. Long-term exposure to air with a high concentration of pollutants may also increase the incidence of COPD. The combined effects of different pollutants may become more complex in the future; hence, there is a need for more intensive research on specific at-risk populations, and formulating corresponding protective strategies is crucial. We aimed to review the epidemiological evidence on the effect of air pollution on COPD, the possible pathophysiological mechanisms underlying this effect, as well as protective measures against the effects of air pollutants in patients with COPD.

Large-scale optimization of multi-pollutant control strategies in the Pearl River Delta region of China using a genetic algorithm in machine learning

A scientifically sound integrated assessment modeling (IAM) system capable of providing optimized cost-benefit analysis is essential in effective air quality management and control strategy development. Yet scenario optimization for large-scale applications is limited by the computational expense of optimization over many control factors. In this study, a multi-pollutant cost-benefit optimization system based on a genetic algorithm (GA) in machine learning has been developed to provide cost-effective air quality control strategies for large-scale applications (e.g., solution spaces of ~1035). The method was demonstrated by providing optimal cost-benefit control pathways to attain air quality goals for fine particulate matter (PM2.5) and ozone (O3) over the Pearl River Delta (PRD) region of China. The GA was found to be >99% more efficient than the commonly used grid searching method while providing the same combination of optimized multi-pollutant control strategies. The GA method can therefore address air quality management problems that are intractable using the grid searching method. The annual attainment goals for PM2.5 (< 35 μg m-3) and O3 (< 80 ppb) can be achieved simultaneously over the PRD region and surrounding areas by reducing NOx (22%), volatile organic compounds (VOCs, 12%), and primary PM (30%) emissions. However, to attain stricter PM2.5 goals, SO2 reductions (> 9%) are needed as well. The estimated benefit-to-cost ratio of the optimal control strategy reached 17.7 in our application, demonstrating the value of multi-pollutant control for cost-effective air quality management in the PRD region.

Age- and season-specific effects of ambient particles (PM1, PM2.5, and PM10) on daily emergency department visits among two Chinese metropolitan populations

BACKGROUND

Ambient PM_2.5 has been identified as the top leading cause of risk-attributable deaths worldwide, particularly in China. Evidence suggested that PM₁ contributed the most majority of PM_2.5 concentrations in Chinese cities. However, epidemiologic knowledge to date is of wide lack regarding PM₁-associated health effects.

METHODS

We collected daily records of all-cause emergency department visits (EDVs) and ground measurements of ambient air pollutants and meteorological factors in Guangzhou and Shenzhen, China, 2015-2016. Case-crossover design and conditional logistic regression models were used to comparatively assess the short-term effects of ambient PM₁, PM_2.5, and PM₁₀ on EDVs. Stratified analyses by gender, age and season were performed to identify vulnerable groups and periods.

RESULTS

PM₁, PM_2.5 and PM₁₀ were all significantly associated with increased EDVs in both cities. Population risks for EDVs increased by 2.2% [95% confidence interval, 1.8 to 2.6] in Guangzhou and 1.7% [1.0 to 2.4] in Shenzhen, for a 10 μg/m³ rise in PM₁ at lag 0-1 days and lag 0-4 days, respectively. Relatively lower risks were found to be associated with PM_2.5 and PM₁₀. PM-EDVs associations exhibited no gender differences, but varied across age groups. Compared with adults and the elderly, children under 14 years-of-age suffered higher PM-induced risks. Results from both cities suggested greatly significant effect modification by season, with consistently stronger PM-EDVs associations during cold months.

CONCLUSIONS

Our study added comparative evidence for increased EDVs risks associated with short-term exposures to ambient PM₁, PM_2.5 and PM₁₀. Besides, PM-associated effects were significantly stronger among children and during cold months.

