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A framework for investigating the air quality variation characteristics based on the monitoring data: Case study for Beijing during 2013-2016

机译:基于监测数据调查空气质量变化特性的框架:2013 - 2016年北京案例研究

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摘要

In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors (i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations (MC) of PM2.5, SO2, NO2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6% and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions (25.8%similar to 46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation (IMCV) of PM2.5 and NO2. For different pollution periods, gradually increase of frequency of S-1 (PM2.5, 0 similar to 75 mu g/m(3)) made S-1 become the largest contributor (28.8%) to the MC of PM2.5 in 2016, it had a negative contribution (-13.1%) to the IMCV of PM2.5; obvious decreases of frequencies of heavily polluted and severely polluted dominated (44.7% and 39.5%) the IMCV of PM2.5. For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease (22.5%similar to 62.5%), and those decrease contributed most to the IMCV of PM2.5 (143.3%), SO2 (72.0%), NO2 (55.5%) and CO (190.3%); the west airflow had negative influences to the IMCV of PM2.5, NO2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy. (C) 2019 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.
机译:在本研究中,提出了一种分析框架,通过北京的案例研究来调查每年/年度空气质量变化以及来自不同因素(即季节,污染期和气流方向)的年度/年间空中质量变化和贡献从2013年到2016年。结果表明,PM2.5,SO2,NO2和CO的年平均浓度(MC)分别下降7.5%,28.6%,2013年至2016年的年平均值为7.5%,28.6%,4.6%和15.5% 。在季节中,MC在冬季将最大的分数(25.8%与46.4%相似)捐赠给年度MC,夏季MC的变化对PM2.5和NO2的年度MC变异(IMCV)贡献最大。对于不同的污染期,逐渐增加S-1的频率(PM2.5,0,类似于75 mu G / M(3))使S-1成为PM2.5的MC的最大贡献者(28.8%) 2016年,它对PM2.5的IMCV进行了负面贡献(-13.1%);明显减少严重污染和严重污染的频率(44.7%和39.5%)PM2.5的IMCV。对于不同的气流方向,南部气流下的污染物MC具有最显着的降低(22.5%,与62.5%相似),减少对PM2.5的IMCV贡献最大贡献(143.3%),SO2(72.0%), NO2(55.5%)和CO(190.3%);西部气流对PM2.5,NO2和CO的IMCV产生负面影响。框架有助于进一步分析和利用大量监测数据;分析结果可以为进一步的空气污染缓解政策提供科学支持。 (c)2019中国科学院生态环境科学研究中心。 elsevier b.v出版。

著录项

  • 来源
    《Journal of environmental sciences》 |2019年第2019期|共13页
  • 作者单位

    Beijing Univ Technol Key Lab Beijing Reg Air Pollut Control Coll Environm &

    Energy Engn Beijing 100124 Peoples R China;

    Beijing Univ Technol Key Lab Beijing Reg Air Pollut Control Coll Environm &

    Energy Engn Beijing 100124 Peoples R China;

    Beijing Univ Technol Key Lab Beijing Reg Air Pollut Control Coll Environm &

    Energy Engn Beijing 100124 Peoples R China;

    Beijing Univ Technol Key Lab Beijing Reg Air Pollut Control Coll Environm &

    Energy Engn Beijing 100124 Peoples R China;

    Beijing Univ Technol Key Lab Beijing Reg Air Pollut Control Coll Environm &

    Energy Engn Beijing 100124 Peoples R China;

    Beijing Municipal Environm Monitoring Ctr Beijing 100048 Peoples R China;

    Beijing Municipal Environm Monitoring Ctr Beijing 100048 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 环境污染及其防治;
  • 关键词

    Monitoring data analysis; Air quality variations; Airflow directions; Pollution periods; Beijing;

    机译:监测数据分析;空气质量变化;气流方向;污染期;北京;
  • 入库时间 2022-08-20 09:15:23

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