GIS技术在空气污染物数值预报中的应用研究  

Application of GIS Technology in Numerical Prediction of Air Pollutants

作　　者：段利军 古意瑾 欧虹伶 吴倩茵 廖志朗 Duan Lijun;Gu Yijin;Ou Hongling;Wu Qianyin;Liao Zhilang(Hezhou Municipal Meteorological Service,Hezhou 542899,China)

机构地区：[1]贺州市气象局,广西贺州542899

出　　处：《环境科学与管理》2024年第5期138-142,共5页Environmental Science and Management

摘　　要：为实现空气污染物数值预报精度的提升,研究GIS技术在空气污染物数值预报中的应用。选择十六个预报点,通过3S技术采集预报点的地理信息数据、遥感数据与栅格数据、矢量数据。选取12个常规地面观测的相关气象要素作为空气污染物预报试验中的预报因子,利用逐步回归的方式构建该地区的空气污染物预报回归模型。预报该地区各预报点的空气污染物浓度,计算实测值与预报结果之间的平均相对误差与平均绝对误差。实验结果表明,模型对于PM_(10)、NO_(2)、SO_(2)的小时预报整体比较准确,小时预报平均相对误差与平均绝对误差均较低。In order to improve the accuracy of air pollutant numerical forecast,the application of GIS technology in air pollutant numerical forecast was studied.The geographic information data,remote sensing data,raster data and vector data of 16 prediction points were collected by 3S technology.Twelve meteorological elements of conventional ground observation were selected as the forecasting factors in the air pollutant forecast experiment,and the regression model of air pollutant forecast in this region was constructed by stepwise regression method.The average relative error and average absolute error between the measured values and the forecast results are calculated.The experimental results show that the hourly forecast of PM_(10),NO_(2)and SO_(2)is generally accurate,and the average relative error and average absolute error of hourly forecast are low.

关 键 词：地理信息技术 GIS软件 空气污染物数值预报 逐步回归 

分 类 号：X831[环境科学与工程—环境工程]