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Abstract - The impact of air emissions from electricity generation depends on the spatial distribution of power plants and electricity dispatch decisions. Thus, any realistic evaluation of the air quality impacts of lower-carbon electricity must account for the spatially heterogeneous changes in associated emissions. Here, we present an analysis of the changes in fine particulate matter (PM2.5) associated with current, expected, and proposed energy efficiency and renewable energy policies in Wisconsin. We simulate the state’s electricity system and its potential response to policies using the MyPower electricity-sector model, which calculates plant-by-plant reductions in NOx and SO2 emissions. We find that increased efficiency and renewable generation in a 2024 policy scenario substantially reduce statewide emissions of NOx and SO2 (55% and 59% compared to 2008, 32% and 33% compared to 2024 business-as-usual, BAU). PM2.5 is quantified across the Great Lakes region using the EPA Community Multiscale Air Quality (CMAQ) model for some emissions scenarios. We find that summer mean surface concentrations of sulfate and PM2.5 are less sensitive to policy changes than emissions. In the 2024 policy scenario, sulfate aerosol decreases less than 3% over most of the region relative to BAU and 3-13% relative to 2008 over most of Wisconsin. The lower response of these secondary aerosols arises from chemical and meteorological processing of electricity emissions, and mixing with other emission sources. An analysis of model performance and response to emission reduction at five sites in Wisconsin shows good model agreement with observations and a high level of spatial and 1 temporal variability in sulfate and PM2.5 reductions. In this case study, the marginal improvements in emissions and air quality associated with carbon policies were less than the technology, renewable, and conservation assumptions under a business-as-usual scenario. In this case study, the marginal improvement associated with carbon policies was much less than the technology, renewable, and conservation assumptions under a business-as-usual scenario. However, this analysis for Wisconsin shows how integrated modeling can quantify the emission and air quality co-benefits associated with carbon reduction measures, and that this approach can be applied to other regions and larger geographical scales.
Plachinski, S., T. Holloway, P. J. Meier, G. F. Nemet, A. Rrushaj, J. Oberman, P. Duran, & C. Voigt (2014) Quantifying the Emissions and Air Quality Co-benefits of Lower-Carbon Electricity Production, Atmospheric Environment (In Press).