摘要
基于预报气象条件、广州及周边城市的重点企业排放清单,采用CALPUFF模型模拟2010年亚运会开幕式期间重点企业对广州市内空气质量监测点的相对环境浓度影响,据此筛选得出预报不利气象条件下工业点源应急强化减排名单,并利用GIS可视化技术分析点源强化减排效果,为空气质量保障的专家会商提供依据.广州亚运会期间点源应急强化减排实施效果表明,有针对性地对测点环境浓度影响大的企业实施强化减排措施,可有效缓解个别点位的一定范围内超标问题.本文提出的研究方法和配套的GIS软件可为不利气象条件下工业点源的应急强化减排提供辅助决策服务和数据支持.
Based on meteorological forecasts and the air emission inventories in the greater Guangzhou metroplex,the air quality impacts caused by industrial emission sources during the 2010 Guangzhou Asian Games were assessed using puff dispersion model,CALPUFF. The model results were analyzed to generate a list of emission reduction requirements to achieve targeted urban air quality under unfavorable weather conditions. Coupled with the GIS analysis tool,we present an integrated modeling assessment approach that provides policy makers information about specific emitters for contingent emission reduction using weather forecast data. The practice effectively assisted the air quality management during the Asian Games and served as a sound science-based approach for point source emission control under unfavorable meteorological conditions.
出处
《环境科学学报》
CSCD
北大核心
2014年第8期1912-1921,共10页
Acta Scientiae Circumstantiae
基金
广东省大气环境与污染控制重点实验室基金(No.x2hjB2111750)
中央高校基本科研业务费专项资金(No.2014ZM0068)~~
关键词
工业点源
空气质量应急
强化减排
大气污染模拟
辅助决策
industrial point sources
air quality emergency
emission reduction enhancing
atmospheric pollution simulation
decision support
