摘要
中国的灰霾十分严重,如何有效地控制某一地区的PM_(2.5)浓度,同时保证GDP的中高速增长,需要建立GDP-PM_(2.5)的量化关系模型,做好宏观预测。充分利用城市大气污染物、气象、经济的多年统计数据,以及该地PM_(2.5)源解析、源清单和大气边界层信息,从中确定2种重要的辅助变量,一是单位GDP某种大气污染物排放量,二是各污染物形成PM_(2.5)的转化率,它们把GDP、PM_(2.5)和污染物排放量联系起来。再运用系统动力学(SD)建立GDP和PM_(2.5)动态关系模型。文章以东莞为例,预测了"确保经济、确保环境、源头治理、全面治理"这4种模式下污染物减排措施对GDP和PM_(2.5)的影响,并提出定量的减排建议。预测结果显示,"全面治理"的发展模式较为合理,既能保证经济的可持续发展,又能实现东莞PM_(2.5)减排目标。
For the purpose of controlling regional PM2.5 concentration and,at the same time,keeping GDP growth in a medium-high speed way,a GDP-PM2.5 quantitative model was in need for better macro-prediction. In this study,a city＇s different kinds of statistics data were applied such as urban air pollutants,meteorology and economy,as well as the source apportionment information of PM2.5,the pollution source list and atmospheric boundary layer;thereby two important auxiliary variables could be calculated：one is the amount of a certain air pollutant emission per unit of GDP and the other is the conversion rate of each pollutant transforming to PM2.5,by which the amounts of GDP,PM2.5 and pollutants emissions could be linked. Then a GDP-PM2.5 dynamic model was established by system dynamics（SD）. In a case study of Dongguan City in Guangdong Province,this model was used to predict the impacts of emissions reduction in 4 patterns,i.e. to guarantee economic development,to safeguard environment,to control pollution from the source,and comprehensive management,on GDP and PM2.5 concentration,and quantitative suggestions were thereby proposed regarding emissions reduction. According to the prediction results,the development scenario of Comprehensive Management was relatively reasonable and acceptable,which can guarantee the sustainable development of economy,and realize the PM2.5 emissions reduction target in the City.
出处
《环境科学与技术》
CAS
CSCD
北大核心
2016年第4期161-167,共7页
Environmental Science & Technology
基金
国家自然科学基金项目(71171089)
东莞市PM2.5污染特征与防治对策研究(东采单[2013]222号)
关键词
系统动力学
GDP
PM2.5
预测
污染减排
东莞市
system dynamics
GDP
PM2.5
prediction
air pollutants emission reduction
Dongguan city
