Meteorological mechanism of regional PM2.5 transport building a receptor region for heavy air pollution over Central China

Abstract Background Positive associations between ambient PM2.5 and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM2.5 based on an entire population of a megalopolis. In addition, most studies in China have used averaged data, which results in variations between monitoring and personal exposure values, creating an inherent and unavoidable type of measurement error. Methods This study was conducted in Wuhan, a megacity in central China with about 10.9 million people. Daily hospital admission records, from October 2016 to December 2018, were obtained from the Wuhan Information center of Health and Family Planning, which administrates all hospitals in Wuhan. Daily air pollution concentrations and weather variables in Wuhan during the study period were collected. We developed a land use regression model (LUR) to assess individual PM2.5 exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposure to PM2.5. We also conducted stratification analyses by age, sex, and season. Results A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 cardiovascular disease admissions and 159,365 respiratory disease admissions. Short-term exposure to PM2.5 was associated with an increased risk of a cardiorespiratory hospital admission. A 10 μg/m3 increase in PM2.5 (lag0–2 days) was associated with an increase in hospital admissions of 1.23% (95% CI 1.01–1.45%) and 1.95% (95% CI 1.63–2.27%) for cardiovascular and respiratory diseases, respectively. The elderly were at higher PM-induced risk. The associations appeared to be more evident in the cold season than in the warm season. Conclusions This study contributes evidence of short-term effects of PM2.5 on cardiorespiratory hospital admissions, which may be helpful for air pollution control and disease prevention in Wuhan.

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How Did Distribution Patterns of Particulate Matter Air Pollution (PM2.5 and PM10) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17176274 ◽

2020 ◽

Vol 17 (17) ◽

pp. 6274 ◽

Cited By ~ 2

Author(s):

Zhiyu Fan ◽

Qingming Zhan ◽

Chen Yang ◽

Huimin Liu ◽

Meng Zhan

Keyword(s):

Air Pollution ◽

Regression Analysis ◽

Particulate Matter ◽

Socioeconomic Factors ◽

Influencing Factors ◽

Geographically Weighted Regression ◽

Meteorological Factors ◽

Central China ◽

Weighted Regression ◽

Pm2.5 And Pm10

Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM2.5 and PM10 during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis. Four meteorological factors and two socioeconomic factors, i.e., the decline of intra-city mobility intensity (dIMI) representing the effect of traffic mobility and the decline rates of the secondary industrial output values (drSIOV), were adopted in the regression analysis. Then, multi-scale geographically weighted regression (MGWR), a model allowing the particular processing scale for each independent variable, was applied for investigating the relationship between PM pollution reductions and influencing factors. For comparison, ordinary least square (OLS) regression and the classic geographically weighted regression (GWR) were also performed. The research found that there were 16% and 20% reduction of PM2.5 and PM10 concentration across China and significant PM pollution mitigation in central, east, and south regions of China. As for the regression analysis results, MGWR outperformed the other two models, with R2 of 0.711 and 0.732 for PM2.5 and PM10, respectively. The results of MGWR revealed that the two socioeconomic factors had more significant impacts than meteorological factors. It showed that the reduction of traffic mobility caused more relative declines of PM2.5 in east China (e.g., cities in Jiangsu), while it caused more relative declines of PM10 in central China (e.g., cities in Henan). The reduction of industrial operation had a strong relationship with the PM10 drop in northeast China. The results are crucial for understanding how the decline pattern of PM pollution varied spatially during the COVID-19 outbreak, and it also provides a good reference for air pollution control in the future.

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Comparison of emissions inventories of anthropogenic air pollutants and greenhouse gases in China

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-6393-2017 ◽

2017 ◽

Vol 17 (10) ◽

pp. 6393-6421 ◽

Cited By ~ 48

Author(s):

Eri Saikawa ◽

Hankyul Kim ◽

Min Zhong ◽

Alexander Avramov ◽

Yu Zhao ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Emission Inventory ◽