Monitoring history and change trends of ambient air quality in China during the past four decades

This study summarized the history of ambient air quality monitoring and air pollution prevention and control, and it analyzed the spatiotemporal patterns of ambient air pollutants during 1981-2017 in China. The results showed that monitoring of ambient air quality has changed dramatically in terms of determinants, sampling methods, monitoring extent, and evaluation basis during the previous four decades. Annual average concentrations of total suspended particulates, PM₁₀ and SO₂ have shown obvious decreasing trends during the studied period. These improvements have been closely related to the considerable efforts and various approaches undertaken to prevent and control air pollution. However, although policy implementation has been decisive and, at least in part, it has been enforced effectively, significant challenges remain. Air pollution control cannot be accomplished without a long-term strategy designed to achieve clean air in all parts of China.

Characteristics of Air Pollution and Their Relationship with Meteorological Parameters: Northern Versus Southern Cities of China

Air pollution shows a generally decreasing trend from the north to the south in China since 2013 (GB3095-2012, the current standard for monitoring). However, an opposite observation was recorded in 2017, especially in winter. In this study, we collected monitoring data of six air pollutants in 2016 and 2017, from a northern city (Beijing) and a southern city (Nanjing) for comparison. As air pollution was highly dependent upon meteorological conditions, we further analyzed their relationships to explain this abnormal phenomenon. Seasonal averaged PM2.5, PM10, SO2, CO, and NO2 were negatively correlated with wind scale (WS) while 8-h O3 exhibited an opposite relationship. Relative humidity (RH) has opposite effects on the concentrations of different pollutants in Beijing and Nanjing. The 8-h O3 showed the closest positive correlation with temperature (T), which is due to its formation mechanism. In Beijing, decreased RH, together with more wind from northwest in winter, resulted in an improved air quality in 2017. In Nanjing, WS, RH, T, and wind direction fluctuated within a narrow range in each season, leading to relatively stable pollutant concentrations. These results suggest that meteorological conditions are important factors to evaluate the air quality and implement control measures.

Variation trends and principal component analysis of nitrogen oxide emissions from motor vehicles in Wuhan City from 2012 to 2017

In addition to fine particulate matter and oxysulfides, nitrogen oxides (NO_x) emitted by motor vehicles are among the most important pollutants affecting air quality and public health in those urban areas where centralized heating and chemical industry absent. We utilized correlation analysis (pearson correlation coefficient and spearman correlation coefficient) and principal component analysis (PCA) to identify the variation trends and main causes of NO_x emissions from motor vehicles in Wuhan City. We considered the total number of motor vehicles (TN), ratios of motor vehicles of different emission standards (RE), rations of labeled motor vehicles (RL), and rations of motor vehicles' fuel types (RF). The results show that: 1) with an increase in the total amount of motor vehicles, the NO_x emissions of motor vehicles have been decreasing since 2015; 2) three sub-categories (the ratio of the State III emission standard, the ration of yellow label diesel vehicles, and the ration of diesel vehicles) were recognized as key indexes of PE, PL and PF, respectively, in the PCA; 3) a new parameter, the ES_index is proposed as an index to represent the variation trend of the NO_x emissions of motor vehicles in Wuhan City.

The contributions of socioeconomic indicators to global PM2.5 based on the hybrid method of spatial econometric model and geographical and temporal weighted regression

PM_2.5 pollution poses a negative effect on human health and economic growth. However, the major socioeconomic driving forces of global PM_2.5 pollution during a long-term period remained unclear. In this study, we explored the potential association between socioeconomic indicators and the PM_2.5 level worldwide using a spatial econometric model coupled with a geographical and temporal weighted regression (GTWR). The results suggested that renewable energy consumption ratio, per capita gross domestic production (GDP), per capita CO₂ emission, urban population ratio, and fossil fuel consumption ratio were major factors responsible for the global PM_2.5 pollution. The impacts of socioeconomic indicators on the PM_2.5 level varied with the income-level and time. Fossil fuel consumption ratio, per capita CO₂ emission, urban population ratio were major contributors for severe PM_2.5 pollution in the developing countries (e.g., China and India). Further, these impacts have become more remarkable in recent years. Per capita GDP still played a crucial role on the PM_2.5 pollution in India, indicating that energy-intensive industries were major contributors to its economic growth, thereby leading to the higher PM_2.5 concentration in India. However, China has strode across the inflection of Environmental Kuznets Curve (EKC) as a whole and decreased the reliance on the secondary industries. Compared with the developing countries, the impacts of socioeconomic indicators on PM_2.5 pollution in most of the developed countries remained relatively stable and weak, implicating that fossil fuel consumption and urbanization were not major contributors for local PM_2.5 level. The findings of this study clarified major contributors for PM_2.5 pollution, and provided scientific basis for mitigating the PM_2.5 pollution.

