i
Note:
This document was updated by P. Schulze on 14 Sep 2009 to incorporate
436,020 kWh of electricity consumption inadvertently omitted from J.
Rutledge’s original thesis due to a misunderstanding that occurred when
electricity consumption data were initially provide to J. Rutledge. The
electricity consumption used in Jade’s calculations was based only on the
college’s “primary grid.” The new values in this document, and reflected in
the college’s FY 2008 GHG report (submitted to ACUPCC Sep 2009) and
that report’s supporting CACP spreadsheet, include all 14 of the campus
accounts and 140 kWh of consumption by the buildings at the McCarley and
Sneed preserves. The bulk of the difference between this present document
and Jade’s original thesis is that her thesis inadvertently omitted the
electricity consumption of the dorm called Roo Suites. The magnitudes of
the changes are minor. For example, electricity now accounts for 50% of
emissions whereas Jade originally calculated electricity to account for 49% of
emissions.
I have left the changed and reconfirmed values in this blue font to facilitate
any comparisons to Jade’s printed thesis.
The CACP spreadsheet and the report to the ACUPCC also reflect
Renewable Energy Certificates that were purchased for 10% of campus grid
(14 meters, not including Sneed and McCarley accounts) electricity
consumption beginning January 2008 (1/2 way through FY 2008). Jade was
not aware that the REC purchasing arrangement began during FY 2008 so
no mention of those RECS is included in the remainder of this document.
AUSTIN COLLEGE GREENHOUSE GAS EMISSIONS INVENTORY
by
JADE ELYSE RUTLEDGE
A Thesis
Presented to the Faculty
of Austin College
In Partial Fulfillment of the Requirements
for the
ii
HONORS PROGRAM of the Center for Environmental Studies
Sherman, Texas
30 April 2009
iii
Approved by _______________________________, Thesis Director
Dr. Peter Schulze
Professor of Biology and Environmental Science
_______________________________
Dr. David Baker
Associate Professor of Physics
______________________________
Dr. Todd Penner
Associate Professor of Religious Studies
iv
Acknowledgements
I would like to thank Peter Schulze, my thesis director, who helped me
immensely and guided me through this project. I would also like to thank my
committee members David Baker and Todd Penner. Additionally, I would like to
thank David Baker for his assistance with the calculator. I would like to thank
Oscar Page for signing the commitment and making it possible for me to do this
project.
I would like to thank the following people for assisting with information
and data: John Jennings, Ellen Miles, Jeannean Smith, Linda Welch, Michael
Imhoff, Mary Buick, Valerie Roberts, Gail Lewis, Sandra Miller, Michael
Springer, David Merriman, Sandy Beach, Sheryl Bradshaw, Heidi Ellis, Keith
Larey, Genna Bethel, Shauna Redman, Judy Wheaton, Lawanna Slaughter, Tim
Millerick, Keith Kisselle, Marie Pfarr, and Keaton Hoppe.
I would also like to thank Jenn Andrews from Clean Air Cool Planet for
answering my questions and producing helpful webinars. I would like to thank my
fellow members of the PCC Committee that were not previously mentioned for all
their ideas and support: Sarah Stevens, Brad Smucker, Cary Wacker, Doug
Darby, George Diggs, and Larry Caylor.
v
Table of Contents
Acknowledgements……………………………………………….……….…….iii
List of Tables…………………………………………………………….….…...vi
List of Figures…………………………………………………………….……..vii
Abstract…………………………………………………….………..….……….viii
Introduction……………………………………………………………………..1
Global Climate Change…………………………………………….…...1
American College and University President’s Climate Commitment......3
Objectives of Inventory………………………………………………....4
Methods……………………………………………………………………........5
Choice of Calculator…………………………………………….……....5
Data Requirements and Sources…………………………..…………….6
Challenges in Data Collection…...............................................................7
Data Quality and Assumptions……………………….……………...….11
Historical Data and Trends………………………………………….......14
Alterations to the Calculator………………………………………...…..15
Results…………………………………………………………………...………17
Discussion………………………………………………………………………19
Recommendations for Actions to Reduce Emissions…………………..19
Opportunities for Reform of the Data Collection Process…………….…26
Opportunities for Strengthening Data Quality……………………….…..28
Conclusions…………………………………………………………..………..…30
vi
References……………………………………………………………………..…32
Tables……………………………………………………………………….........37
Figures………………………………………………………………………..….44
Appendix 1: Calculator Tables………………………………………………..…51
Appendix 2: Inventory Report for the PCC and AASHE….................................58
Appendix 3: Commuting Survey: Original and Revised Versions…………..….65
Appendix 4: Austin College Current Staff Members…………………………....67
Appendix 5: Notes for Future Users of the CACP GHG Calculator at Austin
College……………………………………………………………………...……68
Appendix 6: Fleet Vehicle for Staff Cars Data and Calculations…………..……79
Appendix 7: Data of Survey Respondents for Commuting…………………..…81
Appendix 8: Data and Calculations of Directly Financed Flight Data ………….88
Appendix 9: Sports Air Travel Data and Calculations ……………………….…95
Appendix 10: Data for January Term Flights ……………………………….…..96
Appendix 11: Data for Study Abroad Semester and Year Long Trips ………….97
Appendix 12: Calculations of Solid Waste Averages………………………..….99
Appendix 13: Summary of Recommendations for Record Keeping Improvements
with pertinent Staff/Faculty member…………………………….………….….100
vii
List of Tables
Table 1: President’s Climate Commitment Actions to Reduce Greenhouse
Gases………………………………………………………………………...37
Table 2. Explanation of Emissions Sources at Austin College…………..….38
Table 3. Items not Included in the CACP calculator………………………...42
Table 4: Sensitivity Test for Trash Receptacle Fullness…………………….42
Table 5: Price of Offsetting Emissions per Source for Fiscal Year 2008…...43
viii
List of Figures
Figure 1: Model of the Greenhouse Effect……………………………..44
Figure 2: Past and Potential Temperature Change from 1900-2100……45
Figure 3: Concentrations of GHGs in the atmosphere………………….46
Figure 4: Changes in Killowatt-Hours and Student Popuatlion per Fiscal Year
from 2004 to 2008………………………………………………………47
Figure 5: Change in Killowatt-Hours and Total Campus Building Size (ft2) per
Fiscal Year 2004 to 2008……………………………………………….48
Figure 6: The Percentage and Metric Tonnes of Equivalent CO2 per Emissions
Source……………………………………………………………………49
Figure 7: The Percentage and Metric Tonnes of Equivalent CO2 for Scope 1,
Scope 2, and Scope 3 Emissions………………………………………….50
ix
Abstract
Global climate change has caused air and ocean temperatures to increase
and will continue to do so as the concentration of greenhouse gas emissions in the
atmosphere increase. In response to this concern President Oscar Page signed the
American College and University President’s Climate Commitment (PCC) in the
summer of 2008.
The first major step in meeting the PCC requirements is to perform a
greenhouse gas emissions inventory for the college. The thesis presents Austin
College’s first greenhouse gas emissions inventory. The inventory was performed
using Clean Air Cool Planet’s extensive spreadsheet. The calculator includes
emissions from energy use, automobile and air travel, solid waste and water
waste, printer paper, leaked chemicals, and fertilizer. Data collected from college
employees were used within the calculator to generate the results.
The college emitted a total of 14,302 MT CO2-equivalent of greenhouse
gas emissions. Major sources were purchased electricity (50%), natural gas (17%)
and air travel (17%). Emissions from automobile travel, solid waste, wastewater,
printer paper, leaked chemicals and fertilizer collectively accounted for 16% of
the total. These results, combined with costs of various emissions reduction
options, result in specific recommendations regarding the purchase of “green”
electricity, conservation measures, and the purchase of greenhouse gas “offsets”
as the most cost-effective mechanisms for reducing the college’s greenhouse gas
footprint.
1
Introduction
Global Climate Change
A natural phenomenon called the greenhouse effect keeps the planet warm
and supports life on earth (EPA, 2007a). When visible radiation from the sun
arrives at the earth much passes through the atmosphere and hits the earth surface.
Some gets absorbed by the planet and some is reflected back to space (EPA,
2007a). The absorbed light energy warms the planet and is re-radiated as infrared
radiation. Greenhouse gases (GHGs) in the atmosphere absorb the infrared
radiation, warming the atmosphere (Figure 1, EPA, 2007a). GHGs include water
vapor (H2O), carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O)
(EPA, 2007a). CO2 is naturally removed from the atmosphere by vegetation
during photosynthesis and released back into the atmosphere through respiration
(EPA, 2008).
Since 1750, the concentrations of CO2, CH4, and N2O in the atmosphere
have increased, primarily as a result of burning fossil fuels and deforestation by
humans (EPA, 2007a). Since the 1700s, there has been a 35% rise in CO2 in the
atmosphere (Figure 3, EPA, 2008). It is estimated that 60% of methane emissions
are due to human activities (Figure 3, IPCC, 2001b).
Air and ocean temperature increases have led scientists to conclude that
global climate systems have altered since industrialization (IPCC, 2007). Due to
the increase of GHGs in the atmosphere, more heat has been trapped than
2
naturally occurs and surface temperature has increased (EPA, 2007a). Evidence
that the earth is getting warmer includes an increase in globally averaged air and
ocean temperatures, the melting of snow and ice, and a rise in sea level (IPCC,
2007). Eleven of the past twelve years have been ranked as the warmest on record
prior to that year (IPCC, 2007). Climate modeling has allowed for best estimates
of potential changes and scenarios to predict future effects (IPCC, 2007). If our
emissions of GHGs continue to rise as they currently are, the average surface
temperature of Earth is projected to increase by 2 to 11.5°F (1.1-6.4°C) by 2100
(IPCC, 2007). Even if emissions were held at the current rate, temperature could
increase by up to 1.6ºF or 0.9 ºC by the end of the 21st century (Figure 2, IPCC,
2007).
