Feasibility of using visible and near-infrared reflectance spectroscopy to monitor heavy metal contaminants in urban lake sediment

doi:10.1016/j.catena.2017.11.020

CORC > 武汉植物园 > 中国科学院武汉植物园

	Feasibility of using visible and near-infrared reflectance spectroscopy to monitor heavy metal contaminants in urban lake sediment
	Jiang, Qinghu 1; Liu, Minxia 1,2; Wang, Jun 1; Liu, Feng 1
刊名	CATENA
	2018-03-01
卷号	162 页码:72-79
关键词	Heavy metal Urban lake sediments Visible and near-infrared reflectance spectroscopy Spectral feature selection Predictive mechanism
ISSN号	0341-8162
DOI	10.1016/j.catena.2017.11.020
英文摘要	Contamination of urban lake sediments by heavy metals is a major threat to environmental safety and human health due to its high toxicity and persistence. This paper aims to examine the feasibility of using visible and near-infrared reflectance spectroscopy (VNIRS) to rapidly quantify heavy metals (i.e., As, Cd, Cr, Cu, Hg, Ni, Pb and Zn) in urban lake sediments. Lake sediment samples (n = 103) were collected from the East Lake in Wuhan, China. Partial least squares regression (PLSR) calibration models were developed for the heavy metals estimation. Genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) were compared to test whether spectral feature selection could improve heavy metals predications or not. Correlation analysis was carried out to gain better understanding of the predictive mechanism for the assessment of the heavy metals in sediments using VNIRS. PLSR calibration models showed that Cd, Hg, Ni and Pb had acceptable model prediction (with r(cv)(2) values range from 0.32 to 0.40), while model results for As, Cr, Cu and Zn were unsatisfactory (with r(cv)(2) values of 0.01-0.06). These different accuracies were likely caused by the different relationships between heavy metals and spectrally-active constitutes (e.g., total organic carbon, TOC). When compared with full-spectrum PLSR models, GA-PLSR and CARS-PLSR models slightly increased the accuracies by remove uninformative spectral variables. Given these undesired practices, this study demonstrated that VNIRS should not be recommended for heavy metals estimation in urban lake sediment. The inherent correlations between heavy metals and spectrally-active constitutes (e.g., TOC) rather than modeling method (e.g., feature selection algorithms) were critical for the limited heavy metals estimation using VNIRS.
资助项目	Chinese National Key Development Program for Basic Research[2014CB954004] ; Natural Science Foundation of China[31600377] ; Chinese Academy of Sciences
WOS研究方向	Geology ; Agriculture ; Water Resources
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000423004800008
内容类型	期刊论文
源URL	[http://202.127.146.157/handle/2RYDP1HH/4516]
专题	中国科学院武汉植物园
通讯作者	Liu, Feng
作者单位	1.Chinese Acad Sci, Wuhan Bot Garden, Key Lab Aquat Bot & Watershed Ecol, Wuhan 430074, Hubei, Peoples R China 2.Shanxi Agr Univ, Coll Forestry, Taigu 030801, Peoples R China
推荐引用方式 GB/T 7714	Jiang, Qinghu,Liu, Minxia,Wang, Jun,et al. Feasibility of using visible and near-infrared reflectance spectroscopy to monitor heavy metal contaminants in urban lake sediment[J]. CATENA,2018,162:72-79.
APA	Jiang, Qinghu,Liu, Minxia,Wang, Jun,&Liu, Feng.(2018).Feasibility of using visible and near-infrared reflectance spectroscopy to monitor heavy metal contaminants in urban lake sediment.CATENA,162,72-79.
MLA	Jiang, Qinghu,et al."Feasibility of using visible and near-infrared reflectance spectroscopy to monitor heavy metal contaminants in urban lake sediment".CATENA 162(2018):72-79.