4.1.1.1. 4.1.1.1 Methods and Assumptions

Emissions were estimated for the proposed management actions in each alternative for particulate matter less than 10 microns in diameter (PM10 ), particulate matter less than 2.5 microns in diameter (PM2.5 ), nitrogen oxides (NOx ), sulfur dioxide (SO2), carbon monoxide (CO), volatile organic compounds (VOCs), and HAPs. The BLM estimated emissions for the base year (2005) corresponding to Alternative A. This year was selected for the base year because it was the closest year with the most complete information. The BLM also estimated emissions for two future years (2015 and 2024) to examine potential impacts mid-way through the 20-year plan and at the end of the plan. The analysis compares operational emissions for 2015 and 2024 to base-year emissions to determine the expected future change in emission levels for each alternative. Given the uncertainties concerning the number, nature, duration, and specific location of future emission sources and activities, the emission comparison approach provides an appropriate basis for comparing the potential impacts under each alternative.

Activity data used to estimate emissions for proposed emission sources were obtained from the BLM Resource Specialists in the Cody and Worland field offices (CYFO and WFO). Emission factors used to estimate proposed emissions were obtained from (1) the U.S. Environmental Protection Agency (EPA) NONROAD2008a Emissions Model (EPA 2008), (2) Wyoming Department of Environmental Quality (DEQ) best available control technology (BACT) levels for natural-gas-fired internal combustion engines, and (3) the EPA MOBILE6.2.03 mobile emissions factor model for on-road motor vehicles (EPA 2003). The Technical Support Document for Air Quality (Appendix U) includes information regarding the data and assumptions used to estimate emissions for each project alternative and the detailed emission totals for each activity per year.

Methods and assumptions used in this impact analysis include the following:

Analysts calculated emissions for the following types of development and use activities: (1) oil development, (2) natural gas development, (3) salable minerals development, (4) locatable minerals development, (5) renewable energy development, (6) livestock management activities, (7) vegetation management, (8) vegetation management of invasive species, (9) fire management (including prescribed fire), (10) forests, woodlands, and forest products activities, (11) rights-of-way (ROW) and corridors, (12) OHV use, and (13) resource road maintenance. Emission estimates are provided for all of the alternatives. Fugitive VOC emissions from oil and gas development operations and emissions from any prescribed fire activities conducted on BLM land within the Planning Area have not been estimated in this analysis. In addition, activities related to the management of cultural resources, paleontology, recreation, and fish and wildlife would produce inconsequential amounts of emissions to the atmosphere.

It should be noted that impacts for all alternatives have been analyzed herein using estimates of emissions only, rather than any type of air quality modeling. If a particular project is proposed under any of the alternatives, the BLM may require that a quantitative air quality modeling analysis be conducted to determine the potential effects from proposed emission sources and the effects of potential mitigation strategies for projects expected to approach or exceed the applicable standards. For quantifying the potential impacts of project emissions on ozone and secondary PM2.5 , an air quality modeling system such as the EPA’s Community Multiscale Air Quality (CMAQ) model or the similar, alternative Comprehensive Air Quality Model with extensions CAMx model, would be used. The modeling exercise would require substantial resources and time to (1) gather regional precursor emissions from all anthropogenic and biogenic sources, (2) simulate the meteorological conditions for a sufficient period of time (typically a 1-year period) with a meteorological model, and (3) use this information to apply the air quality model and assess future-year impacts using the future-year emission estimates. Because ozone and PM2.5 are secondary pollutants and the atmospheric chemistry of their formation is not always linear, the application of an air quality modeling system such as CMAQ (or CAMx) is the best way to assess potential future air quality impacts for these pollutants. With models such as CMAQ or CAMx, impacts from individual sources or groups of sources can be separately assessed to quantify impacts and evaluate potential control or mitigation measures to reduce emissions.