@article{rastogi_frey_wei_2023, title={Identifying emissions hotspots and strategies to reduce real-world fuel use and emissions for passenger rail: A spatially resolved approach}, volume={896}, ISSN={["1879-1026"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85164224998&partnerID=MN8TOARS}, DOI={10.1016/j.scitotenv.2023.165110}, abstractNote={The objectives of this work are to model spatially resolved passenger locomotive fuel use and emission rates, locate emissions hotspots, and identify strategies to reduce trip train fuel use and emissions. Train fuel use and emission rates, speed, acceleration, track grade, and track curvature were quantified based on over-the-rail measurements, using portable emission measurement systems, for diesel and biodiesel passenger rail service on the Amtrak-operated Piedmont route. Measurements included 66 one-way trips and 12 combinations of locomotives, consists, and fuels. A locomotive power demand (LPD) based emissions model was developed based on the physics of resistive forces opposing train motion, taking into account factors such as speed, acceleration, track grade, and curvature. The model was applied to locate spatially-resolved locomotive emissions hotspots on a passenger rail route, and also identify train speed trajectories with low trip fuel use and emissions. Results show that acceleration, grade, and drag are the major resistive forces affecting LPD. Hotspot track segments have 3 to 10 times higher emission rates than non-hotspot segments. Real-world trajectories are identified that reduce trip fuel use and emissions by 13 % to 49 % compared to the average. Strategies for reducing trip fuel use and emissions include dispatching energy-efficient and low-emitting locomotives, using a 20 % blend of biodiesel, and operating on low-LPD trajectories. Implementing these strategies will not only decrease trip fuel use and emissions but reduce the number and intensity of hotspots and, thus, lowering the potential for exposure to train-generated pollution near railroad tracks. This work provides insights on reducing railroad energy use and emissions, which would lead to a more sustainable and environmental-friendly rail transportation system.}, journal={SCIENCE OF THE TOTAL ENVIRONMENT}, author={Rastogi, Nikhil and Frey, H. Christopher and Wei, Tongchuan}, year={2023}, month={Oct} }
 @article{ahn_aredah_rakha_wei_frey_2023, title={Simple Diesel Train Fuel Consumption Model for Real-Time Train Applications}, volume={16}, ISSN={["1996-1073"]}, url={https://doi.org/10.3390/en16083555}, DOI={10.3390/en16083555}, abstractNote={This paper introduces a simple diesel train energy consumption model that calculates the instantaneous energy consumption using vehicle operational input variables, including the instantaneous speed, acceleration, and roadway grade, which can be easily obtained from global positioning system (GPS) loggers. The model was tested against real-world data and produced an error of −1.33% for all data and errors ranging from −12.4% to +8.0% for energy consumption of four train datasets amounting to a total of 5854 km trips. The study also validated the proposed model with separate data that were collected between Valencia and Cuenca, Spain, which had a total length of 198 km and found that the model was accurate, yielding a relative error of −1.55% for the total energy consumption. These results show that the proposed model can be used by train operators, transportation planners, policy makers, and environmental engineers to evaluate the energy consumption effects of train operational projects and train simulation within intermodal transportation planning tools.}, number={8}, journal={ENERGIES}, author={Ahn, Kyoungho and Aredah, Ahmed and Rakha, Hesham A. and Wei, Tongchuan and Frey, H. Christopher}, year={2023}, month={Apr} }
 @article{yuan_frey_wei_2022, title={Fuel use and emission rates reduction potential for light-duty gasoline vehicle eco-driving}, volume={109}, ISSN={["1879-2340"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85134667996&partnerID=MN8TOARS}, DOI={10.1016/j.trd.2022.103394}, abstractNote={Eco-driving offers potential to reduce fuel use and emission rates for light-duty gasoline vehicles (LDGVs). The objective is to quantify real-world route-level and segment-level fuel use and emission rates reduction potential for LDGV eco-driving. Three million seconds of real-world speed trajectory data were analyzed based on predominantly naturalistic driving of 160 drivers on eight mesoscale routes. The routes were further divided into 199 segments. A Vehicle Specific Power modal model was used to estimate trajectory-average fuel use and emission rates of CO2, CO, hydrocarbons, NOx, and particulate matter and to identify eco-driving trajectories. For route-level eco-driving, fuel use and emission rates reduction potential ranges from 6% to 40%, compared to average fuel use and emission rates estimated based on all trajectories. Eco-driving focused on fuel savings typically reduced air emissions and vice versa. Route-level eco-driving typically but not always concurrently reduces segment-level fuel use and emission rates. These co-benefits and tradeoffs can be used to guide LDGV eco-driving decisions.