Tessum, Christopher WHill, Jason DMarshall, Julian D2014-11-252014-11-252014-11-25https://hdl.handle.net/11299/167997The repository includes five main files: DatasetS1.xls: A directory of Microsoft Excel files containing emissions amounts disaggregated by life cycle stage for each scenario. DatasetS2.pdf: Maps of annual average ground level concentrations of PM2.5, O3, PM10, NOx, HCHO, NH3, particulate SO4, particulate NH4, particulate NO3, organic aerosol, elemental carbon aerosol, particle number, and CO; maps of annual average daily peak O3 concentrations; and maps of PM2.5 and O3 concentrations animated by month of year, day of week, and hour of day for the baseline simulation and each scenario. A pdf viewer that allows embedded javascript, such as Adobe Acrobat, is required to view the animations. VideoS1.mp4: A video showing temporal variation in PM2.5 concentrations attributable to each scenario. VideoS2.mp4: A video showing temporal variation in O3 concentrations attributable to each scenario. PublicationFigures.pdf: A PDF containing Figures 2 and 3, along with accompanying data, from the related publication (dx.doi.org/10.1073/pnas.1406853111).This is the supporting information for an article entitled "Life cycle air quality impacts of conventional and alternative light-duty transportation in the United States", published in the Proceedings of the National Academy of Sciences of the United States (dx.doi.org/10.1073/pnas.1406853111). The study assesses the life cycle air quality impacts on human health of 10 alternatives to conventional gasoline vehicles, including vehicles powered by diesel, natural gas, ethanol, and electricity. This supporting information is comprised of 1) A Microsoft Excel file containing emissions amounts disaggregated by life cycle stage for each scenario; 2) maps of ground-level concentrations of 13 different air pollutants attributable to each scenario; and 3) videos showing temporal variation in ground-level fine particulate matter (PM2.5) and ozone (O3) concentrations attributable to each scenario. The data here were generated using state-of-the-science air pollutant emission and transport models.Attribution-NonCommercial-ShareAlike 3.0 United Stateshttp://creativecommons.org/licenses/by-nc-sa/3.0/us/bioelectricbiofuelchemicalelectricLCAspatialtemporaltransportationvehiclesvideomapair qualityDatasethttp://dx.doi.org/10.13020/D6159V