引用本文: | 安 军a,b,王 丹a.基于 VAR 模型的重庆市大气污染物分析及研究(J/M/D/N,J:杂志,M:书,D:论文,N:报纸).期刊名称,2023,40(5):72-80 |
| CHEN X. Adap tive slidingmode contr ol for discrete2ti me multi2inputmulti2 out put systems[ J ]. Aut omatica, 2006, 42(6): 4272-435 |
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摘要: |
目的 研究重庆市首要空气污染物 PM2. 5 与 PM10 、SO2 、NO2 、CO、O3 的动态影响关系,为政府制定防治大气
污染措施及相关政策提供有价值的建议。 方法 收集重庆市 2021-05-01—2021-10-31 日的 PM2. 5 、PM10 、SO2 、
NO2 、CO、O3 这 6 项大气污染物的日浓度数据,利用 Eviews8. 0 软件,对原始数据进行序列平稳性检验;根据
Granger 因果检验结果选择变量,建立时间序列 VAR 模型,并检验模型的稳定性;利用广义脉冲响应分析和方差分
解分析,研究各污染物浓度对 PM2. 5 的动态影响及相对重要性。 结果 Granger 因果检验表明:PM10 、SO2 、NO2 、O3
是 PM2. 5 的 Granger 原因, CO 不是 PM2. 5 的 Granger 原因;广义脉冲响应分析表明:NO2 对 PM2. 5 的影响最大;方差
分解分析表明:NO2 的浓度对 PM2. 5 的影响最大;O3 对 PM2. 5 的影响次之,对 SO2 的影响作用最小。 所以,从长期
影响效应看,NO2 对 PM2. 5 具有长期较大的影响,SO2 对 PM2. 5 的影响最弱。 结论 防治 PM2. 5 对重庆市空气的污染
应着重控制 NO2 的污染,因此,政府应大力发展绿色交通,控制交通污染;大力监管高污染行业,将烟雾、粉尘、颗粒
物等排放量较大的行业作为工业污染源治理的重点;大力发展清洁能源,加快化石燃料替代资源的开发利用。 |
关键词: PM2. 5 VAR 模型 广义脉冲响应 方差分解分析 |
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Analysis and Study of Air Pollutants in Chongqing Based on VAR Models |
AN Juna b, WANG Dana
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a. School of Mathematics and Statistics b. Chongqing Key Laboratory of Social Economic and Applied Statistics
Chongqing Technology and Business University Chongqing 400067 China
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Abstract: |
Objective The dynamic impact relationships between PM2. 5 the primary air pollutants in Chongqing and
PM10 SO2 NO2 CO and O3 were studied to provide valuable suggestions for the government to formulate air pollution
prevention and control measures and related policies. Methods The daily concentration data of PM2. 5 PM10 SO2 NO2
CO and O3 were collected from May 1 2021 to October 31 2021 in Chongqing and the original data were tested for
sequence stationarity using software of Eviews 8. 0. Variables were selected based on the results of Granger causality tests
time series VAR models were developed and the stability of the models was tested. Generalized impulse response analysis
and variance decomposition analysis were used to investigate the dynamic effects and relative importance of each pollutant
concentration on PM2. 5. Results The results of the Granger causality test showed that PM10 SO2 NO2 and O3 were the
Granger causes of PM2. 5 and CO was not the Granger cause of PM2. 5. Generalized impulse response analysis showed that
NO2 had the greatest effect on PM2. 5. Variance decomposition analysis showed that the concentration of NO2 had the largest effect on PM2. 5 O3 had the second largest effect on PM2. 5 and SO2 had the smallest effect. Therefore in terms of
the long-term effect NO2 has a large long-term effect on PM2. 5 while SO2 has the weakest effect on PM2. 5. Conclusion
The prevention and control of PM2. 5 pollution in the air in Chongqing should focus on controlling NO2 pollution. Therefore
the government should vigorously develop green traffic and control traffic pollution vigorously supervise and regulate highpolluting industries and make industries with high emissions of smoke dust and particulate matter the focus of industrial
pollution source governance and vigorously develop clean energy and accelerate the development and utilization of
alternative fossil fuel resources. |
Key words: PM2. 5 VAR model generalized impulse response analysis of variance decomposition |