}, journal={TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT}, author={Yuan, Weichang and Frey, Christopher and Wei, Tongchuan}, year={2022}, month={Aug} }
 @article{wei_frey_2022, title={Intermodal comparison of tailpipe emission rates between transit buses and private vehicles for on-road passenger transport}, volume={281}, ISSN={["1873-2844"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85129721755&partnerID=MN8TOARS}, DOI={10.1016/j.atmosenv.2022.119141}, abstractNote={Modal shift from private vehicles (PVs) to transit buses has the potential to reduce energy use and emissions from on-road passenger transport. Comparisons between these modes may be sensitive to key factors, such as vehicle size, fuel and powertrains, passenger load, and travel routes. The objectives are to evaluate the sensitivity of emission rates to route alignment, and compare emission rates between PVs and buses accounting for variability in key factors. Real-world bus speed trajectories were measured on actual bus routes for four origin-destination pairs (ODPs). To evaluate the sensitivity of emission rates to route alignment, hypothetical alternative bus routes were posited based on shortest distance, shortest travel time, or observed PV routes for each ODP. Trajectories and emission rates for PVs were quantified based on prior measurements of two routes per ODP using portable emission measurement systems. Trip-based tailpipe CO2, CO, total hydrocarbons (THC), NOx, and particulate matter (PM) emission rates were estimated for each ODP for gasoline and gasoline-hybrid PVs based on a Vehicle Specific Power modal model and for compressed natural gas, diesel, and diesel-hybrid buses based on the Transit Bus Emissions Model. Break-even passenger load (BEPL) was quantified to assess the minimum bus passenger load needed to achieve lower per passenger-trip emissions compared to PVs. Bus emission rates per bus-trip on actual bus routes are generally higher than those on hypothetical routes. As a bounding analysis, compared to single-occupancy PVs, fully occupied buses are estimated to have 82%–94% lower CO2, 99% lower to 308% higher CO, 99% lower to 145% higher THC, 67% lower to 62% higher NOx, and 94%–99% lower PM emission rates per passenger-trip depending on vehicle size, fuel and powertrain, passenger load, and route. BEPL varies depending on vehicle size, fuel and powertrain, route, and pollutant. The relative importance of key factors affecting intermodal comparisons differs by pollutants. The intermodal comparison is also affected by interactions among key factors, such as passenger load and route alignment, which reinforces the need for joint consideration of key factors.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Wei, Tongchuan and Frey, H. Christopher}, year={2022}, month={Jul} }
 @article{wei_frey_2021, title={Sensitivity of light duty vehicle tailpipe emission rates from simplified portable emission measurement systems to variation in engine volumetric efficiency}, volume={6}, ISSN={["2162-2906"]}, url={https://doi.org/10.1080/10962247.2021.1923586}, DOI={10.1080/10962247.2021.1923586}, abstractNote={ABSTRACT Light-duty gasoline vehicle (LDGV) tailpipe emission rates can be quantified based on pollutant concentrations measured using portable emission measurement systems (PEMS). Emission rates depend on exhaust flow. For simplified and micro-PEMS, exhaust flow is inferred from engine mass air flow (MAF) and air-to-fuel ratio. For many LDGVs, MAF is broadcast via the on-board diagnostic (OBD) interface. For some vehicles, only indirect indicators of MAF are broadcast. In such cases, MAF can be estimated using the speed-density method (SDM). The SDM requires an estimate of the engine volumetric efficiency (VE), which is the ratio of actual to theoretical MAF. VE is affected by intra-vehicle variability in the engine load and