Source identification of heavy metals in peri-urban agricultural soils of southeast China: An integrated approach

Highlights

• Integration of SA, IRA, PMF and IFA consistently apportioned the soil heavy metal sources.

• Inputs of heavy metals to soils were mainly allocated to fertilization and atmospheric deposition.

• Stable Pb isotope ratio analysis (IRA) supports the assessment of anthropogenic impact on soils.

• Regular monitoring and source control should be implemented to prevent soil heavy metals pollution.

Abstract

Intensive human activities, in particular agricultural and industrial production have led to heavy metal accumulation in the peri-urban agricultural soils of China threatening soil environmental quality and agricultural product security. A combination of spatial analysis (SA), Pb isotope ratio analysis (IRA), input fluxes analysis (IFA), and positive matrix factorization (PMF) model was successfully used to assess the status and sources of heavy metals in typical peri-urban agricultural soils from a rapidly developing region of China. Mean concentrations of Cd, As, Hg, Pb, Cu, Zn and Cr in surface soils (0–20 cm) were 0.31, 11.2, 0.08, 35.6, 44.8, 119.0 and 97.0 mg kg⁻¹, respectively, exceeding the local background levels except for Hg. Spatial distribution of heavy metals revealed that agricultural activities have significant influence on heavy metal accumulation in the surface soils. Isotope ratio analysis suggested that fertilization along with atmospheric deposition were the major sources of heavy metal accumulation in the soils. Based on the PMF model, the relative contribution rates of the heavy metals due to fertilizer application, atmospheric deposition, industrial emission, and soil parent materials were 30.8%, 33.0%, 25.4% and 10.8%, respectively, demonstrating that anthropogenic activities had significantly higher contribution than natural sources. This study provides a reliable and robust approach for heavy metals source apportionment in this particular peri-urban area with a clear potential for future application in other regions.

Introduction

There is an increasing public concern about the accumulation of heavy metals in agricultural soils which, in turn, has the potential to restrict the soil's function, cause toxicity to crops and ground water, and hence to threaten human health (Hou et al., 2014; Lu et al., 2015; Qu et al., 2016; Toth et al., 2016). Intensive human activities have led to heavy metal accumulation in peri-urban agricultural soils of China threatening soil environmental quality and food safety (Huang et al., 2006; Luo et al., 2009; Hu et al., 2013; Hu et al., 2017). Heavy metals can enter agro-ecosystems through geogenic sources and anthropogenic activities (Cloquet et al., 2006; Yang et al., 2016). Geogenic sources of heavy metals mainly come from weathering of the parent materials. Anthropogenic activities include inputs of heavy metals through application of fertilizers and organic manures, irrigation, atmospheric deposition, waste disposal, sewage application, and other human activities (Sharma et al., 2008; Hu et al., 2013; Hou et al., 2014; Pan and Wang, 2015). Inputs of heavy metals to soils through agricultural activities have increased within the past decades due to increasing food demands from a rapidly expanding population (Huang et al., 2015; Hu et al., 2017).

Heavy metal source apportionment is a crucial step towards prevention or reduction of heavy metal pollution (Huang et al., 2015). Identification of heavy metal sources in agricultural soils is a basis for undertaking appropriate actions to protect soil quality and to develop sustainable management strategies (Lu et al., 2012). In this context, peri-urban agricultural soils are priority areas for research of source apportionment as they are generally located close to multiple pollutant sources such as construction/excavation works, industry, traffic and urban waste disposal (Huang et al., 2015). Despite public concerns, quantitative knowledge of heavy metals in agricultural soils from different sources especially from different anthropogenic sources remains scarce. Discriminating the natural and different anthropogenic sources and their rates of contribution to heavy metal accumulation in soils are crucial for soil environmental protection and food safety (Pan and Wang, 2015).

The spatial distribution of heavy metals based on Geographical Information System (GIS) can be used as an aid to identify their possible sources and pollution hot spots (Chai et al., 2015). Identification of soil heavy metal sources and spatial delineation of areas with heavy metal pollution is important for decision makers to develop effective management strategies to improve environmental quality (Zhao et al., 2010; Pan and Wang, 2015). So far, studies on regional input and output fluxes of heavy metals are mostly based on model calculations, statistical yearbooks, and literature data (Luo et al., 2009; Belon et al., 2012; Lofts et al., 2013; Hou et al., 2014). This classical approach to source apportionment can be substantially improved by use of receptor models that are based on application of multivariate statistical methods to identify and quantify apportionment of pollutants to their sources (Wang et al., 2009). Although the positive matrix factorization (PMF) model has been successfully applied for pollutant source identification for atmospheric (Song et al., 2006; Alleman et al., 2010; Gupta et al., 2012; Jang et al., 2013) and sedimentary sources (Chen et al., 2013; Pekey and Dogan, 2013; Gonzalez-Macias et al., 2014), few studies have employed this approach to identify heavy metal sources in soils (Xue et al., 2014; Dong et al., 2015). Furthermore, stable Pb isotope ratio analysis is commonly used to trace the sources of Pb pollution in different environmental compartments at local to global scales (Wong et al., 2003; Cloquet et al., 2006; Komarek et al., 2008; Reimann et al., 2012; Yu et al., 2016). Although previous studies have been conducted to identify the sources of heavy metals in soils using the different individual method, integration of the different methods in the same area to accurately evaluate and validate the source identification results by the different approaches is lacking.

Therefore, a combination of spatial analysis (SA), isotope ratio analysis (IRA), input flux analysis (IFA), and positive matrix factorization (PMF) model has been used in this study to identify the status and sources of selected heavy metals (Cd, As, Hg, Pb, Cu, Zn and Cr) in typical peri-urban agricultural soils. The tested soils were from a rapidly developing region in southeast China, where a large number of samples of soils, crops, fertilizers and atmospheric depositions were collected and analysed. This work provides baseline information to develop effective policies and standards to control and reduce heavy metal inputs and long-term accumulation in agricultural soils as well as to provide the theoretical basis and technical support for sustainable agricultural production and management.