Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models
Abstract
Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols aremore »
- Authors:
-
[1];
[5];
[6];
[1];
- Beijing Normal Univ., Beijing (China)
- Univ. of Wyoming, Laramie, WY (United States); Beijing Normal Univ., Beijing (China)
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Tsinghua Univ., Beijing (China)
- Beijing Normal Univ., Beijing (China); Univ. of Maryland, College Park, MD (United States)
- Nanjing Univ., Nanjing (China)
- Publication Date:
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1421322
- Report Number(s):
- PNNL-SA-130097
Journal ID: ISSN 1680-7324
- Grant/Contract Number:
- AC05-76RL01830
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Atmospheric Chemistry and Physics (Online)
- Additional Journal Information:
- Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 18; Journal Issue: 2; Journal ID: ISSN 1680-7324
- Publisher:
- European Geosciences Union
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES
Citation Formats
Fan, Tianyi, Liu, Xiaohong, Ma, Po -Lun, Zhang, Qiang, Li, Zhanqing, Jiang, Yiquan, Zhang, Fang, Zhao, Chuanfeng, Yang, Xin, Wu, Fang, and Wang, Yuying. Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models. United States: N. p., 2018.
Web. doi:10.5194/acp-18-1395-2018.
Fan, Tianyi, Liu, Xiaohong, Ma, Po -Lun, Zhang, Qiang, Li, Zhanqing, Jiang, Yiquan, Zhang, Fang, Zhao, Chuanfeng, Yang, Xin, Wu, Fang, & Wang, Yuying. Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models. United States. https://doi.org/10.5194/acp-18-1395-2018
Fan, Tianyi, Liu, Xiaohong, Ma, Po -Lun, Zhang, Qiang, Li, Zhanqing, Jiang, Yiquan, Zhang, Fang, Zhao, Chuanfeng, Yang, Xin, Wu, Fang, and Wang, Yuying. Thu .
"Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models". United States. https://doi.org/10.5194/acp-18-1395-2018. https://www.osti.gov/servlets/purl/1421322.
@article{osti_1421322,
title = {Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models},
author = {Fan, Tianyi and Liu, Xiaohong and Ma, Po -Lun and Zhang, Qiang and Li, Zhanqing and Jiang, Yiquan and Zhang, Fang and Zhao, Chuanfeng and Yang, Xin and Wu, Fang and Wang, Yuying},
abstractNote = {Here, global climate models often underestimate aerosol loadings in China, and these biases can have significant implications for anthropogenic aerosol radiative forcing and climate effects. The biases may be caused by either the emission inventory or the treatment of aerosol processes in the models, or both, but so far no consensus has been reached. In this study, a relatively new emission inventory based on energy statistics and technology, Multi-resolution Emission Inventory for China (MEIC), is used to drive the Community Atmosphere Model version 5 (CAM5) to evaluate aerosol distribution and radiative effects against observations in China. The model results are compared with the model simulations with the widely used Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) emission inventory. We find that the new MEIC emission improves the aerosol optical depth (AOD) simulations in eastern China and explains 22–28 % of the AOD low bias simulated with the AR5 emission. However, AOD is still biased low in eastern China. Seasonal variation of the MEIC emission leads to a better agreement with the observed seasonal variation of primary aerosols than the AR5 emission, but the concentrations are still underestimated. This implies that the atmospheric loadings of primary aerosols are closely related to the emission, which may still be underestimated over eastern China. In contrast, the seasonal variations of secondary aerosols depend more on aerosol processes (e.g., gas- and aqueous-phase production from precursor gases) that are associated with meteorological conditions and to a lesser extent on the emission. It indicates that the emissions of precursor gases for the secondary aerosols alone cannot explain the low bias in the model. Aerosol secondary production processes in CAM5 should also be revisited. The simulation using MEIC estimates the annual-average aerosol direct radiative effects (ADREs) at the top of the atmosphere (TOA), at the surface, and in the atmosphere to be –5.02, –18.47, and 13.45 W m–2, respectively, over eastern China, which are enhanced by –0.91, –3.48, and 2.57 W m–2 compared with the AR5 emission. The differences of ADREs by using MEIC and AR5 emissions are larger than the decadal changes of the modeled ADREs, indicating the uncertainty of the emission inventories. This study highlights the importance of improving both the emission and aerosol secondary production processes in modeling the atmospheric aerosols and their radiative effects. Yet, if the estimations of MEIC emissions in trace gases do not suffer similar biases to those in the AOD, our findings will help affirm a fundamental error in the conversion from precursor gases to secondary aerosols as hinted in other recent studies following different approaches.},
doi = {10.5194/acp-18-1395-2018},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 2,
volume = 18,
place = {United States},
year = {Thu Feb 01 00:00:00 EST 2018},
month = {Thu Feb 01 00:00:00 EST 2018}
}
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- Rahimi, Stefan; Liu, Xiaohong; Wu, Chenglai
- Atmospheric Chemistry and Physics, Vol. 19, Issue 18
Constraining Aging Processes of Black Carbon in the Community Atmosphere Model Using Environmental Chamber Measurements
journal, October 2018
- Wang, Yuan; Ma, Po‐Lun; Peng, Jianfei
- Journal of Advances in Modeling Earth Systems, Vol. 10, Issue 10
Anthropogenically-driven increases in the risks of summertime compound hot extremes
journal, February 2020
- Wang, Jun; Chen, Yang; Tett, Simon F. B.
- Nature Communications, Vol. 11, Issue 1