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Implications of the Implementation of the MOBILE6 Emissions Factor Model on Project-Level Impact Analyses Using the CAL3QHC Dispersion Model

3 Summary of Findings

As a result of this study, a number of useful insights have been developed on the impact of MOBILE6 on project-level analysis. Summarized in this section are the most critical and sensitive input parameters, along with the identification of methods to develop key inputs, if needed. In addition, a screening-level procedure for project-level studies using MOBILE6 is discussed.

3.1 Key Findings from MOBILE5 versus MOBILE6 Model Comparison

A review of the MOBILE6 changes relevant to the impact on project-level analysis suggested that ten scenarios, described below, will be of primary interest to the project-level analyst in assessing the change between using MOBILE5 and MOBILE6. These scenarios reflect both typical applications and/or potential changes from national distributions with anticipated significant impacts on CO emission factors. The scenarios evaluated were:

For 2005, MOBILE6 produces lower emission factors than MOBILE5 at low speeds (between idle and 19.5 mph) across all temperatures and scenarios. This trend reverses for higher speeds. For 2035, MOBILE6 emission factors are lower than the corresponding MOBILE5 emission factors for all scenarios, including higher speeds. Thus, for the earlier years, MOBILE6 will always estimate lower emission rates than MOBILE5 for low speeds, but higher emission rates for higher speeds. For later years, MOBILE6 will always provide lower emission rates than MOBILE5.

For I/M changes, both models behave in a similar manner. The shift of three years in the average fleet distribution is treated in a similar manner by both MOBILE5 and MOBILE6 in both 2005 and 2035. For the 30% shift in the light-duty vehicle VMT fraction for 2005 and 2035, MOBILE5 is slightly more influenced by the shift in fleet than is MOBILE6.

For all scenarios, MOBILE6 factors change less rapidly as a function of speed than the corresponding MOBILE5 factors. For the scenarios assessed, the largest changes between MOBILE5 and MOBILE6 are the scenarios with shifts in the average age fleet distribution for light-duty vehicles and trucks with differences of up to 57% lower in the 2005 MOBILE6 emissions and 80% lower in 2035.

3.2 MOBILE6 Impact on CAL3QHC Validity

Two studies have performed extensive monitored-to-modeled comparison of the CAL3QHC model. The first study, "Evaluation of CO Intersection Modeling Techniques Using a New York City Database" (Sigma Research, 1992), was conducted in 1989 and used the MOBILE4.1 emission factor model. This study formed the basis for EPA's selection of the CAL3QHC model as the preferred guideline model for project-level analysis. The second study is NCHRP25-6, "Intersection Air Quality Modeling," which is a mid-1990s study, which used the MOBILE5 emission factor model for three intersections in Tucson, Arizona; Denver, Colorado; and Sterling, Virginia.

CAL3QHC was evaluated for three key intersections all located in Manhattan. Studies have shown that CAL3QHC model simulation results are usually driven by queue length and number of lanes (queue density) for overcapacity conditions. Queue emissions result from idling. In most cases the highest CO concentrations occurred during overcapacity situations. Thus, the focus for the validation study was on how idle emissions have changed between the two versions of the model.

Overall, the idle emissions decreased significantly for MOBILE6.2, relative to either MOBILE5 or MOBILE4.1, while moving emissions increased. Historically, analyses of roadway intersections have found that high concentrations are a result of large queue emissions and hence, the idle emission factor. This tradeoff in emissions will likely impact the CAL3QHC model by lowering concentrations in most situations where queue length is important. Because the model performance evaluation of CAL3QHC in the Route 9a study tended to underpredict for all three intersections, the model bias will likely increase. However, this somewhat contrasts with the NCHRP25-6 study results which suggest that MOBILE6.2 will improve model performance relative to its evaluation based on using MOBILE5. Some of this difference may be the result of changes in engine technology since these evaluation studies were based on pre-1990 and pre-1995 vehicles. It is possible that differences between the two MOBILE models may be considerably different for a newer fleet of vehicles. If however, today's fleet is analogous to the NCHRP's pre-1995 fleet then the use of the MOBILE6.2 model as input to CAL3QHC for project-level analysis will likely improve model performance.

