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
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