Comparison and Analysis of Estimation Methods for Heavy Metal Pollution of Farmland Soils

doi:10.5814/j.issn.1674-764x.2020.05.001

Abstract

Abstract:

Heavy metal pollution of farmland soils is a serious environmental problem. The accurate estimation of heavy metal pollution levels of farmland soils is very crucial for sustainable agriculture. Concentrations of heavy metal elements (As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn) in farmland soils at 186 sampling sites in the Baghrash Lake Basin, NW China, were determined and analyzed based on the pollution index (P_i), the geo-accumulation index (I_geo), the enrichment factor (EF), the ecological risk index (ER), and the environmental risk index (I_er). The results of these five different estimation methods were compared and discussed. The obtained results indicated that the average concentrations of all the heavy metals in the farmland soils of the study area were lower than the Soil Environmental Quality of China (GB 15168-2018) levels, but the average concentrations of Cd, Cr, Ni, Pb, and Zn exceed the corresponding background values. Significant differences in estimation results existed between the five estimation methods. Based on the identified concentrations, the average P_i, I_geo, and EF values of the heavy metals in farmland soils decreased in the order of: Zn > Pb > Cd > Cr > Ni > Cu > As, whereas the average ER values decreased in the order of: Cd > As > Cu > Pb > Ni > Cr > Zn, and the average I_er values decreased in the order of: Cd > Cu > Zn > As = Pb > Cr > Ni. The pollution class values with different estimation methods were ranked as: P_i > I_geo = EF > ER = I_er. The obtained results suggest that the most appropriate estimation method and soil background values of farmlands should be used for better understanding the environmental quality of farmland soils. Overall, the EF and ER methods are recommended for assessing heavy metal pollution risks of farmland soils.

Key words: farmland soil, heavy metal, pollution index, comparison, Baghrash Lake Basin

Mamattursun EZIZ, Adila HAYRAT, YANG Xiuyun. Comparison and Analysis of Estimation Methods for Heavy Metal Pollution of Farmland Soils[J]. Journal of Resources and Ecology, 2020, 11(5): 435-442.

Figures/Tables 7

References 34

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Index	Calculating formula	Characteristics of parameters
P_i	P_i = C_i /B_i	Where C_i represents the concentration of element i in the soil sample, and B_i represents the background value of element i
I_geo	I_geo = log₂(C_i /1.5B_i)	Where C_i and B_i are the same as above, and 1.5 represents a background matrix correction factor that includes possible variations of the background values due to lithogenic effects
EF	EF = (C_i /C_r) /(B_i /B_r)	Where C_i and B_i are the same as above, C_r is the concentration of the reference metal, and B_r is the background value of the reference elements
ER	ER = (C_i /S_i) × T_i	Where C_i is the same as above, S_i is the limit-risk concentration of element i, and T_i is the toxic response factor of element i in the soil sample
I_er	I_er = (C_i /S_i) - 1	Where C_i and S_i are the same as above

Index	Calculating formula	Characteristics of parameters
P_i	P_i = C_i /B_i	Where C_i represents the concentration of element i in the soil sample, and B_i represents the background value of element i
I_geo	I_geo = log₂(C_i /1.5B_i)	Where C_i and B_i are the same as above, and 1.5 represents a background matrix correction factor that includes possible variations of the background values due to lithogenic effects
EF	EF = (C_i /C_r) /(B_i /B_r)	Where C_i and B_i are the same as above, C_r is the concentration of the reference metal, and B_r is the background value of the reference elements
ER	ER = (C_i /S_i) × T_i	Where C_i is the same as above, S_i is the limit-risk concentration of element i, and T_i is the toxic response factor of element i in the soil sample
I_er	I_er = (C_i /S_i) - 1	Where C_i and S_i are the same as above

Class	P_i	Pollution degree	I_geo	Pollution degree	EF	Pollution degree	ER	Risk degree	I_er	Risk degree
Ⅰ	≤0.7	Unpolluted	≤0	Unpolluted	≤2	Unpolluted	≤40	Low risk	≤0	Low risk
Ⅱ	0.7-1	Low	0-1	Unpolluted to moderately	2-5	Low	40-80	Moderate risk	0-1	Moderate risk
Ⅲ	1-2	Moderately	1-2	Moderately	5-20	Moderately	80-160	Considerable risk	1-3	Considerable risk
Ⅳ	2-3	High	2-3	Moderately to strongly	20-40	High	160-320	High risk	3-5	High risk
Ⅴ	> 3	Extremely	3-4	Strongly	> 40	Extremely	> 320	Extremely high risk	> 5	Extremely high risk
Ⅵ	-	-	4-5	Strongly to extremely	-	-	-	-	-	-
Ⅶ	-	-	> 5	Extremely	-	-	-	-	-	-

Class	P_i	Pollution degree	I_geo	Pollution degree	EF	Pollution degree	ER	Risk degree	I_er	Risk degree
Ⅰ	≤0.7	Unpolluted	≤0	Unpolluted	≤2	Unpolluted	≤40	Low risk	≤0	Low risk
Ⅱ	0.7-1	Low	0-1	Unpolluted to moderately	2-5	Low	40-80	Moderate risk	0-1	Moderate risk
Ⅲ	1-2	Moderately	1-2	Moderately	5-20	Moderately	80-160	Considerable risk	1-3	Considerable risk
Ⅳ	2-3	High	2-3	Moderately to strongly	20-40	High	160-320	High risk	3-5	High risk
Ⅴ	> 3	Extremely	3-4	Strongly	> 40	Extremely	> 320	Extremely high risk	> 5	Extremely high risk
Ⅵ	-	-	4-5	Strongly to extremely	-	-	-	-	-	-
Ⅶ	-	-	> 5	Extremely	-	-	-	-	-	-

Items	As	Cd	Cr	Cu	Mn	Ni	Pb	Zn
Minimum (mg kg^-1)	0.52	0.05	33.68	19.45	312.82	19.45	0.99	38.99
Maximum (mg kg^-1)	28.87	0.38	123.39	73.12	789.68	55.97	96.36	434.88
Median (mg kg^-1)	4.78	0.21	53.80	30.08	501.72	33.96	37.45	73.72
Average (mg kg^-1)	6.50	0.20	55.73	30.52	503.28	34.21	41.16	89.31
Standard deviation (mg kg^-1)	4.22	0.06	11.63	6.22	61.76	6.77	24.16	57.80
CV	0.65	0.30	0.21	0.20	0.12	0.20	0.59	0.65
Background value (mg kg^-1)	11.20	0.12	39.60	35.80	688.00	26.40	13.50	16.80
National Standard (GB 15618-2018) (mg kg^-1)	25.00	0.60	250.00	100.00	-	190.00	170.00	300.00