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Diesel commuter rail emissions affect populations near rail corridors. An approach is demonstrated to quantify mesoscale and microscale diesel commuter rail fuel use and emission rates (FUERs) of CO2, CO, NOx, particulate matter, and total hydrocarbons based on two U.S. systems. A speed trajectory simulator, an energy model, and an emissions model were calibrated, evaluated, and applied. FUERs and potential reductions from eco-driving were quantified based on simulated trajectories. Hotspots were defined as sections with ≥ 90th percentile of section-average FUERs by species. A few key variables explain 74–80% of variability in mesoscopic and microscopic FUERs. On average, FUERs are 7–8 times greater for hotspots than non-hotspots. Eco-driving was estimated to reduce segment-average FUERs by 3–33% and eliminate 2–11% hotspots. However, mesoscale oriented eco-driving can, at some locations, increase microscopic FUERs. The approach is adaptable to other diesel commuter rail systems.
Weichang Yuan; H. Christopher Frey. Multi-scale evaluation of diesel commuter rail fuel use, emissions, and eco-driving. Transportation Research Part D: Transport and Environment 2021, 99, 102995 .
AMA StyleWeichang Yuan, H. Christopher Frey. Multi-scale evaluation of diesel commuter rail fuel use, emissions, and eco-driving. Transportation Research Part D: Transport and Environment. 2021; 99 ():102995.
Chicago/Turabian StyleWeichang Yuan; H. Christopher Frey. 2021. "Multi-scale evaluation of diesel commuter rail fuel use, emissions, and eco-driving." Transportation Research Part D: Transport and Environment 99, no. : 102995.
Spatially varying diesel locomotive fuel use and emission rates (FUERs) are needed to accurately quantify local emission hotspots and their health impacts. However, existing locomotive FUER data are typically not spatially resolved or representative of real-world locomotive operation. Therefore, existing data are of limited use in quantifying the spatial variability in real-world FUERs. The objectives of this work are to quantify spatial variability in locomotive FUERs and identify factors differentiating hotspots from non-hotspots. FUERs were measured based on real-world measurements conducted for the Piedmont passenger rail service using a portable emission measurement system. FUERs were quantified based on 0.25 mile track segments on the Piedmont route. Hotspots were defined as segments in the top quintile of segment-average FUERs. On average, hotspots contributed 40–50% to trip fuel use and emissions. Hotspots were typically associated with low-to-medium speed, and high acceleration and grade. In contrast, non-hotspots were associated with high speed, and low acceleration and grade. Hotspots were typically located near populated areas and, thus, may exacerbate air pollutant exposure. The method demonstrated here can be applied to other passenger train services to assess key trends in hotspot locations and factors that explain the occurrence of hotspots.
Nikhil Rastogi; H. Christopher Frey. Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service. Environmental Science & Technology 2021, 55, 10633 -10644.
AMA StyleNikhil Rastogi, H. Christopher Frey. Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service. Environmental Science & Technology. 2021; 55 (15):10633-10644.
Chicago/Turabian StyleNikhil Rastogi; H. Christopher Frey. 2021. "Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service." Environmental Science & Technology 55, no. 15: 10633-10644.
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.
Tongchuan Wei; H. Christopher Frey. Sensitivity of light duty vehicle tailpipe emission rates from simplified portable emission measurement systems to variation in engine volumetric efficiency. Journal of the Air & Waste Management Association 2021, 71, 1127 -1147.
AMA StyleTongchuan Wei, H. Christopher Frey. Sensitivity of light duty vehicle tailpipe emission rates from simplified portable emission measurement systems to variation in engine volumetric efficiency. Journal of the Air & Waste Management Association. 2021; 71 (9):1127-1147.
Chicago/Turabian StyleTongchuan Wei; H. Christopher Frey. 2021. "Sensitivity of light duty vehicle tailpipe emission rates from simplified portable emission measurement systems to variation in engine volumetric efficiency." Journal of the Air & Waste Management Association 71, no. 9: 1127-1147.
