首页  |  本刊简介  |  编委会  |  投稿须知  |  订阅与联系  |  微信  |  出版道德声明  |  Ei收录本刊数据  |  封面
保定市大气污染变化趋势及特征
摘要点击 2089  全文点击 776  投稿时间:2019-12-24  修订日期:2020-04-07
查看HTML全文 查看全文  查看/发表评论  下载PDF阅读器
中文关键词  大气污染  变化趋势  污染类型  高位浓度占比  保定市
英文关键词  atmospheric pollution  variational trend  pollution type  high concentration ratio  Baoding City
作者单位E-mail
苟银寅 贵州大学资源与环境工程学院, 贵阳 550025
中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012 
18786774573@163.com 
张凯 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012 zhangkai@craes.org.cn 
李金娟 贵州大学资源与环境工程学院, 贵阳 550025  
吕文丽 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012  
竹双 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012  
黎洁 贵州大学资源与环境工程学院, 贵阳 550025
中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012 
 
何珊珊 河北省保定环境监测中心, 保定 071000  
郑悦 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012  
支敏康 中国环境科学研究院环境基准与风险评估国家重点实验室, 北京 100012  
中文摘要
      为了解保定市近年来大气污染变化趋势和污染特征,对2013~2018年保定市空气质量和大气污染物浓度进行分析,结果表明:①从2013~2018年保定市综合指数由11.6下降到6.6,重度污染天数由114 d下降到27 d,重度污染时污染物累积浓度由57.34%下降到20.59%.表明2013~2018年保定市空气质量逐年改善,不仅重污染天数减少、污染物年均浓度降低,而且重污染时污染物累积浓度的占比也在下降,同时与"2+26"城市平均浓度水平的差距越来越小.②夏季ρ(O3-8h)逐年上升,2017年和2018年由O3导致的重污染天分别占当年重污染天的17.0%和14.8%,臭氧污染逐渐突出;秋季NO2特征值高于SO2、CO、PM2.5和PM10,说明秋季污染类型偏机动车型;冬季污染类型由2013~2014年的偏燃煤型转向2015~2018年的偏燃煤型和不完全燃烧的混合影响.③2016、2017和2018年高污染季PM2.5高位累积浓度占比较2015年同期分别下降5.56%、6.21%和2.58%,是6种污染物中降幅最大的;其次为PM10;SO2和NO2降幅较小,说明应急措施对保定市重污染期间颗粒物削峰效果优于气态污染物.2018年高污染季重污染事件中,偏燃煤型污染较2017年高污染季有所增加,说明燃煤仍是保定市需要控制的污染源之一.综上,保定市秋季应加强对机动车的管控,冬季由原来的控煤措施逐渐转变为控煤和控柴相结合;未来的大气污染防治重点应加强O3污染治理.
英文摘要
      To understand the trends and characteristics of air pollution in Baoding in recent years, an analysis of air quality and air pollutant concentrations in Baoding from 2013 to 2018 was carried out. The results showed that: 1 from 2013 to 2018, the comprehensive index of Baoding dropped from 11.6 to 6.6, the days of severe pollution decreased from 114 days to 27 days, and cumulative concentration of pollutants during severe pollution decreased from 57.34% to 20.59%. This indicated that the air quality of Baoding city has improved year on year from 2013 to 2018. Not only has the number of heavy pollution days and the annual average concentration of pollutants decreased, but also the proportion of cumulative concentrations of pollutants during heavy pollution has decreased. the difference between the average concentration level of Baoding city and "2+26" Cities is getting smaller and smaller. ② Summer ρ(O3-8h) increased year on year. In 2017 and 2018, the heavy pollution days caused by O3 accounted for 17.0% and 14.8% of the heavy pollution days of the year, respectively, and the ozone pollution gradually became prominent; the characteristic value of NO2 in autumn was higher than that of SO2, CO, PM2.5, and PM10, indicating that the type of pollution in autumn was more motorized. The sources of pollution in winter changed from the partial combustion of coal in 2013-2014 to a mixed influence of partial combustion of coal and incomplete combustion in 2015-2018. ③ In 2016, 2017, and 2018, a high cumulative concentrations of PM2.5 during the high pollution season that accounted for 5.56%, 6.21%, and 2.58% declined as compared to that during the same period in 2015; this was the largest decline among the six pollutants; PM10 followed; The decreases of SO2 and NO2 were small, indicating that the emergency measures were better in cutting peaks of particulate matter than the gaseous pollutants during heavy pollution in Baoding. In a heavy pollution event during the high pollution season in 2018, partial-burning coal-type pollution increased as compared to that during the high pollution season in 2017, indicating that the coal combustion was still one of the pollution sources that Baoding city needed to control. In summary, Baoding should strengthen the management and control of motor vehicles in autumn, and gradually change from the original coal control measures to a combination of coal control and diesel control in winter; in the future, the focus of air pollution prevention and control should be strengthened toward O3 pollution.

您是第54223150位访客
主办单位:中国科学院生态环境研究中心 单位地址:北京市海淀区双清路18号
电话:010-62941102 邮编:100085 E-mail: hjkx@rcees.ac.cn
本系统由北京勤云科技发展有限公司设计  京ICP备05002858号-2