首页 >  2013, Vol. 17, Issue (4) : 929-943

摘要

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引用本文:

DOI:

10.11834/jrs.20133063

收稿日期:

2013-03-18

修改日期:

2013-05-14

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利用细模态气溶胶光学厚度估计PM2.5
1.中国科学院遥感与数字地球研究所, 国家环境保护卫星遥感重点实验室, 北京 100101;2.中国科学院大学, 北京 100049
摘要:

本文利用2013年1月AERONET (Aerosol Robotic Network) 北京站的气溶胶光学厚度AOD (Aerosol Optical Depth)、细颗粒物光学厚度占总光学厚度的比例即气溶胶细模态比例η以及地面监测的细颗粒物PM2.5 (Particulate Matter 2.5)质量浓度数据建立气溶胶细模态光学厚度AODf(fine-mode Aerosol Optical Depth)与PM2.5的线性回归关系,并利用2013年2月1日—15日的数据验证该方法。结果表明,利用2013年1月建立的回归方法能够有效估算灰霾期间PM2.5,获得PM2.5的均值为8 5 μg/m3,均方根误差为50 μg/m3。利用气溶胶细模态订正方法估算的AODf与PM2.5的相关系数大于AOD与PM2.5的相关系数,这表明灰霾期间以PM2.5为代表的细模态颗粒物成为气溶胶消光的主体,且AOD与PM2.5的关系转化为AODf与PM2.5的相关关系时,相关程度提高。垂直分布修正在灰霾时对改善AOD与PM2.5相关关系作用不明显;当相对湿度大于80%时,湿度订正效果受到较大限制。

Estimation of PM2.5 from fine-mode aerosol optical depth
Abstract:

The correlation between fine Particulate Matters (PM2.5) and Fine-mode Aerosol Optical Depth (AODf) is established. AODf is obtained from product of Aerosol Optical Depth (AOD) and fine-mode fraction at Beijing site belonging to the AErosol RObotic NETwork (AERONET) in January 2013. And then we compare estimation with observation of PM2.5 from 1 to 15 February,2013. The results show that the developed correction method is effective to estimate PM2.5 during haze, with root-mean-square error of 50 μg/m3 at a mean level of 85 μg/m3. The relationship between AODf and PM2.5 is obviously better than that of AOD and PM2.5. It is also found that when the relative humidity is higher than 80%, the humidity correction on AOD-PM2.5 correlation is limited, and the vertical correction cannot improve the correlation during haze.

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