基于GIS的苏锡常地区PM_(2.5)分布模拟

PM_(2.5)'s Distribution Simulation in Suzhou-Wuxi-Changzhou Area Based on GIS

基于GIS技术和多元线性回归方法,采用苏锡常地区的PM_(2.5)浓度观测资料和同期苏锡常及周边地区的气象资料,构建了基于气象要素的多元线性回归模型,模拟2013年春季苏锡常地区PM_(2.5)的空间分布状况。对比此模型与IDW插值方法的精度,结果表明,该模型利用气象要素与PM_(2.5)浓度显著的相关性建立多元线性回归模型,有效地模拟了PM_(2.5)的空间分布状况;2013年春季苏锡常地区PM_(2.5)的空间分布具有整体上东南低、西北高、局部上分布小范围低值区的特点;该模型有效地消除了单一使用IDW插值方法容易受到监测站空间分布的影响而出现极值区域和极值中心偏差的现象,对于研究PM_(2.5)的空间分布规律具有一定的实际应用价值。

By using GIS and multiple linear regression method, we built a multiple linear regression model based on meteorological elements in this paper. Relying on PM2.5 observation data and meteorological data for Suzhou-Wuxi-Changzhou Area as well as its surrounding area, we simulated the spatial distribution pattern of PM2.5 in SuzhouWuxi-Changzhou Area in the spring of 2013 and compared with the IDW interpolation method in accuracy. The results show that using correlation between meteorological elements and distribution of PMffectively. ①the model PM_(2.5) can simulate the spatial 2.5 etribution pattern of PM_(2.5) in Suzhou-Wuxi-Changzho the characteristics that the concen②The spatial disu Area in the spring of 2013 has tration in the south-east is lower than that in the north-west and low value range appears in local areas. ③ The model eliminates the phenomenon effectively that using IDW interpolation method simply is easier to be influenced by the spatial distribution of monitoring stations and appear extreme area and extreme value distribution. The model has certain practical application value in the study of spatial distribution law of PM_(2.5).