Source Apportionment of Heavy Metals in Soils Along a National Highway Using Spatial Interpolation and PMF Model: A Case Study of the Yueyang Section of National Highway 107

doi:10.19657/j.geoscience.1000-8527.2024.064

Abstract

Abstract:

To assess the impacts of national highway traffic on adjacent soil properties, this study examines the characteristics and sources of heavy metal contamination along a section of National Highway 107 in Yueyang County. A total of 246 surface soil samples were collected from a 1-km range on both sides of the highway, and the concentrations of eight heavy metals (i.e.Pb, As, Cd, Cr, Cu, Ni, Zn, and Hg) were measured. By comparing the differences in heavy metal contamination and elemental contents between the soils on each side of the highway, and by integrating Kriging spatial interpolation with the Positive Matrix Factorization (PMF) mo-del, we revealed the potential sources of these heavy metals. The study results show that: (1) The soils along the Yueyang County section of National Highway 107 are strongly acidic, and the differences in heavy metal concentrations reflect the significant impacts of land use types and human activities. (2) Single-factor pollution indices indicate no pollution from Cr, Ni, Zn, and Cd, but slight pollution from Cu, As, Hg, and Pb. The Nemerow comprehensive pollution index indicates that the soil in the study area is overall slightly polluted. (3) Spatial interpolation analysis reveals high overlaps in spatial distribution of As, Cr, Cu, and Ni, while Pb and Zn are distributed across agricultural fields. Cd exhibits an anomalous spatial distribution mainly around the town of Xinkai. The spatial distribution characteristics of Hg show low values in forested areas, indicating a complex interplay between natural geological backgrounds and land use types. (4) PMF source analysis ide.pngied four pollution sources, i.e.traffic, agriculture, natural sources, and atmospheric sources. Traffic and agriculture sources account for 80.3% of the influence on heavy metal content in the soil, indicating a significant impact of transportation and human activities along National Highway 107. In conclusion, the results from spatial interpolation and the PMF model closely corroborate each other, making this integrated method ideal for ide.pngying source components.

Key words: National Highway 107, soil heavy metal, spatial distribution, Kriging algorithm, PMF model

CLC Number:

P642.11

YANG Pengzhi, ZHAO Yuan, XIAO Yuexin, MIN Yingzi, DENG Zhao, GUO Jun, WEI Xiaokun. Source Apportionment of Heavy Metals in Soils Along a National Highway Using Spatial Interpolation and PMF Model: A Case Study of the Yueyang Section of National Highway 107[J]. Geoscience, 2024, 38(03): 694-705.

Figures/Tables 10

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元素	分析方法	检出限 (mg·kg^-1)
Pb	电感耦合等离子质谱法(ICP-MS)	2
As	原子荧光光谱法(HG-AFS)	1
Cd	电感耦合等离子质谱法(ICP-MS)	0.03
Cr	电感耦合等离子体发射光谱法(ICP-OES)	5
Cu	电感耦合等离子体发射光谱法(ICP-OES)	1
Ni	电感耦合等离子体发射光谱法(ICP-OES)	2
Zn	电感耦合等离子体发射光谱法(ICP-OES)	4
Hg	原子荧光光谱法(HG-AFS)	0.0005

元素	分析方法	检出限 (mg·kg^-1)
Pb	电感耦合等离子质谱法(ICP-MS)	2
As	原子荧光光谱法(HG-AFS)	1
Cd	电感耦合等离子质谱法(ICP-MS)	0.03
Cr	电感耦合等离子体发射光谱法(ICP-OES)	5
Cu	电感耦合等离子体发射光谱法(ICP-OES)	1
Ni	电感耦合等离子体发射光谱法(ICP-OES)	2
Zn	电感耦合等离子体发射光谱法(ICP-OES)	4
Hg	原子荧光光谱法(HG-AFS)	0.0005

数值类型	Pb (mg·kg^-1)	As (mg·kg^-1)	Cd (mg·kg^-1)	Cr (mg·kg^-1)	Cu (mg·kg^-1)	Ni (mg·kg^-1)	Zn (mg·kg^-1)	Hg (mg·kg^-1)	pH
最大值	171.00	74.60	5.25	237.00	179.00	111.00	509.00	0.32	5.99
最小值	21.40	3.26	0.04	25.70	12.10	9.94	36.70	0.03	4.10
国道两侧土壤平均值	36.53	13.39	0.30	77.96	27.20	24.69	77.93	0.11	4.85
未干扰地区土壤平均值	37.15	18.25	0.21	82.27	28.72	24.34	79.80	0.08	4.87
干扰地区土壤平均值	36.29	11.49	0.34	76.28	26.61	24.83	77.19	0.12	4.85
标准偏差	12.41	7.49	0.39	23.19	14.21	8.33	41.49	0.05	-
未干扰地变异系数	0.60	0.61	1.05	0.42	0.76	0.57	0.91	0.45	-
干扰地变异系数	0.14	0.36	1.28	0.22	0.37	0.19	0.24	0.39	-
变异系数	0.34	0.56	1.29	0.30	0.52	0.34	0.53	0.44	-
洞庭湖背景值	31.69	12.35	0.31	88.20	26.01	27.50	86.10	0.10	-

数值类型	Pb (mg·kg^-1)	As (mg·kg^-1)	Cd (mg·kg^-1)	Cr (mg·kg^-1)	Cu (mg·kg^-1)	Ni (mg·kg^-1)	Zn (mg·kg^-1)	Hg (mg·kg^-1)	pH
最大值	171.00	74.60	5.25	237.00	179.00	111.00	509.00	0.32	5.99
最小值	21.40	3.26	0.04	25.70	12.10	9.94	36.70	0.03	4.10
国道两侧土壤平均值	36.53	13.39	0.30	77.96	27.20	24.69	77.93	0.11	4.85
未干扰地区土壤平均值	37.15	18.25	0.21	82.27	28.72	24.34	79.80	0.08	4.87
干扰地区土壤平均值	36.29	11.49	0.34	76.28	26.61	24.83	77.19	0.12	4.85
标准偏差	12.41	7.49	0.39	23.19	14.21	8.33	41.49	0.05	-
未干扰地变异系数	0.60	0.61	1.05	0.42	0.76	0.57	0.91	0.45	-
干扰地变异系数	0.14	0.36	1.28	0.22	0.37	0.19	0.24	0.39	-
变异系数	0.34	0.56	1.29	0.30	0.52	0.34	0.53	0.44	-
洞庭湖背景值	31.69	12.35	0.31	88.20	26.01	27.50	86.10	0.10	-