Source apportionment of soil heavy metals: A new quantitative framework coupling receptor model and stable isotopic ratios

Abstract

Tracing the source of heavy metals in soils is crucial for reversing the worrisome situation of heavy metal contamination. In this study, the origins of heavy metal pollution in soil were examined in a primary electronic waste treatment and disposal hub in China, using a synergistic source apportionment framework consisting of the positive matrix factorization (PMF) model and the Bayesian stable-isotope analysis mixing model (MixSIAR). Industrial activity is significant to heavy metal contamination in both industrial park and farmland soils, however, the contribution varied through PMF model (industrial park, 64.2%; farmland, 35.6%). In the industrial park, Pb was identified as the major pollutant in the soils, and the local children suffered from noncarcinogenic risks. Moreover, the contribution of Pb contamination sources were allocated more accurately (electronic waste dismantling, 25.1%; industrial production, 23.7%; vehicle exhaust from leaded gasoline, 9.1%; vehicle exhaust from unleaded gasoline, 20.2%; natural process, 21.9%) using MixSIAR for the first time. The main soil contaminants in surrounding farmland were Cd, Cu, and Zn. The variations in heavy metal pollution sources in soils were found to be associated with local policies and regulations, such as the phasing out of leaded gasoline and the conversion of industrial park from electronic waste demolition switched to production and storage. The identification of the source of heavy metals in soil will support targeted reduction of the associated emissions, which can immediately help alleviating soil contamination and control human health risks.