Global climate change will significantly impact ecosystems worldwide.
Sea levels could potentially rise between 0.18 and 0.59 meters (0.59-1.9 feet) in
the next 90 years (IPCC, 2007). This could have a dire effect on populations
living in coastal areas. The ocean’s acidity will likely increase which could cause
problems particularly with coral, plankton, and deep sea biota, especially in shell
formation (IPCC, 2007; Caldeira, 2003). Furthermore, IPCC research predicts that
wind patterns, precipitation, extreme weather, and ice will alter due to climate
change (2007). Snow cover and sea ice are both predicted to shrink (IPCC, 2007).
The IPCC notes that “it is very likely that hot extremes, heat waves and heavy
precipitation events will continue to become more frequent” (2007). Due to the
potential rise in tropical sea temperature, tropical storms may become more
3
intense with higher winds and more precipitation (IPCC, 2007). According to the
IPCC report, precipitation will increase in areas of high altitude and decrease in
tropical areas (2007). When taken together, all of these potential results of global
climate change will drastically alter human life, as well as all life on Earth. Food,
water, natural disasters, extinction, and health issues will become more adverse as
global climate change intensifies.
The American College and University President’s Climate Commitment
The American College and University President’s Climate Commitment
(PCC) was created to address global warming by encouraging institutions to
commit to reducing GHG emissions (PCC, 2008). The PCC was created in
December 2006 and now includes more than 600 signatories including large
public institutions, small private colleges, and community colleges (PCC, 2008).
President Oscar Page signed the PCC in the summer of 2008. The commitment
encourages institutions to include climate change education and research in
institutional goals (PCC, 2008). Higher education has a unique position to act as a
role model for the community and equip students with the skills they can use to
reverse global climate change (PCC, 2008). This commitment by the college to
sustainability will be a part of a national and international effort to reduce
greenhouse gas emissions with the goal of lessening the impact of global climate
change.
4
When institutions sign the commitment they are expected to work towards
the ultimate goal of climate neutrality. Climate neutrality is defined as creating
zero net emissions of GHGs, i.e. all GHGs are avoided or offset. An “offset” is an
action that reduces GHGs in the atmosphere that would have otherwise been
emitted. This action tends to be funded by an institution wishing to negate GHGs
emitted by their activities. Initially, schools are expected to choose two or more
actions from a list of seven to implement on campus (Table 1). Schools are also
expected to create a GHG reduction plan which includes a target date for
achieving climate neutrality and interim target goals along the way. Also, the
GHG reduction plan includes further actions that the college plans to take to meet
the reduction goals. Participating schools must make their progress public by way
of online reporting mechanisms (PCC, 2008).
Objectives of Inventory
An inventory of GHG emissions for Austin College serves as the initial
step for the college to undertake the PCC requirements and reduce our carbon
footprint. The GHG inventory acts as a baseline for comparison to future
emissions. The inventory also enables the college to identify the greatest potential
targets for emissions reductions and plan climate initiatives. It also acts as a way
to communicate our GHG emissions to college community members and the
public. This document explains how Austin College’s first GHG inventory was
compiled, describes the results, and provides a guide for future GHG inventories
5
Methods
Choice of Calculator
Clean Air Cool Planet Calculator 6.1 (CACP, 2008) was chosen to
determine GHG emissions. This calculator was chosen because: it is endorsed by
the PCC; it is relatively comprehensive and easy to use; and it facilitates
comparison with over 1,200 other campuses that have used it (CACP, 2008).
Sources of emissions are entered into the calculator in their original units of
measurement. The calculator then converts measurements into Global Warming
Potentials (GWP) which are measures of how much a GHG contributes to global
warming. All conversion factors are taken from government documents and
referenced in the calculator (CACP, 2008).
The calculator allows for the emissions to be viewed by source as CO2,
CH4, or N2O in kilograms or as Million British Thermal Units (MMBtu) which is
the energy generated in the consumption of source fuels. Since each different
GHG has a different GWP, an option for viewing all emissions in a single unit is
available in the form of Metric Tonnes of CO2 (MT-eCO2). This converts all
gases into a CO2 equivalent so all emissions can be viewed as a single amount
(CACP, 2008).
6
Data Requirements and Sources
The calculator includes energy use, automobile and air travel, solid waste
and water waste, printer paper, leaked chemicals, and fertilizer (Table 2), but
excludes some other sources of GHG emissions (Table 3) due to the difficulty of
collecting data or tracking emissions. Table 3 is not comprehensive, but gives a
sense of some important GHG emissions not considered in the calculator. The
calculator does not include food or material purchases, except those mentioned
above. Distribution and transportation of these all physical materials to campus
are not reflected in the calculations. Emissions from the supply chain of materials
used on campus are not reflected in the calculator. The items not included in the
calculator are based on their production and disposal impact. The electricity used
in powering mentioned devices are included in the calculated results.
The CACP calculator requires a variety of inputs. The items included in
the calculator fall within three categories that are common among all carbon
accounting projects. Scope 1 describes “direct emissions from sources that are owned
and/or controlled by your institution” (CACP, 2008). Scope 2 describes “indirect
emissions from sources that are neither owned nor operated by your institution but
whose products are directly linked to on-campus energy consumption” (CACP,
2008). Scope 3 describes “emissions from sources that are neither owned nor
operated by your institution but are either directly financed or are otherwise
linked to the campus via influence or encouragement” (CACP, 2008). The data
requirements and sources for the calculator are shown in Table 2. All data were
7
collected on the basis of the College’s fiscal year, which is defined as July 1 to
June 30. The data were largely provided by staff and faculty of Austin College,
with one community official providing information.
Challenges in Data Collection
There were some data requirements within the calculator that were
difficult to collect. This is due to the fact that information is not amassed for
purposes of the inventory as they become available. Thus, collection of data is
done all at once for the sole purpose of the inventory from various sources.
Therefore, many data requirements had to be synthesized from several pieces of
information to calculate the emissions for a single source. The following section
explains how certain data that were difficult to amass were collected and
calculated.
The total commuter miles and gasoline used in the fiscal year are
calculated from commuting behaviors collected through an online survey. The
survey was sent to students, faculty, and staff via an internet survey machine
(www.surveymonkey.com, November 11, 2008). Behaviors used to calculate
commuting data are: % driving a personal vehicle, % carpooling, car type (for
average mpg), trips per week, weeks per trip, and distance per round trip to
campus. The survey created for the purpose of the inventory was made to collect
the aforementioned data used in the commuting calculations (Appendix 6).
8
Once all survey responses were collected, the data requirements for the
calculator were obtained from the results of the survey. To obtain the automobile
fuel efficiency, the year, make, and model vehicle for each respondent that drove
to campus regularly was found on the EPA Fuel Economy website
(www.fueleconomy.gov, April 22, 2009). Each vehicle’s average mpg of city and
highway travel was collected. All mpg were averaged for this figure. For percent
that drive personal vehicles for students, staff and faculty, the proportion of the
total respondents that drove to campus was collected. For percent that carpool for
students, faculty, and staff, the proportion that carpools out of those that drove to
campus was collected. For trips per week for students, faulty, and staff, the
answers to the trips per week question in the survey were averaged. For weeks per
year for students, staff, and faculty, a question in the survey had respondents
categorize which parts of the year they commuted to campus. The weeks per year
were averaged. For distance per round trip for students, faculty, and staff, the
survey response for distance from residence to campus was averaged.
These averages and percentages were entered into the calculator input
sheet and the calculator estimated distance and gasoline used for commuting
annually for students, faculty, and staff. The results of the commuting calculations
were based on the populations of total students, staff, and faculty, not just those
that responded to the survey, i.e. the calculator extrapolates the averages to the
whole campus population.
9
Accumulation of necessary air travel information was challenging and
inefficient. The calculator requires passenger miles per trip. Business Office
Records supplied by the Assistant Director of Finance showed each flight taken
by Austin College community members that Austin College financed. This
information originated from two sources: Account 5410 (airfare) voucher queries
and purchasing card records. For the voucher query, 83% of the entries had
destinations that were already in the records in one document. For purchasing
card records, all purchasing card expenditures are together in one record and can
not be filtered by air travel. Therefore, a work study student for the Business
Office went through all the purchasing card entries to extract flight purchases and
destinations for three years of records. This process took a considerable amount of
time. All purchasing card entries had destinations included when obtained for the
inventory due to the efforts of the work study student.
For the flights that did specify destinations from the voucher and
purchasing card records, distances in miles were calculated from an online
distance calculating tool (TerraPass, 2004). The passengers per trip from Austin
College multiplied by miles per trip were calculated for each flight. Flight
distances were totaled for all flights per year and entered into the calculator.
Study abroad air travel was a data requirement that involved amassing a
large amount of information from several sources. This figure includes the sum of
January term study abroad flights and the sum of semester and year long study
abroad flights. For each trip, miles were multiplied by the number of Austin
10
College passengers for a total distance per flight. For January term flights, two to
three separate Excel spreadsheets for each year were provided by the Secretary of
Academic Affairs. One document included the destination and another included
the students attending each trip. Some years, the students attending international
and national locations were separated into two Excel documents, meaning that
there were three documents to work with for some years. From these records, a
number of passenger miles per trip were found for each flight and summed.
