中文摘要：

运用脱钩理论和VAR模型,分析了北京三类空气污染物与经济增长之间的脱钩状态、相互间动态影响方向和程度。主要结论为：1SO_2和NO_2浓度经历了从强脱钩到弱脱钩的循环过程,SO_2浓度强脱钩年份稍多;PM10浓度经历了从强脱钩—弱脱钩—强脱钩—扩张连接的循环过程,三类污染物浓度均未出现持续强脱钩状态。2三类空气污染物和经济增长间均存在长期协整关系且呈负向,SO_2浓度弹性系数最大,其次是PM10浓度,最后是NO_2浓度,表明北京空气污染治理力度取得了部分成效。3脉冲响应分析结果表明,今后一段时期内,经济增长和三类空气污染物相互间的脉冲响应值总体上是负向的,并呈波动性变化趋势。方差分解结果表明,三类空气污染物对经济增长的方差分解贡献度逐步上升,SO_2浓度贡献度最大,其次是PM10浓度,NO_2浓度最小;经济增长对SO_2浓度方差分解的贡献度最大,其次是PM10浓度和NO_2浓度,均持续上升。

英文摘要：

Using the deeoupling theory and VAR model, this paper analyzed the deeoupling state and dynamic interaction direction and degree between three kind air pollution and economic growth in Beijing, the main conclusions inluded：①The decoupling state of NO2 concentration and SO2 concentration experienced the cycle process from strong decouphng to weak decoupling, just the SO2 concentration had more strong decouphng. The decoupling state of PM10 concentration experienced the cycle process from strong decoupling to weak decoupling to strong decoupling to expansion connection, three air pollutions did not have the continuous strong decoupling state. ② There was a long term co - integration relationship between three kind air pollution and economic growth with a negative relationship, the elastic coefficient of SO2 concentration was the largest, followed by the concentration of PM10, and finally NO2 concentration, showing the success in air pollution control in Beijing. ③The impulse response analysis results showed that the next period of time, the impulse response value was generally negative between the economic growth and three kinds of air pollutants with the wave trend. Variance decomposition indicated that the three kinds of air pollutants on the decomposition of variance of economic growth cont- ribution was gradually increased, the concentration of SO2 in the largest contribution, the second was the concentration of PM10, the minimum concen- tration of NO2, the contribution of economic growth to three kinds of air pollutants variance decomposition was also gradually increased, from large to small in turn was SO2 concentration,PM10 concentration and NO2 concentration.