Lynette Cheah
Singapore University of Technology and Design
Lynette Cheah is an Assistant Professor in Engineering Systems at the Singapore University of Technology and Design. There, she leads the Sustainable Urban Mobility research group, which focuses on developing models, tools and solutions to assess and reduce the energy and environmental impacts of road transport. Lynette holds bachelor degrees in civil and environmental engineering from Northwestern University, a masters degree in management science from Stanford, and a Ph.D. in engineering systems from MIT.
Accurate profiling of road vehicle emissions is crucial in portraying and reducing the contribution to national inventories of greenhouse gases and other air pollutants. Vehicle rated emissions are determined by application of standardized, laboratory-based driving cycles, designed to be representative of real world driving. In reality, actual emissions often differ from rated or laboratory-measured values, depending on the vehicle, driver behavior, local driving conditions and environmental characteristics. This difference is important, as the life cycle environmental profile of automobiles is dominated by their use-phase [1]. Adequate characterization of use-phase data is central to better understanding key contributions to uncertainty in life cycle emissions [2]. Vehicle emission models widely used by recent studies disaggregate parameters such as vehicle class, age, road grade and operating mode. However, studies often employ predefined routes, representing all available road grades and traffic conditions, or highly used arterial roads, rather than incorporate ‘real’ driving. Recent developments in modelling have introduced flexibility to incorporate project-level high-resolution data for a study’s specific needs [3,4].
In this study we use vehicle telematics to collect data on real-world vehicle use in the city-state of Singapore. Recent developments in pervasive sensing and data-logging technologies permit collection of large quantities of high-quality travel data, reduces data collection costs, and collects engine performance information that could not be supplied by the driver. On-board diagnostic (OBD) data loggers [5] and GPS modules were deployed in compact and mid-sized passenger vehicles for a minimum period of eight weeks, generating data at a frequency of 1 Hz. Data thus reflected users’ daily behavior rather than a predetermined representative journey. We examine the influence of interindividual variability on vehicle running exhaust and cold start emissions, and tank to wheel fuel use. Emission factors were estimated for a range of pollutant species employing the EMFAC-HK[6] vehicle emissions model. Results show a range of emissions amongst users, and indicate that rated fuel consumption significantly underestimated the measured actual fuel consumption. Recorded data reveals patterns in users’ behavior, including speed, driving time, trips, and interaction with prevailing climatic conditions. Thus through characterizing real-life day-to-day driving in the model we identify behavioral, temporal, and environmental influences on the use-phase emissions profile. This study highlights the benefits of a data-driven approach and underscores the importance of considering user variation in any life cycle assessment.
[1] Cheah, L. (2013) Use phase parameter variation and uncertainty in LCA: automobile case study. Re-engineering Manufacturing for Sustainability, p553-557. Springer, Singapore
[2] Noshadravan, A. et al. (2015) Stochastic comparative assessment of life-cycle greenhouse gas emissions from conventional and electric vehicles. Int J Life Cycle Assess (2015) 20: 854-864
[3] EPA (2015) MOVES2014a UserGuide. EPA-420-B-15-095. US Environmental Protection Agency. Washington DC, USA
[4] Abou-Senna, H. & Radwan, E. (2013) VISSIM/MOVES integration to investigate the effect of major key parameters on CO2 emissions. Transportation Research Part D, 21: 39-46
[5] LiveDrive (2014) i2D Telematics. Available: https://www.i2d.co/i2dpubporta...
[6] EPD (2017) EMFAC-HK User's Guide version 3.3. Calculating emissions inventories for vehicles in Hong Kong. Environmental Protection Division, Hong Kong
• Advances in methods (e.g., life cycle assessment, social impact assessment, resilience a , • Decision support methods and tools
