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沈阳市冬季环境空气质量统计预报模型建立及应用

         

摘要

In this paper, the automatic monitoring atmosphere data and meteorological data of Shenyang city in 1-2 month in 2013 were used, and 19 predictors were selected, then Shenyang city winter air quality of the environment statistical forecast model were established by stepwise regression method. The forecast projects included fine particulate matter ( PM2�5 ) , inhalable particulate matter ( PM10 ) , sulfur dioxide ( SO2 ) , nitrogen dioxide ( NO2 ) , carbon monoxide ( CO) daily average concentration and maximum 8 hours average concentration of ozone ( O3 ) . Using the above model and the revision of experience, Shenyang city environmental air quality forecast were processed from November 2013 to January 2014. The results of comparing between the prediction results and measured shows that the rate of the air environment prediction level accuracy reached 79�1%, and the primary pollutant accuracy is 73�6%.%利用沈阳市2013年1-2月大气自动监测数据和同期气象资料,选取19项预报因子,采用逐步回归方法建立了沈阳市冬季环境空气质量统计预报模型,预报项目包括细颗粒物( PM2�5)、可吸入颗粒物( PM10)、二氧化硫( SO2)、二氧化氮( NO2)、一氧化碳( CO)日均浓度及臭氧( O3)日最大8 h平均浓度。2013年11月至2014年1月,应用该模型并结合人为经验修订,开展了沈阳市环境空气质量预报工作,预报结果与实测结果的对比验证结果表明,环境空气预测结果级别准确率达到79�1%,首要污染物准确率为73�6%。

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