inter-vehicle variability in engine characteristics (e.g., the type of valvetrain). The suitability of SDM-based estimates of MAF in conjunction with simplified and micro-PEMS has not been adequately evaluated. Therefore, the objectives are to: (1) quantify VE accounting for intra- and inter-vehicle variability; and (2) evaluate the accuracy of SDM-based vehicle emission rate estimation approaches. Seventy-seven naturally-aspirated LDGVs were measured using PEMS. For each vehicle, VE was estimated using three approaches: (1) constant VE calibrated to actual fuel use; (2) average estimates of VE for Vehicle Specific Power modes imputed from OBD data; and (3) modeled VE using multilinear regression (MLR). The MLR models were developed based on engine load and engine characteristics. The best model was selected based on various statistical diagnostics. When engines were under load, variability in VE was most sensitive to variations in engine load. During idling, VE differed between engines depending on engine characteristics. The constant and modeled VE estimation approaches enable the accurate estimation of microscale and mesoscale emission rates, with errors typically within ±10% compared to values imputed from OBD data. Thus, accurate emission rates can be obtained from simplified and micro-PEMS. Implications: Simplified and micro portable emission measurement systems (PEMS) enable widespread measurement of vehicle exhaust emission. As a cost saving measure, they estimate exhaust flow indirectly rather than via measurement, typically based on engine mass air flow (MAF). For some vehicles, MAF is not reported by the on-board diagnostic (OBD) system but can be inferred from other reported variables and volumetric efficiency (VE). However, VE is typically proprietary. Methods demonstrated here for estimating VE enable accurate quantification of emission rates, thereby enabling use of these PEMS for policy-relevant applications such as technology assessments, trends analysis, and emissions inventories.}, number={9}, journal={JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION}, publisher={Informa UK Limited}, author={Wei, Tongchuan and Frey, H. Christopher}, year={2021}, month={Jun} }
 @article{wei_frey_2020, title={Evaluation of the Precision and Accuracy of Cycle-Average Light Duty Gasoline Vehicles Tailpipe Emission Rates Predicted by Modal Models}, volume={2674}, ISSN={["2169-4052"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85094930128&partnerID=MN8TOARS}, DOI={10.1177/0361198120924006}, abstractNote={ A vehicle specific power (VSP) modal model and the MOtor Vehicle Emission Simulator (MOVES) Operating Mode (OpMode) model have been used to evaluate and quantify the fuel use and emission rates (FUERs) for on-road vehicles. These models bin second-by-second FUERs based on factors such as VSP, speed, and others. The validity of binning approaches depends on their precision and accuracy in predicting variability in cycle-average emission rates (CAERs). The objective is to quantify the precision and accuracy of the two modeling methods. Since 2008, North Carolina State University has used portable emission measurement systems to measure tailpipe emission rates for 214 light duty gasoline vehicles on 1,677 driving cycles, including 839 outbound cycles and 838 inbound cycles on the same routes. These vehicles represent a wide range of characteristics and emission standards. For each vehicle, the models were calibrated based on outbound cycles and were validated based on inbound cycles. The goodness-of-fit of the calibrated models was assessed using linear least squares regression without intercept between model-predicted versus empirical CAERs for individual vehicles. Based on model calibration and validation, the coefficients of determination ( R2) typically range from 0.60 to 0.97 depending on the vehicle group and pollutant, indicating moderate to high precision, with precision typically higher for higher-emitting vehicle groups. The slopes of parity plots for each vehicle group and all vehicles typically range from 0.90 to 1.10, indicating good accuracy. The two modeling approaches are similar to each other at the microscopic and macroscopic levels. }, number={7}, journal={TRANSPORTATION RESEARCH RECORD}, author={Wei, Tongchuan and Frey, H. Christopher}, year={2020}, month={Jul}, pages={566–584} }
