摘要
基于通用多尺度空气质量模型The Weather Research and Forecasting model coupled with CMAQ(WRF-CMAQ)对常州市2018年6~12月的空气质量预报结果,结合实况资料,进行了预报效果评估,以期为常州市空气质量的预报提供更好的参考。结果表明:(1)模式对常州市各预报时效空气质量指数(AQI)和各污染物浓度的标准化平均偏差(MFB)和标准化分数误差(MFE)均处于“理想水平”范围,能较好的反映实际空气质量变化趋势。(2)当空气质量为优良时,AQI和空气质量等级(AQI等级)预报效果最好,当空气质量达中度及以上污染时,预报效果最差,应进一步优化调整。(3)模式对首要污染物24小时预报准确率为66.9%,当空气质量为轻度污染及以上级别时,预报准确率较高。(4)模式对AQI的预报总体存在负偏差,对细颗粒物(PM 2.5)浓度的模拟结果较好,对臭氧(O 3)和可吸入颗粒物(PM 10)存在低估现象,对二氧化硫(SO 2)、二氧化氮(NO 2)和一氧化碳(CO)等3项污染物浓度均有所高估。
Based on the air quality forecast in Changzhou City from June to December,2018 By Community Multiscale Air Quality model(WRF-CMAQ),combing with corresponding actual data,the forecast results of air quality were evaluated to provide better reference for air quality forecast in Changzhou City.The results showed that:1)The mean fractional bias(MFB)and mean fractional error(MFE)of air quality index(AQI)and each pollutant concentration in different forecast time periods in Changzhou were all in the"ideal level"range,which can better reflect the changing trend of actual air quality.2)When the air quality was excellent and good,the AQI and AQI grads forecasting effect were best and when the air quality was moderate pollution or above,the forecasting effect was the worst.So,further optimization and adjustment should be made.3)The 24-hour prediction accuracy of the model for primary pollutants was 66.9%,when the air quality was light pollution or above,the forecasting accuracy was high.4)Overall,the deviations of AQI prediction and measurement were all negative,the simulation results of fine particulate matter(PM 2.5)concentration were good,ozone(O 3)and inhalable particulate matter(PM 10)were underestimated,and the concentration of sulfur dioxide(SO 2),nitrogen dioxide(NO 2)and carbon monoxide(CO)were overestimated.
作者
杨卫芬
夏京
赵亚芳
江飞
唐志鑫
YANG Wei-fen;XIA Jing;ZHAO Ya-fang;JIANG Fei;TANG Zhi-xin(Changzhou Environmental Monitoring Center of Jiangsu Province,Changzhou,Jiangsu 213001,China;International Institute for Earth System Science,Nanjing University,Nanjing 210046,China;Nanjing Chuanglan Technology co. LTD,Nanjing 210008,China)
出处
《四川环境》
2019年第5期119-125,共7页
Sichuan Environment
