Modeling spatial trends and exchange fluxes of contaminants in agricultural soil under pollution prevention measures.

ABSTRACT

Modeling the long-term trends of contaminants in topsoil under controlled measures is critical for sustainable agricultural environmental management. Traditional mass balance equations cannot predict spatial variation and exchange flux of regional soil contaminants for it lacks a method of assigning input-output parameters to each simulated cell. To overcome this limitation, we allocate the estimated source contribution flux to the spatial grid cell in the regional chemical mass balance by integrated positive matrix factorization (P-RCMB) with historical trends quantification. Focusing on Cd and As, which are elements with elevated risks of food intake and volatilization/infiltration, the model is applied to 30 ha of agricultural land near the enterprise. Predictions indicate an additional 13.5% of the soil is contaminated, and approximately 2.57 ha may accrue after 100 years at the site, with an uncertainty range of 0.98-5.3 ha. Clean water irrigation (CWI) reduces contamination expansion by approximately 42%, including approximately 4813 g ha-1 yr-1 net As infiltration, playing a dominant role in preventing the formation of severely contaminated soil. Stop straw return, green fertilizers use, and reduced atmospheric deposition control the exchange flux of Cd (114.9 g ha-1 yr-1) in moderate/slight contamination areas. For the different contaminants' cumulative trends in dryland and paddy fields, achieving a net cumulative flux close to zero in marginally contaminated areas presents a viable approach to optimize current emission standards. if trade-off straw removal and additional fertilizer inputs, a straw return rate of approximately 40% in Cd-contaminated soil will yield overall benefits. This model contributes valuable insights and tools for policymaking in contaminated land sustainable utilization and emission standard optimization.