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Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China

机译:在多个时间尺度上了解空气污染的模式和驱动因素:以中国北方为例

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摘要

China’s rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM~(2.5)was the dominant air pollutant in the Beijing–Tianjin–Hebei region, while PM~(2.5)and PM~(10)were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM~(2.5)accumulation; low wind speed and high relative humidity constrained PM~(10)accumulation; and short sunshine duration and high wind speed constrained O~(3)accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.
机译:在过去的三十年中,中国经济的快速增长导致了许多环境问题,包括空气质量恶化。有必要更好地了解空气污染物的空间格局如何随时间尺度变化以及驱动这些变化的因素。为了解决这些问题,本研究的重点是中国北方空气污染最严重的地区之一。我们首先对空气污染的空间格局进行了量化,然后使用约束线方法,相关性分析以及年代,年度和季节尺度的逐步回归系统地研究了空气污染与若干社会经济和气候因素之间的关系。我们的结果表明,PM〜(2.5)是京津冀地区的主要空气污染物,而PM〜(2.5)和PM〜(10)都是农牧交错带(APTZ)地区的重要污染物。 。我们的统计分析表明,该行业的能源消耗和国内生产总值(GDP)是十年尺度上空气污染的最重要因素,但气候因素的影响也可能很大。在年和季节尺度上,高风速,相对湿度低和日照时间长限制了PM〜(2.5)的积累;低风速和高相对湿度限制了PM〜(10)的积累;日照时间短,风速高限制了O〜(3)的积累。我们的研究表明,在多个时间尺度上进行分析不仅是确定空气污染的主要驱动因素所必需的,而且对于理解空气污染的空间格局也很有见地,这对于城市规划和空气污染控制非常重要。

著录项

  • 来源
    《Environmental Management》 |2018年第6期|1048-1061|共14页
  • 作者单位

    Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University;

    Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University,School of Life Sciences and School of Sustainability, Arizona State University;

    Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University;

    Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University;

  • 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

    PM2.5; Air quality index; Constraint line analysis; Correlation analysis; Stepwise regression;

    机译:PM2.5;空气质量指数;约束线分析;相关分析;逐步回归;

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