Source Apportionment of Soil Heavy Metals in Urban Agglomerations Based on the APCS-MLR Model

Yanjie Zhang, Yunxia Wang, Yuan Zhang, Xinmiao Wang, Min Li and Lei Yang ()
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Yanjie Zhang: Hebei Technology Innovation Center for Geographic Information Application, Institute of Goegraphical Sciences, Hebei Academy of Sciences, Shijiazhuang 050011, China
Yunxia Wang: Hebei Technology Innovation Center for Geographic Information Application, Institute of Goegraphical Sciences, Hebei Academy of Sciences, Shijiazhuang 050011, China
Yuan Zhang: Hebei Technology Innovation Center for Geographic Information Application, Institute of Goegraphical Sciences, Hebei Academy of Sciences, Shijiazhuang 050011, China
Xinmiao Wang: State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Min Li: State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
Lei Yang: State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China

Sustainability, 2025, vol. 17, issue 21, 1-15

Abstract: In order to study the differential characteristics of heavy metal contamination levels and their sources in soils under various land use types and anthropogenic activities at a regional scale, this study focused on the Beijing–Tianjin–Hebei (BTH) urban agglomeration in North China. We analyzed heavy metal content in three land use types (urban green spaces, croplands, and vegetable fields/orchards) through field sampling and laboratory analysis, with content determined by inductively coupled plasma mass spectrometry (ICP-MS). The sources of heavy metals were quantitatively apportioned their sources using the absolute principal component score–multiple linear regression (APCS-MLR) method. Results of this study are as follows: (1) Heavy metal content varied among different soil types, with vegetable fields/orchards soils showing relatively higher content. Urban green spaces and cropland soils exhibited comparable heavy metal levels, though urban green spaces displayed higher spatial heterogeneity, while cropland soils showed more homogeneous distributions. (2) The APCS-MLR model identified five pollution sources: mixed traffic–coal combustion sources, industrial sources, agricultural sources, natural sources, and unknown sources. Natural sources were consistently the dominant contributors of arsenic (As), chromium (Cr), and nickel (Ni) across all three land use types, with contribution rates of 32.62–70.26%. Traffic and coal combustion emissions were the primary sources of lead (Pb) and copper (Cu) in urban green spaces, accounting for 40.28–66.26%, while industrial activities showed the highest contributions to zinc (Zn) and cadmium (Cd) in urban green spaces, at 45.88–65.25%. Agricultural activities contributed similarly to Cd accumulation in both cropland and vegetable fields/orchards soils (41.68–51.32%), but their contributions to Cu and Zn in vegetable fields/orchards soils (46.62–55.58%) were significantly higher than those in cropland (9.21–13.40%). Notably, unexplained sources accounted for 18.64–42.59% of heavy metals in vegetable fields/orchards soils, suggesting particularly complex sources in these systems. This study provides a scientific basis for sustainable soil management strategies and promoting coordinated pollution control in urban agglomeration regions.

Keywords: heavy metals; urban agglomeration; land use; source apportionment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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