The reduction of NOx emissions in a VOC-limited region can lead to an increase of the local O3 concentration. An evaluation of the net health effects of such pollutant changes is therefore important to ascertain whether the emission control measures effectively improve the overall protection of public health. In this study, we use a short-term health risk (added health risk or AR) model developed for the multi-pollutant air quality health index (AQHI) in Hong Kong to examine the overall health impacts of these pollutant changes. We first investigate AR changes associated with NO2 and O3 changes, followed by those associated with changes in all four AQHI pollutants (NO2, O3, SO2, and particulate matter (PM)). Our results show that for the combined health effects of NO2 and O3 changes, there is a significant reduction in AR in urban areas with dense traffic, but no statistically significant changes in other less urbanized areas. The increase in estimated AR for higher O3 concentrations is offset by a decrease in the estimated AR for lower NO2 concentrations. In areas with dense traffic, the reduction in AR as a result of decreased NO2 is substantially larger than the increase in AR associated with increased O3. When additionally accounting for the change in ambient SO2 and PM, we found a statistically significant reduction in total AR everywhere in Hong Kong. Our results show that the emission control measures resulting in NO2, SO2, and PM reductions over the past decade have effectively reduced the AR over Hong Kong, even though these control measures may have partially contributed to an increase in O3 concentrations. Hence, efforts to reduce NOx, SO2, and PM should be continued.
Shakhaoat Hossain; H. Christopher Frey; Peter K.K. Louie; Alexis K.H. Lau. Combined effects of increased O3 and reduced NO2 concentrations on short-term air pollution health risks in Hong Kong. Environmental Pollution 2020, 270, 116280 .
AMA StyleShakhaoat Hossain, H. Christopher Frey, Peter K.K. Louie, Alexis K.H. Lau. Combined effects of increased O3 and reduced NO2 concentrations on short-term air pollution health risks in Hong Kong. Environmental Pollution. 2020; 270 ():116280.
Chicago/Turabian StyleShakhaoat Hossain; H. Christopher Frey; Peter K.K. Louie; Alexis K.H. Lau. 2020. "Combined effects of increased O3 and reduced NO2 concentrations on short-term air pollution health risks in Hong Kong." Environmental Pollution 270, no. : 116280.
Over 50% of new refuse truck sales have been compressed natural gas (CNG). Compared to diesel, CNG is less expensive on diesel gallon equivalent (dge) basis. This study quantifies the real-world fuel use and tailpipe exhaust emissions from three front- and three side-loader refuse trucks, each with a spark ignition CNG engine, three-way catalyst, and similar gross weight. Measurements were made at 1 Hz using a portable emissions measurement system (PEMS). Inter-cycle and inter-vehicle variability is quantified. Effect of vehicle weight was analyzed and comparisons were made with MOVES predicted cycle average emission rates. In total, about 220,000 s of data covering 490 miles of operation were recorded. The average fuel economy was 1.9 miles per dge. On average the trucks spent 53% of time in idle, which includes trash collection activity. The average speeds were 10 mph and 5 mph, for front- and side-loader trucks, respectively. Overall, compared to side-loader trucks, front-loader trucks had 55% better fuel economy and 60% lower emission rates. Compared to diesel trucks, CNG truck cycle average NOx and PM emission rates, at 1.2 g/mile and 0.006 g/mile respectively, were substantially lower while CO and HC rates, at 29 g/mile and 6 g/mile respectively, were considerably higher. Fuel use and CO2 emissions rates increased by 10% due to increase in truck weight during trash collection, while CO emissions rates increased by up to 30%. Compared to measured values, MOVES estimated cycle average fuel use and CO2 emissions were 25% lower, CO emissions are 70% lower, and NOx emissions were 200% higher. Results from this study can be used to improve solid waste life cycle and tailpipe emission factor models and, when combined with previous studies on diesel refuse trucks, evaluate the effect on fuel use and emissions from adoption of CNG refuse trucks.
Gurdas S. Sandhu; H. Christopher Frey; Shannon Bartelt-Hunt; Elizabeth Jones. Real-world activity, fuel use, and emissions of heavy-duty compressed natural gas refuse trucks. Science of The Total Environment 2020, 761, 143323 .
AMA StyleGurdas S. Sandhu, H. Christopher Frey, Shannon Bartelt-Hunt, Elizabeth Jones. Real-world activity, fuel use, and emissions of heavy-duty compressed natural gas refuse trucks. Science of The Total Environment. 2020; 761 ():143323.
Chicago/Turabian StyleGurdas S. Sandhu; H. Christopher Frey; Shannon Bartelt-Hunt; Elizabeth Jones. 2020. "Real-world activity, fuel use, and emissions of heavy-duty compressed natural gas refuse trucks." Science of The Total Environment 761, no. : 143323.
