Exploring soil heavy metal sources is of great significance for ensuring the safety of ecological environments and agricultural product safety, as well as for guiding pollution control and management policies. This paper retrieved 452 research papers on soil heavy metal source analysis published over the 2004–2024 period from the Web of Science database. The collected literature was subjected to multidimensional bibliometric analysis using the CiteSpace 6.3.R1. The results showed significantly increasing trends in the scientific outputs and the number of papers on heavy metal source analysis in soils and water over the study period. In addition, related research topics have expanded from single to multiple heavy metal elements in environmental media and have increasingly recognized the impact of water pollution on soil contamination. Research methods have also evolved from basic statistical analysis to complex spatial analysis techniques, covering agricultural and urban soils. Previous related studies have focused on heavy metal pollution in different areas, and related research on heavy metal source analysis has now extended from ecological environments to associated human health risks. The present study provides directions for future related research and guidance for ensuring effective source control of heavy metal pollution and safe utilization of land and water resources.

The potentially toxic element pollution of agricultural soils has become a significant environmental threat to food safety and human health. Accurately identifying sources of potentially toxic element pollution is key to developing effective pollution prevention and control measures. In this study, regional potentially toxic element pollution of the soils in the Nanliujiang River Basin was analyzed using the positive matrix factorization (PMF) model and the geo-detector model. First, topsoil samples from the study area were collected to analyze eight potentially toxic elements in the soil, including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. The PMF model was used to conduct source apportionment of the potentially toxic element data and identify the primary pollution sources and their contribution rates. Then, the geo-detector model was used to analyze the key factors affecting the spatial distribution of the potentially toxic elements and the influence of natural and human factors on the distribution of the potentially toxic elements. There are four potentially toxic element pollution sources of the agricultural soil in the study area: geological background, agricultural activities, industrial discharge, and river irrigation. The geological background contributed the most. The main factors affecting the spatial distribution of potentially toxic elements included agricultural activities, industrial discharge, and river irrigation. This integrated method can analyze the formation of potentially toxic element pollution in depth from the perspectives of source apportionment and spatial differentiation and provide a scientific basis and decision support for preventing and controlling potentially toxic element pollution in agricultural soils. This study provides a new method and scientific basis for identifying and preventing potentially toxic element pollution sources in agricultural soil and can guide the formulation of targeted soil pollution control measures.

Potentially toxic element pollution caused by coal mining activities, especially the accumulation of cadmium, has become a major threat to the global environment and health. Long-term mining activities in China, a major coal consumer, caused a large accumulation of coal gangue. Gangue weathering and leaching release Cd, which threatens the ecological safety of the surrounding soil and water bodies. Although the government has implemented ecological restoration projects in the mining areas, there is still a lack of systematic evaluation of pollution control of downstream farmlands. For this study, remote sensing analyses of fractional vegetation coverage (FVC), geo-accumulation index (I_geo), and potential ecological risk index (EI) data, as well as the pollution characteristics and ecological risks of Cd, were evaluated for a coal mining area in Jiangxi Province. Coal gangue, restoration cover soil, downstream farmland soil, irrigation water, and sediment samples were used in the analyses. After restoration, the Cd concentration in the mining cover soil (0.23 mg/kg) was significantly lower than that of the coal gangue (1.18 mg/kg), while the Cd concentration in the downstream farmland soil (0.44 mg/kg) was roughly an average of the two. The geo-accumulation index indicates that the farmland soil is mainly unpolluted (with an average I_geo of −0.25). However, some points have reached the level of no pollution to moderate pollution. Coal gangue poses a relatively high ecological risk (with an average EI of 118), while cover soil and farmland soil pose low risks (with an average EI of 22.5 and 39.86, respectively). The restoration project significantly reduced the Cd input in the downstream farmlands. The study revealed the effective blocking of external soil cover on Cd migration, providing a key scientific basis for the optimization of ecological restoration strategy and risk prevention and control in similar mining areas worldwide.

The pursuit of sustainable development, particularly the mitigation of climate change (SDG 13), necessitates a thorough understanding of the environmental consequences of international trade. The form and pattern of international trade have changed with the rise of preferential trade agreements. The following important question arises: how do preferential trade agreements affect the transfer of trade-embodied carbon emissions? This study establishes a comprehensive bilateral trade database and uses a staggered difference-in-differences model to empirically examine how preferential trade agreements affect embodied carbon emissions. Furthermore, this study explores the underlying mechanisms and investigates heterogeneous effects in diverse contexts. The key findings of this study are as follows. (1) The signing of preferential trade agreements between bilateral trading partners helps reduce the level of carbon embodied in exports. (2) This reduction is achieved by improving production efficiency and facilitating technological spillovers, thereby reducing the carbon footprint associated with export activities. (3) The level of development of bilateral trading countries and the strength of environmental regulations play a role in the heterogeneous impact of preferential trade agreements on embodied carbon emissions. These findings provide critical empirical evidence for designing PTAs that not only facilitate trade but also actively contribute to global climate action and the achievement of broader sustainability objectives.