(371x) Meteorological Feasibility of a Moisture Capture System from Air Using Mixed-Integer Linear Fractional Programming

Atomspheric water harvesting (AWH) for distributed freshwater production and direct air capture (DAC) for CO₂ removal have garnered great attention in recent years. One of the biggest challenges is quantifying climate variability enabling appropriate decision-making regarding process systems engineering (PSE).

This work showed the generalizable methodology for identifying the meteorological feasibility, integrating the two-stage stochastic programming (TSSP) with mixed-integer linear fractional programming (MILFP). It was especially novel that the objective function was formulated as a fractional term to consider the capturing cost and performance ratio, thereby screening out effectively the economically infeasible solution.

The adsorption-based atmospheric moisture capture system was introduced as an example. Three core phases of the framework consisted of (1) characterizing the meteorological characteristics, (2) developing the energy and cost model, and (3) implementing TSSP with MILFP.

Through the work, we derived the climate window for the viable operation. We contributed to the decision on site selection, initial capital investment, and operability from a practical point of view. This work will give an insight into the interplay between climate variability and processes that handle the ambient air as a system.