4.7 Article

A study on the spatiotemporal characteristics and change trend of the atmospheric environmental carrying capacity in the Jing-Jin-Ji region, China

期刊

JOURNAL OF CLEANER PRODUCTION
卷 211, 期 -, 页码 27-35

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.11.045

关键词

Jing-Jin-Ji region; Atmospheric environmental carrying capacity (AECC); Spatial-temporal characteristics; Atmospheric environmental overloading index (AEOI); Rank correlation coefficient; Fluctuating network

资金

  1. National Natural Science Foundation of China [41701121, 41871202]
  2. Beijing Youth Talents Funds [2017000020124G190]
  3. Fundamental Research Funds for the Central Universities [2-9-2017-041]
  4. China Geological Survey [DD20160227]

向作者/读者索取更多资源

The Jing-Jin-Ji region is one of the most atmospherically polluted regions in the world. In this study, the concepts, calculations, and classifications of the atmospheric environmental overloading index (AEOI) have been further developed. The AEOI has been calculated using the daily monitoring values of the concentrations of six main atmospheric pollutants from a total of 13 cities in the region from 2013.12.2 to 2017.04.18. Based on this index, the spatiotemporal characteristics and trends of the atmospheric environmental carrying capacity (AECC) are evaluated. In the temporal dimension, the regional AECC has gradually improved, and the amplitude of the average annual comprehensive AEOI has decreased, by up to 36.28% and 21.97%, respectively. In the spatial dimension, the AECC in the region decreases gradually from north to south. Regarding the change trend, decreasing comprehensive AEOI values were observed for 78.85% of the cities in the region. A significant reduction of up to 53.85% indicates a significant improvement in the regional AECC. Construction of a fluctuation network for the AEOI further confirmed the overall characteristics of the AEOI change in the atmospheric environment in this region, and the cities that are independent from the overall fluctuation could be identified. (C) 2018 Elsevier Ltd. All rights reserved.

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