Air Pollutant ◽

Central China ◽

Pollutant Emissions ◽

Mitigation Measures ◽

Economic Activities ◽

Temporal And Spatial Distribution ◽

Emissions Inventories

Abstract. Anthropogenic air pollutant emissions have been increasing rapidly in China, leading to worsening air quality. Modelers use emissions inventories to represent the temporal and spatial distribution of these emissions needed to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates. Thus, assessing differences in these inventories is essential for the better understanding of air pollution over China. We compare five different emissions inventories estimating emissions of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter of 10 µm or less (PM10) from China. The emissions inventories analyzed in this paper include the Regional Emission inventory in ASia v2.1 (REAS), the Multi-resolution Emission Inventory for China (MEIC), the Emission Database for Global Atmospheric Research v4.2 (EDGAR), the inventory by Yu Zhao (ZHAO), and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008, during which Chinese economic activities more than doubled. In addition to national totals, we also analyzed emissions from four source sectors (industry, transport, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements exist among the five inventories at disaggregated levels. These disagreements lead to differences of 67 µg m−3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modeled regional concentrations in China. We also find that all the inventory emissions estimates create a volatile organic compound (VOC)-limited environment and MEIC emissions lead to much lower O3 mixing ratio in East and Central China compared to the simulations using REAS and EDGAR estimates, due to their low VOC emissions. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding effective mitigation measures for reducing national and regional air pollution in China.

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Effect of Ambient Fine Particulate (PM2.5) on Hospital Admissions for Respiratory and Cardiovascular Diseases in Wuhan, China

10.21203/rs.3.rs-117251/v1 ◽

2020 ◽

Author(s):

Zhan Ren ◽

Xingyuan Liu ◽

Tianyu Liu ◽

Dieyi Chen ◽

Kuizhuang Jiao ◽

...

Keyword(s):

Air Pollution ◽

Cardiovascular Diseases ◽

Hospital Admission ◽

Respiratory Diseases ◽

Hospital Admissions ◽

Conditional Logistic Regression ◽

Central China ◽

Air Pollution Control ◽

Short Term ◽

Increased Risk

Abstract Background: The positive associations between ambient PM2.5 and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM2.5 based on an entire population of megalopolis. In addition, due to the lack of accurate methods of assessing individual PM2.5 exposure, further studies are still necessary to be launched in China.Methods: The study was conducted in Wuhan, a megacity in central China with about 10.8929 million population. Daily hospital admission records, from October 2016 to December 2018, were obtained from Wuhan Information center of Health and Family Planning, which administrates all the hospitals in Wuhan. The daily air pollution concentration and weather variable in Wuhan during the study period were collected. We developed Land use regression model (LUR) to assess individual PM2.5 exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposures to PM2.5. We also conducted stratification analyses by age, sex and season.Results: A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 for total cardiovascular diseases and 159,365 for total respiratory diseases. We found short-term PM2.5 exposure was associated with increased risk of cardiorespiratory hospital admission in Wuhan. Per 10 μg/m3 increase of PM2.5 at lag0~2 days was associated with 1.23% (95%CI: 1.01–1.45%) and 1.95% (95%CI: 1.63–2.27%) elevated risk of admission from cardiovascular and respiratory diseases respectively. The elderly were at higher PM-induced risks. The associations appeared to be more evident in the cold season than in the warm season.Conclusions: This study contributed evidence to support the short-term effects of PM2.5 on cardiorespiratory hospital admission, which may be helpful for air pollution control and disease prevention in Wuhan.

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Acute Effects of Air Pollution on Ischemic Heart Disease Hospitalizations: A Population-Based Time-Series Study in Wuhan, China, 2017–2018

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182312527 ◽

2021 ◽

Vol 18 (23) ◽

pp. 12527

Author(s):

Wanglin Xu ◽

Xingyuan Liu ◽

Zenghui Huang ◽

Yating Du ◽

Biao Zhang ◽

...

Keyword(s):

Air Pollution ◽

Time Series ◽

Heart Disease ◽

Ischemic Heart Disease ◽

Air Pollutants ◽

Central China ◽

Ischemic Heart ◽

Acute Effects ◽

Time Series Study ◽

Series Study

Evidence of the acute effects of air pollutants on ischemic heart disease (IHD) hospitalizations based on the entire population of a megacity in central China is lacking. All IHD hospitalization records from 2017 to 2018 were obtained from the Wuhan Information Center of Health and Family Planning. Daily air pollutant concentrations and meteorological data were synchronously collected from the Wuhan Environmental Protection Bureau. A time-series study using generalized additive models was conducted to systematically examine the associations between air pollutants and IHD hospitalizations. Stratified analyses by gender, age, season, hypertension, diabetes, and hyperlipidemia were performed. In total, 139,616 IHD hospitalizations were included. Short-term exposure to air pollutants was positively associated with IHD hospitalizations. The age group ≥76 was at higher exposure risk, and the associations appeared to be more evident in cold seasons. PM2.5 and PM10 appeared to have greater effects on males and those without hypertension or diabetes, whereas NO2 and SO2 had greater effects on females and those with hypertension or diabetes. The risk of IHD hospitalization due to air pollutants was greater in people without hyperlipidemia. Our study provides new evidence of the effects of air pollution on the increased incidence of IHD in central China.

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