The National Research Council has identified the lack of sufficient microenvironmental air pollution exposure data as a significant barrier to quantification of human exposure to air pollution. Transportation microenvironments, including pedestrian, transit bus, car, and bicycle, can be associated with higher exposure concentrations than many other microenvironments. Data are lacking that provide a systematic basis for comparing exposure concentrations in these transportation modes that account for key sources of variability, such as time of day, season, and types of location along a route such as bus stops and intersections. The objectives of this work are: to quantify and compare particulate matter (PM2.5), CO, and O3 exposure concentrations in selected active and passive transportation microenvironments; and to quantify the effect of season, time of day, and location with respect to variability in transportation mode exposure concentrations. Measurements were made with an instrumented backpack and were repeated for multiple days in each season to account for the effect of inter-run variability. Results include mean trends, spatial variability, and contribution to variance. Pedestrian and cycle mode exposure concentrations were approximately similar to each other and were substantially higher than for bus and car cabins for both PM2.5 and O3. Based on over 30 days of field measurements conducted over three seasons and for two times of day on weekdays, transportation mode and season were the largest contributors to variability in exposure for PM2.5 and O3, whereas location type alone and in combination with transport mode helped explain variability in CO exposures.
H. Christopher Frey; Disha Gadre; Sanjam Singh; Prashant Kumar. Quantification of Sources of Variability of Air Pollutant Exposure Concentrations among Selected Transportation Microenvironments. Transportation Research Record: Journal of the Transportation Research Board 2020, 2674, 395 -411.
AMA StyleH. Christopher Frey, Disha Gadre, Sanjam Singh, Prashant Kumar. Quantification of Sources of Variability of Air Pollutant Exposure Concentrations among Selected Transportation Microenvironments. Transportation Research Record: Journal of the Transportation Research Board. 2020; 2674 (9):395-411.
Chicago/Turabian StyleH. Christopher Frey; Disha Gadre; Sanjam Singh; Prashant Kumar. 2020. "Quantification of Sources of Variability of Air Pollutant Exposure Concentrations among Selected Transportation Microenvironments." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 9: 395-411.
Tanzila Khan; H. Christopher Frey; Nikhil Rastogi; Tongchuan Wei. Geospatial Variation of Real-World Tailpipe Emission Rates for Light-Duty Gasoline Vehicles. Environmental Science & Technology 2020, 54, 8968 -8979.
AMA StyleTanzila Khan, H. Christopher Frey, Nikhil Rastogi, Tongchuan Wei. Geospatial Variation of Real-World Tailpipe Emission Rates for Light-Duty Gasoline Vehicles. Environmental Science & Technology. 2020; 54 (14):8968-8979.
Chicago/Turabian StyleTanzila Khan; H. Christopher Frey; Nikhil Rastogi; Tongchuan Wei. 2020. "Geospatial Variation of Real-World Tailpipe Emission Rates for Light-Duty Gasoline Vehicles." Environmental Science & Technology 54, no. 14: 8968-8979.
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.
Tongchuan Wei; H. Christopher Frey. Evaluation of the Precision and Accuracy of Cycle-Average Light Duty Gasoline Vehicles Tailpipe Emission Rates Predicted by Modal Models. Transportation Research Record: Journal of the Transportation Research Board 2020, 2674, 566 -584.
AMA StyleTongchuan Wei, H. Christopher Frey. Evaluation of the Precision and Accuracy of Cycle-Average Light Duty Gasoline Vehicles Tailpipe Emission Rates Predicted by Modal Models. Transportation Research Record: Journal of the Transportation Research Board. 2020; 2674 (7):566-584.
Chicago/Turabian StyleTongchuan Wei; H. Christopher Frey. 2020. "Evaluation of the Precision and Accuracy of Cycle-Average Light Duty Gasoline Vehicles Tailpipe Emission Rates Predicted by Modal Models." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 7: 566-584.
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.
Tongchuan Wei; H. Christopher Frey. Factors affecting variability in fossil-fueled transit bus emission rates. Atmospheric Environment 2020, 233, 117613 .
AMA StyleTongchuan Wei, H. Christopher Frey. Factors affecting variability in fossil-fueled transit bus emission rates. Atmospheric Environment. 2020; 233 ():117613.
Chicago/Turabian StyleTongchuan Wei; H. Christopher Frey. 2020. "Factors affecting variability in fossil-fueled transit bus emission rates." Atmospheric Environment 233, no. : 117613.
