Input Variables and Data Sources
The following sections introduce the various categories of mobile source emissions reduction measures and provide quantification equations for estimating environmental benefits and cost effectiveness of individual measures under these categories. Input variables are defined for these equations and are necessary to analyze and document the emissions benefits of MOSERS. The input variables required for the quantification of emissions reductions achievable for various measures vary according to the type of measure. These variables are individually defined in the following sections and follow a consistent naming system based on the type of input variable. The types of inputs include:
Scoping Inputs – are inputs relating to the scope and scale of the measure, such as lengths (of facilities, etc.) or numbers (such as usage levels, number of trips or number of households, etc.), times, or fees/charges associated with the measures.
Traffic Inputs – include those related to traffic volumes/annual average daily traffic (AADT), delay, idling times, vehicle occupancies, mode shifts, trip lengths, parking facility utilization rates, vehicle miles of travel (VMT), or number of vehicle trips.
Emissions Inputs – include exhaust emissions factors (such as running exhaust, start exhaust, and evaporative hot soak) and trip emissions factors.
Factor Inputs – relate to percentage compliance or percentage usage of certain strategies or facilities, trip capture rates, and elasticities.
Detailed information about the input variables can be found in the appendix to this module. Locally specific data should be the preferred source for analysis, along with conservative, realistic assumptions applied where necessary. The equations documented in this module are a starting point. Users can make their case about data limitation and modify equations to get valid results. All assumptions and modifications should be documented for the benefit of review agencies.
Broadly speaking, data sources for these inputs range from those that are fairly easy to acquire from local data or knowledge to those that may require specialized surveys or field data collection. In the absence of local data, informed assumptions based on practitioner knowledge can be used. Default values should only be used if local-specific values are not available, too costly, or difficult to collect. The Texas Department of Transportation (TxDOT), metropolitan planning organizations (MPOs), transit agencies, city departments of transportation (DOTs), and other local agencies are all valuable sources of data and information. TxDOT, for example, performs local traffic counts statewide and is a valuable source of basic traffic volume information. City DOTs and MPOs may also have traffic volume data. Other important sources of data include regional travel demand model outputs, other traffic analysis data, census data, and local travel surveys. EPA’s current emissions model (MOVES) can provide emissions factors needed for many of the emissions-related variables. The final unit of measure for each strategy is grams per day.