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The pattern and mechanism of air pollution in developed coastal areas of China: From the perspective of urban agglomeration
- Source :
- PLoS ONE, Vol 15, Iss 9, p e0237863 (2020), PLoS ONE
- Publication Year :
- 2020
- Publisher :
- Public Library of Science (PLoS), 2020.
-
Abstract
- The green development of coastal urban agglomerations, which are strategic core areas of national economic growth in China, has become a major focus of both academics and government agencies. In this paper, China's coastal urban agglomeration is taken as the research area, aiming at the serious air pollution problem of coastal urban agglomeration, geographic information system (ArcGIS10.2) spatial analysis and the spatial Dubin model were applied to National Aeronautics and Space Administration atmospheric remote sensing image inversion fine particulate matter (PM2.5) data from 2010-2016 to reveal the temporal and spatial evolution characteristics and Influence mechanism of PM2.5 in China's coastal urban agglomerations, with a view to providing a reference value for coordinating air pollution in the coastal cities of the world. From 2010-2016, the PM2.5 concentration in China's coastal urban agglomerations decreased as a whole, and large spatial differences in PM2.5 concentration were observed in China's coastal urban agglomerations; the core high-pollution areas were the Beijing-Tianjin-Hebei, Shandong Peninsula, and Yangtze River Delta urban agglomerations. Large spatial differences in PM2.5 concentration were also observed within individual urban agglomerations, with higher PM2.5 concentrations found in the northern parts of the urban agglomerations. Significant spatial autocorrelation and spatial heterogeneity were observed among PM2.5-polluted cities in China's coastal urban agglomerations. The northern coastal urban agglomerations formed a relatively stable and continuous high-pollution zone. The spatial Dubin model was used to analyze the driving factors of PM2.5 pollution in coastal urban agglomerations. Together, meteorological, socioeconomic, pollution source, and ecological factors affected the spatial characteristics of PM2.5 pollution during the study period, and the overall effect was a mixed effect with significant spatial variation. Among them, meteorological factors were the greatest driver of PM2.5 pollution. In the short term, the rapid increase in population density, industrial emissions, industrial energy consumption, and total traffic emissions were the important driving factors of PM2.5 pollution in the coastal urban agglomerations of China.
- Subjects :
- Time Factors
010504 meteorology & atmospheric sciences
Air pollution
Social Sciences
010501 environmental sciences
medicine.disease_cause
01 natural sciences
Urban Environments
Geographical Locations
Environmental protection
media_common
Air Pollutants
Multidisciplinary
Ecology
Geography
Pollution
Terrestrial Environments
Spatial heterogeneity
Urban ecology
Delta Ecosystems
Medicine
Palestinian Territories
Algorithms
Research Article
China
Asia
Urban agglomeration
media_common.quotation_subject
Gross Domestic Product
Science
Human Geography
Ecosystems
Wetland Ecosystems
Urban Geography
Urbanization
Air Pollution
medicine
Urban Ecology
Cities
Particle Size
Ecosystem
0105 earth and related environmental sciences
Driving factors
Ecology and Environmental Sciences
Water Pollution
Biology and Life Sciences
Models, Theoretical
People and Places
Earth Sciences
Geographic Information Systems
Environmental science
Spatial variability
Particulate Matter
Factor Analysis, Statistical
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 15
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....93b855af96fd1d8df197ee29f6b656b1