An Evaluation of Reduced-Complexity Models of Air Quality Over Historical, Policy-Relevant PM2.5 Concentration Changes

This archive contains output from three reduced-complexity models (RCMs) of air quality: AP3 (Muller and Mendelsohn, 2007), EASIUR (Heo et al., 2017), and InMAP (Tessum et al., 2017). This archive also contains outputs from the chemical transport model PMCAMx, observational datasets, and analysis notebooks used to generate the figures in the associated manuscript. The directory is organized as follows: Top-level Jupyter notebooks used to generate figures: CTM_RCM_Comparison.ipynb Emis_Pop_WT_PM.ipynb PM_Conc_Maps.ipynb RCM_Change_PM25.ipynb The top-level directory also includes the following script, required to run some analysis code: pyeasiur_inmap.py The folder labled “Data” includes all model and observation files needed to run each Jupyter Notebook. Citations: Heo, J., Adams, P. J., & Gao, H. O. (2017). Public health costs accounting of inorganic PM2.5 pollution in metropolitan areas of the United States using a risk-based source-receptor model. Environment International, 106, 119–126. https://doi.org/10.1016/j.envint.2017.06.006 Muller, N. Z., & Mendelsohn, R. (2007). Measuring the damages of air pollution in the United States. Journal of Environmental Economics and Management, 54(1), 1–14. https://doi.org/10.1016/j.jeem.2006.12.002 Tessum, C. W., Hill, J. D., & Marshall, J. D. (2017). InMAP: A model for air pollution interventions. PLOS ONE, 12(4), e0176131. https://doi.org/10.1371/journal.pone.0176131