Air pollution and its influential factors in China's hot spots

Yuan

Science of The Total Environment

et al. 2020

250

201

Section: Air Quality During the Control Of Covid-19mentioning

confidence: 94%

Changes in air quality related to the control of coronavirus in China: Implications for traffic and industrial emissions

Yuan

Science of The Total Environment

et al. 2020

250

201

Advances in Meteorology

“…e problem of air pollution has drawn much attention in recent decades with rapid development of economy and urbanization, especially in developing countries [1]. In China, particulate matter (PM) pollution has become the major air pollutant throughout the year [2].…”

Section: Introductionmentioning

confidence: 99%

PM_2.5/PM₁₀ Ratios in Eight Economic Regions and Their Relationship with Meteorology in China

Zhao

Chen

et al. 2019

Self Cite

China is suffering severe ambient air pollution in recent decades and particulate matter (PM) has become the major pollutant, especially for PM2.5 and PM10, which have highly raised scholars and policy-makers’ attention in last few years. The existing research has focused on the characteristics of PM2.5 and PM10, respectively, or analyzed the correlation between the two pollutants, while the ratio of PM2.5 to PM10 has been taken less consideration. In this study, daily mean PM2.5 and PM10 mass concentrations in 31 provincial capitals from 2014 to 2016 were used to present the temporal variations and spatial distribution of PM2.5/PM10 ratios among eight economic regions. And then, statistical method and correlation analysis were adopted to investigate the relationship between the ratios and AQI, the rate of change on the ratios, and the impact of meteorological parameters on the ratios. The results indicated that PM2.5/PM10 ratios showed an increasing trend from northwest to southeast due to different economic development and industrial types. The highest values were observed in winter among all regions, and the ratios on weekends were higher than that of on weekdays in most of the regions. Besides, domestic heating in northern China had a significant contribution to the ratios. Moreover, ratios had less changes, and the rate of change was stable in summer. As for air quality, the higher the ratio, the larger the possibility of high AQI so that the air pollution will be more severe. In terms of meteorological factors, the results demonstrated that relative humidity, precipitation, and pressure were the most important factors and had significantly positive impacts, while sunshine duration, temperature, and wind speed had negative effects on the ratios. The findings could identify the pollution sources among PM10 and be helpful for making regulation locally to reduce emission which considers anthropogenic sources and meteorological diffusion simultaneously.

“…The coefficient of spatial autocorrelation r is statistically positive, thereby confirming a positive spatial correlation of SO 2 emissions among provinces in China. Zhao, Chen [37] used spatial panel data to explore temporal trends and spatial differences in air pollution and the impacts of macro influential factors on four pollutants in five hot spots in China. The results indicated that gross domestic product (GDP) and private cars were significant positive factors for PM 2.5 , and the contribution of energy consumption was also significant.…”

Section: Introductionmentioning

confidence: 99%

The Spatial and Temporal Research on the Coupling and Coordinated Relationship between Social Economy and Energy Environment in the Belt and Road Initiatives

et al. 2019

The Belt and Road Initiative (BRI) was presented by China’s central government to achieve regional economic cooperation under the background of economic globalization. Energy and environmental problems, as by-products of economic success, are fundamental concerns in this grand project. An integrated method that combined the coupling coordinated degree model, Moran’s I, and the spatial panel data model was used in the research zone. Results of the coupling coordinated degree model indicated that the statuses of the social economy and the energy environment of the countries in the research zone improved from 1997 to 2014, with the changes in China and Eastern Europe being particularly significant. From the spatial econometric perspective, the coupling coordinated degrees of the countries in the research zone appeared in the spatial cluster in accordance with Moran’s I. The result of the spatial panel data model indicated that the coupling coordinated degree of one country positively affected those of its neighboring countries.