基于数值模拟与资料同化探究长三角地区冬季PM_(2.5)污染过程的气象影响  

The influence of meteorological parameters on particulate matter in the Yangtze River Delta Region based on numerical simulation and data assimilation

作　　者：熊一帆 丁秋冀 舒卓智[1,2] 刘玉宝 赵天良 XIONG Yifan;DING Qiuji;SHU Zhuozhi;LIU Yubao;ZHAO Tianliang(School of Atmospheric Physics,Nanjing University of Information Science and Technology,Nanjing 210044;Precision Regional Earth Modeling and Information Center,Nanjing University of Information Science and Technology,Nanjing 210044)

机构地区：[1]南京信息工程大学大气物理学院,南京210044 [2]南京信息工程大学精细化区域地球模拟和信息中心,南京210044

出　　处：《环境科学学报》2022年第4期293-303,共11页Acta Scientiae Circumstantiae

基　　金：中国气象局西北人工影响天气工程能力建设项目(No.ZQC-R19081,ZQC-R19176)。

摘　　要：细颗粒物(PM_(2.5))累积主导着长三角地区冬季空气污染,其中,气象要素具有重要的作用.本文结合WRF-Chem模式和WRF-FDDA技术,针对2019年1月12—16日发生在长三角地区的一次典型PM_(2.5)污染过程进行数值模拟分析.通过敏感性试验,量化分析地面气象因素(温度、风速、相对湿度)对该地区PM_(2.5)浓度的影响,并利用对自动气象站观测资料的四维资料同化试验,探究气象场改进对PM_(2.5)模拟的改善.模拟结果表明,长三角地区PM_(2.5)污染受气象条件影响程度较为显著,PM_(2.5)浓度与风速和温度呈显著负相关,与相对湿度呈正相关.水平风速减少40%、温度增加3℃、相对湿度增加20%分别造成了+4.68%、-2.82%与+2.2%的PM_(2.5)浓度变化.而同化气象资料显著地改善了模拟的气象场精度,其均方根误差(RMSE)统计项中相对湿度减小9.68%,温度减小1.02℃,风速减小0.35 m·s^(-1),这也使得PM_(2.5)浓度的模拟效果有所改善,其中,模拟与观测PM_(2.5)浓度的相关系数提高了0.11,RMSE减小9.17μg·m^(-3).气象要素变化对大气污染物影响的量化研究,以及资料同化对PM_(2.5)模拟的改进,可促进大气污染的预报水平和有效控制.Accumulation of fine particulate matter(PM_(2.5)) is responsible to winter air pollution in the Yangtze River Delta(YRD)region and meteorological factors play an important role.In this study,the chemistry version of the Weather Research and Forecasting model(WRF-Chem)and the four-dimensional data assimilation(WRF-FDDA)scheme were employed to simulate a typical heavy pollution event occurred in the YRD region from January 12 to 16,2019.The impact of near-surface temperature,wind speed,and relative humidity disturbances on the surface PM_(2.5) was analyzed by carrying out a series of sensitivity experiments.A four-dimensional data assimilation experiment with WRF-FDDA that assimilates automatic weather station observation data was also conducted to demonstrate the improvements of the meteorological field modeling as well as that of PM_(2.5) concentration by the data assimilation process.The results show that in the YRD region,the PM_(2.5) concentration has a negative correlation with wind speed and temperature,but a positive correlation with relative humidity.In the three sensitivity experiments with horizontal wind speed is decreased by 40%,temperature is increased by 3 ℃,and relative humidity is increased by 20% respectively,the corresponding PM_(2.5) concentrations were affected by +4.68%,-2.82%,and +2.2%.By assimilating meteorological observations,the accuracy of the meteorological simulation is significantly improved.The root mean square error(RMSE)of relative humidity,temperature and wind speed decreases by 9.68%,1.02 ℃,and 0.35m·s^(-1),respectively.The correlation coefficient between the observed and simulated PM_(2.5) increased by 0.11 and RMSE decreased by 9.17 μg·m^(-3).These results are valuable to further improve the forecast accuracy and support effective control of air pollution in the YRD region.

关 键 词：PM_(2.5)WRF-Chem 气象因子 长三角地区 四维资料同化(FDDA) 

分 类 号：X51[环境科学与工程—环境工程] X16