Similarly, information for semester and year long study abroad travel was
found in several worksheets of an Excel document provided by the Assistant
Director of Study Abroad. For each year, a worksheet included each student
traveling abroad and the destination. Mileage was found for each trip and all trips
per year were summed. The sums of January terms and semester and year long
study abroad trips were added together for the final figure that was entered into
the calculator.
For waste statistics, the Solid Waste Supervisor for the City of Sherman
was contacted. The communication was time consuming due to the need of
permission from Physical Plant to collect such information.
11
Data Quality and Assumptions
Some data requirements were not exact figures due to the lack of record
keeping for some sources. The figures without exact records were calculated from
other information. The calculations, assumptions, and averages used are stated
below.
The fleet vehicle data for staff vehicles was calculated using averages of
business miles driven annually. For each vehicle, the starting mileage at purchase
was subtracted from the current mileage. This figure was divided by the years that
Austin College owned each vehicle to obtain an average mileage per year for each
vehicle. The personal miles for each vehicle for fiscal year 2008 were collected
and subtracted from the average annual mileage of the corresponding vehicle.
This figure is the amount of business miles on average put on each car for fiscal
year 2008. These numbers were summed and added to the other fleet vehicles,
which are police, physical plant, and biology van vehicles.
The data for commuting could be strengthened to reflect more accurate
results. The question about weeks per year was not exact because the respondents
were not asked how many weeks exactly, but were asked about the times of the
year that they commute to campus based on campus calendar time increments.
The options were: fall and spring semesters only, all year except for school
breaks, and all year even during school breaks. The weeks per response type were
estimated based on the fiscal year 2008 academic calendar. For fall and spring
semester only answers, 30 weeks were estimated. For all year, except school
12
breaks answers, 40 weeks were estimated. For all year, even during school breaks,
50 weeks were estimated. 416 community members responded to the survey. The
number of respondents to the survey may be due to lack of incentive. Some staff
members do not have email accounts and they were not included in the survey.
Air travel information had some sources of error. For the voucher queries,
not all entries were necessarily airplane miles, but were sometimes other types of
entries, e.g. flight change fees. 17% of the flights in the voucher records were
lacking destination information. When the voucher information is entered, there is
an option to add comments such as destination and number of those flying, but
this is not always entered. Many individuals enter voucher data and entry is not
consistent. To account for the missing 17% of destination data, the final directly
financed airfare figure was adjusted to account for the missing 17% assuming
they are the same approximate distances.
Study Abroad data had missing information in the records leading to the
necessity of some assumptions. Study abroad flights had all country destinations
provided by the Assistant Director of Study Abroad and the Secretary of
Academic Affairs. For semester and year long programs, 3% of trips had country
destinations, but did not specify a city.
So, the city was assumed to be the capitol city when mileage was
calculated. For January term trips, 57% had only the country of destinations, so
the capitol city was assumed for these trips. For trips within the U.S. that were
13
within driving distance, but were far enough to fly, it was assumed that half of the
class participants drove and half flew when calculating flight mileage.
Another issue in data quality was the mileage reimbursement for personal
automobiles. This figure may not be complete because some community members
may not turn in their personal mileage for reimbursements. There is no way to
account for how many community members do not turn in personal mileage
because there are no records. Thus, miles that are not turned in are not reflected in
the calculations because they are not recorded for any other reason.
The solid waste calculations included assumptions made when estimating
weight. Trash quantities were calculated from averages, since there are no meters
on the equipment to measure the actual tons of waste. Thus, an average amount of
campus waste of 22.22 tons per cubic yard (CURC Campus Refuse Profile, 1997)
was used to calculate trash based on the size of our receptacles and the frequency
of pickup. The fullness of the receptacles is not known in detail, and is based on a
statement made by the Associate Director of Physical Plant, that receptacles are
full 95% of the time. A sensitivity test was performed to determine the extent that
the results differ depending on the fullness of the receptacles (Table 4). The
results did not differ significantly and the difference between 100% and 80% full
accounted for only 0.5% of the total emissions. The 100% full figure was used in
the final calculations since the estimate by staff was 95% and 100% is a
conservative overestimate.
14
Historical Data and Trends
The CACP calculator has the ability to track historical emissions sources
back to the year 1990. This allows for a detection of historical trends and for
projections of future emissions sources. The calculator requires that a baseline be
chosen for the earliest complete year of data. At Austin College, fiscal year 2008
was chosen as the baseline year because it is the only complete year within the
calculator. This is the only complete year because some data sources could only
be found for the most current year, which is fiscal year 2008. Some data sources
were able to be collected for multiple past years. Data sources that were available
for fiscal year 2008 only were; the gasoline fleet, refrigerants, fertilizer,
commuting, bus travel, wastewater, and paper usage. These data were not
archived in records because there was no need to retain such information for
multiple years. Since all data does not exist for previous years, trends can not be
detected for the entire emissions profile, but some single sources can be tracked to
identify trends over time.
Purchased Electricity was tracked from 2004 to 2008 with population of
students (Figure 4). This was presented to track the trajectory of electricity use
over time and to locate a trend of energy use. Purchased Electricity was tracked
from 2004 to 2008 with the square footage of all buildings on campus from 2004
to 2008 (Figure 5). The changes in purchased electricity over time probably most
closely relates to the size of campus and the number of buildings requiring power.
In 2004, Luckett Hall, a dormitory residence, was demolished, which decreased
15
electricity usage between 2004 and 2005. The efficiency of Physical Plant
increased as well, leading to diminished electricity use. Again between 2005 and
2006, electricity usage decreased due to efficiency. The increase in electricity in
2008 corresponds with the addition of the Forster Art Complex and the Founders
Plaza in 2008. This has implications for future building additions on campus. All
campus additions will cause an increase in electricity use and climate actions and
initiatives will have to be adjusted to allow for such changes. But, electricity
usage did not increase between 2007 and 2008 as much as would be expected
with the rise in square footage because of efficiency from Physical Plant upgrades
and also because a smaller student population than previous years.
Alterations to the Calculator
The calculator was altered in three instances to increase the exactness of
the inventory results. The calculator was changed to reflect the fuel efficiency of
the Austin College community rather than national averages. A survey question
concerning the year, make, and model of vehicles driven to school was used to
find average fuel efficiency for each vehicle. All of the mpg were averaged for
students, faculty, and staff. These averages were then changed in the commuter
worksheet in the calculator for fiscal year 2008.
A radiation factor is included in the calculations to adjust for radiative
forcing due to air travel. The Radiation Forcing Index (RFI) in the calculator was
changed from 2.8 to 2 for all flights. Radiative forcing is any change in the
16
balance between radiation coming into the atmosphere and radiation going out.
Positive radiative forcing warms the surface of the Earth, and negative radiative
forcing cools it (Imperial College, 2005). The RFI for air travel accounts for the
amount of clouds created from airplane travel and the clouds’ affect on climate
change. Scientists have found that cirrus clouds formed by the exhaust of aircraft
can increase the Earth’s average surface temperatures (NASA, 2004). The figure
in the calculator uses a RFI of 2.8 which reflects IPCC measurements in 1992
which set the RFI at 2.7 (IPCC, 1999). In another scenario, the IPCC estimates the
RFI for total human activities at 1 (IPCC, 1999). A radiation factor of 2 was
chosen because it is a median between low estimates of 1 and higher estimates of
3.
Another alteration was made with study abroad flights because these
flights are largely international, whereas directly financed air travel flights are
usually domestic. When the CACP calculates flights, it assumes the short haul
domestic flight emissions amount. International flights are usually considerably
longer than domestic flights. The take off and landing portions of flights require
the highest amount of emissions. The longer the flight the smaller the proportion
of emissions is used in the take off and landing, so long flights user fewer
emissions proportionally on take off and landing than shorter flights. To adjust for
this assumption, the study abroad air travel kilograms of CO2 per mile figure was
multiplied by .64 to reflect the lower emissions for longer, international flights
(DEFRA, 2008).
17
Results
The college emitted 14,302 MT-eCO2 in fiscal year 2008. Approximately
11 MT-eCO2 are emitted by the college per student per year. Purchased electricity
was the largest emissions source in fiscal year 2008, making up 50% of the total
greenhouse gas emissions from the college and emitting 7,106 MT-eCO2. The
next largest source was natural gas, which accounted for 17% of total emissions
and releases 2,466 MT-eCO2. Study abroad flight emissions were the third largest
source, with 11% of total emissions and 1,598 MT-eCO2. The next largest sources
were directly financed air travel (6%, 875 MT-eCO2), emissions associated with
transportation and distribution of purchased energy (5%, 703 MT-eCO2), student
(3%, 438 MT-eCO2) and staff/faculty (3%, 384 MT-eCO2) commuting, solid
waste (3%, 383 MT-eCO2), office paper (1%, 155 MT-eCO2), and fleet vehicles
(1%, 121 MT-eCO2) (Figure 6).
Mileage reimbursements and bus mileage (28 MT-eCO2), refrigerants (23
MT-eCO2), wastewater (13 MT-eCO2), and fertilizer (9 MT-eCO2) accounted for
less than 1% of the total emissions each (Figure 6). Altogether, these emissions
made up 0.5% of the total emissions and may be counted as de minimus emissions
according to CACP (CACP, 2008). According to the PCC protocol, de minimus
need not be collected every year and the upper-bound estimate of emissions for
fiscal year 2008 may be added for future inventory years (CACP, 2008).
