A new model for assessing bioelectrochemical denitrification
Agricultural runoff contributes significantly to anthropogenic nitrate discharge to natural waters, and excessive nitrate in water leads to eutrophication – the biggest water quality problem globally. This is particularly pertinent to Montana as an agriculture state. Current technologies fall short of effective nitrate remediation, because they are prohibitively expensive, impractical (i.e., requiring injection of chemicals), or inefficient (permeable reactive barrier) for the largest source of anthropogenic nitrate discharge – agricultural runoff. On the other hand, Bioelectrochemical Denitrification (BED) holds unique promise in agricultural runoff remediation, as it is chemical-free, solar-powered, and highly efficient, which overcomes the key limitation of existing technologies. The aim of the project is to develop a first-of-its-kind model to predict the performance of BED, taking into account engineering conditions, microbial community composition, and stochasticity. The outcome of the model prediction could be used to optimize the design of BED.
Dr. Tianyu Zhang is an Associate Professor in the Department of Mathematical Sciences at Montana State University. Dr. Daqian Jiang is an Assistant Professor in the Department of Environmental Engineering at Montana Tech.