Suppr超能文献

利用 MODIS 产品估算中国柱状黑碳气溶胶浓度。

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

机构信息

Center for Oceanic and Atmospheric Science at SUSTech (COAST), Department of Ocean Sciences and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.

Shenzhen Key Laboratory of Marine Archaea Geo-Omics, Southern University of Science and Technology, Shenzhen 518055, China.

出版信息

Environ Sci Technol. 2020 Sep 15;54(18):11025-11036. doi: 10.1021/acs.est.0c00816. Epub 2020 Aug 31.

Abstract

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.

摘要

黑碳(BC)是吸光性最强的颗粒,被认为在区域空气质量和全球气候变化中发挥着重要作用。本研究利用中分辨率成像光谱仪产品的高质量,通过详细模拟 BC 和非 BC 气溶胶混合状态,开发了一种新的算法来估算中国的 BC 柱浓度。结果表明,我们的新算法能够可靠地估算 BC 气溶胶,其中 BC 柱浓度及其相关参数(气溶胶吸收和 BC 表面浓度)与地面测量值具有较好的一致性和较低的偏差。BC 反演的不确定性主要与算法中使用的地表和气溶胶假设有关,在较高气溶胶光学深度(AOD>0.5)时,不确定性范围为-14%至 44%。该算法通过成功区分 BC 与其他气溶胶,提高了星载气溶胶遥感的能力。获得的 BC 柱浓度能够描述华东地区严重 BC 气溶胶污染的空间格局,表明冬季污染水平更高。这些全国性的结果有助于估算 BC 排放,提出空气污染缓解策略,并可能减少气候变化研究的不确定性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验