18
Scope 1 emissions accounted for 18% and emitted 2,619 MT-eCO2. Scope
2 emissions equaled 50% of all emissions and created 7,106 MT-eCO2. Scope 3
emissions made up 32% of the total and emitted 4,576 MT-eCO2 (Figure 7).
19
Discussion
The results reveal that electricity is close to half of the total emissions.
Thus, purchased electricity should be a priority for achieving climate neutrality.
Natural gas is the second largest source and should be considered strongly when
implementing the climate action plan. Air travel (study abroad and directly
financed air travel) should be focused on for initiatives, since it is the third largest
source. Together, purchased electricity, natural gas, and air travel make up 84% of
the total emissions. Thus, any climate action planning must address all three of
these sources. The rest of the sources account for the remaining 16% of Austin
College’s climate footprint. To achieve climate neutrality, these emissions
sources will need to be reduced or offset.
Recommendations for Actions to Reduce Emissions
Several options are available for reducing the college’s GHG footprint.
My recommendations focus on the sources responsible for the bulk of the
campus’s GHG releases, but some smaller sources may warrant early attention
due to potential to help raise awareness and educate the campus community.
Purchased electricity, natural gas, and air travel collectively account for 84% of
the college’s GHG emissions, and therefore deserve priority consideration. The
three avenues to decrease emissions are conservation behavior, emissions
avoidance through renewable energy or campus renovations, or offsetting
emissions. Conservation and avoidance are preferable solutions due to cost and
20
impact. These actions do not release emissions in the first place, whereas offsets
just compensate for emissions already released. Offsets are controversial and are
sometimes criticized as a way to pay someone else to reduce GHG emissions
while the institution does nothing to reduce emissions themselves. Therefore,
“investing in offsets can be a short-term tool for reducing an institutions carbon
footprint after efforts to avoid and reduce internal emissions have been initiated,
but it should be of secondary focus” (PCC, 2008). Thus, offsets should be used
with restraint and conservation and avoidance should be the preferred action over
offsetting emissions. Conservation efforts are the most cost saving emissions
reducing tactic because it saves money from the actual purchasing of the energy
or product not used and it saves money for offsets. Thus, conservation activities
act like a multiplier effect with financial savings. By increasing sustainability
efforts on campus, potential donors may be attracted to the cause and may want to
feel as though they helped to make Austin College sustainable.
With the assistance of David Baker, I recommend the offset provider
NativeEnergy, based on ratings from Clean Air Cool Planet, Tufts University, and
Carbon Concierge (CACP Consumer’s Guide to Retail Carbon Offset Providers,
2006; Teiwes, 2008; Kollmus et al., 2007). NativeEnergy was chosen because it
was consistently rated in the top five choices of providers for each rating system
and had one of the most reasonable pricing schemes of top rated providers.
Purchased electricity is the largest emissions source making up 50% of the
total emissions and creating 7,106 MT-eCO2 in fiscal year 2008. Three alternative
21
options for carbon reductions regarding purchased electricity are purchasing wind
energy, offsetting MT-eCO2 emitted from purchased electricity, or conservation
efforts.
One option to decrease or eliminate GHG emissions from purchased
electricity is to purchase 100% wind power. This would satisfy action e. from the
PCC chosen options for reductions (Table 1). Starting January 1, 2008, 10% of
the college’s electricity came from renewable sources. Starting January 1, 2009,
15% is from such sources. The cost of 100% wind power from our current
provider has not been made available, but a quote from Green Mountain Energy
gave a 5% price increase from 10% wind power to 100% wind power for a three
year contract (personal correspondence, Dr. Pete Schulze, April 4, 2009). If our
current provider had similar price increases from 10% to 100% wind power, the
price for electricity could increase by approximately $50,000 for 100% wind
electricity during fiscal year 2008. For comparison, the price to offset all electrical
power through our chosen provider NativeEnergy for 2008 would be $70,541
(Table 5). Offsetting would be an increase of 6% above what we currently pay for
electricity. Therefore, it would be more cost effective to purchase wind energy
from our electricity provider than to offset all purchased electricity. It would also
have less of an environmental impact to avoid these emissions rather than offset,
because emissions are not released in the first place with avoidance.
Conservation efforts could include enhancing efficiency on campus
through retro-fitting, policy alterations, or behavioral changes. As an example, the
22
Director of Physical Plant, John Jennings, stated that changing policies on
temperature parameters in the future may help energy savings (personal
communication, April 2, 2009). Conservation efforts have been overwhelmed by
new building construction which caused energy use to increase despite
conservation projects. Figure 5 illustrates the increase in energy in 2008 due to the
new buildings despite fewer students and more conservation projects. This
increase in energy usage can be attributed to the construction and additional
energy use of the Forster Art Complex and the Founders Plaza. Although
initiatives are beneficial, wind energy or offsetting will be necessary to achieve
carbon neutrality because campus buildings will still use electricity and natural
gas despite efficiency.
Energy reduction campaigns could include competitions for energy
reduction amongst dormitories and other activities to raise awareness and
encourage savings. Energy saving campaigns tend to have a small effect on total
electricity and may only be successful over short time periods. But, conservation
is a cheaper option for reductions and all savings help reduce the overall
emissions. Competitions between dormitories in other schools tend to reduce
electricity emissions by about 10% of the total electricity consumption (Peter
Schulze, personal communication, April 7, 2009). If Austin College had a
dormitory competition that reduced 10% of dormitory energy use over the year, it
would save the college approximately $11,000 that could be put towards
renewable energy or offset purchases.
23
The college has committed to an Energy Star (www.energystar.gov, April
3, 2009) purchasing policy, which meets the requirement for PCC option b.
(Table 1). This action may help with energy conservation, but will not make a
difference until electronics need to be replaced. Thus, this will not take an
immediate effect and may be slow in creating noticeable changes in total
emissions. The Energy Star purchases will reduce energy use over time and save
money in the long run.
The school has committed to a policy that all new buildings align with
LEED (Leadership in Energy and Environmental Design) certification standards
(www.usgbc.org, April 5, 2009), which satisfies the PCC option a. (Table 1). This
initiative will be helpful, but due to the fact that new buildings increase the
campus building square footage, the amount of GHG emissions on campus will
increase with new construction regardless of building efficiency.
The second largest source of emissions on campus was natural gas.
Emissions due to natural gas could be offset or reduced with conservation efforts.
Natural gas is used for heating buildings, cooking, and hot water. This figure can
be reduced through increasing the efficiency of building heating and making sure
to heat buildings only when in use and only when it is necessary. Offsetting
natural gas for 2008 numbers would cost $24,480, which is 7% over the total cost
of natural gas for 2008 (Table 5). Both reduction efforts and offsets together
would be my recommendation for reducing natural gas.
24
The third largest source is air travel. Offsets for air travel have been
planned for study abroad flights and I would recommend extending this policy to
include all air travel the school finances. This would meet the requirement for
option c. from the PCC actions for GHG reductions (Table 1). Offsetting all study
abroad flights with the chosen provider would cost approximately $15,863 (Table
5). January Terms flights are added in the student cost for the course, but are paid
for by the college (personal communication, Assistant Director of Study Abroad,
Valerie Roberts, April 6, 2009). The offsetting would be a cost supported by the
student for January Term. The cost of offsetting could be an addition to the course
fee for each off campus January term trip. The students would also pay the
offsetting fee for study abroad flights within their study abroad budget (personal
communication, Assistant Director of Study Abroad, Valerie Roberts, April 6,
2009). Offsetting directly financed air travel for fiscal year 2008 would cost
approximately $8,686 annually. This money would have to be funded by the
college. In summary, the total cost of offsetting all flights for fiscal year 2008
would be $24,549. Study Abroad and January Term students would pay for
$15,863 (65%) of this total and the college would pay for sports team travel and
faculty and staff travel ($8,686, 35%). Apart from offsetting or conserving flights
with phone and video communication, little can be done to curb emissions from
this source. I would highly recommend offsetting for flights because Austin
College has a commitment to global experience with the study abroad program.
25
The Quality Enhancement Plan has set a goal to have 100% participation in study
abroad programs, so flights will most likely increase over the next years.
The remaining 16% percent of emissions could be offset for $22,716 for
fiscal year 2008. The cost of offsetting all emissions would cost $141,976 (Table
5). An option of a green fee for students, faculty, and staff could be offered to
allow for community members to offset their carbon footprint associated with the
school. If each student, staff, and faculty member offset their emissions with a
green fee, it would cost approximately $89 annually per person if there are 1,600
community members.
The college will need to create a target goal date to reach climate
neutrality with interim dates of reductions. I propose that the college should have
a goal of climate neutrality by 2019. The college could enact a system of phasing
in offset purchases by 10% a year until 100% of emissions not conserved or
avoided are offset. The college could increase the purchase of wind energy by
$8,000 a year, until our current contract for electricity ends in 2018. A contract
with a new provider could be arranged to allow for 100% wind energy. If the
college offset 10% of emissions excluding electricity and purchased $8,000 of
wind energy, the college would spend about $17,500 next year. A green fee could
be offered to offset a community member’s carbon footprint through the college
for $89.
In the meantime, conservation efforts could be made through maintenance
projects and behavior changes. Dormitory competitions could save the school
26
$11,000 if 10% of dorm electricity is cut per year based on an average amount of
savings from dormitory competitions at other schools experience based on the rate
of our current electricity. Dormitory conservation projects also allow for students
to get involved and educated about sustainability. The Physical Plant could
continue to enhance the efficiency of the campus with projects such as changing
the parameters for temperature settings for on campus buildings.
