1School of Environment, and State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, China
2The U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
3School of Environmental Science and Engineering, South China University of Technology, Guangzhou 510006, China
Received: 06 Sep 2010 – Discussion started: 07 Dec 2010
Abstract. Statistical response surface methodology (RSM) is successfully applied for a Community Multi-scale Air Quality model (CMAQ) analysis of ozone sensitivity studies. Prediction performance has been demonstrated through cross validation, out-of-sample validation and isopleth validation. Sample methods and key parameters, including the maximum numbers of variables involved in statistical interpolation and training samples have been tested and selected through computational experiments. Overall impacts from individual source categories which include local/regional NOx and VOC emission sources and NOx emissions from power plants for three megacities – Beijing, Shanghai and Guangzhou – were evaluated using an RSM analysis of a July 2005 modeling study. NOx control appears to be beneficial for ozone reduction in the downwind areas which usually experience high ozone levels, and NOx control is likely to be more effective than anthropogenic VOC control during periods of heavy photochemical pollution. Regional NOx source categories are strong contributors to surface ozone mixing ratios in three megacities. Local NOx emission control without regional involvement may raise the risk of increasing urban ozone levels due to the VOC-limited conditions. However, local NOx control provides considerable reduction of ozone in upper layers (up to 1 km where the ozone chemistry is NOx-limited) and helps improve regional air quality in downwind areas. Stricter NOx emission control has a substantial effect on ozone reduction because of the shift from VOC-limited to NOx-limited chemistry. Therefore, NOx emission control should be significantly enhanced to reduce ozone pollution in China.
Revised: 18 May 2011 – Accepted: 25 May 2011 – Published: 31 May 2011
Xing, J., Wang, S. X., Jang, C., Zhu, Y., and Hao, J. M.: Nonlinear response of ozone to precursor emission changes in China: a modeling study using response surface methodology, Atmos. Chem. Phys., 11, 5027-5044, doi:10.5194/acp-11-5027-2011, 2011.