Journal metrics
IF 5.318
5.896CiteScore
5.72SNIP 1.330
SJR 3.207
h5-index 89
|
https://doi.org/10.5194/acp-2017-646
© Author(s) 2017. This work is distributed under the Creative Commons Attribution 4.0 License. 
|
Research article
04 Aug 2017
1Ministry of Education Key Laboratory for Earth System Modeling, Department for Earth System Science, Tsinghua University, Beijing, China
2International Institute for Applied Systems Analysis (IIASA), Laxenburg, 2361, Austria
3State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
4Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
anow at: Max-Planck Institute for Chemistry, Mainz, Germany
Received: 09 Jul 2017 – Accepted for review: 01 Aug 2017 – Discussion started: 04 Aug 2017
Abstract. Bottom-up emission inventories provide primary understanding of sources of air pollution and essential input of chemical transport models. Focusing on SO2 and NOx, we conducted a comprehensive evaluation of two widely-used anthropogenic emission inventories over China, ECLIPSE and MIX, to explore the potential sources of uncertainties and find the clues in improving emission inventories. We first compared the activity rates and emission factors used in two inventories, and investigated the reasons of differences and the impacts on emission estimates. We found that SO2 emission estimates are consistent between two inventories (with 1 % differences), while NOx emissions in ECLIPSE's estimates are 16 % lower than those of MIX. Discrepancies at sectorial and provincial level are much higher. We then examined the impacts of different inventories on model performance, by using the nested GEOS-Chem model. We finally derived top-down NOx emissions by using the NO2 columns from the Ozone Monitoring Instrument (OMI) and compared with the bottom-up estimates. To our knowledge, this is the first work where source-sector comparisons are made along with the remote sensing retrievals and chemical transport modeling. Through the comparison between bottom-up emission inventories and evaluation with top-down information, we summarized the potential directions for further improvement in inventory development.
Citation: Li, M., Klimont, Z., Zhang, Q., Martin, R. V., Zheng, B., Heyes, C., Cofala, J., and He, K.: Comparison and evaluation of anthropogenic emissions of SO2 and NOx<\sub> over China, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-646, in review, 2017.
2International Institute for Applied Systems Analysis (IIASA), Laxenburg, 2361, Austria
3State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
4Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Canada
anow at: Max-Planck Institute for Chemistry, Mainz, Germany
Citation: Li, M., Klimont, Z., Zhang, Q., Martin, R. V., Zheng, B., Heyes, C., Cofala, J., and He, K.: Comparison and evaluation of anthropogenic emissions of SO2 and NOx<\sub> over China, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-646, in review, 2017.