Opportunities for Reform of the Data Collection Process
The inventory procedure was inefficient due to the necessity of collecting
data from a variety of sources in a variety of formats and converting the data into
forms that the calculator requires. Inventories will need to be completed once a
year and the process would be more effective if modest efforts were made to
collect data in anticipation of the inventory. The following recommendations for
reforms should be considered for implementation to make the inventory process
less complicated and time consuming.
For flight information, the budget records could keep flights separate from
other budget entries to avoid ambiguity within the purchasing card entries and the
voucher entries. To avoid sorting through all the purchasing card entries at once, a
policy could be enacted by the Director of the Business Office to keep purchasing
card entries that are flights in a separate document with specified destinations and
passengers when they are entered, rather all at once for the inventory.
27
For Study Abroad records, record keeping could be changed to include a
summary document with succinct data of destination and passenger count per trip.
For January Term trips, the Secretary of Business Affairs could create a summary
document for each January that includes the number of passengers for each trip,
including professors and students, and the destination country and city. For
semester and year long flights, the Assistant Director of Study Abroad could
create a similar summary document that includes each city and country
destination and the number of Austin College students that traveled there
annually. These summary documents would make data collection much more
effective in the future.
Regarding communication with the city, a member of the physical plant
could collect information from the city directly, per the request of the inventory
creator, which would expedite this process because it would remove the City’s
cumbersome process of gaining authority to release college billing data to a
student or students working on the inventory.
28
Opportunities for Strengthening Data Quality
The data collection process can be reformed to acquire more precise data
that will strengthen the subsequent precision of the inventory results. If any
substantial changes in data collection or calculations occur in the future that may
improve precision, then, if possible, the baseline year should also be altered
according to this reform. The following reforms will help the data quality, but
should not skew the data substantially, but will just make the data more exact.
Fleet vehicles data collection reforms have already been implemented by
the Purchasing Representative. The Purchasing Representative will email all staff
that use fleet vehicles to collect car mileage at the end and the beginning of every
fiscal year. This mileage change will enable determination of the exact mileage
for each car each fiscal year, rather than an average over several years. Personal
mileage should be collected for the fiscal year by the Benefits Representative.
Once the personal mileage is collected and subtracted from total mileage change,
the average mpg from the car type will be used to estimate the amount of gasoline
used by fleet vehicles annually.
For commuting data, a way to ensure better quality of data would be to
create a way to survey those community members without email accounts. A
paper survey could be distributed to those without email accounts. The proposed
survey revisions should be adopted for survey distribution in the future.
To enhance the collection of the air travel data, business office account
forms should be standardized and a policy should be made that ensures each
29
voucher entry includes the destination and passenger count per entry in the
description area. This policy should be created and enforced by the Director of the
Business Office. It is possible to get the destination for every entry because each
flight has a form that includes a receipt of the flight, including the destination.
Solid waste generation data was based on the frequency that dumpsters
were emptied and average degree to which dumpsters were filled when they were
emptied. To avoid using national averages for weight per cubic foot, weight could
be determined by finding an average weight per bag of trash on regular time
intervals and then inventory the amount of bags purchased every year (Director of
Physical Plant, John Jennings, personal communication, March 2009).
30
Conclusions
Global warming is starting to alter our climate and will almost certainly
have a deleterious effect on our planet. Austin College emits greenhouse gases
that contribute to global warming. As an institution of higher learning, Austin
College has a unique standing to make an impact on global climate change by
setting an example in striving for climate neutrality. The carbon emissions
inventory is the preliminary action towards reducing the school’s carbon
footprint. Austin College’s top three emissions sources are purchased electricity,
natural gas, and air travel. These three sources therefore deserve priority when
planning initiatives to reduce GHG emissions. Reductions of emissions from
automobile transportation, solid waste, and paper use can also be planned to
decrease the college’s impact on global warming. Bus travel, refrigerants,
wastewater, and fertilizer are de minimus emissions and need not be reduced
significantly.
The cost to offset all GHG emissions would be $141,976 annually. This
price highlights the need to evaluate other actions that the college could take to
lessen our GHG impact more economically. Purchasing 100% wind energy would
be the most cost efficient ways to make a major impact on our GHG emissions
totals. If 100% of electricity was wind generated, then our emissions would
decrease by half. The cost would be about 5% above what the college pays
currently, assuming that our electricity provider has similar prices to those that
Green Mountain Energy quoted for our electricity usage. Offsets for all remaining
31
GHG sources besides electricity would cost approximately $71,435 annually.
Therefore, increasing the percentage of electricity that is wind generated would
make the largest impact for the lowest price. The college should offer the option
to students, staff, and faculty to offset their emissions with an annual $89 green
fee, which would save the college money in offsetting costs.
I propose the college sets a goal of climate neutrality by 2019. Each year,
the college could increase offset purchases by 10% until 100% of emissions not
conserved or avoided will be offset in 2019. The college could purchase a larger
proportion of wind electricity by $8,000 a year, until the current contract ends in
2018. Then an electricity provider could be chosen that could offer 100% wind
electricity. I would recommend that conservation and avoidance are the primary
actions because offsetting is an expensive activity. Conservation is the cheapest
form of emissions reduction because it saves money on energy and on offsets.
Therefore, conservation and avoidance should be the primary focus for emissions
reductions and offsets should be used to cover the remaining emissions.
32
References
Andrews, Jennifer, et al. "Campus Carbon Calculator Version 6.1." 2008. Climate
Action Toolkit. Clean Air-Cool Planet. 1 October 2008
<http://www.cleanair-coolplanet.org/toolkit/inv-calculator.php>.
Caldeira, Ken and Michael E. Wickett. "Anthropogenic carbon and ocean pH."
Nature 425.6956 (2003): 365.
Clean Air-Cool Planet. "A Consumers' Guide to Retail Carbon Offset Providers."
2006. Clean Air-Cool Planet. Ed. Bill Burtis. 12 March 2009
<http://www.cleanaircoolplanet.org/ConsumersGuidetoCarbonOffsets.pd
>.
College and University Recycling Council (CURC) Standards Committee.
"Volume-To-Weight Conversion Chart." 1997. RecycleMania. 12 March
2009 <http://www.recyclemaniacs.org/doc/measurement
tracking/conversions.pdf>.
DEFRA. "Methodology Paper for Transport Emission Factors." July 2008. 2008
Guidelines to Defra’s GHG Conversion Factors. 5 April 2009
<http://www.defra.gov.uk/environment/business/envrp/pdf/passenger
transport.pdf>.
33
Environmental Protection Agency. Carbon Dioxide. 9 September 2008. EPA. 19
January 2009 <http://www.epa.gov/climatechange/emissions/co2.html>.
—. "Energy Star." Environmental Protection Agency. 3 April 2009
<http://www.energystar.gov/>.
—. Future Temperature Changes. 20 December 2007b. EPA. 19 January 2009
<http://www.epa.gov/climatechange/science/futuretc.html>.
—. Science. 20th December 2007a. EPA. 19th January 2009
<http://www.epa.gov/climatechange/science/index.html>.
Hough, Ian, et al. "Campus Carbon Calculator User's Guide Vol. 6." 2008.
Climate Action Toolkit. Clean Air-Cool Planet. 1 October 2008
<http://www.cleanair-coolplanet.org/toolkit/inv-calculator.php>.
Intergovernmental Panel on Climate Change. Aviation and the Global
Atmosphere. Cambridge, United Kingdom: Cambridge University Press,
1999.
—. Climate Change 2001 Synthesis Report. Cambridge, United Kingdom:
Cambridge, 2001a.
34
—. Climate Change 2001 The Scientific Basis. Cambridge, United Kingdom:
Cambridge, 2001b.
—. Climate Change 2007: The Physical Science Basis. Contribution of Working
Group I to the Fourth Assessment. Cambridge, United Kingdom:
Cambridge University Press, 2007.
Imperial College. "Climate Change and the Future of Air Travel." 25 January
2005. Imperial College London. 5 April 2009
<http://www.imperial.ac.uk/P5997.htm>.
IRS. "Standard Mileage Rates." 21 July 2008. Tax Professionals. 1 December
2008 <http://www.irs.gov/taxpros/article/0,,id=156624,00.html>.
Kollmuss, Anja, Benjamin Bowell and Tufts Climate Initiative. "Voluntary
Offsets For Air-Travel Carbon Emissions." Vers. 1.3. December 2006.
Tufts University Institute of the Environment. 12 March 2009
<http://www.tufts.edu/tie/carbonoffsets/TCI_Carbon_Offsets_Paper_Apri
-2-07.pdf>.
U.S. Green Building Council. "LEED Version 3." 2009. Leadership in Energy and
Environmental Design. 5 April 2009
<http://www.usgbc.org/DisplayPage.aspx?CMSPageID=1970>.
35
NativeEnergy. NativeEnergy. 2008. 12 March 2009
<http://www.nativeenergy.com/>.
National Aeronautics and Space Administration. "Predicting Future Warming."
2007. NASA Earth Observatory. 5 April 2009
<http://eob.gsfc.nasa.gov/Features/GlobalWarming/global_warming_upd
te5.php>.
—. "Clouds Caused By Aircraft Exhaust May Warm The U.S. Climate." 27 April
2004. Langley Research Center. 5 April 2009
<http://www.nasa.gov/centers/langley/news/releases/2004/04-140.html>.
