Performance Evaluation of Measure Emission Rates: a Comparison to Mobile5a

For the past five years, the Georgia Tech Research Partnership has been developing a research-grade motor vehicle emissions model within a geographic information system (GIS) framework. The model has been developed under a cooperative agreement with the US Environmental Protection Agency (USEPA) and the Federal Highway Administration (FHWA), and has involved the direct funding and in-kind contributions from a variety of public and private research partners. MEASURE (Mobile Emissions Assessment System for Urban and Regional Evaluation) is a comprehensive modeling package that integrates predictive modules for vehicle fleet composition, vehicle activity, onroad modal operation, and vehicle emission rates. The GIS framework of the model allows the linkage of typical 4-step travel demand model outputs, simulation model outputs, or monitored ATMS traffic volume estimates. The MEASURE model also contains several new modal emissions modeling approaches designed to improve predictions of CO, HC, and NOx for the onroad vehicle fleet. Hot stabilized emission rate algorithms within the MEASURE predict emission rates for motor vehicle technology groups as a function of the conditions under which the vehicles are operating, specifically speed and acceleration profiles. Vehicle activity variables modeled in MEASURE include average speed, acceleration rates, deceleration rates, idle time, and surrogates for power demand imposed on the engine. Vehicle and emission control technology variables include fuel metering system, catalytic converter type, supplemental air injection, and transmission speed. Although previous MEASURE-related papers have detailed model estimation methods, to date the authors have not reported the results of model validation. Previous publications have also never offered a comparison of the MEASURE model emission rate algorithms to those employed in the USEPA's MOBILE5a emission rate model. The validation efforts reported in this paper test of the ability of the MEASURE statistical model to adequately represent emissions cause-effect relationships and compare the MEASURE validation results with those of MOBILE5a. The statistical comparisons show that the MEASURE model provides significant improvements in both average emissions estimates and explanatory power over MOBILE5a for all three pollutants across almost every operating cycle tested. The most significant improvements arise in the CO and HC estimates, but even NOx emissions, which are a function of average speed, improve under the MEASURE modeling regime. In addition, the MEASURE model appears to be less biased (the most critical model performance measure for pointestimate forecasts) than MOBILE5a.