苏州市机动车尾气中主要污染物特征分析
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摘要
为了解苏州市机动车尾气中主要污染物浓度特征,运用SPSS19.0时间序列建模器,预测了未来5年(2017—2021年)苏州市机动车保有量,分析和对比了苏州市路边站点和国控站点的主要污染物数据。结果表明,未来5年,苏州市机动车保有量呈现上升趋势,2020年机动车保有量将达到373.1万辆,相比2014年增加约37.5%;路边站点NO2值略高于国控站点,但差异不显著;路边站点CO值明显高于国控站点;路边站点PM10和PM2.5值总体略高于国控站点;路边站点苯系物值高于国控站点。
In order to study the characteristics of the main pollutants in the vehicle exhausting gas in Suzhou,the SPSS19.0 time series modeler was used to predict Suzhou motor vehicle ownership in the next 5 years(2017—2021),the main pollutant concentration monitoring data of the roadside station and the national control point in Suzhou were analyzed and compared.The results showed that Suzhou motor vehicle ownership shows an upward trend in next 5 years.Motor vehicle ownership will reach 3.731 million in 2020,increase 37.5%(compared to 2014).The concentration of NO2 in roadside stations was slightly higher than that in national control city points with no significant difference.The concentration of CO in roadside stations was significantly higher than that in national control city points.The concentration of PM_(10) and PM_(2.5) in roadside stations was slightly higher than that in national control city points.The concentration of benzenes in roadside stations was higher than that in national control city points.
In order to study the characteristics of the main pollutants in the vehicle exhausting gas in Suzhou,the SPSS19.0 time series modeler was used to predict Suzhou motor vehicle ownership in the next 5 years(2017—2021),the main pollutant concentration monitoring data of the roadside station and the national control point in Suzhou were analyzed and compared.The results showed that Suzhou motor vehicle ownership shows an upward trend in next 5 years.Motor vehicle ownership will reach 3.731 million in 2020,increase 37.5%(compared to 2014).The concentration of NO2 in roadside stations was slightly higher than that in national control city points with no significant difference.The concentration of CO in roadside stations was significantly higher than that in national control city points.The concentration of PM_(10) and PM_(2.5) in roadside stations was slightly higher than that in national control city points.The concentration of benzenes in roadside stations was higher than that in national control city points.
引文
[1]环境保护部.中国机动车环境管理年报(2017)[EB/OL].(2017-06-03)[2018-08-20]. http://www. mee. gov. cn/gkml/sthjbgw/qt/201706/t20170603_415265. htm.
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[3]江苏省统计局.江苏省统计年鉴[R].北京:中国统计出版社,2017.
[4]环境保护部.环境空气质量监测点位布设技术规范:HJ 664—2013[S].北京:中国标准出版社,2013.
[5]迈克尔.阿拉贝.空气中的烟、雾、酸——明天的空气会怎么样?[M].上海:上海科学技术文献出版社,2014.
[6]姚志良.机动车能源消耗及污染物排放与控制[M].北京:化学工业出版社,2012.
[7]游秋雯,葛蕴珊,尤可为,等.汽油车非常规污染物排放特性研究[J].环境科学,2009,30(2):336-341.
[8]魏山峰,滕曼,付强,等.车辆限行前后奥运场馆附近空气中苯系物污染特征与来源[J].中国环境监测,2007,23(6):48-52.