Microplastics abundance.xlsx

Subsurface microplastic migration in karst regions exhibits pronounced uncertainties due to complex terrain and interactions with precipitation and soil conditions. This study investigates vertical migration patterns of microplastics in karst soils and establishes predictive models for subsurface transport. Soil samples from Guizhou karst areas were analyzed using a custom-designed simulation apparatus. Controlled experiments were conducted under varying rainfall intensities (10, 30, 50 mm/h) and soil fissure degrees (1%, 3%, 5%). Stratified sampling (0–5 cm, 5–10 cm, 10–20 cm, 20–30 cm) enabled systematic evaluation of organic matter distribution, aggregate characteristics, and their interactions with microplastic mobility. Linear regression and artificial neural network models were developed to predict vertical migration patterns. Rainfall intensity and soil fissure degree positively correlate with microplastic vertical migration. Their changes can significantly affect the proportions of organic matter and aggregates in the soil. No correlation was found between microplastic vertical migration and soil organic matter. The particle size of soil aggregates affects microplastic migration, with aggregates < 5 mm being a key factor. Linear regression models fit the data well, and neural network models clearly show the impact and direction of each feature on the prediction. Aggregates hinder microplastic vertical migration in karst areas.