Source Analysis Based on the Positive Matrix Factorization Models and Risk Assessment of Heavy Metals in Agricultural Soil

Abstract

Soil heavy metal pollution is a severe and growing problem, and it is crucial to assess the level of soil heavy metal contamination and determine the origins of pollutants. However, there is limited research on soil heavy metal source apportionment and its carcinogenic and non-carcinogenic hazards. Positive Matrix Factorization (PMF) is a powerful technique for source apportionment of pollutants in environmental matrices such as atmospheric particulate matter and soil, as it can handle missing and imprecise data to ensure data reliability, among other benefits. In order to explore the distribution characteristics and main sources of heavy metals in agricultural land, the contents of Cd, Cr, Cu, Pb, and Ni were collected and determined. The positive matrix factorization (PMF) model was used to analyze the source of heavy metals in the soil in the study area, and the human health risk evaluation was carried out. The results showed that (1) the coefficient of variation of Cd in the four areas was much higher than that of the other four heavy metals, which showed strong variability; (2) the content and distribution of heavy metals in different regions were different under the influence of different environments; (3) the PMF model analysis showed that the heavy metal pollution sources in the four areas were divided into two types: the soil parent material, which had industrial pollution, traffic pollution, and agricultural pollution; and the contribution rate of each pollution source; (4) the non-carcinogenic risks of heavy metals in children at all points in the study area were greater than those of adults, and the carcinogenic risks were the opposite of the carcinogenic risk in the study area. And the most serious carcinogenic risk in the study area was the harm caused by oral ingestion of heavy metal Cr into the adults’ bodies.

Spatial-temporal variation and source analysis of heavy metal in urban and peri-urban soils：The case study of Beilun District (Ningbo, China) from 2015 to 2022

“…There is no systematic and complete source analysis method. The commonly used source analysis methods include absolute PCA-multiple linear regression, PMF, and the UNMIX model [34] . These methods, which can quantitatively analyze pollution sources, allocate risk based on the contributions of pollution sources and effectively identify pollution sources by combining geostatistical methods and land use data, are highly important for pollution control and management [35,36] .…”

Comparison of the Effects of Different Organic Amendments on the Immobilization and Phytoavailability of Lead

“…Natural activities, such as the weathering of rocks and the deposition of atmospheric heavy metals, can also release Pb into soil [4]. In addition, Pb accumulated in soils can be consumed by humans via food chains, where it accumulates in the nervous, blood, kidney, and immune systems, although low concentrations can also increase ecosystem and organ health risks [5]. Therefore, measures are needed to reduce the toxicity and mobility of Pb in order to reduce its ecological risks and bioaccumulation in plants.…”

Comparative Study on Different Interpolation Methods and Source Analysis of Soil Toxic Element Pollution in Cangxi County, Guangyuan City, China

“…Among these models, the PMF (positive matrix factorization) has been highlighted for its convenience and efficiency. Additionally, its analysis results are noted for their accuracy [22,[24][25][26].…”