Search

As input to a winter use plan, activity, fuel use, and tailpipe exhaust emissions of over snow vehicles (OSV), including five snow coaches and one snowmobile, were measured on a designated route in Yellowstone National Park (YNP). Engine load was quantified in terms of vehicle specific power (VSP), which is a function of speed, acceleration, and road grade. Compared to highway vehicles, VSP for OSVs is more sensitive to rolling resistance and less sensitive to aerodynamic drag. Fuel use rates increased linearly (R2 > 0.96) with VSP. For gasoline-fueled OSVs, fuel-based emission rates of carbon monoxide (CO) and nitrogen oxides (NOx) typically increased with increasing fuel use rate, with some cases of very high CO emissions. For the diesel OSVs, which had selective catalytic reduction and diesel particulate filters, fuel-based NOx and particulate matter (PM) emission rates were not sensitive to fuel flow rate, and the emission controls were effective. Inter vehicle variability in cycle average fuel use and emissions rates for CO and NOx was substantial. However, there was relatively little inter-cycle variation in cycle average fuel use and emission rates when comparing driving cycles. Recommendations are made regarding how real-world OSV activity, fuel use, and emissions data can be improved. [ABSTRACT FROM AUTHOR]

Plug-in hybrid electric vehicles (PHEVs) could reduce transportation air emissions and energy use. However, a method is needed for estimating on-road emissions of PHEVs. To develop a framework for quantifying microscale energy use and emissions (EU&E), measurements were conducted on a Toyota Prius retrofitted with a plug-in battery system on eight routes. Measurements were made using the following: (1) a data logger for the hybrid control system; (2) a portable emissions measurement system; and (3) a global positioning system with barometric altimeter. Trends in EU&E are estimated based on vehicle specific power. Energy economy is quantified based on gasoline consumed by the engine and grid energy consumed by the plug-in battery. Emissions from electricity consumption are estimated based on the power generation mix. Fuel use is approximately 30% lower during plug-in battery use. Grid emissions were higher for CO2, NOx, SO2, and PM compared to tailpipe emissions but lower for CO and hydrocarbons. EU&E depends on engine and plug-in battery operation. The use of two energy sources must be addressed in characterizing fuel economy; overall energy economy is 11% lower if including grid energy use than accounting only for fuel consumption. [ABSTRACT FROM AUTHOR]

Background: A critical aspect of air pollution exposure assessments is determining the time spent in various microenvironments (ME), which can have substantially different pollutant concentrations. We previously developed and evaluated a ME classification model, called Microenvironment Tracker (MicroTrac), to estimate time of day and duration spent in eight MEs (indoors and outdoors at home, work, school; inside vehicles; other locations) based on input data from global positioning system (GPS) loggers., Objective: In this study, we extended MicroTrac and evaluated the ability of using geolocation data from smartphones to determine the time spent in the MEs., Method: We performed a panel study, and the MicroTrac estimates based on data from smartphones and GPS loggers were compared to 37 days of diary data across five participants., Results: The MEs were correctly classified for 98.1% and 98.3% of the time spent by the participants using smartphones and GPS loggers, respectively., Significance: Our study demonstrates the extended capability of using ubiquitous smartphone data with MicroTrac to help reduce time-location uncertainty in air pollution exposure models for epidemiologic and exposure field studies., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)