Real world emissions at high spatial resolution

Development of real-world vehicle emissions in high spatial resolutions and their impacts on air quality and health

Road transport plays a significant role in economic and social development. However, it cannot be denied that road transport negatively affects the environment and well-being of people. In urban area, the transport is recognised as the greatest source of air pollutant such as CO, NOx, PM and SO2, as well as GHGs such as CO2. Various studies have shown that vehicle emission contribute to several respiratory diseases, cardiovascular, cancer, and pre-mature mortality. Greater efforts to alleviate vehicle emissions are implemented by traffic engineers, transportation planners and policy makers. In order to take air pollution into account for any policy implementations, it is crucial to estimate real-world vehicle emissions and to assess its impact on urban air quality and population exposure.

Typically, vehicle emissions have been estimated using numerical models or measured through loop detectors to obtain traffic data. These approaches may not reflect the actual emissions because emission factors vary from locations, vehicle characteristics and traffic conditions. This research attempts to utilise the benefit of vehicle GPS trajectories as an opportunistic data, which can be used for real-world driving conditions and traffic situations. The emission estimations take into account instantaneous driver behaviours, such as speed, accelerations, and stop-and-go conditions. Meanwhile, the traffic flow which is one of the key parameters for total emission prediction, is obtained throughout the road network. As a result, a real-world vehicle emission in high spatial resolutions can be estimated.

Vehicle emission is a significant health hazard. Another key objective of this research is to assess the impacts of emissions on air quality and human exposure. The exposure levels are measured through an integration of traffic activities, real-world emission estimations, pollution concentrations, as well as demographical data. In addition, the effects of feasible future traffic policies are assessed, and their potential health impacts are compared to a business as usual scenario.

Research team:

• Dr Marc Stettler
• Manlika Sukitpaneenit