Metro rail energy efficiency needs to be improved to compensate for growing capacity demand. Eco-driving aims to reduce energy consumption without affecting safety and passenger comfort. Estimates of energy savings from train eco-driving are typically based on theoretical speed trajectory optimization models. However, achievable energy savings from eco-driving should be assessed based on realistic trajectories. A Markov chain speed trajectory simulator calibrated to measured trajectories was used to simulate realistic inter-run variability in 1 Hz trajectories. The simulator was calibrated and applied to the Washington Metropolitan Area Transit Authority Metrorail system. Estimated energy consumption for each trajectory includes auxiliary loads and tractive effort to overcome resistive forces. Inter-run variability in estimated energy consumption implies opportunities for energy savings via eco-driving. Energy savings was quantified by comparing the lowest and average segment energy consumption. A segment is the one-way rail track between adjacent stations of each line. Simulated trajectories are similar to measured trajectories based on mean absolute error and coefficient of determination (R2) for the same operation mode sequence. Based on 100 simulations per segment, energy savings ranging from 5% to 50% among segments and from 14% to 18% at the system level can be achieved without modifying travel time. Energy savings lead to reduced electricity consumption and, therefore, reduced power generation emissions. The method demonstrated here to quantify opportunities for metro train energy conservation and emissions mitigation is broadly applicable to electric metro and commuter trains and rail segments. Implications for energy-efficient passenger rail planning and operation are discussed.
Weichang Yuan; H. Christopher Frey. Potential for metro rail energy savings and emissions reduction via eco-driving. Applied Energy 2020, 268, 114944 .
AMA StyleWeichang Yuan, H. Christopher Frey. Potential for metro rail energy savings and emissions reduction via eco-driving. Applied Energy. 2020; 268 ():114944.
Chicago/Turabian StyleWeichang Yuan; H. Christopher Frey. 2020. "Potential for metro rail energy savings and emissions reduction via eco-driving." Applied Energy 268, no. : 114944.
Compared to comparably sized conventional light duty gasoline vehicles (CLDGVs), plug-in hybrid electric vehicles (PHEVs) may offer benefits of improved energy economy, reduced emissions, and the flexibility to use electricity as an energy source. PHEVs operate in either charge depleting (CD) or charge sustaining (CS) mode; the engine has the ability to turn on and off; and the engine can have multiple cold starts. A method is demonstrated for quantifying the real-world activity, energy use, and emissions of PHEVs, taking into account these operational characteristics and differences in electricity generation resource mix. A 2013 Toyota Prius plug-in was measured using a portable emission measurement system. Vehicle specific power (VSP) based modal average energy use and emission rates are inferred to assess trends in energy use and emissions with respect to engine load and for comparisons of engine on versus engine off, and cold start versus hot stabilized running. The results show that, compared to CLDGVs, the PHEV operating in CD mode has improved energy efficiency and lower CO2, CO, HC, NOx, and PM2.5 emission rates for a wide range of power generation fuel mixes. However, PHEV energy use and emission rates are highly variable, with periods of relatively high on-road emission rates related to cold starts.
H. Christopher Frey; Xiaohui Zheng; Jiangchuan Hu. Variability in Measured Real-World Operational Energy Use and Emission Rates of a Plug-In Hybrid Electric Vehicle. Energies 2020, 13, 1140 .
AMA StyleH. Christopher Frey, Xiaohui Zheng, Jiangchuan Hu. Variability in Measured Real-World Operational Energy Use and Emission Rates of a Plug-In Hybrid Electric Vehicle. Energies. 2020; 13 (5):1140.
Chicago/Turabian StyleH. Christopher Frey; Xiaohui Zheng; Jiangchuan Hu. 2020. "Variability in Measured Real-World Operational Energy Use and Emission Rates of a Plug-In Hybrid Electric Vehicle." Energies 13, no. 5: 1140.
Exposure to air pollutants causes a range of adverse health effects. These harmful effects occur whenever and wherever people come into direct contact with air pollution. Therefore, individual actions that reduce the frequency, duration, and severity of personal contact with air pollution can reduce health risks. We developed a system that empowers the public with personalized information on air quality and exposure health risk. This system, the Personalised Real-Time Air Quality Informatics System for Exposure – Hong Kong (PRAISE-HK, http://praise.ust.hk/), is embodied in an interactive mobile application. PRAISE-HK is based on real-time data on emissions, high resolution urban morphology, meteorology, physical and chemical processes affecting pollutant transport and transformations, extensive measurements of air pollution concentrations in typical locations such as homes, schools, offices, and transportation, and big data integration of sensor monitoring to accurately estimate current and short-term forecasted street-level air quality. The street-level air quality simulation has been validated against reference monitoring data. Ongoing and planned future enhancements to PRAISE-HK include prediction of personal exposure and health response. PRAISE-HK is an example of the use of collective intelligence in a smart city to engage citizens in learning about and managing their own exposure to air pollution.
