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Discussion papers
https://doi.org/10.5194/acp-2019-183
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2019-183
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 22 May 2019

Submitted as: research article | 22 May 2019

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

Development and application of observable response indicators for design of an effective ozone and fine particle pollution control strategy in China

Jia Xing1,2, Dian Ding1,2, Shuxiao Wang1,2, Zhaoxin Dong1,2, James T. Kelly3, Carey Jang3, Yun Zhu4, and Jiming Hao1,2 Jia Xing et al.
  • 1State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
  • 2State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
  • 3Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
  • 4College of Environmental Science & Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou, China

Abstract. Designing effective control policies requires efficient quantification of the nonlinear response of air pollution to emissions. However, neither the current observable indicators nor the current indicators based on response-surface modeling (RSM) can fulfill this requirement. Therefore, this study developed new observable RSM-based indicators and applied them to ambient fine particulate matter (PM2.5) and ozone (O3) pollution control in China. The performance of these observable indicators in predicting O3 and PM2.5 chemistry was compared with that of the current RSM-based indicators. H2O2 × HCHO/NO3 and total ammonia ratio, which exhibited the best performance among indicators, were proposed as new observable O3- and PM2.5-chemistry indicators, respectively. Strong correlations between RSM-based and traditional observable indicators suggested that a combination of ambient concentrations of certain chemical species can serve as an indicator to approximately quantify the response of O3 and PM2.5 to changes in precursor emissions. The observable RSM-based indicator for O3 (observable peak ratio) effectively captured the strong NOx-saturated regime in January and the NOx-limited regime in July, as well as the strong NOx-saturated regime in northern and eastern China and their key regions, including the Yangtze River Delta and Pearl River Delta. The observable RSM-based indicator for PM2.5 (observable flex ratio) also captured strong NH3-poor condition in January and NH3-rich condition in April and July, as well as NH3-rich in northern and eastern China and the Sichuan Basin. Moreover, analysis of these newly developed observable response indicators suggested that the simultaneous control of NH3 and NOx emissions produces greater benefits in provinces with higher PM2.5 exposure by up to 12 µg m−3 PM2.5 per 10 % NH3 reduction compared with NOx control only. Control of volatile organic compound (VOC) emissions by as much as 40 % of NOx controls is necessary to obtain the co-benefits of reducing both O3 and PM2.5 exposure at the national level when controlling NOx emissions. However, the VOC-to-NOx ratio required to maintain benefits varies significantly from 0 to 1.2 in different provinces, suggesting that a more localized control strategy should be designed for each province.

Jia Xing et al.
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Short summary
The study aims at addressing the challenge in efficient quantification of the nonlinear response of air pollution to precursor emission perturbations. The new-developed observable response indicators can be easily calculated by a combination of ambient concentrations of certain species. Their capability in representing the spatial and temporal variation of PM2.5 and O3 chemistry has also been well evaluated and applied in China.
The study aims at addressing the challenge in efficient quantification of the nonlinear response...
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