Traffic Forecasting and Emission Mitigation Strategies via Traffic Flow and Fuel Consumption Models

ICCUE 2024 Rome

1. Traffic Forecasting and Emission Mitigation Strategies via Traffic Flow and Fuel Consumption Models Kelvin J. A. Ooi Department of Physics, Xiamen University Malaysia [email protected]

2. 3rd Largest energy consumption sector

3. Greenhouse Gas Health and Environmental Concerns Public health and environmental concern due to road transport exhaust emissions People living in urban areas are at higher health risk Technological improvements and policy settings does not keep pace with the increase of travelling demand Particularly in developing countries where emissions regulation were inadequate

4. Urban Transport in Malaysia Malaysia has one of the lowest public transportation users level among Asia. Initiation of the Green Technology Master Plan (2017–2030) Increase the overall public transport modal share to 40% by the year of 2030.

5. Georgetown, Penang, Malaysia

6. Strategic Planning Determine the fuel consumption of vehicles within study area Perform modal shift using PCU and passenger load factors Determine the fuel consumption of vehicles at 20%, 30% and 40% public transport mod a l share Greenshield’s macroscopic stream models to determine the change in traffic flow parameters associated with mod a l shift Evaluate the effectiveness of mitigation strategy

7. Traffic Composition *Data obtained from Halcrow Report

8. Fuel Calculation and Projection Travelling Fuel Consumption Congestion Fuel Consumption (Idling) Idle Time Estimation      

9. Traffic Forecast Adapting data into Greenshield’s model Transportation mode Passengers/ vehicle Car 1.55 Motorcycle 1.2 Bus 18.4

10. Fuel Consumption Forecast

11. Fuel Consumption Forecast

12. Comparison with Literature Ong et. al [*]: 6% savings on 10% shift to public transportation. Our model: 5.9% savings on first 10% shift to public transportation 7.46% savings on next 10% shift 8.35% savings on next 10% shift 6% savings come from the reduction of vehicles travelling on the roads. Additional savings comes from the multiplier effect originating from reduction of traffic congestion and idle time! *Ong, H. C et al, (2011). A review on emissions and mitigation strategies for road transport in Malaysia. Renewable and Sustainable Energy Reviews, 15(8), 3516–3522.

13. Summary Traffic forecasting and Fuel consumption models to inform governmental policies on public transportation. More than 20% fuel consumption reduction leading to mitigation of Greenhouse gases emissions. Shows the dynamics of multiplier effect of Reducing number of vehicles on the road Reducing congestion and hence lowering idle-fuel burning Reduce total fuel consumption by 21%, which is equivalent to 0.6 million liters per year.