Wenwei Che; H. Christopher Frey; Jimmy C.H. Fung; Zhi Ning; Huamin Qu; Hong Kam Lo; Lei Chen; Tze-Wai Wong; Michelle K.M. Wong; Ophelia C.W. Lee; David Carruthers; Freeman Cheung; Jimmy W.M. Chan; David W. Yeung; Yik Him Fung; Xuguo Zhang; Jenny Stocker; Christina Hood; Tilman Leo Hohenberger; King Wai Leung; Phillip Y.K. Louie; Alison T.Y. Li; Li Sun; Peng Wei; Zhiyuan Li; Yumiao Zhang; Meilan Wang; Qiaomu Shen; Wei Huang; Enoch Lee; Ashraf Patwary; Xiayu Lei; Steven Cheng; Shakhaoat Hossain; Kimberly Tasha Jiayi Tang; Xiang Qian Lao; Rae Leung; Denise Chan; Ying Li; Zibing Yuan; Alexis K.H. Lau. PRAISE-HK: A personalized real-time air quality informatics system for citizen participation in exposure and health risk management. Sustainable Cities and Society 2019, 54, 101986 .
AMA StyleWenwei Che, H. Christopher Frey, Jimmy C.H. Fung, Zhi Ning, Huamin Qu, Hong Kam Lo, Lei Chen, Tze-Wai Wong, Michelle K.M. Wong, Ophelia C.W. Lee, David Carruthers, Freeman Cheung, Jimmy W.M. Chan, David W. Yeung, Yik Him Fung, Xuguo Zhang, Jenny Stocker, Christina Hood, Tilman Leo Hohenberger, King Wai Leung, Phillip Y.K. Louie, Alison T.Y. Li, Li Sun, Peng Wei, Zhiyuan Li, Yumiao Zhang, Meilan Wang, Qiaomu Shen, Wei Huang, Enoch Lee, Ashraf Patwary, Xiayu Lei, Steven Cheng, Shakhaoat Hossain, Kimberly Tasha Jiayi Tang, Xiang Qian Lao, Rae Leung, Denise Chan, Ying Li, Zibing Yuan, Alexis K.H. Lau. PRAISE-HK: A personalized real-time air quality informatics system for citizen participation in exposure and health risk management. Sustainable Cities and Society. 2019; 54 ():101986.
Chicago/Turabian StyleWenwei Che; H. Christopher Frey; Jimmy C.H. Fung; Zhi Ning; Huamin Qu; Hong Kam Lo; Lei Chen; Tze-Wai Wong; Michelle K.M. Wong; Ophelia C.W. Lee; David Carruthers; Freeman Cheung; Jimmy W.M. Chan; David W. Yeung; Yik Him Fung; Xuguo Zhang; Jenny Stocker; Christina Hood; Tilman Leo Hohenberger; King Wai Leung; Phillip Y.K. Louie; Alison T.Y. Li; Li Sun; Peng Wei; Zhiyuan Li; Yumiao Zhang; Meilan Wang; Qiaomu Shen; Wei Huang; Enoch Lee; Ashraf Patwary; Xiayu Lei; Steven Cheng; Shakhaoat Hossain; Kimberly Tasha Jiayi Tang; Xiang Qian Lao; Rae Leung; Denise Chan; Ying Li; Zibing Yuan; Alexis K.H. Lau. 2019. "PRAISE-HK: A personalized real-time air quality informatics system for citizen participation in exposure and health risk management." Sustainable Cities and Society 54, no. : 101986.
With more stringent U.S. fuel economy (FE) standards, the effect of auxiliary devices such as air-conditioning (AC) have received increased attention. AC is the largest auxiliary engine load for light duty gasoline vehicles (LDGVs). However, there are few data regarding the effect of AC operation on FE for LDGVs based on real-world measurements, especially for recent model year vehicles. The Motor Vehicle Emission Simulator (MOVES) is a regulatory model for estimating on-road vehicle energy-use and emissions. MOVES adjusts vehicle energy-use rates for AC effects. However, MOVES-predicted FE with AC has not been evaluated based on empirical measurements. The research objectives are to quantify the LDGVs FE penalty from AC and assess the accuracy of MOVES2014a-predicted FE with AC. The AC effect on real-world fleet-average FE was quantified based on 78 AC-off vehicles versus 55 AC-on vehicles, measured with onboard instruments on defined study routes. MOVES2014a-based FE penalty from AC was evaluated based on real-world estimates and chassis dynamometer-based FE test results used for FE ratings. The real-world FE penalty ranges between 1.3% and 7.5% among a wide range of driving cycles. Fuel consumption at idle is 13% higher with AC on. MOVES underestimates the real-world FE with AC by 6%, on average. MOVES overestimates the AC effect on cycle-average FE ranging between 13.5% and 18.5% for real-world and MOVES default cycles, and between 11.1% and 14.5% for standard cycles.
Tanzila Khan; H. Christopher Frey. Effect of Air-Conditioning on Light Duty Gasoline Vehicles Fuel Economy. Transportation Research Record: Journal of the Transportation Research Board 2019, 2673, 131 -141.
AMA StyleTanzila Khan, H. Christopher Frey. Effect of Air-Conditioning on Light Duty Gasoline Vehicles Fuel Economy. Transportation Research Record: Journal of the Transportation Research Board. 2019; 2673 (5):131-141.
Chicago/Turabian StyleTanzila Khan; H. Christopher Frey. 2019. "Effect of Air-Conditioning on Light Duty Gasoline Vehicles Fuel Economy." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5: 131-141.
Passenger train energy consumption is dependent on speed trajectories. The variability of passenger train energy consumption owing to the variability in speed trajectories can help identify ways to reduce train energy use via improved operations. Empirical fuel use data from a portable measurement emission measurement system (PEMS) and empirical speed trajectories measured using a global positioning system (GPS) receiver were used to verify and quantify real-world energy consumption variability and the variability in empirical speed trajectories, respectively. To identify potential realistic speed trajectories that can lead to energy saving (i.e., eco-driving), a Markov chain based speed trajectory simulator was used to simulate inter-run variability in speed trajectories. An energy index model (EIM) was used to compare energy consumption among different speed trajectories. The results show inter-run variability in fuel use associated with inter-run variability in the empirical speed trajectories. There is also inter-segment variability in fuel use related to the segment length and grade. The Markov chain based speed trajectory simulator can simulate realistic inter-run variability in speed trajectories based on calibration using empirical speed trajectories. The number of empirical speed trajectories used for simulator calibration affects the range of simulated inter-run variability. The EIM provides an accurate estimation of the empirical fuel use. Eco-driving, such as reducing the peak speed, can reduce energy consumption without compromising travel time. The methodology shown in this study is not system-specific and can be applied to other passenger train systems.
Weichang Yuan; H. Christopher Frey; Nikhil Rastogi. Quantification of Energy Saving Potential for A Passenger Train Based on Inter-Run Variability in Speed Trajectories. Transportation Research Record: Journal of the Transportation Research Board 2019, 2673, 153 -165.
AMA StyleWeichang Yuan, H. Christopher Frey, Nikhil Rastogi. Quantification of Energy Saving Potential for A Passenger Train Based on Inter-Run Variability in Speed Trajectories. Transportation Research Record: Journal of the Transportation Research Board. 2019; 2673 (5):153-165.
Chicago/Turabian StyleWeichang Yuan; H. Christopher Frey; Nikhil Rastogi. 2019. "Quantification of Energy Saving Potential for A Passenger Train Based on Inter-Run Variability in Speed Trajectories." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5: 153-165.
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.
Weichang Yuan; H. Christopher Frey; Tongchuan Wei; Nikhil Rastogi; Steven VanderGriend; David Miller; Lawrence Mattison. Comparison of real-world vehicle fuel use and tailpipe emissions for gasoline-ethanol fuel blends. Fuel 2019, 249, 352 -364.
AMA StyleWeichang Yuan, H. Christopher Frey, Tongchuan Wei, Nikhil Rastogi, Steven VanderGriend, David Miller, Lawrence Mattison. Comparison of real-world vehicle fuel use and tailpipe emissions for gasoline-ethanol fuel blends. Fuel. 2019; 249 ():352-364.
Chicago/Turabian StyleWeichang Yuan; H. Christopher Frey; Tongchuan Wei; Nikhil Rastogi; Steven VanderGriend; David Miller; Lawrence Mattison. 2019. "Comparison of real-world vehicle fuel use and tailpipe emissions for gasoline-ethanol fuel blends." Fuel 249, no. : 352-364.
Ambient PM2.5 concentrations measured at fixed site monitors (FSM) are often biased with respect to exposure concentrations because of spatial variability and infiltration. Based on comparison of ambient concentrations from 14 FSMs and of exposure concentrations measured indoors and outdoors at two schools in Hong Kong for winter and summer seasons, the magnitude and sources of exposure error based on using FSMs as a surrogate for exposure are quantified. An approach for bias correcting surrogate exposure estimates from FSMs is demonstrated. The approach is based on a proximity factor (PF) that accounts for differences in spatial locations, proximity to emissions and deviation from dominant wind direction, and an infiltration factor (IF) that varies by season. The combination of the PF and IF reduce bias in mean school exposure estimates from ±90% to ±20%. Bias in exposure estimates from using FSMs as surrogates tend to be smaller for which the exposure site and FSM are aligned with wind direction, have similar sampling height, and are in close proximity. The methodology demonstrated to assess concordance between FSMs and exposure measurement sites can be applied more broadly to help reduce exposure error, which may help to interpret seasonal variations in health estimates.
Wenwei Che; H. Christopher Frey; Zhiyuan Li; Xiangqian Lao; Alexis K. H. Lau. Indoor Exposure to Ambient Particles and Its Estimation Using Fixed Site Monitors. Environmental Science & Technology 2018, 53, 808 -819.
AMA StyleWenwei Che, H. Christopher Frey, Zhiyuan Li, Xiangqian Lao, Alexis K. H. Lau. Indoor Exposure to Ambient Particles and Its Estimation Using Fixed Site Monitors. Environmental Science & Technology. 2018; 53 (2):808-819.
Chicago/Turabian StyleWenwei Che; H. Christopher Frey; Zhiyuan Li; Xiangqian Lao; Alexis K. H. Lau. 2018. "Indoor Exposure to Ambient Particles and Its Estimation Using Fixed Site Monitors." Environmental Science & Technology 53, no. 2: 808-819.
Eco-driving involves alterations to driving style to improve energy efficiency. The observed driving style reflects the combined effects of roadway, traffic, driver, and vehicle performance. Although the effect of roadway and traffic characteristics can be inferred from microscale driving activity data, the effect of vehicle performance on driving style is not properly understood. This paper addresses two questions: (1) how different is an individual driver’s driving style when operating vehicles with differences in performance?; and (2) how dissimilar are the driving styles of different drivers when operating vehicles that have similar performance? To answer these questions, we have gathered microscale vehicle activity measurements from 17 controlled real-world driving schedules and two years of naturalistic driving data from five drivers. We also developed a metric for driving style termed “envelope deviation,” which is a distribution of gaps between microscale activity (1 Hz) and fleet average envelope. We found that there is significant inter-driver heterogeneity in driving styles when controlling for vehicle performance. However, no significant inter-vehicle heterogeneity was present in driving styles while controlling for the driver. Findings from this study imply that the choice of vehicle does not significantly alter the natural driving style of a driver.
Shams Tanvir; H. Christopher Frey; Nagui M. Rouphail. Effect of Light Duty Vehicle Performance on a Driving Style Metric. Transportation Research Record: Journal of the Transportation Research Board 2018, 2672, 67 -78.
AMA StyleShams Tanvir, H. Christopher Frey, Nagui M. Rouphail. Effect of Light Duty Vehicle Performance on a Driving Style Metric. Transportation Research Record: Journal of the Transportation Research Board. 2018; 2672 (25):67-78.
Chicago/Turabian StyleShams Tanvir; H. Christopher Frey; Nagui M. Rouphail. 2018. "Effect of Light Duty Vehicle Performance on a Driving Style Metric." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 25: 67-78.
Samuel L. Altshuler; Alberto Ayala; Susan Collet; Judith C. Chow; H. Christopher Frey; Rashid Shaikh; Eric D. Stevenson; Michael P. Walsh; John G. Watson. Trends in on-road transportation, energy, and emissions. Journal of the Air & Waste Management Association 2018, 68, 1015 -1024.