 @article{wei_frey_2020, title={Factors affecting variability in fossil-fueled transit bus emission rates}, volume={233}, ISSN={["1873-2844"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85084988997&partnerID=MN8TOARS}, DOI={10.1016/j.atmosenv.2020.117613}, abstractNote={Globally, there are over 10 million transit buses. Exhaust emissions from transit buses include carbon dioxide (CO2), carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NOx), and particulate matter (PM). Key factors affecting bus emission rates have been evaluated separately or in limited combinations in prior studies, including bus size, fuel and powertrain, passenger load, driving cycle, and model year. However, bus emission rates are jointly affected by all of these factors. To systematically evaluate these factors, a transit bus emissions model (TBEM) was developed. TBEM is calibrated based on generic compressed natural gas (CNG) and diesel bus types represented in the U.S. Environmental Protection Agency MOtor Vehicle Emission Simulator and empirical cycle average emission rates from the Integrated Bus Information System. The importance of the factors varies depending on the pollutant. For emission rates per vehicle-kilometer, model year is an important factor for NOx and PM, fuel and powertrain is an important factor for CO and THC, and driving cycle and bus size are important factors for CO2. For emission rates per passenger-kilometer, passenger load is generally an important factor for each pollutant. For a given fuel and powertrain and pollutant, smaller buses have lower emission rates per vehicle-kilometer than larger buses. However, a full large bus has lower emission rates per passenger-kilometer than a full small bus. There are tradeoffs among bus types regarding emission rates, especially for THC and PM. The comparison of bus emission rates is dependent on interactions between these key factors. For example, the effect of bus size and passenger load on emission rates is larger for lower speed driving cycles. For 2010 and newer model year buses and for moderate to high speed driving cycles, diesel buses have the lowest NOx emission rates whereas for low speed cycles, CNG buses have the lowest NOx emission rates. However, for 2007 to 2009 model year buses, CNG buses have the lowest NOx emission rates regardless of driving cycle. The study will be useful in helping transit planners and policy makers to develop strategies to reduce transit bus fleet emissions and in providing accurate emission factors for use in bus life cycle inventories and emission inventories.}, journal={ATMOSPHERIC ENVIRONMENT}, author={Wei, Tongchuan and Frey, H. Christopher}, year={2020}, month={Jul} }
 @article{yuan_frey_wei_rastogi_vandergriend_miller_mattison_2019, title={Comparison of real-world vehicle fuel use and tailpipe emissions for gasoline-ethanol fuel blends}, volume={249}, ISSN={["1873-7153"]}, url={https://doi.org/10.1016/j.fuel.2019.03.115}, DOI={10.1016/j.fuel.2019.03.115}, abstractNote={Differences in fuel use and emission rates of carbon dioxide (CO2), carbon monoxide (CO), hydrocarbons (HC), nitrogen oxide (NOx), and particulate matter (PM) were quantified for three gasoline-ethanol blends and neat gasoline measured for one flexible-fuel vehicle (FFV) and four non-FFVs using a portable emission measurement system (PEMS). The purpose was to determine if non-FFVs can adapt to a mid-level blend and to compare the fuel use and emission rates among the fuels. Each vehicle was measured on neat gasoline (E0), 10% ethanol by volume (E10) “regular” (E10R) and “premium” (E10P), and 27% ethanol by volume (E27). Four real-world cycles were repeated for each vehicle with each fuel. Second-by-second fuel use and emission rates were binned into Vehicle Specific Power (VSP) modes. The modes were weighted according to real-world standard driving cycles. All vehicles, including the non-FFVs, were able to adapt to E27. Octane-induced efficiency gain was observed for higher octane fuels (E10P and E27) versus lower octane fuels (E0 and E10R). E27 tends to lower PM emission rates compared to E10R and E10P and CO emission rates compared to the other three fuels. HC emission rates for E27 were comparable to those of E10R and E10P. No significant difference was found in NOx emission rates for E27 versus the other fuels. Intervehicle variability in fuel use and emission rates was observed. Lessons learned regarding study design, vehicle selection, and sample size, and their implications are discussed.}, journal={FUEL}, publisher={Elsevier BV}, author={Yuan, Weichang and Frey, H. Christopher and Wei, Tongchuan and Rastogi, Nikhil and VanderGriend, Steven and Miller, David and Mattison, Lawrence}, year={2019}, month={Aug}, pages={352–364} }