汾渭平原CUACE模式空气质量预报性能的检验订正及环境评估

利用2019年1—6月地面环境监测资料和PM_2.5气象条件评估指数，结合滚动偏差订正方法，对汾渭平原CUACE空气质量预报产品进行了检验订正，并对气象条件和污染减排影响进行了评估。结果表明：CUACE模式对空气质量指数(AQI)、PM_2.5和SO₂浓度预报值较接近观测值，PM₁₀、CO和NO₂预报值小于观测值，O₃预报值大于观测值；对首要污染物O₃和PM_2.5及重度和严重等级污染的预报的TS评分最高，漏报率和空报率最小，预报偏差最接近1；滚动偏差订正方法对改善CUACE空气质量预报效果较为明显，尤其是对PM₁₀、O₃和NO₂改善最为明显；汾渭平原2019年上半年气象条件变化使PM_2.5浓度较2018年同期和过去5年同期分别上升了18.26%和11.18%，减排措施使PM_2.5浓度较2018年同期和过去5年...

Verification and correction of air quality forecasting products and environmental assessment aiming for CUACE model in Fenwei Plain

In Fenwei Plain the air quality prediction products of CUACE were verified and corrected and the impacts of meteorological conditions and pollution reduction were evaluated by using the ground environmental monitoring data and the evaluation on meteorological condition index of PM2.5 pollution (EMI) from January to June 2019 and the rolling error correction method. The results show that the air quality index (AQI), PM2.5 and SO2 concentrations predicted by CUACE model are closer to the observed values, the predicted PM10, CO and NO2 are smaller than the observed values, and the predicted O3 are larger than the observed values. For the O3 and PM2.5 primary pollutants, as well as the serious and heavy grade pollutions, the TS scores are the highest, the point overs and false alarm ratios are the smallest, and the forecast biases are closest to 1. The effect of rolling error correction method on CUACE air quality prediction is obvious, especially for PM10, O3 and NO2. In the first half of 2019, the changes of meteorological conditions increase PM2.5 concentrations by 18.26 % and 11.18 % respectively and the emission reduction measures make PM2.5 concentrations decrease by 14.23 % and 20.29 % respectively compared with the same period in 2018 and the past five years over Fenwei Plain.