Asymmetrically Spatial Effects of Urban Scale and Agglomeration on Haze Pollution in China

Rapid urbanization in China not only promotes the rapid expansion of urban population and economic agglomeration, but also causes the aggravation of haze pollution. In order to better clarify the asymmetric and nonlinear effects of urban scale and agglomeration on haze pollution, this paper quantitatively evaluates the spatial spillover effects of population size and economic agglomeration on haze pollution in 342 Chinese cities from 2001 to 2016 by using exploratory spatial data analysis (ESDA) and spatial econometric model. The results show the following: (1) During the research period, the distribution of urban scale, agglomeration, and haze pollution in China presented complex asymmetrical features, with the former two presenting a “core–periphery” distribution mode, while the latter having a tendency to spread around. In addition, under the influence of urban population size and economic agglomeration, haze pollution in Chinese cities presents significant spatial autocorrelation, with the agglomeration degrees showing a fluctuating upward trend during the study period. (2) Both urban scale and urban agglomeration have positive global spatiotemporal correlation with haze pollution. Local spatial correlation features are more obvious in China’s emerging urban agglomerations like Beijing–Tianjin–Hebei and Yangtze River Delta. (3) The spatial effects of haze pollution are better evaluated by spatial Durbin model (SDM) with spatial fixed effects, obtaining a coefficient of 0.416, indicating haze in neighboring cities affected each other and had significant spillover. By decomposing the effect of urban scale and agglomeration on haze as direct and indirect effects, the direct effect of urban population size and the indirect effect of urban economic agglomeration are found to be more prominent, reflecting that significant asymmetrical characteristics exist in the spatial effects of urban size and agglomeration on urban haze. (4) Among the control variables that affect China’s rapid urbanization, the level of urban economic development has a positive effect on haze pollution, while the high-level industrial structure and improved technical level can effectively reduce haze pollution. Continuous decline of haze concentration of Chinese cities in recent years has been indicating the spatial relationships between haze and urban size and agglomeration have a decoupling trend. The findings contribute to theory by emphasizing the spillover effect and spatial heterogeneities of geographical factors, and have implications for policy makers to deal with haze pollution reasonably and effectively.

Spatiotemporal variation in PM2.5 concentrations and their relationship with socioeconomic factors in China's major cities

The air quality issues caused by extreme haze episodes in China have become increasingly serious in recent years. In particular, fine particulate matter (PM_2.5) has become the major component of haze with many adverse impacts and has therefore become of great concern to scientists, government, and the general public in China. This study investigates the spatiotemporal variation in PM_2.5 in 269 Chinese cities from 2015 to 2016 and its associations with socioeconomic factors to identify the possible strategies for PM_2.5 pollution mitigation. Specifically, we first quantified the spatial pattern of PM_2.5 concentrations in both 2015 and 2016, and then changes between the two years. Next, we examined the relationship between socioeconomic factors and PM_2.5 concentrations and changes. The results showed that most cities in eastern China experienced decreases in PM_2.5 concentration, although most of these cities already had high PM_2.5 pollution level. Cities with low PM_2.5 concentrations experienced increases in PM_2.5 concentrations and were mostly located in southern and southwestern China. The PM_2.5 concentration was the highest in winter, followed by in spring, autumn and summer; for changes in PM_2.5 concentrations, the highest magnitude of decrease occurred in summer, followed by the decreases in winter, autumn and spring. Cities with high PM_2.5 concentrations tended to be clustered, but the clustered characteristics were not clearly related to the changes in PM_2.5 concentrations. The relationship between PM_2.5 concentration and urban size was an inverse U-shaped curve, suggesting the existence of the Environmental Kuznets Curve for air quality in China. Population density and secondary industry share are the keys factors relating to air pollution control. In comparison to other cities, most moderately developed cities had a greater magnitude of decrease in PM_2.5 concentrations and the key factor for pollution improvement was industrial structure; however, smaller cities tended to have a greater increase in PM_2.5 concentrations and population density was the most important influencing factor. As a result, for air pollution control in China, specific regulations should be carried out according to different regions and different developmental stages based on the locations of cities.

