An integrated framework for exploring the tradeoffs between cost-optimized fuel allocation and regional air quality impacts in a water-energy nexus infrastructure.

Abstract

This paper presents an integrated framework in which an air quality dispersion model is combined with an economic dispatch model to address the environmental tradeoffs of a cost-optimized fuel allocation strategy. A unit commitment dispatch model was developed to re-allocate fuel between power generation and desalination plants. Then, an air quality dispersion model was run for a 1-year period to simulate the spatiotemporal transport of pollutants and the possible formation of air pollution hotspots. The results showed that optimizing fuel allocation can reduce the associated fuel cost by as much as 16.5% of the total cost (1.08 billion USD). The optimized fuel allocation approach resulted in reducing the base case emissions of NOx, SO2, CO, and PM10 by 25%, 4.6%, 3.1%, and 7.6%, respectively. However, the air quality impact of the optimized fuel allocation scheme was not as favorable. The 1-h-averaged maximum concentration of SO2 increased, and NOx concentrations were slightly above the allowable limits. Although fewer pollutants were emitted over the study period in the optimized fuel allocation case, the variability in how fuel was allocated between power and desalination plants concentrated emissions near residential areas. As a result of this trend, the maximum 1-h concentrations of all pollutants increased, with increases ranging from 1% for CO to 29% for PM10. In addition, the total number of hourly SO2 concentration violations increased dramatically, leading to additional hotspot areas. Therefore, the effectiveness of any environmental-economic fuel dispatch strategy should be tested based on additional indicators such as the allowable limits of pollutant concentrations and not exclusively the overall emissions of the system. This approach could promote the selection of the most economic fuel dispatch method while simultaneously considering regional air quality impacts.