Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Atmos. Chem. Phys., 18, 1395-1417, 2018
https://doi.org/10.5194/acp-18-1395-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
01 Feb 2018
Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models
Tianyi Fan1, Xiaohong Liu2,1, Po-Lun Ma3, Qiang Zhang4, Zhanqing Li1,5, Yiquan Jiang6, Fang Zhang1, Chuanfeng Zhao1, Xin Yang1, Fang Wu1, and Yuying Wang1 1College of Global Change and Earth System Science, State Key Laboratory of Earth Surface Processes and Resource Ecology, and Joint Center for Global Change and Green China Development, Beijing Normal University, Beijing, China
2Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming, USA
3Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
4Center for Earth System Science, Tsinghua University, Beijing, China
5Department of Atmospheric and Oceanic Science & ESSIC, University of Maryland, College Park, Maryland, USA
6Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Nanjing, China
Abstract. 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.

Citation: Fan, T., Liu, X., Ma, P.-L., Zhang, Q., Li, Z., Jiang, Y., Zhang, F., Zhao, C., Yang, X., Wu, F., and Wang, Y.: Emission or atmospheric processes? An attempt to attribute the source of large bias of aerosols in eastern China simulated by global climate models, Atmos. Chem. Phys., 18, 1395-1417, https://doi.org/10.5194/acp-18-1395-2018, 2018.
Publications Copernicus
Download
Short summary
We found that 22–28 % of the low AOD bias in eastern China simulated by the Community Atmosphere Model version 5 can be improved by using a new emission inventory. The concentrations of primary aerosols are closely related to the emission, while the seasonal variations of secondary aerosols depend more on atmospheric processes. This study highlights the importance of improving both the emission and atmospheric processes in modeling the atmospheric aerosols and their radiative effects.
We found that 22–28 % of the low AOD bias in eastern China simulated by the Community Atmosphere...
Share