Quantitative Soil Characterization for Biochar-Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization.

ABSTRACT: Soil pollution with cadmium (Cd) poses serious health and environmental consequences. The study investigated the incubation of several soil samples and conducted quantitative soil characterization to assess the influence of biochar (BC) on Cd adsorption. The aim was to develop predictive models for Cd concentrations using statistical and modeling approaches dependent on soil characteristics. The potential risk linked to the transformation and immobilization of Cd adsorption by BC in the soil could be conservatively assessed by pH, clay, cation exchange capacity, organic carbon, and electrical conductivity. In this study, Long Short-Term Memory (LSTM), Bidirectional Gated Recurrent Unit (BiGRU), and 5-layer CNN Convolutional Neural Networks (CNNs) were applied for risk assessments to establ

SUBMITTER: Rashid MS 

PROVIDER: S-EPMC11359006 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature