多尺度气象条件对济南PM2.5污染的影响  

The Impact of Multi-Scale Meteorological Conditions on PM2.5 Pollution over Ji’nan

作　　者：尹承美[1] 何建军[2] 于丽娟 焦洋[1] 周乐晨 YIN Chengmei;HE Jianjun;YU Lijuan;JIAO Yang;ZHOU Lechen(Ji'nan Meteorological Bureau of Shandong Province,Ji'nan 250102,Shandong,China;State Key Laboratory of Severe Weather&Key Laboratory of Atmospheric Chemistry of China Meteorological Administration,Chinese Academy of Meteorological Sciences,Beijing 100081,China;Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China)

机构地区：[1]济南市气象局,山东济南250102 [2]中国气象科学研究院灾害天气国家重点实验室/中国气象局大气化学重点开放实验室,北京100081 [3]中国科学院大气物理研究所,北京100029

出　　处：《高原气象》2019年第5期1120-1128,共9页Plateau Meteorology

基　　金：国家自然科学基金项目(41705080);济南市科技局社会民生重大专项(201704137);中国气象局预报员专项(CMAYBY2019-063);山东省气象局重点课题(2016sdqxz05)

摘　　要：长时间序列空气质量数据和气象数据分析济南大气污染与气象条件关系的研究相对较少。利用2010-2016年济南市环境空气质量监测数据、气象再分析和观测数据,分析了济南市PM2.5污染特征、PM2.5浓度与2 m温度(T)、2 m相对湿度(RH)、10 m高度U和V风速(U和V)、10 m风速(WS)、K指数(K)、A指数(A)和边界层高度(BLH)的相关性、天气类型对PM2.5浓度的影响,并基于逐步回归分析方法构建统计模型,利用解释方差量化气象条件对PM2.5浓度变化的影响。分析发现,济南PM2.5浓度存在显著的季节变化和年际变化特征,年均PM2.5浓度呈下降趋势;近地面PM2.5浓度与T、RH、K和A显著正相关,与WS和BLH显著负相关,U和V与PM2.5浓度相关性不显著(p<0.05);不同天气类型对应的PM2.5浓度均值存在显著差异;基于回归模型分析发现气象条件可以解释10%~40%的PM2.5浓度逐日变化,气象条件的影响有明显的季节变化。Based on long-term air quality and meteorological data,the analysis of the relationship between air pollution and meteorological conditions over Ji'nan is relatively rare.Using air quality monitoring data,meteorological reanalysis data,and meteorological observation data in Ji'nan City from 2010 to 2016,this paper analyzes PM2.5 pollution characteristics,the relation between PM2.5 concentration and 2-m temperature(T),2-m relative humidity(RH),10-m U and V component of wind speed(U and V),10-m wind speed(WS),K index(K),A index(A)and boundary layer height(BLH),and circulation types.Based on the stepwise regression model,the influence of meteorological conditions on the day-to-day variation of PM2.5 concentration was quantified by explained variance.The results recover that there are a significant seasonal and interannual variations in PM2.5 concentration in Ji'nan.The annual average PM2.5 concentration decreases significantly during 2010 to 2016.PM2.5 concentration is positive correlated with T,RH,K and A significantly,while negative correlated with WS and BLH(p<0.05).The correlations between PM2.5 concentration and U and V component do not pass t-test at 95%confidence interval.The mean PM2.5 concentrations for different circulation types have significant difference.Based on regression model analysis,it is found that meteorological conditions can explain the day-to-day variation of PM2.5 concentration from 10%to 40%in Ji'nan.Obvious seasonal difference of impact of meteorological conditions is detected.

关 键 词：济南 PM2.5 相关分析 多元回归 气象条件 

分 类 号：P401[天文地球—大气物理学与大气环境]