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, Beijing, 100875, China.
School of Life Sciences and School of Sustainability, Arizona State University, Tempe, AZ, 85287, USA.
Environ Manage. 2018 Jun;61(6):1048-1061. doi: 10.1007/s00267-018-1026-5. Epub 2018 Mar 21.
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 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM and PM 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 accumulation; low wind speed and high relative humidity constrained PM accumulation; and short sunshine duration and high wind speed constrained O 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.
中国在过去三十年的快速经济增长导致了许多环境问题，包括空气质量恶化。有必要更好地了解污染物在空间上随时间尺度的变化模式，以及是什么驱动了这些变化。为了解决这些问题，本研究聚焦于中国华北地区污染最严重的地区之一。我们首先量化了空气污染的空间格局，然后使用约束线方法、相关分析和逐步回归，在十年、年和季节尺度上系统地研究了空气污染与几个社会经济和气候因素的关系。研究结果表明，PM 是京津冀地区的主要空气污染物，而 PM 和 PM 则是农牧交错带的重要污染物。我们的统计分析表明，在十年尺度上，能源消耗和工业部门的国内生产总值（GDP）是空气污染的最重要因素，但气候因素的影响也可能很显著。在年和季节尺度上，高风速、低相对湿度和长日照时间会抑制 PM 的积累；低风速和高相对湿度会抑制 PM 的积累；而短日照时间和高风速会抑制 O 的积累。本研究表明，在多个时间尺度上进行分析不仅是确定空气污染主要驱动因素的必要条件，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。
