Click for next page ( 7


The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 6
6 The regression model predicts the change in the growth rate potential impacts of traffic-flow improvements on heavy-duty in households and employment in each zone of the region vehicle and transit vehicle emissions are neglected. (The nec- as a function of the relative change of accessibility for each essary information on heavy-duty vehicle emission rates zone. Although not sophisticated enough to predict actual by mode of operation was not available at the time of this growth, the model should be sufficient to predict how small research.) Modal emission factors from the University of Cali- changes in travel time accessibility can affect the predicted fornia, Riverside, NCHRP 25-11 Comprehensive Modal baseline growth rate in specific zones of the region. Emission Model (CMEM) and Emission Factor 2000 The module presumes that total regional growth will be (EMFAC2000) are used to produce the emission estimates. unaffected by traffic-flow improvements (in other words, the The primary effects of traffic-flow improvement projects module will not be sensitive to the potential effects of differ- relate to speeds and delay along specific corridors. The direct ing levels of regional traffic-flow improvements on the com- emission effects include petitiveness of regions for attracting new households or jobs). The module predicts only how regional growth might be real- Running exhaust emissions (due to changes in vehicle located from marginally less accessible zones to more acces- speed and acceleration profiles, as well as changes in USER'S GUIDE sible zones within the region. VMT due to route choice), Running loss emissions (due to changes in total travel 2.6 VEHICLE MODAL ACTIVITY MODULE time), and Refueling and CO2 emissions (due to changes in fuel The Vehicle Modal Activity Module converts the macro- efficiency). scopic vehicle activity data produced by the previous modules (VHT and VMT by link, mode, and time period) to micro- CMEM was used to produce running exhaust emission scopic modal activity data (VHT by speed and acceleration rates for the specified speed and acceleration frequency dis- category). Four tables (Uncongested Freeway, Congested tributions (SAFDs) contained in the modal activity data. Freeway, Uncongested Arterial, Congested Arterial) contain- The impacts of traffic-flow improvements on running loss ing percentages are used to determine the proportion of total emissions and refueling/CO2 emissions are currently not vehicles-hours on each street and freeway segment that are included in the NCHRP 25-21 methodology. This is because spent in each speed/acceleration category. These tables were the NCHRP 25-21 methodology is based on CMEM, which derived from microsimulation of vehicle activity on example does not include these emissions. real-world sections of freeways and arterial streets using There are two secondary effects of traffic-flow improve- the Federal Highway Administration Corridor Simulation ment projects that influence emissions. First, to the extent (CORSIM) model. that traffic-flow improvement projects reduce total travel Additional tables for other facility types and varying intel- time, there may be some increase in the number of trips made, ligent transportation systems (ITS) and traffic management resulting in additional start emissions. Second, both reduced options can be created using the FHWA CORSIM program. travel time and increased numbers of trips alter the number The creation of such tables was beyond the resources of this and timing of hot soak, diurnal, and resting loss periods for research project and was consequently deferred to future the vehicle. Neither of these effects is included in CMEM, research. and, consequently, neither is included in the current version of the NCHRP 25-21 methodology. 2.7 VEHICLE EMISSION MODULE Virtually all emission rates depend on ambient tempera- ture. The NCHRP 25-21 methodology uses an average sum- The Vehicle Emission Module converts the passenger car mer day temperature profile for VOC and NOX, and an aver- modal activity data into estimates of vehicular emissions. The age winter day for CO analyses.