Spatiotemporal assessment and scenario simulation of the risk potential of industrial sites at the regional scale

Yefeng Jiang; Xi Guo; Yingcong Ye; Zhe Xu; Yin Zhou; Fang Xia; Zhou Shi

doi:10.1016/j.scitotenv.2023.167537

Spatiotemporal assessment and scenario simulation of the risk potential of industrial sites at the regional scale

Sci Total Environ. 2024 Jan 1:906:167537. doi: 10.1016/j.scitotenv.2023.167537. Epub 2023 Oct 2.

Authors

Yefeng Jiang¹, Xi Guo², Yingcong Ye², Zhe Xu², Yin Zhou³, Fang Xia⁴, Zhou Shi⁵

Affiliations

¹ Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Jiangxi Agricultural University, Nanchang 330045, China; Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
² Key Laboratory of Poyang Lake Watershed Agricultural Resources and Ecology (Co-construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Jiangxi Agricultural University, Nanchang 330045, China.
³ Institute of Land and Urban-Rural Development, Zhejiang University of Finance and Economics, Hangzhou 310018, China.
⁴ College of Economics and Management, Zhejiang A&F University, Hangzhou 311300, China.
⁵ Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China. Electronic address: shizhou@zju.edu.cn.

PMID: 37793450
DOI: 10.1016/j.scitotenv.2023.167537

Abstract

Spatiotemporal risk and future evolutionary distribution characteristics of industrial sites are crucial for regional environmental supervision. However, traditional site survey methods have long cycles, high costs, and small coverage and usually only consider the static risk of a single industrial site to a single receptor. Low-cost, large-scale, and long-term multi-source data can compensate for the shortcomings of traditional site surveys. Previous studies have rarely considered the spatiotemporal heterogeneity of industrial sites and assessed their dynamic risks at the regional scale. This study used China's Yangtze River Delta Urban Agglomeration as the study area. We assessed the risk potential of industrial sites from 2000 to 2020 using multi-source and multiperiod data. We also simulated the risk potential for 2030 and 2050 using a patch-generating land use simulation (PLUS) model under different scenarios. The results indicated that the proportion of medium- and high-risk potential grids from 2000 to 2020 ranged from 2.53 % to 5.61 % in the study area, with the vast majority of areas (94.39 %-97.47 %) having low- or no-risk potential. The PLUS model exhibited remarkable reliability from 2005 to 2020, with the overall accuracy, Kappa coefficient, and Moran's index ranging from 83 % to 89 %, 0.38 to 0.59, and 0.34 to 0.56, respectively. The future prediction results indicated that the number of high-risk potential grids (>5 %) showed an upward trend under natural development scenarios in 2030 and 2050 and a downward trend under the ten-chapter soil pollution action plan or strict control scenarios. This study provides vital information for addressing the challenges of industrial site management and environmental risks in similar regions.

Keywords: Industrial site; Risk assessment; Spatiotemporal simulation; Yangtze River Delta urban agglomerations.