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Future Air Pollution and Environmental Justice in California: Achieving Equity for all Socio-economic Classes
YITING LI, Anikender Kumar, Yin Li, Michael Kleeman, University of California, Davis
Abstract Number: 294
Working Group: Environmental Justice: Technology, Frameworks, and Outcomes
Abstract
California has committed to an 80% reduction in GHG emissions by the year 2050. This massive reduction will require a transformation in the energy system that will also impact air quality. The optimal future energy portfolio will not only reduce climate change and improve air quality at minimum economic cost, but it should also seek to provide equal benefits for all socio-economic classes by achieving environmental justice (EJ) principles.
Predicting how different energy scenarios affect air quality for each socio-economic class requires analysis at neighborhoods scales, which poses a major computational challenge for the chemical transport models CTMs) used in such studies. We start our analysis by using the source-oriented WRF/Chem (SOWC) model at 250m, 1km, 4km, and 12km spatial resolution to analyze air quality and EJ in California during the year 2016. Exposure to PM0.1 and PM2.5 concentrations is estimated for different socio-economic classes based on income and race-ethnicity. The model spatial resolution needed to bring EJ issues into focus at the smallest computational cost is identified. The modeling system is then used to study EJ in the year 2050 under two different energy scenarios to achieve GHG reductions: (i) a Business as Usual (BAU) scenario and (ii) a low-carbon GHG-Step scenario. Future year 2050 air quality simulations were carried out for 32 randomly-selected weeks between 2046-2055 (to account for effects of medium-term meteorological cycles such as ENSO). Population exposure to PM2.5, PM0.1 total mass, primary PM was then estimated for different socio-economic classes under the BAU and GHG-Step scenarios. The results from this study identify the optimal spatial resolution needed for EJ analysis in California, and compare the benefits of future BAU and GHG-Step energy scenarios across socio-economic classes.