Responses of future air quality to emission controls over North Carolina,Part II: Analyses of future-year predictions and their policy implications |
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| Authors: | Yang Zhang Xiao-Huan Liu Kristen M Olsen Wen-Xing Wang Bebhinn A Do George M Bridgers |
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| Institution: | 1. Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA;2. Environment Research Institute, Shandong University, 27 Shanda Nanlu, Jinan, Shandong Province, PR China 250100;3. Division of Air Quality, North Carolina Department of Environment and Natural Resources, Raleigh, NC 27699, USA;1. SAS Institute Inc., Cary, NC, USA;2. North Carolina State University, Raleigh, NC, USA;1. Ocean University of China, Qingdao 266100, Shandong Province, PR China;2. North Carolina State University, Department of Marine, Earth, and Atmospheric Sciences, Campus Box 8208, NCSU, Raleigh, NC 27695, USA;1. Institut für Meteorologie, Freie Universittit Berlin, Carl–Heinrich–Becker–Weg 6–10, 12165, Berlin, Germany;2. Faculty of Civil Eng., Shahrood University, Shahrood, Iran;3. Senate Department for Urban Development and the Environment, Berlin, Germany;1. Departamento de Engenharia Electrotécnica, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal;2. CISUC - Centre for Informatics and Systems of the University of Coimbra, Pólo II da Universidade de Coimbra, 3030-290 Coimbra, Portugal;1. Computer School, Wuhan University, Wuhan 430072, China;2. State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China;3. Centre for Quantum Computation and Intelligent Systems, Faculty of Engineering and Information Technology, University of Technology, Sydney, NSW 2007, Australia |
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| Abstract: | The MM5/CMAQ system evaluated in Part I paper is applied to study the impact of emission control on future air quality over North Carolina (NC). Simulations are conducted at a 4-km horizontal grid resolution for four one-month periods, i.e., January, June, July, and August 2009 and 2018. Simulated PM2.5 in 2009 and 2018 show distribution patterns similar to those in 2002. PM2.5 concentrations over the whole domain in January and July reduced by 5.8% and 23.3% in 2009 and 12.0% and 35.6% in 2018, respectively, indicating that the planned emission control strategy has noticeable effects on PM2.5 reduction in this region, particularly in summer. More than 10% and 20% of 1-h and 8-h O3 mixing ratios are reduced in July 2009 and 2018, respectively, demonstrating the effectiveness of emission control for O3 reduction in summer. However, O3 mixing ratios in January 2009 and 2018 increase by more than 5% because O3 chemistry is VOC-limited in winter and the effect of NOx reduction dominates over that of VOC reduction under such a condition. The projected emission control simulated at 4-km will reduce the number of sites in non-attainment for max 8-h O3 from 49 to 23 in 2009 and to 1 in 2018 and for 24-h average PM2.5 from 1 to 0 in 2009 and 2018 based on the latest 2008 O3 and 2006 PM2.5 standards. The variability in model predictions at different grid resolutions contributes to 1–3.8 ppb and 1–7.9 μg m?3 differences in the projected future-year design values for max 8-h O3 and 24-h average PM2.5, respectively. |
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