@article{frey_zhang_rouphail_2010, title={Vehicle-Specific Emissions Modeling Based upon on-Road Measurements}, volume={44}, ISSN={["1520-5851"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-77951826102&partnerID=MN8TOARS}, DOI={10.1021/es902835h}, abstractNote={Vehicle-specific microscale fuel use and emissions rate models are developed based upon real-world hot-stabilized tailpipe measurements made using a portable emissions measurement system. Consecutive averaging periods of one to three multiples of the response time are used to compare two semiempirical physically based modeling schemes. One scheme is based on internally observable variables (IOVs), such as engine speed and manifold absolute pressure, while the other is based on externally observable variables (EOVs), such as speed, acceleration, and road grade. For NO, HC, and CO emission rates, the average R(2) ranged from 0.41 to 0.66 for the former and from 0.17 to 0.30 for the latter. The EOV models have R(2) for CO(2) of 0.43 to 0.79 versus 0.99 for the IOV models. The models are sensitive to episodic events in driving cycles such as high acceleration. Intervehicle and fleet average modeling approaches are compared; the former account for microscale variations that might be useful for some types of assessments. EOV-based models have practical value for traffic management or simulation applications since IOVs usually are not available or not used for emission estimation.}, number={9}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Frey, H. Christopher and Zhang, Kaishan and Rouphail, Nagui M.}, year={2010}, month={May}, pages={3594–3600} }
 @article{zhang_frey_2008, title={Evaluation of response time of a portable system for in-use vehicle tailpipe emissions measurement}, volume={42}, ISSN={["0013-936X"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-37549066979&partnerID=MN8TOARS}, DOI={10.1021/es062999h}, abstractNote={The objective of this paper is to quantify and evaluate the effects of response time of a portable emission measurement system (PEMS). The PEMS measures tailpipe emissions and vehicle dynamics on a second-by-second basis. Response times of the PEMS for exhaust concentrations were quantified on the basis of fixed periods of measurement of calibration gases for NO, hydrocarbons (HC), CO, and CO2. The time constant was quantified on the basis of the time to reach 63% of the maximum measured value when calibration gas was continuously administered for a period of typically 20 s or more. The time constant was found to be 6 s for NO and 3 s each for CO, HC, and CO2. Measurement errors associated with the response time of the PEMS were quantified. A first-order dynamic discrete model was developed to simulate the instrument measurements. Simulations showed that correction improves the measurement accuracy. Correction with smoothing better improves the measurement accuracy, especially when the noise is relatively large. On a trip level, the average error of the simulated measurements relative to the simulated signal before correction is -4%, which is deemed to be acceptable. For real-world data, smoothing and correction is recommended for major peaks to improve the measurement accuracy.}, number={1}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Zhang, Kaishan and Frey, Christopher}, year={2008}, month={Jan}, pages={221–227} }
 @article{frey_zhang_rouphail_2008, title={Fuel use and emissions comparisons for alternative routes, time of day, road grade, and vehicles based on in-use measurements}, volume={42}, ISSN={["1520-5851"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-41649109289&partnerID=MN8TOARS}, DOI={10.1021/es702493v}, abstractNote={The objective here is to quantify the variability in emissions of selected light duty gasoline vehicles by routes, time of day, road grade, and vehicle with a focus on the impact of routes and road grade. Field experiments using a portable emission measurement system were conducted under real-world driving cycles. The study area included two origin/destination pairs, each with three alternative routes. Total emissions varied from trip to trip and from route to route due to variations in average speed and travel time. On an average trip basis, the total NO emissions differed by 24% when comparing alternative routes and by 19% when comparing congested travel time with less congested traffic time. Positive road grades were associated with an approximately 20% increase in localized emissions rates, while negative road grades were associated with a similar relative decrease. The average vehicle-specific power based NO modal emission rates differed by more than 2 orders of magnitude when comparing different vehicles. The results demonstrate that alternative routing can significantly impact trip emissions. Furthermore, road grade should be taken into account for localized emissions estimation. Vehicle-specific models are needed to capture episodic effects of emissions for near-road short-term human exposure assessment.}, number={7}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Frey, H. Christopher and Zhang, Kaishan and Rouphail, Nagui M.}, year={2008}, month={Apr}, pages={2483–2489} }
 @article{zhang_frey_2006, title={Road grade estimation for on-road vehicle emissions modeling using light detection and ranging data}, volume={56}, ISSN={["2162-2906"]}, DOI={10.1080/10473289.2006.10464500}, abstractNote={Abstract Vehicle–specific power (VSP) is useful for explaining a substantial portion of variability in real–world vehicle emissions, such as those measured with portable emissions monitoring systems (PEMS). VSP is a function of vehicle speed, acceleration, and road grade. Road grade is shown to significantly affect estimates of both VSP and of real–world emissions via sensitivity analysis and analysis of empirical data. However, road grade is difficult to measure reliably using PEMS. Therefore, alternative methods for estimating road grade were identified and compared. A preferred method for estimating road grade was explored in more detail based on light detection and ranging (LIDAR) data. The method includes buffering LIDAR data onto roadway maps using a geographic information system tool, defining segments of roadway based on criteria pertaining to vertical curvature, quantification of roadway elevations within the buffered segments, and estimation of road grade and banking by fitting a plane to each segment. Factors influencing errors in road grade estimates are discussed. The method was evaluated by application to selected interstate highways and comparison to design drawing data. The development and application of LIDAR–based road grade data are demonstrated via a case study using PEMS data collected in the Research Triangle Park, NC, area. LIDAR data are shown to be reliable and accurate for road grade estimation for vehicle emissions modeling.}, number={6}, journal={JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION}, author={Zhang, Kaishan and Frey, H. Christopher}, year={2006}, month={Jun}, pages={777–788} }