President's Climate Commitment. About American College & University
President's Climate Commitment. 2008. 28 February 2009
<http://www.presidentsclimatecommitment.org/html/about.php>.
Teiwes, Indigo. "Carbon Offset Provider Evaluation Matrix." November 2008.
Carbon Concierge. 12 March 2009
<http://www.carbonconcierge.com/learn/COPEM-Final.pdf>.
36
TerraPass, Inc. TerraPass. 2004. 10 December 2008
<http://www.terrapass.com/carbon-footprint-calculator/#air>.
37
Tables
Table 1: President’s Climate Commitment Actions to Reduce Greenhouse Gases
(PCC, 2008).
a. Establish a policy that all new campus construction will be built to at least the
U.S. Green Building Council’s LEED Silver standard or equivalent.
b. Adopt an energy-efficient appliance purchasing policy requiring purchase of
ENERGY STAR certified products in all areas for which such ratings exist.
c. Establish a policy of offsetting all greenhouse gas emissions generated by air
travel paid for by our institution.
d. Encourage use of and provide access to public transportation for all faculty,
staff, students and visitors at our institution.
e. Within one year of signing this document, begin purchasing or producing at
least 15% of our institution’s electricity consumption from renewable sources.
f. Establish a policy or a committee that supports climate and sustainability
shareholder proposals at companies where our institution's endowment is
invested.
g. Participate in the Waste Minimization component of the national RecycleMania
competition, and adopt 3 or more associated measures to reduce waste.
Note: Austin College has committed to a, b, and g. Austin College has already
accomplished e. Recommendations support c.
38
Table 2: Explanation of emissions sources at Austin College with sources of data.
Institutional Data
Budgets
Operating Budget
Energy Budget
Population Size
Full Time Students
Part-Time Students
Sources
Total expenditures for fiscal
year (dollars).
Monetary sum the school
spends on providing energy
(electricity and natural gas) to
on-campus buildings (dollars).
Population of full time students.
Faculty
Population of part-time
students.
Population of summer school
students.
Faculty population.
Staff
Staff population.
Physical Size
Physical Size of Campus
Buildings
Size of all on campus buildings
(ft2).
Summer School Students
Physical Size of Research
Space
Scope 1 Emissions
Fuels Used on Campus
Natural Gas
Gasoline Fleet
Size of research space (ft2).
Fuel used for heating, hot water,
and cooking (MMBtus).
Gasoline used for collegeowned vehicles including
physical plant, police, biology
vans, and staff vehicles
(gallons). Personal miles put on
fleet vehicles not included.
Assistant to the
President. Found in
Board Minutes.
Assistant Director of
Finance. Found in the
Account Availability
Report.
Vice President for
Academic Affairs
Vice President for
Academic Affairs
Vice President for
Academic Affairs
Vice President for
Academic Affairs
Vice President for
Academic Affairs
Vice President for
Academic Affairs
(current size) and
Administrative Assistant
to Vice President for
Business Affairs
(changes of building
space since 1990).
Vice President for
Academic Affairs
Director of Physical
Plant
Office Manager of
Physical Plant (physical
plant, police, and biology
vehicles).
Purchasing
Representative (staff
vehicles total mileage)
and Benefits
39
Representative (staff
vehicles personal miles).
Refrigerants and Chemicals
HFC-134a Refrigerant
Refrigerants of type HFC-134a
that escaped when maintaining
equipment (lbs).
HCFC-22 Refrigerant
Refrigerants of type HCFC-22
that escaped when maintaining
equipment (lbs).
Fertilizer
Amount of Fertilizer
Amount of Fertilizer (lbs).
% Nitrogen
% nitrogen in fertilizer. If
different % nitrogen for
different fertilizer types, take
weighted average of % nitrogen.
Director of Physical
Plant
Director of Physical
Plant
Director of Physical
Plant
Director of Physical
Plant
Scope 2 Emissions
Purchased Electricity
Custom Fuel Mix
Amount of electricity and the
fuel mix (coal, natural gas,
nuclear, and renewable energy
sources) used by on-campus
buildings (kWh).
Exact fuel mix of electric
utility. % coal, natural gas,
nuclear, renewable, and
purchased by unknown grid
sources.
Director of Physical
Plant
Director of Physical
Plant
Scope 3 Emissions
Commuting
Student Automobile Fuel
Efficiency
% Students Drive
Personal Vehicle
% Students that Carpool
Student Trips per Week
Student Weeks per Year
Commuting behavior was used to calculate gallons of
gasoline used by commuters per year.
Average mpg of student
Online survey of students
vehicles driven to campus.
Average from car year, make
and model. EPA mpg averages
were used
(www.fueleconomy.gov).
% of students that drive
Online survey of students
personal vehicles to campus.
% of students that drive
Online survey of students
personal vehicles that carpool to
campus. Carpooling is defined
as two or more passengers.
Average trips per week students Online survey of students
commuted.
Average weeks per year
Online survey of students
40
Student Miles per Trip
Faculty Automobile Fuel
Efficiency
% Faculty Drive Personal
Vehicle
% Faculty that Carpool
Faculty Trips per Week
Faculty Weeks per Year
Faculty Miles per Trip
Staff Automobile Fuel
Efficiency
% Staff Drive Personal
Vehicle
% Staff that Carpool
Staff Trips per Week
Staff Weeks per Year
Staff Miles per Trip
students commuted.
Average distance per round trip
that students commuted (miles).
Average mpg of faculty
vehicles driven to campus.
Average from car year, make
and model. EPA mpg averages
were used
(www.fueleconomy.gov).
% of faculty that drive personal
vehicles to campus.
% of faculty that drive personal
vehicles that carpool to campus.
Carpooling is defined as two or
more passengers.
Average trips per week faculty
commuted.
Average weeks per year faculty
commuted.
Average distance per round trip
that faculty commuted (miles).
Average mpg of staff vehicles
driven to campus. Average from
car year, make and model. EPA
mpg averages were used
(www.fueleconomy.gov).
% of staff that drive personal
vehicles to campus.
% of staff that drive personal
vehicles that carpool to campus.
Carpooling is defined as two or
more passengers.
Average trips per week staff
commuted.
Average weeks per year staff
commuted.
Average distance per round trip
that staff commuted (miles).
Directly Financed Air Travel
Faculty/Staff Directly
Total distance of faculty/staff
Financed Air Travel
plane travel that the school
wholly or partially finances in
the fiscal year (miles).
Online survey of faculty
Online survey of faculty
Online survey of faculty
Online survey of faculty
Online survey of faculty
Online survey of faculty
Online survey of faculty
Online survey of staff
Online survey of staff
Online survey of staff
Online survey of staff
Online survey of staff
Online survey of staff
Assistant Director of
Finance (all air travel for
staff and faculty, except
study abroad). Found in
Purchasing Card records
and Voucher Query
records. Administrative
Assistant for Athletics
41
Student Directly Financed
Air Travel
Total distance of student plane
travel that the school wholly or
partially finances in the fiscal
year (miles). Only athletic
teams in this figure.
Other Directly Financed Travel
Bus Travel
Charter bus distance from fiscal
year (miles). Only athletic
teams in this figure.
Mileage Reimbursements Distance driven on personal
for Personal Vehicle Use
vehicles that the college
reimbursed (miles). The IRS
mileage rates were used to
calculate mileage (IRS Standard
Mileage Rates, 2008).
Study Abroad Travel
Study Abroad Air Travel
Waste
Solid Waste
Wastewater
Purchased Materials
Office Paper
(Athletic flights)
Administrative Assistant
for Athletics (Athletic
flights)
Administrative Assistant
for Athletics (Athletic
flights)
Assistant Director of
Finance. Found in
Account Availability
Report.
Total distance of semester and
yearlong study abroad flights
and January term flights per
fiscal year (miles).
Assistant Director of
Study Abroad (semester
and year long trips) and
Secretary of Academic
Affairs (January Term).
Solid waste sent to the landfill
from Austin College trash
receptacles. Measured in short
tons (2,000 lbs).
Solid Waste Supervisor
for the City of Sherman
(number of receptacles
and frequency of pick
ups) and the Texoma
Area Solid Waste
Authority, Inc. (landfill
type).
Office Manager of
Physical Plant
Water sent to the city
wastewater treatment plant
(gallons).
Amount of office paper used per Purchasing
year (lbs).
Representative
42
Table 3: Items not Included in the Calculator.
Paper Products: napkins, toilet paper, paper towels, paper dishes,
Cleaning Products and Chemicals
Disposable and reusable plastic ware
Furniture
Scientific equipment and reagents
Construction of buildings
Activities of contract maintenance workers
Student driving other than commuting to campus
Items in the campus bookstore
Office supplies, except printer paper
Lighting materials
Electronics
Table 4: Sensitivity Test for Trash Receptacle Fullness at 100%, 90%, and 80%
full in Kilograms of CH4 and Metric Tonnes of CO2 Equivalents. Also shows the
percentage of total emissions.
Fullness of
Receptacle
Tons per
Year
Kilograms of
CH4
MT-eCO2
100%
353
16,641
383
Percentage of
Total
Emissions
3%
90%
318
14,991
345
2%
80%
283
13,341
307
2%
43
Table 5: Price of Offsetting Emissions per Source for Fiscal Year 2008.
