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对中国黑碳气溶胶的MERRA-2和CAMS再分析评估。

Evaluation of MERRA-2 and CAMS reanalysis for black carbon aerosol in China.

作者信息

Li Weijie, Wang Yaqiang, Yi Ziwei, Guo Bin, Chen Wencong, Che Huizheng, Zhang Xiaoye

机构信息

State Key Laboratory of Severe Weather & Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China.

State Key Laboratory of Severe Weather & Institute of Artificial Intelligence for Meteorology, Chinese Academy of Meteorological Sciences, Beijing, 100081, China.

出版信息

Environ Pollut. 2024 Feb 15;343:123182. doi: 10.1016/j.envpol.2023.123182. Epub 2023 Dec 18.

Abstract

Black carbon (BC) constitutes a pivotal component of atmospheric aerosols, significantly impacting regional and global radiation balance, climate, and human health. In this study, we evaluated BC data in two prominent atmospheric composition reanalysis datasets: the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and the Copernicus Atmosphere Monitoring Service (CAMS), and analyzed the causes of their deviations. This assessment is based on observational data collected from 34 monitoring stations across China from 2006 to 2022. Our research reveals a significant and consistent decline in BC concentrations within China, amounting to a reduction exceeding 67.33%. However, both MERRA-2 and CAMS reanalysis data fail to capture this declining trend. The average annual decrease of BC in MERRA-2 from 2006 to 2022 is only 0.06 μg/m per year, while the BC concentration in CAMS even increased with an average annual value of 0.014 μg/m per year. In 2022, MERRA-2 had overestimated BC concentration by 20% compared to observational data, while CAMS had overestimated it by approximately 66%. In the regional BC concentration analysis, the data quality of the reanalysis data is better in the South China (R = 0.59, R = 0.53), followed by the North China (R = 0.50, R = 0.42). Reanalysis BC data in Northwest China and the Tibetan Plateau are difficult to use for practical analysis due to their big difference with observation. In a comparison of the anthropogenic BC emissions inventory used in the two atmospheric composition reanalysis datasets with the Multi-resolution Emission Inventory model for Climate and air pollution research (MEIC) emissions inventory, we found that: Despite the significant decline in China's BC emissions, MERRA-2 still relies on the 2006 emissions inventory, while CAMS utilizes emission inventories that even show an increasing trend. These factors will undoubtedly lead to greater deviations between reanalysis and observational data.

摘要

黑碳(BC)是大气气溶胶的关键组成部分,对区域和全球辐射平衡、气候及人类健康有着重大影响。在本研究中,我们评估了两个著名的大气成分再分析数据集中的黑碳数据:第二代现代时代回顾性研究与应用分析(MERRA-2)和哥白尼大气监测服务(CAMS),并分析了它们产生偏差的原因。该评估基于2006年至2022年期间从中国34个监测站收集的观测数据。我们的研究表明,中国境内黑碳浓度出现了显著且持续的下降,降幅超过67.33%。然而,MERRA-2和CAMS再分析数据均未捕捉到这一下降趋势。2006年至2022年期间,MERRA-2中黑碳的年均降幅仅为每年0.06微克/立方米,而CAMS中的黑碳浓度甚至呈上升趋势,年均值为每年0.014微克/立方米。2022年,与观测数据相比,MERRA-2对黑碳浓度的高估了20%,而CAMS则高估了约66%。在区域黑碳浓度分析中,再分析数据在华南地区的数据质量较好(R = 0.59,R = 0.53),其次是华北地区(R = 0.50,R = 0.42)。中国西北地区和青藏高原的再分析黑碳数据与观测值差异较大,难以用于实际分析。在将两个大气成分再分析数据集中使用的人为黑碳排放清单与用于气候和空气污染研究的多分辨率排放清单模型(MEIC)排放清单进行比较时,我们发现:尽管中国的黑碳排放量显著下降,但MERRA-2仍依赖2006年的排放清单,而CAMS使用的排放清单甚至呈上升趋势。这些因素无疑将导致再分析数据与观测数据之间出现更大的偏差。

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