摘要
对2022年9月—2023年7月泰州市细颗粒物(PM_(2.5))和臭氧(O_(3))利用SUST-WRFChem模式进行定量预报研究工作。结果表明:污染过程整体预报准确率达70.4%,在PM_(2.5)日均浓度小于115μg/m^(3)、O_(3)-8h浓度小于215μg/m^(3)时,污染物浓度分级预报精准,污染物浓度预报准确率分别为80%、81%;从季节预报来看,PM_(2.5)夏季预报效果最优;从O_(3)-8h来看,春季、夏季、秋季预报效果较好。综合来看,利用本地化SUST-WRF-Chem模式进行定量预报,可对大气污染起到有效的预警作用。
Quantitative forecasting of fine particulate matters(PM_(2.5))and ozone(O_(3))in Taizhou City from September 2022 to July 2023 were carried out using the SUST-WRF Chem model.The results showed that the overall prediction accuracy during air pollution period reached 70.4%.When the daily average concentration of PM_(2.5)was less than 115μg/m^(3)and the concentration of O_(3)-8h was less than 215μg/m^(3),the prediction of pollutants concentration could be classified as Accurate,with accuracy of 80%and 81%,respectively.As concerned as seasonal forecasting,the summer prediction of PM_(2.5)was the most accurate,while the predictions of O_(3)-8h in spring,summer and autumn exhibited satisfactory results.Overall,the localized SUST-WRF Chem model could be exploited for quantitative forecasting and plays an important role in preventing and controlling air pollution,as well as reducing pollutant concentrations.
作者
王玉祥
彭婷
吴莹
程滢
杨文武
WANG Yu-xiang;PENG Ting;WU Ying;CHENG Ying;YANG Wen-wu(Taizhou Environmental Monitoring Center of Jiangsu Province,Taizhou Jiangsu 225300,China)
出处
《中国环保产业》
2024年第12期42-45,共4页
China Environmental Protection Industry
基金
2022年泰州市科技支撑计划(社会发展)项目(TS202230)。
关键词
细颗粒物
臭氧
定量预报
fine particulate matters
ozone
quantitative forecasting
