Capabilities and Limitations of Telematics for Vehicle Emissions Inventories

Abstract

Eastern Research Group, Inc. evaluated the current state of personal vehicle telematics data with respect to emission inventory development, identifying relative strengths and weaknesses, and how these data could align better with the needs of emission modelers. A market survey of telematics firms provided an overview of available data, and identified several candidate sources for location-based and engine-based telematics data on personal vehicles. Data were then purchased from three different vendors: StreetLight Data, Moonshadow Mobile, and Otonomo. These data were applied in case studies conducted in the Denver metro area, U.S., to assess strengths and weaknesses of telematics for developing emission inventories. Case studies included using telematics to estimate regional vehicle miles traveled (VMT) for annual emission inventories; tracking the VMT impacts of COVID shutdown; generating location- and time-specific vehicle activity inputs for project scale “hot spot” air quality analysis; and estimating the distribution of fuel fill level from real-world data, which is important for evaporative emissions. These case studies confirmed that telematics can serve a growing range of emission inventory use cases, and use of these data may help improve emission inventory accuracy. However, there are also several limitations of the data to consider in preparing emission inventories; for example, it can be difficult to assess the representativeness of telematics data because of a lack of vehicle information. The authors encourage telematics firms to cater data products more directly to the needs of emission inventory modelers, to better harness the enormous potential of these data for refining vehicle emission inventory estimates.

Tracer-Gas-Integrated Measurements of Brake-Wear Particulate Matter Emissions from Heavy-Duty Vehicles

“…21,22 The mode diameter found in this study is also close to recent findings that reported the mode diameter of ∼1.4 μm from disc brakes at temperature below 100 °C. 5,38 In this study, the mode diameter stayed at the low end of previous findings potentially because the temperature of the HD drum brakes was generally lower than the disc brakes in previous studies.…”

“…45 A more recent study showed that brake-wear PM emissions are not necessarily at a similar level between the front and rear brakes of HD vehicles. 5 This study is limited to a proof-of-concept by demonstrating brake-wear PM emission measurements from a single brake of each test vehicle that was simulated on a two-wheel chassis dynamometer. For that reason, it was difficult to extrapolate the emissions data collected from a single brake into the total brake-wear PM emissions of HD vehicles in this study.…”

“…CARB has also identified brake-wear as an important source of particulate matter (PM) emissions that are projected to increase in near future . CARB has investigated brake-wear emissions in multiple testing platforms such as near-road, brake dynamometer, and chassis dynamometer in a Running Loss Sealed Housing for Evaporative Emission Determination (RL-SHED) chamber. – The current heavy-duty (HD) vehicle chassis dynamometer study complements the ongoing efforts of CARB and reports brake-wear PM emissions measured from the drum brakes of HD vehicles.…”

Equipping Active Travel Advocates with Digital Mobility Data and Tools: An Evaluation of a US Trial Program

“…This project did not estimate the monetary value of the data tools provided to the advocates. As previously mentioned, licenses for some emerging data software tools can be very expensive (Koupal et al, 2022;Nelson et al, 2021;Lee and Sener, 2020; it should be noted that Strava made their Metro platform free halfway into the MDSS program term). In this pilot program, the project sponsors bore the cost.…”

“…With the emergence of big mobility data, increasingly used by local governments to aid in transportation planning (Englin and Davis, 2021;Yang, Cetin and Ma, 2020), lack of access to the same data may inhibit advocates from contributing to planning. Subscriptions to emerging mobility data tools can be prohibitively expensive for cities (Koupal et al, 2022;Nelson et al, 2021;Lee and Sener, 2020), let alone not-for-profit advocacy groups. Working with emerging mobility data often requires a high level of data science skills (Nelson et al, 2021), which may limit the degree to which advocates could use the tools even if they had access.…”