Environmental taxation and regional inequality in China

In order to combat environmental pollution, China enacted the Environmental Protection Tax Law in early 2018. Yet the impacts of the environmental tax on individual regions with different socioeconomic statuses, which are crucial for social justice and public acceptance, remain unclear. Based on a Multi-Regional Input-Output (MRIO) table and a nationally regulated tax payment calculation method, this study analyzes the distributional impacts of an environmental tax based upon province's consumption from both inter-provincial and rural-urban aspects. The national tax revenue based on the current levy mechanism is estimated to be only one seventh of the economic loss from premature mortality caused by ambient particulate matter (PM_2.5). The taxation may slightly alleviate urban-rural inequality but may not be helpful with reducing inter-provincial inequality. We further analyze two alternative levy mechanisms. If each province imposes taxes to products it consumes (rather than produces, as in the current mechanism), with the tax rate linearly dependent on its per capita consumption expenditure, this would moderately increase the national tax revenue and significantly reduce inter-provincial inequality. To better compensate for the economic costs of air pollution and reduce regional inequality, it would be beneficial to increase the tax rate nationwide and implement a levy mechanism based on provincially differentiated levels of consumption and economic status.

Short-term effects of ambient PM1 and PM2.5 air pollution on hospital admission for respiratory diseases: Case-crossover evidence from Shenzhen, China

BACKGROUND

Ambient PM₁ (particulate matter with aerodynamic diameter ≤1 μm) is an important contribution of PM_2.5 mass. However, little is known worldwide regarding the PM₁-associated health effects due to a wide lack of ground-based PM₁ measurements from air monitoring stations.

METHODS

We collected daily records of hospital admission for respiratory diseases and station-based measurements of air pollution and weather conditions in Shenzhen, China, 2015-2016. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate hospitalization risks associated with short-term exposures to PM₁ and PM_2.5.

RESULTS

PM₁ and PM_2.5 showed significant adverse effects on respiratory disease hospitalizations, while no evident associations with PM_1-2.5 were identified. Admission risks for total respiratory diseases were 1.09 (95% confidence interval: 1.04 to 1.14) and 1.06 (1.02 to 1.10), corresponding to per 10 μg/m³ rise in exposure to PM₁ and PM_2.5 at lag 0-2 days, respectively. Both PM₁ and PM_2.5 were strongly associated with increased admission for pneumonia and chronic obstructive pulmonary diseases, but exhibited no effects on asthma and upper respiratory tract infection. Largely comparable risk estimates were observed between male and female patients. Groups aged 0-14 years and 45-74 years were significantly affected by PM₁- and PM_2.5-associated risks. PM-hospitalization associations exhibited a clear seasonal pattern, with significantly larger risks in cold season than those in warm season among some subgroups.

CONCLUSIONS

Our study suggested that PM₁ rather than PM_1-2.5 contributed to PM_2.5-induced risks of hospitalization for respiratory diseases and effects of PM₁ and PM_2.5 mainly occurred in cold season.

