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Published February 16, 2019 | Published
Journal Article Open

Estimating the contribution of local primary emissions to particulate pollution using high-density station observations

Abstract

Local primary emission, transport, and secondary formation of aerosols constitute the major atmospheric particulate matter (PM) over a certain region. To identify and quantify major sources of ambient PM is important for pollution mitigation strategies, especially on a city scale. We developed two source apportionment methods to make the first‐order estimates of local primary contribution ratio (LCR) of PM_(2.5) (PM with diameter less than 2.5 μm) using the high‐density (about 1/km^2) network observations with high sampling frequency (about 1 hr). Measurements of PM_(2.5) mass concentration from 169 sites within a 20 km × 20 km domain are analyzed. The two methods developed here are mainly based on the spatial and temporal variations of PM_(2.5) within an urban area. The accuracy of our developed methods is subject to the assumptions on the spatial heterogeneity of primary and secondary formed aerosols as well as those from long‐range transport to a city. We apply these two methods to a typical industrial city in China in winter of 2015 with frequent severe haze events. The local primary pollution contributions calculated from the two methods agree with each other that they are often larger than 0.4. The LCR range is from 0.4 to 0.7, with an average value of 0.63. Our study indicates the decisive role of locally emitted aerosols in the urban severe haze formation during the winter time. It further suggests that reductions of local primary aerosol emissions are essential to alleviate the severe haze pollution, especially in industrial cities.

Additional Information

© 2019 American Geophysical Union. Received 25 APR 2018; Accepted 10 JAN 2019; Accepted article online 15 JAN 2019; Published online 2 FEB 2019. This work was supported by the National Key R&D Program on Monitoring, Early Warning and Prevention of Major Natural Disasters under grant 2017YFC1501403, the National Natural Science Foundation of China under grant 41575143, the State Key Laboratory of Earth Surface Processes and Resource Ecology (2017‐ZY‐02), and the Fundamental Research Funds for the Central Universities (2017EYT18 and 312231103). The authors also acknowledge the support by the Division of Geology and Planetary Science, California Institute of Technology (Caltech), as well as the support by the Caltech Jet Propulsion Laboratory, sponsored by NASA. The data used in this study are available by request to Chuanfeng Zhao through czhao@bnu.edu.cn or directly downloaded from ftp: nwpc.nmc.cn under directory zhao_paper_data. We acknowledge the helpful discussions with David Diner at Jet Propulsion Laboratory and Yuanlong Huang and Lu Xu at Caltech. We also thank the three anonymous reviewers for their constructive comments.

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Created:
August 19, 2023
Modified:
October 20, 2023