Linking energy sector and air quality models through downscaling: Long-run siting of electricity generators to account for spatial variability and technological innovation

摘要

Modeling the air pollution implications of long-term energy transitions requires a downscaling process as an intermediate step between national-scale energy models and fine-scaled air quality models. Traditional "Grow-in-Place" (GIP) downscaling methods assume that future patterns of generator siting and emissions will be similar to those in the past. However, rapid technological change and shifting policy might yield very different future spatial patterns of power emissions. Here, we propose a "Site-and-Grow" (SAG) downscaling framework to couple the Electricity Market Module (EMM) of the National Energy Modeling System (NEMS) with the Community Multi-scale Air Quality (CMAQ.) model to simulate future changes in emissions from power sector. The SAG framework consists of two steps. First, we downscale regional energy information to subregions using a modified generation expansion model under the assumption that economic fundamentals drive decisions at that scale. Second, we use GIS-based screening to locate potential sites for new power plants, and specify the final county-level placement using a multicriteria value function, assuming that land use and environmental constraints are most influential. The method is implemented in one EMM region (Carolinas and Virginia) as a case study. We compare spatial and temporal variability of downscaled emissions using both GIP and SAG methods, as well as emissions differences among four NEMS scenarios (base case, high natural gas consumption, high penetration of electric vehicles, and marine vessel electrification in ports). The results indicate that coal power plant emissions such as SO_2 and NO_x continue to dominate emissions from all other traditional power plants even in 2040, which suggests that emission changes will mainly be determined by where old coal plants are retired. An ANOVA (analysis of variance) comparison of four energy scenarios with two downscaling methods shows that the choice of downscaling method can contribute as much to emissions patterns as much as the choice of scenario.