Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

Fan, Tianyi; Liu, Xiaohong; Ma, Po -Lun; Zhang, Qiang; Li, Zhanqing; Jiang, Yiquan; Zhang, Fang; Zhao, Chuanfeng; Yang, Xin; Wu, Fang; Wang, Yuying

doi:10.5194/acp-18-1395-2018

Title: Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models

Journal Article · Thu Feb 01 00:00:00 EST 2018 · Atmospheric Chemistry and Physics (Online)

DOI:https://doi.org/10.5194/acp-18-1395-2018· OSTI ID:1421322

^[1]; Liu, Xiaohong ^[2]; Ma, Po -Lun ^[3]; Zhang, Qiang ^[4];

^[5];

^[6]; Zhang, Fang ^[1]; Zhao, Chuanfeng ^[1];

^[1]; Wu, Fang ^[1]; Wang, Yuying ^[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)

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.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1421322

Report Number(s):: PNNL-SA-130097

Journal Information:: Atmospheric Chemistry and Physics (Online), Vol. 18, Issue 2; ISSN 1680-7324

Publisher:: European Geosciences UnionCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 28 works

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Effect of model errors in ambient air humidity on the aerosol optical depth obtained via aerosol hygroscopicity in eastern China in the Atmospheric Chemistry and Climate Model Intercomparison Project datasets Chang, Wenyuan Atmospheric and Oceanic Science Letters, Vol. 12, Issue 3 https://doi.org/10.1080/16742834.2019.1588063	journal	March 2019
Quantifying snow darkening and atmospheric radiative effects of black carbon and dust on the South Asian monsoon and hydrological cycle: experiments using variable-resolution CESM Rahimi, Stefan; Liu, Xiaohong; Wu, Chenglai Atmospheric Chemistry and Physics, Vol. 19, Issue 18 https://doi.org/10.5194/acp-19-12025-2019	journal	January 2019
Anthropogenically-driven increases in the risks of summertime compound hot extremes Wang, Jun; Chen, Yang; Tett, Simon F. B. Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-019-14233-8	journal	February 2020

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