| 乌鲁木齐市MODIS气溶胶光学厚度与PM10浓度关系模型研究 |
| |
| 引用本文： | 黄观,刘伟,刘志红,张颖,何沐全. 乌鲁木齐市MODIS气溶胶光学厚度与PM10浓度关系模型研究[J]. 环境科学学报, 2016, 36(2): 649-657 |
| |
| 作者姓名： | 黄观 刘伟 刘志红 张颖 何沐全 |
| |
| 作者单位： | 成都信息工程大学资源环境学院, 成都 610225,成都信息工程大学资源环境学院, 成都 610225,成都信息工程大学资源环境学院, 成都 610225,成都信息工程大学资源环境学院, 成都 610225,成都信息工程大学资源环境学院, 成都 610225 |
| |
| 基金项目： | 国家自然科学基金(No.41405124);四川省科技支撑计划项目(No.2015GZ0241);四川省社会科学研究规划项目(No.SC14C007,SC15ZD01);成都信息工程大学中青年学术带头人科研基金(No.J201213);大气环境模拟与污染控制四川省高校重点实验室资助课题(No.ZZKT2014004) |
| |
| 摘 要： | 为了建立乌鲁木齐市近地面PM10浓度监测的关系模型,利用乌鲁木齐市2013年3—11月、2014年3—11月MODIS AOD产品与同期地面观测的PM10质量浓度进行相关分析,结果表明二者直接相关程度较低(r=0.433,p0.01);然后以WRF模式模拟的大气边界层高度及地面观测的相对湿度数据对AOD进行垂直、湿度订正后,二者相关性得到较大程度提高(r=0.630,p0.01);按照季节分类统计和订正春、夏、秋季的相关系数r分别为0.779、0.393、0.523,均大于统计学上99%的置信度要求,其中春季的订正最为有效,可用性更高;最后,建立全年和各季AOD-PM10最优拟合模型并反演乌鲁木齐市地面PM10质量浓度,全年和三季的反演结果与实测数据的相关系数分别为0.757、0.748、0.652、0.715(p0.01);同时基于卫星遥感AOD反演得到的PM10质量浓度的空间分布与AOD呈现出整体的一致性,并且3个季节AOD平均值表现为:春季秋季夏季.证实了卫星遥感AOD经过垂直和湿度订正后,可以作为辅助监测乌鲁木齐市PM10地面浓度分布的一个有效手段.
|
| 关 键 词： | MODIS 气溶胶光学厚度(AOD) PM10 拟合模型 乌鲁木齐市 |
| 收稿时间： | 2015-07-22 |
| 修稿时间： | 2015-09-01 |
Relationship between MODIS aerosol optical depth and PM10 ground concentration in Urumchi |
| |
| HUANG Guan,LIU Wei,LIU Zhihong,ZHANG Ying and HE Muquan. Relationship between MODIS aerosol optical depth and PM10 ground concentration in Urumchi[J]. Acta Scientiae Circumstantiae, 2016, 36(2): 649-657 |
| |
| Authors: | HUANG Guan LIU Wei LIU Zhihong ZHANG Ying HE Muquan |
| |
| Affiliation: | College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225,College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225,College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225,College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225 and College of Resources and Environment, Chengdu University of Information Technology, Chengdu 610225 |
| |
| Abstract: | Based on the MODIS AOD product and the simultaneous ground concentration of PM10 from March to November in 2013 and 2014 in Urumchi, this study analyzed their correlations in order to establish the PM10 ground concentration monitoring models in Urumchi. The results indicated that the direct correlation between AOD and PM10 ground concentration was relative low (r=0.433,p<0.01). Correlation was greatly improved (r=0.630,p<0.01) after the vertical correction of atmospheric boundary layer height (ABLH) by using WRF model simulation and the relative humidity (RH) correction by using the ground observed data. With season classification and correction, the correlation coefficient of spring, summer and autumn was 0.779, 0.393 and 0.523, respectively(confidence 99%). The correction was more effective in spring. Finally, the best fitting models of AOD and PM10 ground concentration in different seasons and the whole year were established, and the PM10 ground concentration in Urumchi was retrieved. The correlation coefficient of inversion result and observed PM10 ground concentration in the whole year and three seasons was 0.757, 0.748, 0.652 and 0.715(p<0.01), respectively. Meanwhile, the spatial distribution of the PM10 ground concentration retrieved from the MODIS AOD was almost the same as that of AOD, and the average value of AOD in three seasons was presented as: spring> autumn> summer. This study confirmed that MODIS AOD can be used to retrieve PM10 ground concentration in Urumchi after taking aerosol vertical distribution and influence of RH into consideration. |
| |
| Keywords: | MODIS aerosol optical depth (AOD) PM10 fitting model Urumchi |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《环境科学学报》浏览原始摘要信息 |
|
点击此处可从《环境科学学报》下载全文 |
|
