DOI: 10.1016/j.atmosenv.2018.01.053
Scopus记录号: 2-s2.0-85041423082
论文题名: Spatiotemporal variation of PM1 pollution in China
作者: Chen G ; , Morawska L ; , Zhang W ; , Li S ; , Cao W ; , Ren H ; , Wang B ; , Wang H ; , Knibbs L ; D ; , Williams G ; , Guo J ; , Guo Y
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2018
卷: 178 起始页码: 198
结束页码: 205
语种: 英语
英文关键词: China
; Meteorological conditions
; PM1
; PM1/PM2.5 ratio
; PM2.5
Scopus关键词: Air pollution
; Meteorology
; Tectonics
; China
; Generalized additive model
; Meteorological condition
; Meteorological parameters
; PM1/PM2.5 ratio
; PM2.5
; Spatial and temporal distribution
; Spatio-temporal variation
; Pollution
; atmospheric pollution
; concentration (composition)
; particle size
; particulate matter
; public health
; seasonal variation
; spatial distribution
; spatiotemporal analysis
; temporal distribution
; air monitoring
; air pollutant
; air pollution
; airborne particle
; Article
; China
; concentration (parameters)
; meteorology
; model
; particle size
; pollution monitoring
; priority journal
; seasonal variation
; summer
; winter
; China
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: Understanding spatiotemporal variation of PM1 (mass concentrations of particles with aerodynamic diameter < 1 μm) is important due to its adverse effects on health, which is potentially more severe for its deeper penetrating capability into human bodies compared with larger particles. This study aimed to quantify the spatial and temporal distribution of PM1 across China as well as its ratio with PM2.5 (<2.5 μm) and relationships with meteorological parameters in order to deepen our knowledge of the drivers of air pollution in China. Ground-based monitoring PM1 and PM2.5 measurements, along with collocated meteorological data, were obtained from 96 stations in China for the period from November 2013 to December 2014. Generalized additive models were employed to examine the relationships between PM1 and meteorological parameters. We showed that PM1 concentrations were the lowest in summer and the highest in winter. Across China, the PM1/PM2.5 ratios ranged from 0.75–0.88, reaching higher levels in January and lower in August. For spatial distribution, higher PM1/PM2.5 ratios (>0.9) were observed in North-Eastern China, North China Plain, coastal areas of Eastern China and Sichuan Basin while lower ratios (<0.7) were present in remote areas in North-Western and Northern China (e.g., Xinjiang, Tibet and Inner Mongolia). Higher PM1/PM2.5 ratios were observed on heavily polluted days and lower ratios on clean days. The high PM1/PM2.5 ratios observed in China suggest that smaller particles, PM1 fraction, are key drivers of air pollution, and that they effectively account for the majority of PM2.5 concentrations. This emphasised the role of combustion process and secondary particle formation, the sources of PM1, and the significance of controlling them. Smaller particles, PM1 fraction, are key drivers of air pollution in China accounting for the majority of PM2.5 concentrations. © 2018 Elsevier Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/82956
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; International Laboratory for Air Quality and Health, Queensland University of Technology, Gardens Point, Brisbane, Australia; Center for Disease Surveillance & Research, Institute of Disease Control and Prevention of PLA, Beijing, China; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; Institute for Environmental and Climate Research, Jinan University, Guangzhou, China; Air Quality Studies, Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong, Hong Kong; Department of Epidemiology and Biostatistics, School of Public Health, The University of Queensland, Brisbane, Australia; Sate Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
Recommended Citation:
Chen G,, Morawska L,, Zhang W,et al. Spatiotemporal variation of PM1 pollution in China[J]. Atmospheric Environment,2018-01-01,178