Search for: All records

Nutrient recovery from waste is a promising strategy to conserve inputs while reducing nutrient discharge to the natural environment. Multiple waste streams have shown promise with respect to nutrient recovery. Multiple technologies also show promise at a pilot or full scale. These technologies, however, must not exacerbate other environmental issues, with excessive energy use, unsustainable material extraction (e.g., mineral extraction, cement use), or toxin release into the environment. Such technologies must also be feasible from economic and social perspectives. Work, therefore, should focus on both improving our current suite of available technologies for nutrient recovery from waste and framing policies that blend affordability with incentives, thereby fostering an environment conducive to innovation and adoption of sustainable approaches. This review considers the issues associated with nutrient recovery from waste, including technical feasibility and economic, environmental, and social factors, and identifies current knowledge gaps and emerging opportunities for nutrient waste recovery. 

This study presents a novel data-driven optimal control method to minimize the cost of Convection-Enhanced Evaporation (CEE) systems under time-varying weather conditions. CEE is the approach of evaporating water from saline films (brine) on packed evaporation surfaces by air convection. Here, operating variables (brine injection rate, brine temperature, and air speed) are actively controlled as a function of current ambient conditions and daily weather forecast. The controller optimizes the process operation variables based on a dataset consisting of Pareto fronts, obtained in advance by solving a set of optimization problems. Three optimal operation strategies are presented: (1) real-time selection of operating variables, (2) predictive scheduled operation, and (3) hybrid wind-fan operation. The effectiveness of the proposed strategies was assessed through two case studies with distinct geographical locations and weather conditions: Alamogordo, New Mexico, and Minneapolis, Minnesota. The results show significant cost-saving potential relative to static operation. Predictive scheduled operation resulted in an annual average operating costs of $0.91/m3 and $6.63/m3 in Alamogordo and Minneapolis, respectively, with the higher costs in Minneapolis a result of the added thermal energy required to prevent freezing in winter.