An accurate and sufficiently detailed emissions inventory is a key input for air quality modeling, yet significant uncertainties exist with current emissions estimates for non-road mobile sources. These estimates are typically prepared using default activity, spatial, and temporal data contained in tools such as the U.S. EPA’s NONROAD model. The objective of this project was to develop and document methods that could be used to improve the estimation and spatial and temporal allocation of emissions from lawn and garden equipment, an important non-road mobile source category in urban areas.
STI and Population Research Systems conducted surveys of residential and commercial lawn and garden equipment users in Baltimore, Maryland; the case study city selected for the project. Surveys were designed to gather detailed information that could be used to develop improved equipment population, activity, and temporal data for lawn and garden equipment in the region. These data were then used to replace default data in the NONROAD model and calculate improved estimates of criteria pollutant and CO2 emissions from lawn and garden equipment.