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典型城市臭氧污染源贡献及控制策略费效评估
引用本文:盛叶文,朱云,陶谨,陈享华,刘可旋,CareyJang,王书肖,朱振华,危浩,袁颖枝. 典型城市臭氧污染源贡献及控制策略费效评估[J]. 环境科学学报, 2017, 37(9): 3306-3315
作者姓名:盛叶文  朱云  陶谨  陈享华  刘可旋  CareyJang  王书肖  朱振华  危浩  袁颖枝
作者单位:华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006,1. 华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006;2. 国家环境保护大气复合污染来源与控制重点实验室, 清华大学环境学院, 北京 100084,东莞市环境保护局, 东莞 523009,东莞市环境保护局, 东莞 523009,东莞市环境保护局, 东莞 523009,USEPA/Office of Air Quality Planning & Standards, RTP, NC27711, USA,国家环境保护大气复合污染来源与控制重点实验室, 清华大学环境学院, 北京 100084,广州城环云信技术研发有限公司, 广州 510006,华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006,华南理工大学环境与能源学院, 广东省大气环境与污染控制重点实验室, 广州 510006
基金项目:2016国家重点研发计划(No.2016YFC0207606);广东省省级科技计划项目(No.2016A020221001,2014A050503019);NSFC-广东联合基金超级计算科学应用研究专项资助(第二期,U1501501);中央高校基本科研业务费专项资金资助(No.x2hjD2160320)
摘    要:东莞是珠三角O_3污染最严重的城市,使用RSM/CMAQ(曲面响应模型)法分析了珠三角区域人为排放的NO_x和VOCs对东莞市O_3浓度变化源贡献.2014基准年分析结果表明,扣除模型域外区域传输及天然源排放对O_3本底浓度贡献(41.00%)后,东莞本地VOCs排放对O_3贡献最大(18.50%),珠三角区域NO_x减排率13%时可持续降低东莞市O_3浓度.进一步使用ABa CAS-SE(空气污染控制成本效益与达标评估系统)对2017、2020、2025东莞市3个未来年O_3污染控制情景进行了费效评估.评估结果显示,NO_x和VOCs控制比例相对较低的2017年控制情景人体健康效益/区域控制成本比约为1.1;而控制比例相对较高的2025年东莞O_3达标情景效益成本比仅为0.1.这说明,在高减排率情景下,以末端治理为主的控制措施经济可行性较差,需综合采取产业/能源结构调整、清洁生产等措施实现NO_x和VOCs的大比例减排,实现东莞O_3的稳定达标.今后将进一步研究NO_x和VOCs减排对PM_(2.5)环境浓度及健康效益影响,开展多目标污染物协同控制费效评估.

关 键 词:臭氧污染  曲面响应模型  源贡献分析  污染控制  费效评估
收稿时间:2017-02-20
修稿时间:2017-03-23

Source contribution analysis of ambient ozone and cost-benefit assessment of control scenarios in a typical ozone-polluted city
SHENG Yewen,ZHU Yun,TAO Jin,CHEN Xianghu,LIU Kexuan,Carey Jang,WANG Shuxiao,ZHU Zhenhu,WEI Hao and YUAN Yingzhi. Source contribution analysis of ambient ozone and cost-benefit assessment of control scenarios in a typical ozone-polluted city[J]. Acta Scientiae Circumstantiae, 2017, 37(9): 3306-3315
Authors:SHENG Yewen  ZHU Yun  TAO Jin  CHEN Xianghu  LIU Kexuan  Carey Jang  WANG Shuxiao  ZHU Zhenhu  WEI Hao  YUAN Yingzhi
Affiliation:Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006,1. Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006;2. State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084,Environmental Protection of Dongguan, Dongguan 523009,Environmental Protection of Dongguan, Dongguan 523009,Environmental Protection of Dongguan, Dongguan 523009,USEPA/Office of Air Quality Planning & Standards, RTP, NC 27711, USA,State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084,Guangzhou Urban Environmental Cloud Information Technology R & D Company Limited, Guangzhou 510006,Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006 and Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou 510006
Abstract:Dongguan is one of the most ozone-polluted city over the Pearl River Delta (PRD) region in China. We applied the advanced RSM/CMAQ (Responds Surface Model/Community Multi-scale Air Quality) system to analyze the source contribution of anthropogenic emissions of NOx and VOCs for ambient O3 in Dongguan. The base-year analysis in 2014 indicates that local VOCs emissions has the largest contribution to O3 in Dongguan (18.50%) after excluding the background O3 contributions (41%) from transported regional emissions outside model domain and the natural sources. The emission reduction of NOx in the PRD can further lower the ambient O3 concentration in Dongguan when the reduction rate of NOx is greater than >13% comparing to the NOx emissions in the base year of 2014. We further used the ABaCAS-SE (Air Benefit and Cost and Attainment Assessment System-Streamlined Edition) to assess the cost-benefit of O3 pollution control scenarios in 3 future projection years, 2017, 2020 and 2025, in Dongguan. The simulation results show that the benefit/cost ratio (human health benefit over emissions control cost) is about 1.1 when the reduction rate of NOx and VOCs emissions is relatively low in 2017, and the rate will drop down to only 0.1 in 2025 when the control rates of NOx and VOCs become higher. The low rate of benefit/cost means that terminal control technologies-based scenarios is not suitable for the higher emission reduction rates because of potential lower economic feasibility. The source control policies, such as adjusting the comprehensive industrial & energy structure, popularizing cleaner procession technologies etc., should be promoted to reach the attainment goal of O3 national standard in Dongguan by 2025. However, the control benefit of PM2.5 due to NOx and VOCs emissions reduction is not considered in this study and further investigation is needed for multi-pollutant control strategies.
Keywords:ozone pollution  response surface model  source contribution analysis  pollution control  cost-benefit assessment
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