GENERAL INFORMATION

Title: Data and visualizations of air quality impacts of conventional and alternative light-duty transportation in the United States

File Information:
	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.
	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 - PDF showing two figures from related publication; contains graphs comparing mortality and externality costs associated with different emission types. 

Authors:
	Christopher W. Tessum, Department of Civil Engineering, University of Minnesota
	Jason D. Hill, Department of Bioproducts and Biosystems Engineering, University of Minnesota
	Julian D. Marshall, Department of Civil, Environmental, and Geo- Engineering, University of Minnesota

Contact for data set:
	Julian D. Marshall (julian@umn.edu)


Time period covered by data:
	2005

Geographic location covered by data:
	United States

Funding information:
	University of Minnesota Institute on the Environment Initiative for Renewable Energy and the Environment (Grants No. Rl-0026-09 and RO-0002-11)
	U.S. Department of Energy (Award No. DE-EE0004397)
	Computational Resources provided by Minnesota Supercomputing Institute and Department of Energy National Center for Computational Sciences


METHODOLOGICAL INFORMATION

Data collection described in Related Publication:  
	Christopher W. Tessum, Jason D. Hill, and Julian D. Marshall. (In press). “Life cycle air quality impacts of con- ventional and alternative light-duty transportation in the United States”, Proc. Natl. Acad. Sci.

Summary of project: 
	Our study is a life cycle assessment. Life cycle assessment is a method for tracking all of the environmental releases---in this case air pollution emissions---that are caused by a certain product or activity. In our study, the activity is driving in either conventional or alternative vehicles. This data set was generated with models, mainly GREET-cst (http://pubs.acs.org/doi/full/10.1021/es3010514) and WRF-Chem(http://www.sciencedirect.com/science/article/pii/S1352231005003560).

File-specific notes:
	DatasetS1.xls: In the Excel file, each row shows the fraction of total life cycle emissions from each stage or process of the life cycle of vehicle fuels caused by driving a certain number of miles---both from the vehicle tailpipes and from other sources, such as refining the fuels. The last row in each spreadsheet shows the overall total life cycle emissions---emissions from all of the stages of the life cycle combined. Air pollution is made up of many different chemical compounds. Usually when researchers think about air pollution they aggregate the compounds into groups. The "Process" spreadsheets contain emissions aggregated into broad groups of chemicals, whereas the "Speciated" spreadsheets contain emissions split up into more detailed chemical groups.
	DatasetS2.pdf: Each map within a set of maps shows how we predict how pollutant concentrations will change as the result from one of our transportation scenarios. The "gasoline" scenario is where we assume people will keep driving gasoline vehicles, and the other scenarios assume we switch to an alternative technology or fuel.
	Videos: The Excel files are for emissions of pollutants, whereas the videos are for pollutant concentrations. PM2.5 and O3 are the two pollutants that cause the most public health damages, so they're the ones we're interested in predicting concentrations of. The relationship between pollutant emissions (Excel file) and pollutant concentrations (videos and maps) is complex; we use the WRF-Chem meteorology and chemical transport model to estimate the concentrations that result from a given emissions scenario.

Acronyms/Abbreviations:
	The DatasetS1.xls file contains a "README" worksheet. This worksheet serves as a dictionary for all acronyms and abbreviations found throughout the data set. 


SHARING/ACCESS INFORMATION

License: Attribution-NonCommercial-ShareAlike 3.0 United States
License URI: http://creativecommons.org/licenses/by-nc-sa/3.0/us/
Recommended citation for data set:  Tessum, Christopher W.; Hill, Jason D.; Marshall, Julian D.. (2014). Data and visualizations of air quality impacts of conventional and alternative light-duty transportation in the United States [dataset]. Retrieved from the Data Repository for the University of Minnesota, http://dx.doi.org/10.13020/D6159V. 




This README.txt file was generated on Dec. 29, 2014 by John McGrory