3.3 MOBILE6 Impact on Characterizing Start Emissions

With the release of MOBILE6, EPA recommended that, in most instances, the model's emission factor estimates should be used without adjustment for start fraction since nearly all emissions are hot-stabilized, unless the location is near a parking garage, shopping center or similar facility with a large number of start emissions. Additional locations have been identified under which start emissions should be considered. These locations are:

For each of these locations a methodology has been identified for estimating start emission characterizations. In general, these methods use a combination of historical survey data in combination with an estimate of facility size to estimate the number of starts. In addition to borrowing results from these studies, several alternative methods have been presented for collecting data to characterize soak distribution for project-specific locations. These methods are relatively inexpensive to implement relative to a fully instrumented vehicle study.

3.4 MOBILE6 Impact on Project-level Results

Implementation of MOBILE6 will affect the results of project-level analysis. An assessment was made using the CAL3QHC model for typical high volume freeways and high volume intersections. Modeling was performed for a variety of emissions scenarios representing the expected range of differences between MOBILE5 and MOBILE6 models for the base year of 2005 and a future year of 2035. In addition, an assessment was made on the impact of start emissions for an urban and a suburban intersection for several levels of services, assuming that one-fourth of the vehicles arriving are in start mode.

Six scenarios for emissions calculations were developed to create "incremental" emissions factors that were used in the air quality modeling for the MOBILE5 to MOBILE6 change comparison. These were the same scenarios used in the MOBILE5 to MOBILE6 comparison. Each scenario was applied for 2005 and 2035 for a set of temperature and speeds and for an urban and suburban setting.

For the high volume freeway scenario, MOBILE6 produced higher concentrations than MOBILE5 for 2005, while in 2035, MOBILE6 was more comparable to MOBILE5, but produced higher concentrations at the lower temperatures. Thus, application of MOBILE6 for freeways in the near future years coupled with high traffic volumes and high background concentrations may present problems not currently demonstrated with MOBILE5.

For the suburban intersection scenarios, MOBILE6 produced lower ambient CO concentration values for every combination than did MOBILE5, ranging from 40% to 80% reductions. For the CBD intersection, too, the concentrations produced by the MOBILE6 model were always lower than those from MOBILE5, ranging from 34% to about 78% lower. The overall reductions in ambient concentration are somewhat less than for the suburban intersections. For the high number of start scenarios, both the urban and suburban intersections showed problems achieving the eight-hour CO standard. For 2035 the urban intersection meets the eight-hour standard, but the suburban intersection did not. In all cases, these exceedances are associated with the high idle emission factors associated with a high number of starts. Thus, intersections with a high number of start fractions and high volumes appear to have the potential for exceeding the CO standard.

3.5 MOBILE6 Impact on the Process of Project-level Analysis

Use of MOBILE6 has the potential to affect the process in which project-level analysis is performed. The potential processes may affect the need for additional information and local or state procedures, including estimates for background concentration and impacts on mitigation strategies. These three areas were explored primarily as a result of the interviews conducted during the study. A total of 24 individuals affiliated with state DOTs, MPOs and researchers/consultants who have experience working with MOBILE6 on project-level analyses were interviewed.

For those agencies using mostly default values no additional effort was found in applying the MOBILE6 model, while those developing location-specific input indicated that additional effort was needed to develop inputs to the model. Almost all state agencies contacted indicated that more time was required to complete project-level analysis using MOBILE6 compared to using MOBILE5, ranging from several hours to 40 hours. Most states have also found that future background concentrations of CO should be lowered as a result of MOBILE6's strong downward CO emission trends and estimates of regional VMT growth. As a result, a number of locations have, or are looking at, adopting new procedures for determining future background CO levels. For intersection modeling using MOBILE6, areas will need to change their "worst case" modeling receptors from intersection-based to a mid-block location. For mitigation, the traditional approach of increasing intersection capacity to achieve higher average speeds may result in overall emission increases.

