期刊
REMOTE SENSING
卷 2, 期 9, 页码 2136-2147出版社
MDPI
DOI: 10.3390/rs2092136
关键词
aerosol optical thickness; air pollution; meteorological influence; MODIS; China
类别
资金
- National Science and Technology Support Plan of China [2008BAC34B07]
- Key Fundamental Research Projects of Natural Science in Universities affiliated with the Jiangsu Province [08KJA170001]
- Jiangsu Province, China
Whether the aerosol optical thickness (AOT) products derived from MODIS data can be used as a reliable proxy of air pollutants measured near the surface depends on meteorological influence. This study attempts to assess the influence of four meteorological parameters (air pressure, temperature, relative humidity, and wind velocity) on predicting air pollution from MODIS AOT data for the city of Nanjing, China. It is found that PM10 (particulate matter with a diameter < 10 mu m) is linearly predictable from AOT at R-2 = 0.438. Seasonally, the prediction accuracy is much higher in summer (R-2 = 0.749, n = 24) and autumn (R-2 = 0.634, n = 45), but much lower in spring and winter (R-2 < 0.3). Scatterplots of the four meteorological parameters versus the residuals of PM10 estimates from AOT reveal no definite relationship between them. Thus, the seasonality of any parameters cannot account for the variation in the prediction accuracy. Stepwise regression analysis reveals that air pressure (R-2 = 0.268) is the most important factor affecting the residuals of Delta PM10 (Delta PM10) estimates in summer. In winter, the most important parameters are air pressure and air temperature (R-2 = 0.278). This accuracy rises to 0.510, similar to 0.409 for the summer season, if all four parameters are used in modeling PM10. However, no such models can be established for spring and autumn. It is concluded that meteorological parameters exert a mixed influence on the predictability of air pollution from AOT in the study area where air pollutants are dominated by suspended particulates.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据