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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 1
Geosci. Model Dev., 8, 115–128, 2015
https://doi.org/10.5194/gmd-8-115-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 8, 115–128, 2015
https://doi.org/10.5194/gmd-8-115-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 30 Jan 2015

Model description paper | 30 Jan 2015

Assessing the nonlinear response of fine particles to precursor emissions: development and application of an extended response surface modeling technique v1.0

B. Zhao1, S. X. Wang1,2, J. Xing3, K. Fu1, J. S. Fu4, C. Jang3, Y. Zhu5, X. Y. Dong4, Y. Gao4,6, W. J. Wu1, J. D. Wang1, and J. M. Hao1,2 B. Zhao et al.
  • 1State Key Joint Laboratory of Environment 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
  • 3US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA
  • 4Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee 37996, USA
  • 5School of Environmental Science and Engineering, South China University of Technology, Guangzhou 510006, China
  • 6Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington 99352, USA

Abstract. An innovative extended response surface modeling technique (ERSM v1.0) is developed to characterize the nonlinear response of fine particles (PM2.5) to large and simultaneous changes of multiple precursor emissions from multiple regions and sectors. The ERSM technique is developed based on the conventional response surface modeling (RSM) technique; it first quantifies the relationship between PM2.5 concentrations and the emissions of gaseous precursors from each single region using the conventional RSM technique, and then assesses the effects of inter-regional transport of PM2.5 and its gaseous precursors on PM2.5 concentrations in the target region. We apply this novel technique with a widely used regional chemical transport model (CTM) over the Yangtze River delta (YRD) region of China, and evaluate the response of PM2.5 and its inorganic components to the emissions of 36 pollutant–region–sector combinations. The predicted PM2.5 concentrations agree well with independent CTM simulations; the correlation coefficients are larger than 0.98 and 0.99, and the mean normalized errors (MNEs) are less than 1 and 2% for January and August, respectively. It is also demonstrated that the ERSM technique could reproduce fairly well the response of PM2.5 to continuous changes of precursor emission levels between zero and 150%. Employing this new technique, we identify the major sources contributing to PM2.5 and its inorganic components in the YRD region. The nonlinearity in the response of PM2.5 to emission changes is characterized and the underlying chemical processes are illustrated.

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