Fiscal Year 2008
Source
Purchased
Electricity
Natural Gas
Study Abroad Air
Travel
Directly Financed
Air Travel
Scope 2 T and D
Losses
Student
Commuting
Faculty/Staff
Commuting
Solid Waste
Paper
Fleet Vehicles
Personal Mileage
and Bus Travel
Refrigerants and
Chemicals
Wastewater
Fertilizer
GHG
emissions in
MT-eCO2
7106
Percent of
Total
50
Short ton
(2,000
pounds)
7838
2466
1598
17
11
2720
1763
875
6
965
680
5
775
438
3
483
384
3
424
383
155
121
28
3
1
1
0.2
422
171
133
31
Price of Offset
($9 per short
ton)
$ 70,541
$ 24,480
$ 15,863
$ 8,686
$ 6,978
$ 4,348
$ 3,812
$ 3,802
$ 1,539
$ 1,201
$ 278
23.2
13.1
9
0.2
25
0.1
14
0.1
10
Price to Offset Total
Emissions:
$ 228
$ 129
$ 89
$141,976
44
Figures
Figure 1: Model of the Greenhouse Effect.
45
Figure 2: Past and potential temperature change from 1900-2100 with models of
high growth, medium growth, low growth, and constant CO2, reproduced from
NASA, 2007.
46
Figure 3: Concentrations of GHGs in the atmosphere, reproduced from IPCC.
47
Figure 4: Changes in killowatt-hour use and student popuatlion per fiscal year
from 2004 to 2008. These data are based solely on the college’s primary grid,
which does not include the dorm called Roo Suites or a variety of minor accounts
for items such as guard lights (note added by P. Schulze, 11 Sep 2009).
48
Figure 5: Change in killowatt-hours and total campus building size (ft2) per fiscal
year 2004 to 2008. 2006 and 2007 are overlapping due to the closeness in square
footage and kilowatt hour measurements of the two years. These data are based
solely on the college’s primary grid, which does not include the dorm called Roo
Suites or a variety of minor accounts for items such as guard lights (note added by
P. Schulze, 11 Sep 2009).
Figure 6: Equivalent CO2 emissions from various sources. Updated from
original thesis with complete electricity consumption
as
S
ed
D tu
ire d
E
ct y A N lec
ly b
t
Sc F ro atu ric
op in ad ra ity
l
e an
2 ce Air Ga
T d
T s
Fa St an Ai ra
ve
u
r
cu d d
lty en D Tra l
/S t C Lo ve
ta om ss l
e
ff
Co mu s*
Pe
m ti
rs
So m ng
on
lid uti
n
al
W g
Re Mi
a
F
fr lea lee P ste
ig g
er e t V ap
an &
e er
ts Bu hic
& s T les
Ch ra
W em vel
as ic
te als
w
Fe at
rt er
ili
ze
r
Pu
rc
h
Metric Tons Equivalent CO2
49
data.
8000
7000
6000
5000
4000
3000
2000
1000
0
*Scope 2 Transportation and Distribution Losses: the emissions created while
electricity is being transported and distributed to campus.
50
Figure 7: The percentage and metric tonnes of equivalent CO2 for Scope 1, Scope
2, and Scope 3 emissions. Scope 1 is defined as those emissions direclty owned
by the college. Scope 2 is defined as those emissions that the school pays for
through a provider. Scope 3 is defined as emissions that are directly financed or
encouraged for those on campus. Updated from original thesis with complete
electricity consumption data.
Metric Tons Equivalent CO2
8000
7000
6000
5000
4000
3000
2000
1000
0
Scope 1
Scope 2
Scope 3
51
Appendices
Appendix 1: Selected Pages of the CACP Calculator
Input Worksheet:
All of these tables are in one worksheet within the calculator. They were divided
here for ease of review. Most with no data entries have been deleted to save
space.
Budget and Population Cells
Fiscal
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Budget - Click
here to enter
data
Operating
Budget
Population
Energy
Budget
Full Time
Students
$ (2005)
$ (2005)
32,809,884.76
707,226.78
34,400,025.77
759,397.84
28,862,482.54
767,289.21
29,680,990.37
781,087.34
30,192,474.76 1,215,888.61
32,519,155.72
1,318,022.02
33,010,475.90
1,160,391.89
32,856,981.61
1,199,627.87
33,045,437.00
1,264,561.78
34,031,622.93
1,411,405.49
36,964,439.45
951,669.04
38,582,878.68
1,494,624.37
#
1,188
1,129
1,098
1,118
1,044
1,035
1,083
1,141
1,193
1,279
1,278
1,300
1,307
1,345
1,357
1,358
1,344
1,326
1,283
PartTime
Studen
ts
#
15
16
9
10
9
10
14
13
16
16
7
8
16
16
9
12
10
13
15
Summer
School
Students
Faculty
Staff
#
#
#
81
83
110
85
147
103
149
103
175
102
197
106
208
99
104
116
112
114
109
112
125
224
200
210
206
214
219
216
196
111
127
126
115
87
112
129
182
185
181
165
183
147
147
52
Physical Size of Campus Facilities
Fiscal Year Total Building Space
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Total Research
Building Space
Square feet
662,033
662,033
662,033
662,033
662,033
662,033
662,033
662,033
662,033
640,124
721,224
721,224
721,224
721,224
767,424
750,924
750,924
750,924
774,924
Square feet
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
21,000
Scope 1 Sources: Natural Gas, Gasoline Fleet, Refrigerants, Fertilizer
Application.
Fiscal
Year
1990
2003
2004
2005
2006
2007
2008
Natural
Gas
University
Fleet
Refrigerants
&
Chemicals
Gasoline
Fleet
HFC-134a
MMBtu
Gallons
50,350 48,779 37,993 45,239 46,602
13,525
Pounds
4
Fertilizer
Application
HCFC-22
Synthetic
%
Nitrogen
Pounds
Pounds
%
27
8,200
26.40%
53
Scope 2 Sources: Purchased Electricity
Fiscal
Year
1990
2003
2004
2005
2006
2007
2008
Electricity
CLICK TO SET
eGRID
SUBREGION
kWh
-
13,718,036
Custom Fuel Mix Worksheet:
Fiscal Total
Year Electricity
Purchased
(kWh)
1990
2003
2004
2005
2006
2007
2008 13,718,036
Net
Natural
Purchased Gas
(%)
9.45%
Coal
Nuclear Renewable
(wind,
solar)
(%)
(%)
(%)
(%)
39.90% 33.60% 12.05% 5.00%
Total
Percentage
(%)
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
100.00%
54
Scope 3 Emissions:
Commuter Worksheet
(student section shown, Staff and Faculty sections are identical).
Fiscal Year
1990
2007
2008
Students Automobile %
%
Trips /
Fuel
Personal Carpool Week
Efficiency
Vehicle
Weeks
/ Year
Miles /
Trip
#
1,196
1,333
1,291
MPG
%
%
#
#
#
19.87
22.10
24.04
26%
6%
7.00
38
12
Directly Financed Travel and Study Abroad
Fiscal Year
Directly
Financed
Outsourced
Travel
Air Travel
Study
Abroad
Travel
Faculty /
Staff
Students
Bus
Miles
1990
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Miles
1,014,875
1,141,150
1,044,516
Miles
24,803
327,387
531,231
Personal
Mileage
Reimburse
ment
Miles
24,868
Air
Air
Miles
88,349
104,502
61,339
67,638
58,391
67,725
61,686
61,261
44,803
55,457
61,307
58,430
Miles
3,772,149
2,733,457
4,194,577
2,812,927
3,626,052
3,470,191
4,024,220
4,483,480
55
Solid waste, wastewater, and paper usage.
Fiscal
Year
Landfilled
Waste
No CH4
Recovery
Short
Tons
353
353
353
1990
2005
2006
2007
2008
Wastewater
Paper
Aerobic
Gallons
0%
Recycled
lbs
27,173,745
120,000
Total Emissions in Metric Tonnes CO2 Equivalents
The zeros in the results are what the calculator signifies for no data.
Scope 1 MT-eCO2
Scope 1
Other On-Campus
Stationary
MT eCO2
Fiscal
Year
1990
2003
2004
2005
2006
2007
2008
Direct
Transportation
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
2619
Scope 2 MT-eCO2
Scope 2
Fiscal
Year
1990
2007
2008
Purchased Electricity
MT eCO2
0
0
7105.5
0.00
0.00
0.00
0.00
0.00
0.00
120.70
Refrigerants
Agriculture
MT eCO2
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
23.18
9.02
56
Scope 3
Travel Emissions MT-eCO2
Fiscal
Year
Scope 3
Faculty / Staff
Commuting
Student
Commuting
1990
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
383.64
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
437.91
Directly
Financed Air
Travel
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
481.54
707.77
776.43
Other Directly
Financed Travel
Study Abroad
Air Travel
MT eCO2
0.00
0.00
38.37
45.19
26.79
28.95
24.73
28.89
25.94
24.74
18.09
22.39
24.76
28.01
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
1344.39
974.20
1494.94
1002.52
1292.32
1236.77
1434.23
1597.91
Solid waste, wastewater, paper usage, and Scope 2 Transmission and
Distribution Losses MT-eCO2
Fiscal
Year
1990
2005
2006
2007
2008
Solid Waste
Wastewater
Paper
Purchasing
MT eCO2
0.00
0.00
382.75
382.75
382.75
0.00
0.00
0.00
0.00
13.11
0.00
0.00
0.00
0.00
154.86
Scope 2 T&D
Losses
MT eCO2
0.00
0.00
0.00
0.00
702.7
57
Total MT-eCO2 per Scope and Total
Fiscal
Year
1990
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Total Scope 1
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2663.93
2580.81
2010.14
2393.52
2618.53
Total Scope
2
MT eCO2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
7105.5
Total Scope
3
MT eCO2
0.00
0.00
38.37
45.19
26.79
28.95
1369.12
1003.09
1520.88
1027.26
1310.41
2123.46
2549.51
4576
Total
Emissions
MT eCO2
0.00
0.00
38.37
45.19
26.79
28.95
1369.12
1003.09
1520.88
3691.19
3891.23
4133.61
4943.03
14300
58
Appendix 2: Inventory Report to PCC and AASHE
Summary Statistics
Total
Per Full-Time
Per 1000
%
Annual
Enrollment
ft
2
Offset
MT-eCO2
MT-eCO2
MT-eCO2
9725
7.6
12.5
0%
14,302
11.1
18.5
0%
14,302
11.1
18.5
0%
Gross emissions (Scopes 1
+ 2)
Gross emissions (Scopes 1
+ 2 + 3)
Net emissions
Emissions Inventory Methodology and Boundaries
Start date of the 12-month period covered in this
July 1, 2007
report
Consolidation methodology used to determine
Operational Control
organizational boundaries
Approach
If any institution-owned, leased, or operated buildings or other holdings that
should fall within the organizational boundaries are omitted, briefly explain why.
