摘要
基于GIS技术和岭回归分析方法,采用苏锡常地区的MODIS高分辨率气溶胶光学厚度资料、PM_(2.5)浓度观测资料和苏锡常及周边地区的气象观测资料,构建了基于气溶胶光学厚度和气象要素的PM_(2.5)地面浓度分布估算模型,模拟了2013年春季苏锡常地区PM_(2.5)的空间分布状况,并将此模型与气象要素多元回归模型、气溶胶光学厚度直接回归模型进行比较.结果表明:该模型将遥感观测资料与地面气象观测资料相结合,能够有效地模拟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西北高、东南低,中心城区高、城郊区低的趋势,局部高浓度区域可能与工业生产、交通等人为因素有关;该模型能够在保持较高精度的前提下,有效地突出局部地区的变化特征,体现出更强的空间分异性,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 ridge regression analysis method,MODIS AOD,PM_(2.5)observation and meteorological data in the Suzhou-Wuxi-Changzhou area are used to built an estimation model of PM_(2.5). The spatial distribution pattern of PM_(2.5)in Suzhou-Wuxi-Changzhou area in the spring of 2013 was compared with the model only considering meteorological factors and the model only considering AOD in accuracy. The results show that the model combining remote sensing data with meteorological data can effectively simulate the spatial distribution of PM_(2.5). PM_(2.5)in Suzhou-Wuxi-Changzhou area in the spring of 2013 shows higher concentration in the north-west than south-east and higher in urban areas than suburban areas. The model can effectively highlight the characteristics of local areas with high precision,so it can be applied in studying spatial distribution of PM_(2.5).
出处
《环境科学学报》
CAS
CSCD
北大核心
2016年第10期3535-3542,共8页
Acta Scientiae Circumstantiae
基金
国家重大科学研究计划项目(No.2013CB430202)
国家自然科学基金(No.41276187)
江苏高校优势学科建设工程资助项目(PAPD)~~