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DOI: 10.1371/journal.pone.0141642
论文题名:
PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China
作者: Fangfang Huang; Xia Li; Chao Wang; Qin Xu; Wei Wang; Yanxia Luo; Lixin Tao; Qi Gao; Jin Guo; Sipeng Chen; Kai Cao; Long Liu; Ni Gao; Xiangtong Liu; Kun Yang; Aoshuang Yan; Xiuhua Guo
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2015
发表日期: 2015-11-3
卷: 10, 期:11
英文关键词: Air pollution ; Meteorology ; Wind ; Humidity ; Sunlight ; Winter ; Seasonal variations ; Seasons
英文摘要: Objective Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM2.5 and meteorological factors. Methods Daily and hourly PM2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM). Results Annual mean and median of PM2.5 concentrations were 88.07 μg/m3 and 71.00 μg/m3, respectively, from August 2013 to July 2014. PM2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM2.5 concentration using the GAMM model (R2 = 0.59, AIC = 7373.84). Conclusion PM2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM2.5.
URL: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141642
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/14516
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China

Recommended Citation:
Fangfang Huang,Xia Li,Chao Wang,et al. PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China[J]. PLOS ONE,2015-01-01,10(11)
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