Prediction model for cyanide soil pollution in artisanal gold mining area by using logistic regression

被引:23
作者
Razanamahandry, Lovasoa Christine [1 ]
Andrianisa, Harinaivo Anderson [1 ]
Karoui, Hela [1 ]
Podgorski, Joel [2 ]
Yacouba, Hamma [3 ]
机构
[1] Int Inst Water & Environm Engn 2iE, Dept Water & Sanit Engn, Lab Water Decontaminat Ecosyst & Hlth LEDES, 01 POB 594, Ouagadougou 01, Burkina Faso
[2] Swiss Fed Inst Aquat Sci & Technol EAWAG, Dept Water Resources & Drinking Water, Postfach 611, CH-8600 Dubendorf, Switzerland
[3] Int Inst Water & Environm Engn 2iE, Dept Civil & Hydraul Engn, Lab Water Resources & Hydrol LEAH, 01 POB 594, Ouagadougou 01, Burkina Faso
关键词
Hazardous chemicals; Catchment area; Diffuse pollution; Soil contamination; Risk assessment; Burkina Faso; RISK; PERSPECTIVES; HAZARDS; POVERTY; FUTURE; WATER;
D O I
10.1016/j.catena.2017.11.018
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
It has been reported that persistent cyanide pollution occurs in artisanal small-scale gold mining (ASGM)-affected catchment areas in Burkina Faso. In the present study, the logistic regression method was employed to identify the factors that influence the spatial distribution of cyanide pollution as well as to predict the cyanide pollution map risk at catchment level. Soil samples were collected from two ASGM sites in the northern Zougnazagmiline ("North") site and southern Galgouli ("South") site parts of Burkina Faso, covering areas of 22 km(2) and 20 km(2), respectively. Free cyanide concentration in each sample was measured. It was shown that the spatial distribution of cyanide was solely controlled by the soil type in Zougnazagmiline and both the soil type and electric conductivity in Galgouli. On the other hand, the cyanidation zones within the two catchments were the places where the highest risk of cyanide pollution occurs, with probabilities of 0.8 and 1 in Zougnazagmiline and Galgouli, respectively. > 20% of the settled area in the Zougnazagmiline and 5% of that in Galgouli were exposed to cyanide pollution. Logistic regression was able to reliably predict cyanide contamination in areas affected by ASGM. The model could be useful for decision-makers to plan ASGM-site decontamination.
引用
收藏
页码:40 / 50
页数:11
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