Class Project ReportSustainable Air Quality, EECE 449/549, Spring 2009

Washington University, St. Louis, MO

Transportation Carbon Emissions Model - Midtermfor

Commuting

Josh

Katie

Kerry

Michael

EECE 449/549, Spring 2009

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.

SUV/Truck

Bus

MetroElectric

Carbon

PMT Fuels (FM), jEmission (EM), k

Diesel

Car

Students

Gas

ai=1Fraction of PMT

bi

VMT/PMT

djk

Emission/Fuel-

Commutingdistance# of trips

Activity

Walk/Bike

SUV/Truck

Bus

Metro

Car

Walk/Bike

VMTcij

Fuel/VMT

On Campus Trspt distance# of trips

Unv. Mng Traveldistance# of trips

Train

Air

Train

Air

Shuttles Shuttles

Jet Fuel

Faculty

Staff

Scope of the Model – What does the model include

Washington University Transportation Sector - Commuting

SUV/Truck

Bus

Metro

PMT

Car

Students

ai=1Fraction of PMT

CommutingLONG distance

# of trips

Activity

Walk/Bike

On Campus Trspt distance# of trips

Unv. Mng Traveldistance# of trips

Train

Air

Shuttles

Faculty

Staff

CommutingLOCAL distance

# of trips

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?

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

Results

Explain the results of your analysis

Include charts to tell your story

What does this mean for Wash. U.

FACULTY AND STAFF (MO & IL)

STUDENTS LOCAL ADDRESS

WashU PARKING PERMIT

WashU STUDENT POPULATION CHANGE

Student Commuting

1980 1985 1990 1995 2000 2005 2010 2015 20200

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

Number of Students Commuting per Year

Column BColumn N

Year

Num

ber

of S

tude

nts

Student Commuting

1980 1985 1990 1995 2000 2005 2010 2015 20200

2000000

4000000

6000000

8000000

10000000

12000000

14000000

16000000

18000000

Total Annual Miles Traveled by Student Commuters

Column C Column O

Year

Tota

l Ann

ual M

iles

Student Commuting

1980 1985 1990 1995 2000 2005 2010 2015 20200

0.2

0.4

0.6

0.8

1

1.2

1.4

Carbon Emissions from Student Commuters Normalized to 1991

Column M Column W

Year

Nor

mal

ized

to 1

991

Faculty/Staff Commuting

1980 1985 1990 1995 2000 2005 2010 2015 20200.00

200.00

400.00

600.00

800.00

1000.00

1200.00

1400.00

1600.00

1800.00

2000.00

Carbon Emissions from Faculty and Staff Commuters

Column X Column Z Column X Column Z

Year

Carb

on (m

etric

tonn

es)

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?

References