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Carbon Monoxide Impacts of Electronic Tolling Operations: Two Conflicting Assessments of a Promising Intelligent Transportation Technology

UCD-ITS-RP-95-55

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Proceedings of the 88th Air & Waste Management Association Meeting & Exhibition

On November 24, 1993, the US Environmental Protection Agency adopted the transportation conformity rule, pursuant to Section 17 6(c)(4) of the Clean Air Act. The conformity rule requires that transportation plans, programs, and projects funded or approved by the federal government or their agents under Title 23 (Highways) U.S.C. or the Federal Transit Act conform with state or Federal air quality implementation plans. Federal transportation planning regulations contain reciprocal language (40 CFR 450.312(d)), stipulating that the metropolitan planning organization shall not approve any plan or program that does not conform to the state implementation plan as determined in accordance with the conformity rule.

The final transportation/air quality conformity rule (23 CFR Part 450 and 49 CFR Part 613) constrains the development of transportation plans, improvement programs and projects and has increased pressure on statewide metropolitan transportation agencies to ensure that transportation and air quality plans are coordinated. Rigorous requirements for regional and local air quality modeling of transportation systems are included in the final conformity rule, and agencies are working diligently to meet these demands.

In response, transportation and air quality planners are looking for transportation strategies that will provide demonstrable air quality benefits. Emerging Intelligent Transportation Systems (ITS's) are being promoting by transportation planners as a means of reducing congestion delay, improving transportation safety, and also as a means of making vehicle travel "...more energy efficient and environmentally benign." Previous research has identified electronic toll collection using automatic vehicle identification technologies as a promising ITS. Unfortunately, the transportation-air quality community lacks the appropriate tools with which to predict the effects of microscopic changes to vehicular activity induced by ITS's. The currently used emissions models, EMFAC in California, and MOBILE in the remainder of the US, are unable to provide the resolution needed to quantify the effects of these changes. To make matters worse, the transportation activity models that are used to predict transportation activity do not provide the required level of detail to adequately predict emissions.

This research estimates the carbon monoxide (CO) emission impacts (running tailpipe emissions only) of electronic tolling operations in place of conventional toll plaza operations for a sample fleet of motor vehicles. A newly developed modal model, dubbed DITSEM, which takes into account important vehicular modal activity and vehicular attribute variables, is employed to estimate CO emissions. The results are then compared to CO emissions estimated by EMFAC7F, the emission inventory model used in California. The findings suggest that only by employing a true 'modal' model can we begin to identify environmentally beneficial ITS's, as current regional emission and transportation activity models are insufficient for this purpose. The findings are of critical importance to transportation and air quality planners, policy makers, and researchers. The results clearly demonstrate that the current regional emission modeling tools are insufficient and inadequate for assessing the emission impacts of transportation projects designed to smooth vehicular flows. Furthermore, current methods may yield erroneous results, leading to poor decisions and mis-allocation of transportation dollars.

This research is significantly different than previous research presented by the author for several important reasons. First, a newly developed and significantly more robust emission model, DITSEM, IS employed to estimate the emission impacts of electronic tolling. Second, the emission predictions are compared to the predictions offered by CARB's EMFAC7F model.