(651f) Nitrogen Management in the Design of Sustainable Ammonia-Based Food-Energy-Water Systems | AIChE

(651f) Nitrogen Management in the Design of Sustainable Ammonia-Based Food-Energy-Water Systems


Wang, H. - Presenter, University of Minnesota Twin Cities
Zhang, Q. - Presenter, University of Minnesota
Palys, M., University of Minnesota
Daoutidis, P., University of Minnesota-Twin Cities
The large-scale synthesis of ammonia and its use as nitrogen fertilizer has revolutionized the food industry. As the trend of growing global population persists, ammonia will continue to play a central role in agriculture. However, the conventional ammonia production process has an immense carbon footprint, and the excessive use of ammonia as fertilizer has caused significant nitrogen emissions into the environment. To address the first environmental concern, recent efforts focus on using water instead of natural gas as the hydrogen source, through water electrolysis powered by renewable electricity [1]. To mitigate nitrogen loss, practicing nitrogen management, such as need-based fertilizer application and wastewater treatment on drainage water, has shown to be effective [2].

Ammonia production and nitrogen management are closely interrelated and hence need to be considered in a holistic framework. In this work, we extend the integrated ammonia-based sustainable farm model previously introduced by Palys et al. [3] to account for nitrogen flows and nitrogen management processes in the system. We aim to optimize the design of this ammonia-based food-energy-water system while considering detailed scheduling decisions that capture the effect of time-varying parameters such as solar and wind availability. However, introducing needed nitrogen concentration terms into the model causes it to become a large-scale mixed-integer nonlinear program (MINLP) which is very challenging to solve.

As it turns out, our model has a very particular structure that allows the generation of a relatively accurate piecewise-linear surrogate model for the agricultural part of the system, where all nonlinearity resides. The resulting model is an MILP, which can be solved efficiently using off-the-shelf solvers for a sufficiently fine time discretization of the year-long planning horizon. The proposed framework has been applied to a real-world case study based on data from Morris, MN. The results reveal the synergistic effects within the system and especially their impact on nitrogen loss.


[1] Collin Smith, Alfred K. Hill, and Laura Torrente-Murciano. Current and future role of Haber–Bosch ammonia in a carbon-free energy landscape. Energy Environ. Sci., pages –, 2020.

[2] Naiqian Zhang, Maohua Wang, and Ning Wang. Precision agriculture—a worldwide overview. Computers and Electronics in Agriculture, 36(2):113 – 132, 2002.

[3] Matthew J. Palys, Anatoliy Kuznetsov, Joel Tallaksen, Michael Reese, and Prodromos Daoutidis. A novel system for ammonia-based sustainable energy and agriculture: Concept and design optimization. Chemical Engineering and Processing - Process Intensification, 140:11– 21, 2019.