AMA StyleSamuel L. Altshuler, Alberto Ayala, Susan Collet, Judith C. Chow, H. Christopher Frey, Rashid Shaikh, Eric D. Stevenson, Michael P. Walsh, John G. Watson. Trends in on-road transportation, energy, and emissions. Journal of the Air & Waste Management Association. 2018; 68 (10):1015-1024.
Chicago/Turabian StyleSamuel L. Altshuler; Alberto Ayala; Susan Collet; Judith C. Chow; H. Christopher Frey; Rashid Shaikh; Eric D. Stevenson; Michael P. Walsh; John G. Watson. 2018. "Trends in on-road transportation, energy, and emissions." Journal of the Air & Waste Management Association 68, no. 10: 1015-1024.
The World Health Organization estimates 3.7 million deaths in 2012 in low- and middle-income Asian countries due to outdoor air pollution. However, these estimates do not account for the higher exposures of specific particulate matter (PM) components – including fine particles (PM2.5), ultrafine particles (UFP) and black carbon (BC) – typical of transport microenvironments (TMEs). With the rapidly growing number of on-road vehicles in Asia, human exposure to PM is an increasing concern. The aim of this review article is to comprehensively assess the PM2.5, UFP, and BC related studies in Asian TMEs to understand the extent of exposure, the underlying factors leading to such exposure, and how Asian exposures compare to those found in Europe and the United States of America (USA). Pollutants considered and their health impacts are identified, along with the key factors that influence personal exposure in TMEs. We also characterised the human exposure to PM2.5, UFP, and BC in TMEs (walk, cycle, car, and bus) in cities of Asia, Europe, and the USA. Instrumentation and measurement methods, exposure modeling techniques, and regulation are reviewed for PM2.5, UFP, and BC. Relatively few studies have been carried out in urban Asian TMEs (i.e., walk, cycle, car, and bus) where PM2.5, UFP, and BC had generally higher concentrations compared to Europe and USA. Based on available data, PM2.5 concentrations while walking were 1.6 and 1.2 times higher in Asia (average 42 μg m−3) compared to Europe (26 μg m−3) and the USA (35 μg m−3), respectively. Likewise, average PM2.5 concentrations in car (74 μg m−3) and bus (76 μg m−3) modes in Asia were approximately two to three times higher than in Europe and the USA. UFP exposures in Asia were twice as high for pedestrians and up to ∼9-times as high in cars than in Europe or the USA. Asian pedestrians were exposed to ∼7-times higher BC concentrations compared with pedestrians in the USA. Stochastic population-based models have yet to be applied widely in Asia but can be used to quantify inter-individual and inter-regional variability in exposures and to assess the contribution of TMEs to total exposures for multiple pollutants. The review also highlights specific gaps in the data set that need to be filled by future research as UFP and BC studies were rare as were studies of pedestrian and cyclist exposure in Asian TMEs.
Prashant Kumar; Allison Patton; John L. Durant; H. Christopher Frey. A review of factors impacting exposure to PM2.5, ultrafine particles and black carbon in Asian transport microenvironments. Atmospheric Environment 2018, 187, 301 -316.
AMA StylePrashant Kumar, Allison Patton, John L. Durant, H. Christopher Frey. A review of factors impacting exposure to PM2.5, ultrafine particles and black carbon in Asian transport microenvironments. Atmospheric Environment. 2018; 187 ():301-316.
Chicago/Turabian StylePrashant Kumar; Allison Patton; John L. Durant; H. Christopher Frey. 2018. "A review of factors impacting exposure to PM2.5, ultrafine particles and black carbon in Asian transport microenvironments." Atmospheric Environment 187, no. : 301-316.
Prashant Kumar; Ioar Rivas; Anant Pratap Singh; Vikas Julius Ganesh; Monirupa Ananya; H. Christopher Frey. Dynamics of coarse and fine particle exposure in transport microenvironments. npj Climate and Atmospheric Science 2018, 1, 1 .
AMA StylePrashant Kumar, Ioar Rivas, Anant Pratap Singh, Vikas Julius Ganesh, Monirupa Ananya, H. Christopher Frey. Dynamics of coarse and fine particle exposure in transport microenvironments. npj Climate and Atmospheric Science. 2018; 1 (1):1.
Chicago/Turabian StylePrashant Kumar; Ioar Rivas; Anant Pratap Singh; Vikas Julius Ganesh; Monirupa Ananya; H. Christopher Frey. 2018. "Dynamics of coarse and fine particle exposure in transport microenvironments." npj Climate and Atmospheric Science 1, no. 1: 1.