Energy and Health Efficiencies in China with the Inclusion of Technological Innovation

The price people pay for low energy efficiency includes not only high manufacturing costs, but also public health. With technological innovation as the driving factor for improving energy efficiency, this study uses two-stage dynamic undesirable data envelopment analysis (TDU-DEA) under variable return to scale to evaluate energy and health efficiencies with inclusion of technological innovation in 30 provinces of China over the period 2013–2016. The results show that the mean overall efficiencies and ranks in the eastern region are significantly higher than those in the non-eastern region, with or without the inclusion of technological innovations, and that energy efficiency in most provinces is higher than health efficiency. The average technological innovation efficiencies for energy conservation are higher than those for respiratory medical treatment. The former gap between the eastern region and non-east region is also smaller than the latter. Lastly, regions with the best technological innovation efficiencies are Beijing, Shanghai, Guangdong, Fujian, Hainan, Hebei, Inner Mongolia, Ningxia, Qinghai, Shandong, Shanxi, Tianjin, Xinjiang, and Yunnan.

Cardiovascular impact of PM2.5 from the emissions of coal-fired power plants in Spain during 2014

INTRODUCTION AND OBJECTIVES

One of the main sources of energy in Spain is still coal combustion. It releases multiple pollutants into the atmosphere, such as PM_2.5, that has been linked to an increase in cardiovascular morbidity and mortality. The objectives of this paper are: 1) to determine the national distribution of these particles and their proximity to coal plants, 2) to estimate the cardiovascular impact of PM_2.5 particles in Spain in 2014.

METHODS

In order to complete the national pollutant dispersion study, we used the CALPUFF model. The epidemiologic and demographic data were obtained from the National Statistics Institute. The associations «pollutant-effect» were obtained by internationally validated methodologies.

RESULTS

The total number of deaths due to coal pollutants were 709, from which 586 (82.6%) were related to PM_2.5 particles. Most of them were due to myocardial infarctions, fatal strokes and heart failure, adding up to 170 cases of mortality related to PM_2.5 (29%). The greatest densities were found in the regions of Asturias and Castilla y León.

CONCLUSIONS

This study describes an increase in cardiovascular mortality and morbidity in Spain, due to coal combustion pollutants. It finds a greater impact in the provinces of Asturias and Castilla León, where a higher presence of coal power plants can be found. This reflects that the people that live in those areas have a greater risk of cardiovascular death due to PM_2.5 pollutant exposure from coal.

Correlations between PM2.5 and Ozone over China and Associated Underlying Reasons

We investigated the spatial-temporal characteristics of the correlations between observed PM2.5 and O3 over China at a national-scale level, and examined the underlying reasons for the varying PM2.5–O3 correlations by using a chemical transport model. The PM2.5 concentrations were positively correlated with O3 concentrations for most regions and seasons over China, while negative correlations were mainly observed in northern China during winter. The strongest positive PM2.5–O3 correlations with correlation coefficients (r) larger than +0.7 existed in southern China during July, and the strongest negative correlations (r < −0.5) were observed in northern China during January. It was a very interesting phenomenon that the positive PM2.5–O3 correlations prevailed for high air temperature samples, while the negative correlations were generally found in cold environments. Together, the effective inhibitory effect of PM2.5 on O3 generation by reducing photolysis rates and the strong titration effect of freshly emitted NO with O3 contributed to the strongest negative PM2.5–O3 correlations in northern China during January (i.e., in cold environments). The strongest positive correlations in southern China during July (i.e., at high temperature), however, were mainly attributed to the promoting effect of high O3 concentration and active photochemical activity on secondary particle formation.

Effects of PM2.5 on Cardio-Pulmonary Function Injury in Open Manganese Mine Workers

