Effectiveness of predicting spatial contaminant distributions at industrial sites using partitioned interpolation method

doi:10.1007/s10653-020-00673-5

	Effectiveness of predicting spatial contaminant distributions at industrial sites using partitioned interpolation method
	Qiao, Pengwei 1; Yang, Sucai 1; Wei, Wenxia 1; Li, Peizhong 1; Cheng, Yanjun 1; Liang, Shuang 1; Lei, Mei 2; Chen, Tongbin 2
刊名	ENVIRONMENTAL GEOCHEMISTRY AND HEALTH
	2020-07-22
页码	14
关键词	Data partitioning Accuracy Improvement degree Effectiveness Industrial sites Soil pollution
ISSN号	0269-4042
DOI	10.1007/s10653-020-00673-5
通讯作者	Yang, Sucai(liepi_yangsc@163.com) ; Wei, Wenxia(13693649137@163.com)
英文摘要	Soil pollution at industrial sites is an important issue in China and in most other regions of the world. The accurate prediction of the spatial distribution of pollutants at contaminated industrial sites is a requirement for the development of most soil remediation strategies, and is commonly performed using spatial interpolation methods. However, significant and abrupt variations in the spatial distribution of pollutants decrease prediction accuracy. During this study, the use of partition interpolation methods was applied to benzo fluoranthene in four soil layers at a contaminated site to determine their ability to improve prediction accuracy in comparison to unpartitioned methods. The examined methods for partitioned interpolation included inverse distance weighting (IDW), radial basis function (RBF), and ordinary kriging (OK). The prediction results of the three methods for partitioned interpolation were compared, and the applicability of partition interpolation was determined. The prediction error associated with the partitioned interpolation methods decreased by 70% compared to unpartitioned interpolation. The prediction accuracy of IDW-based partition interpolation was higher than that of RBF- and OK-based partition interpolation techniques, and it was suitable for identification of highly polluted areas. Partition interpolation is also applicable to 12 other PAHs controlled by USEPA that can be detected, and the prediction effects could also verify this interpolation choice. In addition, the results also demonstrated that the more the maximum concentration deviated from the "norm", the greater the prediction error was caused by the smoothing effects of the interpolation models. These results suggest that the partition interpolation with IDW method can be effectively used to obtain relatively accurate spatial contaminant distribution information, and to identify highly polluted areas.
资助项目	China Postdoctoral Science Foundation[2019M650552]
WOS关键词	HEAVY-METALS ; SOIL ; PAHS ; ELEMENTS ; CHINA ; HYDROCARBONS ; SEDIMENTS ; ACCURACY ; XUZHOU ; RISK
WOS研究方向	Engineering ; Environmental Sciences & Ecology ; Public, Environmental & Occupational Health ; Water Resources
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000551034600001
资助机构	China Postdoctoral Science Foundation
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/158280]
专题	中国科学院地理科学与资源研究所
通讯作者	Yang, Sucai; Wei, Wenxia
作者单位	1.Environm Protect Res Inst Light Ind, Beijing Key Lab Remediat Ind Pollut Sites, Beijing 100089, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Qiao, Pengwei,Yang, Sucai,Wei, Wenxia,et al. Effectiveness of predicting spatial contaminant distributions at industrial sites using partitioned interpolation method[J]. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH,2020:14.
APA	Qiao, Pengwei.,Yang, Sucai.,Wei, Wenxia.,Li, Peizhong.,Cheng, Yanjun.,...&Chen, Tongbin.(2020).Effectiveness of predicting spatial contaminant distributions at industrial sites using partitioned interpolation method.ENVIRONMENTAL GEOCHEMISTRY AND HEALTH,14.
MLA	Qiao, Pengwei,et al."Effectiveness of predicting spatial contaminant distributions at industrial sites using partitioned interpolation method".ENVIRONMENTAL GEOCHEMISTRY AND HEALTH (2020):14.