4.8 Article

Estimating the Columnar Concentrations of Black Carbon Aerosols in China Using MODIS Products

期刊

ENVIRONMENTAL SCIENCE & TECHNOLOGY
卷 54, 期 18, 页码 11025-11036

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.0c00816

关键词

-

资金

  1. Guangdong Province Science and Technology Planning Project of China [2017A050506003]
  2. National Natural Science Foundation of China [41961160728]
  3. Shenzhen Peacock Teams Plan [KQTD20180411143441009]
  4. National Key Research and Development Program of China [2017YFC0212302]
  5. Shenzhen Key Laboratory Foundation [ZDSYS20180208184349083]
  6. Guangdong Basic and Applied Basic Research Foundation [2019A1515110384]
  7. China Postdoctoral Science Foundation [2019M662169, 2019M662199]

向作者/读者索取更多资源

Black carbon (BC), the strongest light-absorbing particle, is believed to play substantial roles in regional air quality and global climate change. In this study, taking advantage of the high quality of moderate resolution imaging spectroradiometer products, we developed a new algorithm to estimate the BC columnar concentrations over China by simulating the BC and non-BC aerosol mixing states in detail. The results show that our new algorithm produces a reliable estimation of BC aerosols, in which BC columnar concentrations and their related parameters (aerosol absorption and BC surface concentration) show reasonable agreements and low biases compared with ground-based measurements. The uncertainties of BC retrievals are mainly associated with the surface and aerosol assumptions used in the algorithm, ranging from -14 to 44% at higher aerosol optical depth (AOD > 0.5). The proposed algorithm can improve the capability of space-borne aerosol remote sensing by successfully distinguishing BC from other aerosols. The acquired BC columnar concentrations enable the spatial pattern of serious BC aerosol pollution over East China to be characterized, showing that it exhibits higher levels in winter. These nationwide results are beneficial for estimating BC emissions, proposing mitigation strategies for air pollution, and potentially reducing the uncertainties of climate change studies.

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。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据