Exposure to fine particulate matter 2.5 (PM_2.5) is associated with adverse health effects, varying by its components. The health-related effects of PM_2.5 exposure from ore mining may be different from those of environment pollution. The aim of this study was to investigate the effects of different concentrations of PM_2.5 exposure on the cardio-pulmonary function of manganese mining workers. A total of 280 dust-exposed workers who were involved in different types of work in an open-pit manganese mine were randomly selected. According to the different concentrations of PM_2.5 in the working environment, the workers were divided into an exposed group and a control group. The electrocardiogram, blood pressure, and multiple lung function parameters of the two groups were measured and analyzed. The PM_2.5 exposed group had significantly lower values in the pulmonary function indexes of forced expiratory volume in one second (FEV1.0), maximum mid expiratory flow (MMEF), peak expiratory flow rate (PEFR), percentage of peak expiratory flow out of the overall expiratory flow volume (PEFR%), forced expiratory flow at 25% and 75% of forced vital capacity (FEF 25, FEF75), forced expiratory flow when 25%, 50%, and 75% of forced vital capacity has been exhaled (FEF25%,FEF50%, FEF75%), and FEV1.0/FVC% (the percentage of the predicted value of forced vital capacity) than the control group (all p < 0.05). Both groups had mild or moderate lung injury, most of which was restrictive ventilatory disorder, and there was significant difference in the prevalence rate of restrictive respiratory dysfunction between the two groups (41.4% vs. 23.6%, p = 0.016). Electrocardiogram (ECG) abnormalities, especially sinus bradycardia, were shown in both groups, but there was no statistical difference of the prevalence rate between the two groups (p > 0.05). Also, no significant difference of the prevalence rate of hypertension was observed between the PM2.5 exposure and control groups (p > 0.05). PM_2.5 exposure was associated with pulmonary function damage of the workers in the open-pit manganese mine, and the major injury was restrictive ventilatory disorder. The early effect of PM_2.5 exposure on the cardiovascular system was uncertain at current exposure levels and exposure time.

The economic benefits of fulfilling the World Health Organization's limits for particulates: A case study in Algeciras Bay (Spain)

Algeciras Bay is an important industrial and port zone in the south of Spain whose pollution by particulate matter surpasses the threshold levels recommended by the World Health Organization (WHO) in its 2005 Guide on Air Quality. This study analyses the mortality avoided and the economic benefit which would be derived from a reduction of the pollution of PM2.5 and PM10 to the levels recommended by the WHO in Algeciras Bay in the period 2005-2015. The analysis carried out shows that the industrial zones, such as Los Barrios and San Roque, are those which have greater levels of pollution and in which the relative risk is greater. The calculations for Algeciras Bay between 2000 and 2015 show 182 deaths which would be avoided if the particulate matter pollution were reduced to the levels recommended by the WHO. Likewise, the economic valuation which this impact has on health is carried out through two concepts: the cost of illness and the Value of Statistical Life (VSL). The result shows that the economic benefit that would come out with the cost of illness valuation is 5,329,110€ and from the VSL is 414,787,113€. Implications: PM_2.5 has a greater concentration in industrial localities and is linked to the industrial activity. When the particulate matter pollution is reduced to the levels recommended by the WHO in an industrialised area such as Algeciras (Spain), 182 deaths which would be avoided. The result shows that the economic benefit that would come out with the cost of illness valuation is 5,329,110€ and from the value of statistical life is 414,787,113€.

Air pollution intervention and life-saving effect in China

As a critical air pollutant, PM_2.5 is proved to be associated with numerous adverse health impacts and pose serious challenges to human life. This situation is especially important for China as the most populous and one of the heaviest PM_2.5 polluted country in the world. However, health burden estimations reported for China in previous studies may be biased due to the usage of PM_2.5 concentrations at a coarsely spatial resolution, as well as the ignorance of the spatial discrepancies of parameters (e.g. respiratory rate) employed in the exposure-response function. This study therefore utilized a hybrid remote sensing-geostatistical approach to refine PM_2.5 concentrations at 1 km resolution across mainland China from 2013 to 2017. Meanwhile, nationwide exposure parameters were for the first time introduced to weight the integrated exposure response (IER) function to calculate and spatially reallocate the corresponding PM_2.5-attributable premature deaths at 1 km resolution. Results showed that annually averaged PM_2.5 concentrations in mainland China decreased by 39.5%, from 59.1 μg/m³ in 2013 to 35.8 μg/m³ in 2017. Subsequently, PM_2.5 attributable premature deaths reduced 12.6%, from 1.20 million (95% CI: 0.57; 1.71) in 2013 to 1.05 million (95% CI: 0.44; 1.44) in 2017. This declining trend was found in most parts of China except some areas in Xinjiang, Jilin, and Heilongjiang provinces. As a result, 214,821 (95% CI: 96,675; 302,897) life were saved with an estimated monetary value of US$ 210.14 billion (2011 values). However, it has to be acknowledged that, the central and northern China within priority areas of air pollution control were still experiencing high numbers of premature deaths due to the severe PM_2.5 pollution and high-density population. But more worrying than these priority areas are those Harbin-Changchun Metropolitan Region, City Belt in Central Henan and Yangtze-Huaihe City Belt in non-priority areas, which also have been seriously suffering PM_2.5 attributable premature deaths over 28, 000 cases per year. In conclusion, despite the huge gain in life-saving effects in China over the past five years with the help of air pollution intervention policy, future work on cleaner air and better human health is still strongly needed, especially in non-priority areas of air pollution control.

