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Discussion papers
https://doi.org/10.5194/acp-2018-687
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2018-687
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Review article 05 Sep 2018

Review article | 05 Sep 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Characteristics of the main primary source profiles of particulate matter across China: from 1987 to 2017

Xiaohui Bi, Yuan Cheng, Qili Dai, Jianhui Wu, Jiaying Zhang, Yufen Zhang, Lu Wang, Yingze Tian, and Yinchang Feng Xiaohui Bi et al.
  • State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China

Abstract. Based on the published literatures and typical profiles from the source library of Nankai University, a total of 3244 chemical profiles of the main primary sources of ambient particulate matter across China from 1987 to 2017, including coal combustion, industrial emissions, vehicle emissions, fugitive dust, biomass burning, and cooking emissions, were investigated and reviewed to trace the evolution of their main components and identify the main influencing factors to the evolution. As a result, the most complicated profiles are likely attributed to coal combustion and industrial emissions, which are evidently influenced by the decontamination processes and sampling techniques as well as the coal nature and the boiler types. The profiles of vehicle emissions are dominated by OC and EC, and varied with the changing standard of sulfur and additives in the gasoline and diesel as well as the sampling methods. The profiles of fugitive dust, such as soil dust and road dust, are dominated by the crustal materials and influenced by the sampling methods to some extent. The profiles of biomass burning is impacted mainly by the biomass categories and sampling methods. As expected, the profiles of cooking emissions is impacted mainly by the cooking types and materials. The uncertainty analysis and cluster analysis of all these source profiles are conducted to reveal the variations of the different source profiles in the same source category and evaluate the differences between source categories. A relatively large variation has been founded in the source profiles of coal combustion, vehicle emissions, industry emissions and biomass burning, indicating that it is necessary to establish the local profiles for these sources due to their high uncertainties. While the profiles of road dust and soil dust present a less variation with the stable chemical characteristics among the different profiles in the same category, suggesting that the profiles of these sources could be referenced for the cities in China when such local profiles are not available. The presented results highlight the need for increased investigation of more specific markers beyond routine measured components (e.g., isotopes, organic compounds and gaseous precursors) to discriminate sources. Additionally, specific focus should be placed on the sub-type of source profiles in the future, especially for local industrial emissions and geographical areas in China, to support the air quality research communities in their efforts to develop high resolution source apportionment for making a more effective control strategies.

Xiaohui Bi et al.
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Short summary
Source profile is of great importance in the application of receptor models for source apportionment study as it characterizing specific sources from the chemical point of view that revealing the signatures of source emissions. In this work, a total of 3244 chemical profiles of the main primary sources across China from 1987 to 2017 were reviewed. The results highlight the urgent need for increased investigation of more specific markers beyond routine measured components to discriminate sources.
Source profile is of great importance in the application of receptor models for source...
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