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Published February 28, 2020 | Published + Supplemental Material
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Relative effects of open biomass burning and open crop straw burning on haze formation over central and eastern China: modeling study driven by constrained emissions


Open biomass burning (OBB) has a high potential to trigger local and regional severe haze with elevated fine particulate matter (PM_(2.5)) concentrations and could thus deteriorate ambient air quality and threaten human health. Open crop straw burning (OCSB), as a critical part of OBB, emits abundant gaseous and particulate pollutants, especially in fields with intensive agriculture, such as in central and eastern China (CEC). This region includes nine provinces, i.e., Hubei, Anhui, Henan, Hunan, Jiangxi, Shandong, Jiangsu, Shanghai, and Fujian. The first four ones are located inland, while the others are on the eastern coast. However, uncertainties in current OCSB and other types of OBB emissions in chemical transport models (CTMs) lead to inaccuracies in evaluating their impacts on haze formations. Satellite retrievals provide an alternative that can be used to simultaneously quantify emissions of OCSB and other types of OBB, such as the Fire INventory from NCAR version 1.5 (FINNv1.5), which, nevertheless, generally underestimates their magnitudes due to unresolved small fires. In this study, we selected June 2014 as our study period, which exhibited a complete evolution process of OBB (from 1 to 19 June) over CEC. During this period, OBB was dominated by OCSB in terms of the number of fire hotspots and associated emissions (74 %–94 %), most of which were located at Henan and Anhui (> 60 %) with intensive enhancements from 5 to 14 June (> 80 %). OCSB generally exhibits a spatiotemporal correlation with regional haze over the central part of CEC (Henan, Anhui, Hubei, and Hunan), while other types of OBB emissions had influences on Jiangxi, Zhejiang, and Fujian. Based on these analyses, we establish a constraining method that integrates ground-level PM_(2.5) measurements with a state-of-art fully coupled regional meteorological and chemical transport model (the two-way coupled WRF-CMAQ) in order to derive optimal OBB emissions based on FINNv1.5. It is demonstrated that these emissions allow the model to reproduce meteorological and chemical fields over CEC during the study period, whereas the original FINNv1.5 underestimated OBB emissions by 2–7 times, depending on specific spatiotemporal scales. The results show that OBB had substantial impacts on surface PM_(2.5) concentrations over CEC. Most of the OBB contributions were dominated by OCSB, especially in Henan, Anhui, Hubei, and Hunan, while other types of OBB emissions also exerted an influence in Jiangxi, Zhejiang, and Fujian. With the concentration-weighted trajectory (CWT) method, potential OCSB sources leading to severe haze in Henan, Anhui, Hubei, and Hunan were pinpointed. The results show that the OCSB emissions in Henan and Anhui can cause haze not only locally but also regionally through regional transport. Combining with meteorological analyses, we can find that surface weather patterns played a cardinal role in reshaping spatial and temporal characteristics of PM_(2.5) concentrations. Stationary high-pressure systems over CEC enhanced local PM_(2.5) concentrations in Henan and Anhui. Then, with the evolution of meteorological patterns, Hubei and Hunan in the low-pressure system were impacted by areas (i.e., Henan and Anhui) enveloped in the high-pressure system. These results suggest that policymakers should strictly undertake interprovincial joint enforcement actions to prohibit irregular OBB, especially OCSB over CEC. Constrained OBB emissions can, to a large extent, supplement estimations derived from satellite retrievals as well as reduce overestimates of bottom-up methods.

Additional Information

© 2020 Author(s). This work is distributed under the Creative Commons Attribution 4.0 License. Published by Copernicus Publications on behalf of the European Geosciences Union. Received: 08 Sep 2019 – Discussion started: 17 Oct 2019 – Revised: 20 Jan 2020 – Accepted: 24 Jan 2020 – Published: 28 Feb 2020. This study is supported by the Department of Science and Technology of China (nos. 2016YFC0202702, 2018YFC0213506, and 2018YFC0213503), the National Research Program for Key Issues in Air Pollution Control in China (no. DQGG0107), and the National Natural Science Foundation of China (nos. 21577126 and 41561144004). Pengfei Li is supported by the Initiation Fund for Introducing Talents of Hebei Agricultural University (412201904). We acknowledge the great support of SCAS-CERN, Institute of Atmospheric Physics, Chinese Academy of Sciences (CAS), for providing the CARE-China data for analysis. Data availability: The MODIS data can be freely accessed at https://earthdata.nasa.gov/ (last access: 5 August 2019). GFASv1.0 data are available from http://apps.ecmwf.int/datasets/data/cams-gfas/ (last access: 5 August 2019). GFED4s data can be downloaded from https://daac.ornl.gov/VEGETATION/guides/fire_emissions_ v4.html (last access: 5 August 2019). FINNv1.5 data can be found at http://bai.acom.ucar.edu/Data/fire/ (last access: 5 August 2019). The supplement related to this article is available online at: https://doi.org/10.5194/acp-20-2419-2020-supplement. Author contributions: SY and PL designed this study; SY, PL, KM, YW, LW, and JHS carried out analyses, interpreted data, and wrote the article. XC, ZL, YZ, ML, WL, YZ, and DR contributed to the discussion. The authors declare that they have no conflict of interest. This study is supported by the Department of Science and Technology of China (grant nos. 2016YFC0202702, 2018YFC0213506, and 2018YFC0213503), the National Research Program for Key Issues in Air Pollution Control in China (grant no. DQGG0107), the National Natural Science Foundation of China (grant nos. 21577126 and 41561144004), the Initiation Fund for Introducing Talents of Hebei Agricultural University (grant no. 412201904), the SCAS-CERN, the Institute of Atmospheric Physics, and the Chinese Academy of Sciences (CAS). Review statement: This paper was edited by Jianzhong Ma and reviewed by two anonymous referees.

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August 19, 2023
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