摘要
利用拉萨市地面气象观测资料、高空观测和数值天气预报产品,挑选了与空气污染物扩散有关的42个气象因子,进行标准化处理后,基于逐步回归方法利用拉萨市区2008—2012年3种主要空气污染物SO2、NO2和PM10日平均浓度建立不同季节的污染物浓度回归方程,并对宗教活动和节庆假日的焚香、焰火等人类活动作订正得出污染物浓度预报结果。利用2013年的数据作试报表明该预报方法的效果较好：SO2平均绝对误差为0.001~0.0022 mg/m^3,平均相对误差在15.3%~27.0%之间;NO2平均绝对误差为0.003~0.005 mg/m^3,平均相对误差在17.2%~27.5%之间;PM10平均绝对误差为0.006~0.019 mg/m^3,平均相对误差在16.6%~28.6%之间,空气污染指数（API）预报准确率在78.2%~87.8%之间。该预报方法能够满足拉萨市空气污染物浓度预报的需要。
Using meteorological observations, upper- air observations and numerical weather predictionproducts from 2008 to 2012 in Lhasa city, 68 meteorological factors associated with air pollutants were pickedup and standardized to establish the regression equations of SO2, NO2 and PM10 in different seasons. The humanactivities such as Incense and fireworks in religious activities and festivals holidays were revised forecast forthe results obtained concentration of pollutants. The data of 2013 were used to test forecast and took a goodprediction results. In spring, SO2＇s average absolute error（AAE） is between 0.001 and 0.0022 mg/m^3, averagerelative error（ARE） lays 15.3%-27.0%; NO2＇s AAE is between 0.003 and 0.005 mg/m^3, ARE lays 17.2%-27.5%; PM10＇s AAE is between 0.006 and 0.019 mg/m^3, ARE lays 16.6%-28.6%.The Air Pollution Index（API）forecast accuracy is between 78.2%- 87.8%. The prediction method can fulfill the needs of air pollutantconcentrations forecast service in Lhasa city.
出处
《中国农学通报》
2015年第8期218-222,共5页
Chinese Agricultural Science Bulletin
基金
国家自然科学基金(40865008)
中国气象局2014年业务建设项目
关键词
拉萨
空气质量
API
污染物浓度预报
逐步回归
Lhasa
air quality
Air Pollution Index
pollutants concentration forecast
stepwise regression
