【摘 要】
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Objective:Limitedinformation is available regarding spatial-temporal variation of PM2.5 with high resolutions and its relationships with meteorological factors in Beijing, China.This study aimed to de
【机 构】
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School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laborator
【出 处】
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首都医科大学公共卫生学院第四届研究生学术论坛
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Objective:Limitedinformation is available regarding spatial-temporal variation of PM2.5 with high resolutions and its relationships with meteorological factors in Beijing, China.This study aimed to detect the spatial and temporal change patterns of PM2.5 from August 2013 to July 2014, and to assess the relationship between PM2.5 and meteorological factors in Beijing.Methods:Daily and hourly PM2.5data from Beijing Environmental Protection Bureau(BJEPB) were analyzed separately.Ordinary Kriging (OK) interpolation, heatmap and line figure were used to describe the spatial and temporal variations of PM2.5.Mann-Whitney U test was used to test the seasonal and regional differences.Daily meteorological variables (daily mean wind speed (m/s), relative humidity (%), sunlight hours (h), temperature (℃), precipitation (mm)and air pressure (kPa)) were obtained from Chinese Meteorological Bureau (CMB).The relationships between daily PM2.5 and meteorological variables were analyzed using generalized additive mixed model (GAMM).Results:Annual mean and median PM2.5concentration was88.07μg/m3 and 71.00ug/m3 respectively from August 2013 to July 2014.Concentration of PM2.5was significantly higher inwinter (P<0.001) and lower in summer(P<0.001), and significantly higher in south part than in north (P<0.001).Daily variation of PM2.5 concentrationshowedthe long-term trend of fluctuationswith almost 4-6 peaks each month.There were always two concentration peaks during one day (at noon and in the midnight).Meteorological factors were associatedwith daily PM2.5 concentration from GAMM model (R2=0.59, AIC=7373.84).Conclusion: PM2.5 pollution in Beijing showed great spatial-temporal variations.Meteorological factors influenced the PM2.510concentration in certain patterns.
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