1. Class Project Report Sustainable Air Quality, EECE 449/549, Spring 2009 Washington University, St. Louis, MO Transportation Carbon Emissions Model - Midterm for Commuting Josh Katie Kerry Michael EECE 449/549, Spring 2009

2. Objectives of Model What did you group hope to accomplish? To further develop and expand on the work of the 2008 class project, as it relates to carbon emission for short and long distance commuting travel. To more accurately estimate carbon emissions To clarify the impact of each causality node will with possible reduction approaches identified for each. Why care about this particular part of transportation? Commuting, both locally and “home for the holidays,” is a significant part of WashU’s carbon footprint, and therefore something that would be beneficial to investigate how to reduce.

3. SUV/Truck Bus Metro Electric Carbon PMT Fuels (FM), j Emission (EM), k Diesel Car Students Gas  a i =1 Fraction of PMT b i VMT/PMT d jk Emission/Fuel- Commuting distance # of trips Activity Walk/Bike SUV/Truck Bus Metro Car Walk/Bike VMT c ij Fuel/VMT On Campus Trspt distance # of trips Unv. Mng Travel distance # of trips Train Air Train Air Shuttles Jet Fuel Faculty Staff Scope of the Model – What does the model include

4. Washington University Transportation Sector - Commuting SUV/Truck Bus Metro PMT Car Students  a i =1 Fraction of PMT Commuting LONG distance # of trips Activity Walk/Bike On Campus Trspt distance # of trips Unv. Mng Travel distance # of trips Train Air Shuttles Faculty Staff Commuting LOCAL distance # of trips

5. Model Methodology What is the methodology of your approach? Rely not only on data from previous classes, but also on national data regarding method of travel. Consider student trips during holidays in calculating carbon emissions for Washington University. Much of our time was spent improving last year’s model to make it more accessible, and usable in the future. What do the causality factors mean?

6. Model Methodology Include the causality factor calculation What assumptions did you make? Used upper and lower bounds for calculations to show uncertainty in a range Students with different parking passes drive to class more than others Students that live closer to school make more trips home Students that live with in 300 miles fly rather than drive home

7. Results Explain the results of your analysis Include charts to tell your story What does this mean for Wash. U.

8. FACULTY AND STAFF (MO & IL)

9. STUDENTS LOCAL ADDRESS

10. WashU PARKING PERMIT

11. WashU STUDENT POPULATION CHANGE

12. Student Commuting

15. Faculty/Staff Commuting

16. Improvements and Next Steps What do you think could be improved in the course of the rest of this semester? -Because we were limited on what data we received before the deadline for this project, there are improvements we can make by the end of the semester. -Upon receiving parking pass data, we can make more accurate estimations regarding commuting. Forecasting into the future – what are possible scenarios your group thinks should be included?

17. References