This file describes the dataset used in the following manuscript: Shankar, U., B. N. Murphy, M. A. Weber, Y. Ou, S. J. Smith, D. H. Loughlin, C. G. Nolte, "Modeling the Air Quality Impacts of Future Energy Scenarios". This manuscript describes the linkage between a human-Earth system model and a chemical transport model to simulate the air quality impacts of potential large-scale changes in the U.S. energy system. This dataset includes emissions outputs from simulations conducted using the Global Change Analysis Model (GCAM) with state-level representation of the U.S. energy system (GCAM-USA). It also includes a script that is used to generate an emissions control file for the Community Multiscale Air Quality (CMAQ) model, along with the CMAQ source code used in this study. Finally, the dataset includes Excel workbooks that contain data for some of the figures used in the manuscript, as well as postprocessed CMAQ outputs and scripts used to create other figures that appear in the manuscript.

This dataset contains the data contributed by EPA/ORD/NERL/CED researchers to the manuscript "Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3" led by Dr. Ulas Im of Aarhus University in Denmark. This dataset is associated with the following publication: Im, U., J. Christensen, C. Geels, K. Hansen, J. Brandt, E. Solazzo, U. Alyuz, A. Balzarini, R. Baro, R. Bellasio, R. Bianconi, J. Bieser, A. Colette, G. Curci, A. Farrow, J. Flemming, A. Fraser, P. Jimenez-Guerrero, N. Kitwiroon, P. Liu, U. Nopmongcol, L. Palacios-Peña, G. Pirovano, L. Pozolli, M. Prank, R. Rose, R. Sokhi, P. Tuccella, A. Unal, M. Garcia Vivanco, G. Yarwood, C. Hogrefe, and S. Galmarini. Influence of anthropogenic emissions and boundary conditions on multi-model simulations of major air pollutants over Europe and North America in the framework of AQMEII3. Atmospheric Chemistry and Physics. Copernicus Publications, Katlenburg-Lindau, GERMANY, 18: 8929-8952, (2018).

input data for air pollution exposure models. This dataset is associated with the following publication: Breen, M., S.Y. Chang, M. Breen, Y. Xu, V. Isakov, S. Arunachalam, M.S. Carraway, and R. Devlin. Fine-Scale Modeling of Individual Exposures to Ambient PM2.5, EC, NOx, CO for the Coronary Artery Disease and Environmental Exposure (CADEE) Study. ATMOSPHERE. MDPI AG, Basel, SWITZERLAND, 11(1): 65, (2020).

The data are described in detail in the uploaded file "Science hub metadata.docx". This dataset is associated with the following publication: Zhang, Y., J. Bash, S. Roselle, A. Shatas, A. Repinsky, R. Mathur, C. Hogrefe, J. Piziali, T. Jacobs, and A. Gilliland. Unexpected air quality impacts from implementation of green infrastructure in urban environments: a Kansas City Case Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 744(20): 140960, (2020).

File containing the locations where the gridded datasets used in the analysis presented in this manuscript are archived. The actual gridded datasets are too large to upload to sciencehub (several terabytes). This dataset is associated with the following publication: Porter, P.S., S.T. Rao, C. Hogrefe, and R. Mathur. A Reduced Form Model for Ozone Based on Two Decades of CMAQ Simulations for the Continental United States. Atmospheric Pollution Research. Turkish National Committee for Air Pollution Research and Control, Izmir, TURKEY, 8(2): 275-284, (2017).

File containing the locations where the gridded datasets used in the analysis presented in this manuscript are archived. The actual gridded datasets are too large to upload to sciencehub (several terabytes). This dataset is associated with the following publication: Porter, P.S., S.T. Rao, C. Hogrefe, and R. Mathur. A Reduced Form Model for Ozone Based on Two Decades of CMAQ Simulations for the Continental United States. Atmospheric Pollution Research. Turkish National Committee for Air Pollution Research and Control, Izmir, TURKEY, 8(2): 275-284, (2017).

The data sets includes the data used to generate the figures presented in the manuscript. Each worksheet in the attached file provides data for a specific figure (as labeled). This dataset is associated with the following publication: Zhou, L., K. Baker, S. Napelenok, G. Pouliot, R. Elleman, S. O'Neill, S. Urbanski, and D. Wong. Modeling crop residue burning experiments to evaluate smoke emissions and plume transport. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 627: 523-533, (2018).

The US EPA developed a set of modeled meteorology, emissions, air quality and pollutant deposition spanning the years 2002 through 2019. Modeled datasets cover the Conterminous US (CONUS) at a 12km horizontal grid spacing (12US1) and the Northern Hemisphere at a 108km (108NHEMI) using WRFv4.1.1 for meteorology and CMAQv5.3.2 for air quality modeling. New hemispheric and North American emissions inventories were developed using, to the extent possible, consistent input data and methods across all years, including emissions from mobile, fire, and oil and gas sources. Collectively these model outputs represent 100s of TB of data. We have selected a subset of the model input and output datasets that we hope will be most useful to the air quality research community. These datasets include: - Emissions inventory files for the CONUS for 2002-2019 suitable for input into the Sparse Matrix Operator Kernel Emissions (SMOKE) emission processor - CMAQ-ready emissions, initial conditions and boundary condition input files for the 12US1 domain for 2002-2019 - CMAQ-ready meteorology files for the 12US1 domain for 2013-2019. (Fewer years of meteorology data are included due to space constraints.) - Matched meteorology model output with surface observations for 2002-2019 - Daily average CMAQ output for the 12US1 domain for 2002-2019 for 14 pollutants - Daily average 3D CMAQ output for 44 layers for the 108NHEMI domain for 2002–2019

AQS data is a publicly available dataset, which is part of this study. This data can be found on EPA website https://aqs.epa.gov/aqsweb/airdata/download_files.html (accessed on 1 April 2023). PA data is a 3rd party data and restrictions apply to the availability of these data. Data was obtained from Purple Air and are available from PurpleAir API https://community.purpleair.com/t/making-api-calls-with-the-purpleair-api/180 (accessed on 1 April 2023) with the permission of Purple Air. HMS smoke plume data is publicly available and can be downloaded at Office of Satellite and Product Operations website https://www.ospo.noaa.gov (accessed on 1 April 2023). The codes to download and analyze data in this paper is available at this GitHub repo https://github.com/hyang199723/PAFusion (uploaded on 30 June 2023). This dataset is associated with the following publication: Yang, H., S. Ruiz-Suarez, B. Reich, Y. Guan, and A. Rappold. A data fusion approach to assessing the contribution of wildland fire smoke to fine particulate matter in California. Remote Sensing. MDPI, Basel, SWITZERLAND, 15(17): 1, (2023).