Function of cAMP scaffolds in obstructive lung disease: Focus on epithelial-to-mesenchymal transition and oxidative stress

Over the past decades, research has defined cAMP as one of the central cellular nodes in sensing and integrating multiple pathways and as a pivotal role player in lung pathophysiology. Obstructive lung disorders, such as chronic obstructive pulmonary disease (COPD), are characterized by a persistent and progressive airflow limitation and by oxidative stress from endogenous and exogenous insults. The extent of airflow obstruction depends on the relative deposition of different constituents of the extracellular matrix, a process related to epithelial-to-mesenchymal transition, and which subsequently results in airway fibrosis. Oxidative stress from endogenous and also from exogenous sources causes a profound worsening of COPD. Here we describe how cAMP scaffolds and their different signalosomes in different subcellular compartments may contribute to COPD. Future research will require translational studies to alleviate disease symptoms by pharmacologically targeting the cAMP scaffolds. LINKED ARTICLES: This article is part of a themed section on Adrenoceptors-New Roles for Old Players. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v176.14/issuetoc.

Haze Influencing Factors: A Data Envelopment Analysis Approach

This paper investigates the meteorological factors and human activities that influence PM_2.5 pollution by employing the data envelopment analysis (DEA) approach to a chance constrained stochastic optimization problem. This approach has the two advantages of admitting random input and output, and allowing the evaluation unit to exceed the front edge under the given probability constraint. Furthermore, by utilizing the meteorological observation data incorporated with the economic and social data for Jiangsu Province, the chance constrained stochastic DEA model was solved to explore the relationship between the meteorological elements and human activities and PM_2.5 pollution. The results are summarized by the following: (1) Among all five primary indexes, social progress, energy use and transportation are the most significant for PM_2.5 pollution. (2) Among our selected 14 secondary indexes, coal consumption, population density and civil car ownership account for a major portion of PM_2.5 pollution. (3) Human activities are the main factor producing PM_2.5 pollution. While some meteorological elements generate PM_2.5 pollution, some act as influencing factors on the migration of PM_2.5 pollution. These findings can provide a reference for the government to formulate appropriate policies to reduce PM_2.5 emissions and for the communities to develop effective strategies to eliminate PM_2.5 pollution.

PM2.5 Pollution in Xingtai, China: Chemical Characteristics, Source Apportionment, and Emission Control Measures