3.6 MOBILE6 Impact on Screening-Level Procedure

Use of MOBILE6 has the likely potential to affect the screening assessment procedures for project-level analysis. This study has identified current efforts in revising screening-level procedures, as well as developing an approach for setting a threshold screening-level procedure. Also, this study has identified limitations in the applicability of the screening approach.

All of the state agencies interviewed base their screening assessment procedures on the transportation conformity rule which requires a project-level analysis for federally funded projects in CO nonattainment and maintenance areas. The conformity rule requires that a quantitative analysis, (e.g., using CAL3QHC) is required for projects: 1) in or affecting locations identified in the state implementation plan (SIP) as sites of potential or actual violations of the CO NAAQS, 2) affecting intersections that are at or will be at LOS12D or worse or 3) affecting intersections identified in the SIP as having the three highest volumes or three worst levels of service in the nonattainment or maintenance area. Most agencies use a modification of the LOS C screening approach (that is LOS C passes screening) which consists of LOS and traffic volume thresholds. Others use LOS C only. Several agencies are considering revising the procedure in light of MOBILE6, while three agencies are updating their screening procedures because of MOBILE6. In general, it is recommended that state agencies revisit their current screening procedures as MOBILE6 coupled with CAL3QHC does not yield the same results. Some of the key differences which may affect the current screening procedures include: speed curves exhibiting increased emissions following a low point around 30-35 mph, idle emission decreases and moving emission increases and a shift in worst case receptor concentration towards mid-block.

To examine the potential for CO air quality violations for project-level settings, an analysis was performed for a combination of levels of service D, E and F; two high volume, thee-lane approach intersection configurations; and a high volume, six-lane freeway for two speeds and two dispersion settings (urban and rural). The modeling was performed using the MOBILE6 emission factors for the years 2005, 2015, 2025 and 2035. MOBILE6 was applied using national default values to represent typical conditions.

Results suggest a limited potential for violations of the NAAQS at typical high volume locations in the near-term, and by 2015, the potential essentially disappears. However, both freeway and intersection scenarios show the potential for CO violations in 2005, assuming typical background concentrations. Also, modeling results suggest the potential for higher CO levels at a freeway operating at LOS E than at an intersection operating at LOS F. Thus, freeway scenarios should be examined, along with intersections, in setting a screening threshold assessment procedure. Results also show that, for intersections, the corner receptors no longer exhibit the highest concentration; the greatest concentrations are now typically found about 200 feet behind the front of the queue.

To more fully asses the applicability of this screening approach to the most extreme roadway settings, two additional roadway configurations were evaluated. The intersection was expanded to consist of two five-lane approaches, and the freeway was expanded to ten lanes. Results showed that nearly all of the predicted levels are below the CO NAAQS, with the exception of the near-term (2005 modeling runs) and in 2015, only locations in the very near freeway right-of-way.

Overall, this assessment found limited potential for the CO NAAQS violations for project-level studies under most typical conditions. In the past, LOS C has been widely used as a screening threshold to reduce the need for detailed modeling. Due to the changes from MOBILE 5 to MOBILE6, the relative role of cruise emissions has increased, while the idle emission factors have been substantially reduced. It appears likely that detailed modeling can be excluded for both intersection and freeway locations with LOS E or better under a wide variety of conditions, especially when looking beyond the near-term period (2015 or later).

The applicability of this screening approach is dependent on the circumstances of a given project and how closely they resemble the "normal" conditions. This analysis focused on applying a reasonable worst case condition that would capture the majority of real-world conditions. However, several exceptions can be noted: locations in very close proximity to very high volume freeways; locations with an extraordinary rate of start emissions, such as near a park and ride lot or CBD parking garage; a fleet much older than the national default age distribution; and locations with unusually high background concentrations. These type cases would need to be examined on a case-by-case basis. Nevertheless, it appears likely that the vast majority of typical projects will not require detailed modeling if the traffic analysis indicates that all signalized intersections and freeway sections will operate at LOS E or better.

Updated: 07/06/2011
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