PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China.
PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China.
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DOI：
10.1371/journal.pone.0141642
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Guo X
中科院分区：
文献类型：
--
作者：
Huang F;Li X;Wang C;Xu Q;Wang W;Luo Y;Tao L;Gao Q;Guo J;Chen S;Cao K;Liu L;Gao N;Liu X;Yang K;Yan A;Guo X
关于北京地区空气动力学中值直径和2.5μm(PM2.5)的高分辨率粒子的时空变化及其与气象因素的关系的信息有限，中国。本研究旨在检测2013年8月至2014年7月北京地区PM2.5的时空变化规律，并探讨PM2.5与气象因子的关系。对北京市环保局(BJEPB)的PM2.5逐日和逐时数据进行了分析。用普通克立格(OK)插值法、时间序列图、Spearman相关系数和散度系数(COD)来描述PM2.5的时空变化。使用Kruskal-Wallis H检验、Bonferroni修正和Mann-Whitney U检验来评估PM2.5水平与季节、地区、白天和星期几等时空因素的差异。利用广义加性混合模型(GAMM)分析了PM2.5日变化与气象要素的关系。2013年8月至2014年7月，PM2.5年平均值为88.07μg/m~3，中位数为71.00μg/m~3。PM2.5浓度在冬季(P<；0.0083)和城市南部(P<；0.0167)明显较高。PM2.5日变化呈长期波动趋势，每个月有2-6个峰值。PM2.5浓度夜间显著高于白天(P<；0.0167)。气象因素与PM2.5日浓度的GAMM模型相关(R2=0.5 9，AIC=7373.84)。北京PM2.5污染具有很强的时空变异性。气象因素对PM2.5浓度的影响具有一定的规律。总体而言，前日风速、日照时数和降水量与PM2.5呈负相关，而前三天的相对湿度和气压与PM2.5呈正相关。
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. 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). 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 (R 2 = 0.59, AIC = 7373.84). 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.