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Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013-2014

机译:2013-2014年中国31个省会城市六种标准空气污染物的时空变化

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摘要

Long-term air pollution data with high temporal and spatial resolutions are needed to support the research of physical and chemical processes that affect the air quality, and the corresponding health risks. However, such datasets were not available in China until recently. For the first time, this study examines the spatial and temporal variations of PM_(2.5), PM_(10), CO, SO_2, NO_2, and 8 h O_3 in 31 capital cities in China between March 2013 and February 2014 using hourly data released by the Ministry of Environmental Protection (MEP) of China. The annual mean concentrations of PM_(2.5) and PM_(10) exceeded the Chinese Ambient Air duality Standards (CAAQS), Grade 1 standards (15 and 40 μg/m~3 for PM_(2.5) and PM_(10), respectively) for all cities, and only Haikou, Fuzhou and Lasa met the CAAQS Grade Ⅱ standards (35 and 70 μg/m~3 for PM_(2.5) and PM_(10), respectively). Observed PM_(2.5), PM_(10), CO and SO_2 concentrations were higher in cities located in the North region than those in the West and the South-East regions. The number of non-attainment days was highest in the winter, but high pollution days were also frequently observed in the South-East region during the fall and in the West region during the spring. PM_(2.5) was the largest contributor to the air pollution in China based on the number of non-attainment days, followed by PM_(10), and O_3. Strong correlation was found between different pollutants except for O_3. These results suggest great impacts of coal combustion and biomass burning in the winter, long range transport of windblown dust in the spring, and secondary aerosol formation throughout the year. Current air pollution in China is caused by multiple pollutants, with great variations among different regions and different seasons. Future studies should focus on improving the understanding of the associations between air quality and meteorological conditions, variations of emissions in different regions, and transport and transformation of pollutants in both intra- and inter-regional contexts.
机译:需要具有高时空分辨率的长期空气污染数据,以支持影响空气质量以及相应健康风险的物理和化学过程的研究。但是,此类数据集直到最近才在中国可用。本研究首次使用每小时发布的数据调查了2013年3月至2014年2月间中国31个首都城市PM_(2.5),PM_(10),CO,SO_2,NO_2和8 h O_3的时空变化由中国环境保护部(MEP)提供。 PM_(2.5)和PM_(10)的年平均浓度超过了中国环境空气二元性标准(CAAQS),1级标准(PM_(2.5)和PM_(10)分别为15和40μg/ m〜3对于所有城市,只有海口,福州和拉萨达到了CAAQSⅡ级标准(PM_(2.5)和PM_(10)分别为35和70μg/ m〜3。观察到北部地区城市的PM_(2.5),PM_(10),CO和SO_2浓度高于西部和东南地区的城市。冬季,未达标的天数最多,但秋季和秋季的东南部和春季的西南部也经常出现高污染天。按达标天数计算,PM_(2.5)是造成中国空气污染的最大因素,其次是PM_(10)和O_3。除O_3外,其他污染物之间也存在强相关性。这些结果表明,冬季煤炭燃烧和生物质燃烧,春季风吹尘的远距离运输以及全年的二次气溶胶形成都将产生重大影响。中国目前的空气污染是由多种污染物造成的,不同地区,不同季节之间存在很大差异。未来的研究应侧重于增进对空气质量与气象条件,不同区域排放变化以及区域内和区域间污染物的运输和转化之间的关联的理解。

著录项

  • 来源
    《Environment international》 |2014年第12期|413-422|共10页
  • 作者单位

    Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley, CA 9472 0, USA;

    Department of Civil Engineering, Texas A&M University, College Station, TX 77843, USA;

    Department of Gvil and Environmental Engineering, University of California, Davis, Davis, CA 95616, USA;

    Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Spatial variation; Temporal variation; Criteria pollutants; PM_(2.5); Provincial capital cities; China;

    机译:空间变化;时间变化;标准污染物;PM_(2.5);省会城市;中国;

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