Beijing-Tianjin-Hebei (BTH) and its surrounding areas are one of the most polluted regions in China. Xingtai, as a heavy industrial city of BTH and its surrounding areas, has been experiencing a severe PM2.5 pollution in recent years, characterized by extremely high concentrations of PM2.5. In 2014, PM2.5 mass concentrations monitored by online instruments in urban areas of Xingtai were 116, 77, 128, and 200 µg m−3 in spring, summer, autumn and winter, respectively, with annually average concentrations of 130 µg m−3 exhibiting 3.7 times higher than National Ambient Air Quality Standard (NAAQS) value for PM2.5 (35 µg m−3). To identify PM2.5 emission sources, ambient PM2.5 samples were collected during both cold and warm periods in 2014 in urban areas of Xingtai. Organic carbon (OC), sulfate, nitrate, ammonium and elemental carbon (EC) were the dominant components of PM2.5, accounting for 13%, 11%, 12%, 11% and 8% in the cold period, respectively, and 11%, 12%, 9%, 6%, and 5% in the warm period, respectively. Source apportionment results indicated that coal combustion (24.4%) was the largest PM2.5 emission source, followed by secondary sulfate (22.2%), secondary nitrate (18.4%), vehicle exhaust dust (12.4%), fugitive dust (9.7%), construction dust (5.5%), soil dust (3.4%) and metallurgy dust (1.6%). Based on PM2.5 source apportionment results, some emission control measures, such as replacing bulk coal with clean energy sources, controlling coal consumption by coal-fired boiler upgrades, halting operations of unlicensed small polluters, and controlling fugitive and VOCs emission, were proposed to be implemented in order to improve Xingtai’s ambient air quality.

Health benefit assessment of PM2.5 reduction in Pearl River Delta region of China using a model-monitor data fusion approach

The Pearl River Delta (PRD), one of the most polluted and populous regions of China, experienced a 28% reduction in fine particulate matter (PM_2.5) concentration between 2013 (47 μg/m³) and 2015 (34 μg/m³) under a stringent national policy known as the Air Pollution Prevention and Control Action Plan (hereafter Action Plan). In this study, the health and economic benefits associated with PM_2.5 reductions in PRD during 2013-2015 were estimated using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) software. To create reliable gridded PM_2.5 surfaces for BenMAP-CE calculations, a data fusion tool which incorporates the accuracy of monitoring data and the spatial coverage of predictions from the Community Multiscale Air Quality (CMAQ) model has been developed. The population-weighted average PM_2.5 concentration over PRD was predicted to decline by 24%. PM_2.5-related mortality was estimated to decrease by more than 3800 due to decreases in stroke (48%), ischemic heart disease (IHD) (35%), chronic obstructive pulmonary disease (COPD) (10%), and lung cancer (LC) (7%). A 13% reduction in PM_2.5-related premature deaths from these four causes yielded a large economic benefit of about 1300 million US dollars. Our research suggests that the Action Plan played a major role in reducing emissions and additional measures should be implemented to further reduce PM_2.5 pollution and protect public health in the future.

Analysis of the adverse health effects of PM2.5 from 2001 to 2017 in China and the role of urbanization in aggravating the health burden

In this study, the trend of PM_2.5 concentrations and its adverse health effects in China from 2001 to 2017 are estimated utilizing 1-km high-resolution annual satellite-retrieved PM_2.5 data. PM_2.5 concentrations for most of the provinces/cities remained stable from 2001 to 2012; however, following the issue of the Air Pollution Prevention and Control Action Plan (APPCAP) by the central government of China, a dramatic decrease in PM_2.5 concentrations from 2013 to 2017 occurred. Premature mortality caused by PM_2.5 dropped from 1,078,800 in 2014 to 962,900 in 2017. The PM_2.5 caused 17-year average mortality ranges from 3800 in Hainan Province to 124,800 in Henan Province. The health cost benefits gained by the reduction of PM_2.5 pollution amounted to US $193,800 in 2017 (compared to the costs due to PM_2.5 concentrations in 2013), amounting to 1.58% of the total national GDP. The impacts of urbanization on PM_2.5 concentration and mortality are analyzed. The PM_2.5 concentration and its induced mortality density in dense urban areas are much higher than those in rural areas. The aggravation of PM_2.5 associated premature mortality in urban areas is mainly due to the larger amount of emissions and to urban migration, and 6500 deaths in 2014 could have been avoided were the population ratios in dense-urban/normal-urban/rural areas to be reversed to the ones in 2001. It is recommended that people with respiratory-related diseases live in rural areas, where the pollutant concentration is relatively low.