Remediation Technologies of Contaminated Sites in China: Application and Spatial Clustering Characteristics

Jingjing Yu, Panpan Wang, Bei Yuan, Minghao Wang, Pengfei Shi and Fasheng Li ()
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Jingjing Yu: College of Water Sciences, Beijing Normal University, Beijing 100875, China
Panpan Wang: State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Bei Yuan: State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Minghao Wang: China Metallurgical Industry Planning and Research Institute, Beijing 100013, China
Pengfei Shi: College of Water Sciences, Beijing Normal University, Beijing 100875, China
Fasheng Li: College of Water Sciences, Beijing Normal University, Beijing 100875, China

Sustainability, 2024, vol. 16, issue 4, 1-14

Abstract: Screening remediation technologies through the lens of green, low-carbon, and sustainable development is crucial for contaminated land management. To better understand the applicability of remediation technologies, this paper explored their application in China based on a survey of 643 cases. By employing coupled analysis and local spatial autocorrelation methods, this study reveals the alignment between remediation technologies and pollutants, along with their spatial distribution and clustering patterns. Specifically, the four primary remediation technologies identified were cement kiln co-processing (CKCP), chemical oxidation/reduction (CO/CR), thermal desorption (TR), and solidification and stabilization (S/S), collectively accounting for over 90% of the cases. Additionally, our findings indicated significant variation in how different pollutants respond to remediation technologies, largely attributable to the characteristics of the pollutants. We observed High–High clustering patterns for CKCP, CO/CR, TR, and S/S. These were predominantly found in Jiangsu, Chongqing, Shandong, and Guizhou for CKCP and CO/CR and in Hebei, Jiangsu, Shanghai, and Chongqing for CO/CR. TR exhibited a High–High clustering in Shanghai, as did S/S. This research contributes to reducing the economic and resource costs associated with the trial-and-error of screening contaminated soil remediation technologies, offering valuable scientific and technological guidance for contaminated land regulation.

Keywords: land contamination; remediation technology; application characteristics; soil contaminants; spatial clustering distribution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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