Pollution level and distribution characteristics of heavy metals and microplastics in the soils from the Qionghai Lake Wetland, Southwest China

Urban wetlands are reported to be ideal habitats for accumulation of HMs and MPs. However, study on combined pollution of HMs and MPs in soil is rare in urban wetland environment. In this study, the characteristics of HMs and MPs in the soils of the Qionghai Lake wetland in southwest China were studied by using ICP-MS, and FTIR. The results showed that the average concentration of HMs in soil ranges from 0.84 to 552.75 (mg/kg). According to the EF and Igeo analysis results, Cd and Cr in the soil were significant enriched (EF=12.64) and moderately enriched (EF=2.09), and were at the moderate to heavy pollution level (I geo = 2.83) and the unpolluted to moderate pollution level (I geo = 0.23), and the other elements were at a low level. MPs are emerging micropollutants in the soil environment, and the abundance (pieces/g) of MPs in the soil was 3.90, 7.00, 3.10, 3.40, 14.80, and 1.10 at Stations M1, M2, M3, M4, M8, and M9, respectively, with an average of 5.55 +/- 4.92. Films represented the main microplastic shape, accounting for 81.55 %, followed by fibers, accounting for 11.33 %. The proportion of MPs with a particle size of 0.1-0.5 mm is the highest. Black, blue, and green are the predominant colors found in MPs. Polyethylene (PE) and polypropylene (PP) were the main MP materials based on FTIR identification, accounting for 52.16 % and 42.31 % of the total MPs, respectively. The pollution load index (PLI) of MPs was 2.2, which is a level I pollution. The research on HMs and MPs in urban wetland soil is still in its preliminary stage. Our aim is to offer a fresh perspective for evaluating the pollution status and risk associated with these two pollutants in urban wetland soil, while also providing a valuable reference for subsequent studies on wetland soil pollutants. (c) 2024 International Association for Gondwana Research. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.