The college rents a few small houses that are remote from campus. The college
does not pay the utilities for those houses. Those houses are not included in this
report. Other college-owned houses that are residences of administrators are
59
included in this report. All 14 campus electricity accounts are included in this
report, plus the electricity consumption for the house at the McCarley Reserve
and the Pavilion at the Sneed Prairie Restoration.
Emissions calculation tool used
Clean Air-Cool Planet v. 6.1
Please describe why this tool was selected.
This was the suggested calculator and because it is widely used it facilitates
comparision with other campuses. We used version 6.1
Please describe the source(s) of the emissions coefficients used.
Default coefficients were used with the following exceptions. We changed the
Radiation Forcing Index from 2.8 to 2 because various IPCC reports have used
different values and our local expert, Dr. David Baker, does not think the relevant
science warrants specifying this value to two significant figures. We corrected the
CO2 emissions of study abroad flights by a factor of 0.64 to reflect their longer
distances and thus better per mile fuel efficiency than the shorter domestic flights
that the calculator assumes. We used actual community data for communiting
distances, vehicles used, and carpooling based on a detailed survey.
Which version of IPCC's list of global warming
Third Assessment Report
potentials did you use?
Senior Honors Student Jade
Who primarily conducted this emissions inventory?
Rutledge
60
Please describe the process of conducting the inventory.
The inventory was completed by Senior Honors Thesis student Jade Rutledge
(Austin College 2009) under the direction of her thesis committee [Peter Schulze
(chair), David Baker, and Todd Penner]. Peter Schulze is Director of the College's
environmental studies program and Professor of Biology and Environmental
Science. David Baker is a member of the environmental studies program and
Associate Professor of Physics.
Please describe any emissions sources that were classified as de minimis and
explain how a determination of the significance of these emissions was made.
The results of the inventory show that personal mileage, bus travel, refrigerants
and chemicals, wastewater, and fertilizer each compose less than 0.5% of the
colleges GHG emissions, but they were not assumed to be de minimis in the
present analysis. The present analysis is based on data collected for each of these
variables.
Please describe any data limitations related to this submission and any major
assumptions made in response to these limitations.
Commuter gasoline calculations are based on a detailed and extensive survey of
the campus population. We assume the survey respondents were representative.
Solid waste calculations are based upon average waste generated rather than
direct measurements. Air travel records had missing destination data for 17% of
61
flights. We assumed these flights had the same distances as the average of the
other 83% of flights. Fleet vehicle calculations are based upon averages of
mileages on vehicles.
Emissions Data
Emissions from the following sources (in metric tons of CO2 equivalent (CO2e))
Scope 1 Emissions
Stationary Combustion
2,466 MT-eCO2
Mobile Combustion
121 MT-eCO2
Process Emissions
0 MT-eCO2
Fugitive Emissions
32 MT-eCO2
Total Scope 1 emissions
2,619 MT-eCO2
Scope 2 Emissions
Purchased Electricity
7,106 MT-eCO2
Purchased Heating
0 MT-eCO2
Purchased Cooling
0 MT-eCO2
62
Purchased Steam
0 MT-eCO2
Total Scope 2 emissions
7,106 MT-eCO2
Scope 3 Emissions
Commuting
822 MT-eCO2
Air Travel
2,501 MT-eCO2
Solid Waste
383 MT-eCO2
Wastewater
13 MT-eCO2
Paper Purchasing
155 MT-eCO2
Scope 2 T & D losses
703 MT-eCO2
Total Scope 3 emissions
4,577 MT-eCO2
Biogenic Emissions
Biogenic Emissions from Stationary Combustion
Biogenic Emissions from Mobile Combustion
Mitigation Data
NA.
NA.
63
Carbon Offsets
Carbon offsets purchased
0 MT-eCO2
Offset verification program(s)
Not Applicable.
Description of offsets purchased (including vendor, project source, etc.)
Not Applicable.
Renewable Energy Certificates (RECs)
Total RECs purchased
0 kWh
Percent of total electricity consumption mitigated through the
0%
purchase of RECs
Emissions reductions due to the purchase of RECs
0 MT-eCO2
REC verification program(s)
Not Applicable.
Description of RECs purchased (including vendor, project source, etc.)
Not Applicable.
Sequestration and Carbon Storage
Sequestration due to land owned by the institution
Description of how sequestration was calculated
0 MT-eCO2
64
No sequestration assumed. We own some land on which ecosystems are
recovering but we have not attempted to estimate a quantity of carbon dioxide
sequestration.
Carbon storage due to composting
0 MT-eCO2
Normalization and Contextual Data
Building Space
Gross square feet of building space
774,924 sq ft.
Net assignable square feet of laboratory space
21,000 sq ft.
Net assignable square feet of health care space
0 sq. ft.
Net assignable square feet of residential space
246,260 sq ft.
Population
Total Student Enrollment (FTE)
1,283
Residential Students
822
Full-time Commuter Students
417
Part-time Commuter Students
15
Non-Credit Students
Not applicable.
Full-time Faculty
94
Part-time Faculty
15
65
Full-time Staff
193
Part-time Staff
20
Other Contextual Data
Endowment Size
$140,822,803
Heating Degree Days
1890
Cooling Degree Days
2779
Please describe any circumstances specific to your institution that provide context
for understanding your greenhouse gas emissions this year.
Not Applicable.
66
Appendix 3: Commuting Survey
Survey used for this analysis
1. Are you a student, staff, or faculty member?
2. Do you live on or off campus?
3. Do you drive to campus on a regular basis? (Commuting from home before a
semester or during breaks does not count.)
4. What is the year, make, and model of the vehicle that you most often drive
to campus?
5. How many miles one-way is your commute to campus? If you don’t know
this number, then you can use Mapquest (http://www.mapquest.com/) to
find the distance from your home address to campus.
6. Approximately how many round trips do you make per week?
7. Do you commute during:
a. Fall and Spring semesters only
b. All year round, except during school breaks
c. All year round, even during school breaks
8. Do you regularly carpool to campus? If you live with another Austin
College member and you usually drive together, this is considered
carpooling.
67
Recommended Future Survey
1. Are you a student, staff, or faculty member?
2. If a student, are you full or part time?
3. If an employee, are you employed full time or part time?
4. Do you live on or off campus?
5. Do you drive to campus on a regular basis? (not counting commuting to
and from home before a semester or during break).
6. What is the year, make, and model of the vehicle that you most often
drive to campus?
7. How many miles one-way is your commute to campus? If you don’t
know this number, then you can use Mapquest
(http://www.mapquest.com/) to find the distance from your home
address to campus.
8. Approximately how many round trips do you make per week?
9. Approximately how many weeks per year do you drive to campus?
10. Do you regularly carpool to campus? If you live with another Austin
College member and you usually drive together, this is considered
carpooling.
11. If you answered yes to the carpool question, do you drive a personal
vehicle or are you a passenger in someone else’s vehicle?
68
Appendix 4: Individuals Who Provided Data, Austin College
employees unless otherwise noted.
Administrative Assistant for Athletics
Sandra Miller
Administrative Assistant to Vice President
for Business Affairs
Assistant Director of Finance
Shauna Redman
Assistant Director of Study Abroad
Valerie Roberts
Associate Director of Physical Plant
David Merriman
Benefits Representative
Gail Lewis
Director of Human Resources
Keith Larey
Director of Physical Plant
John Jennings
Office Manager of Physical Plant
Linda Welch
Purchasing Representative
Jeannean Smith
Secretary of Academic Affairs
Mary Buick
Solid Waste Supervisor for the City of
Sherman
Vice President for Academic Affairs and
Dean of Faculty
Vice President of Student Affairs
Michael Springer
Ellen Miles
Michael Imhoff
Tim Millerick
69
Appendix 5: Notes for the future users of the CACP GHG
calculator at Austin College
The calculator can be found on the Clean Air Cool Planet website
(http://www.cleanair-coolplanet.org/toolkit/inv-calculator.php). The website
should be checked often for new versions of the calculator. The user must
download the calculator from the website and open it using Excel. The download
includes a User Guide. The calculator has the ability to go back to year 1990, but
only available years need be entered. Cells that are tinted green are meant to have
a number entered into them and cells that are white signify that the information
needs to be entered separately in another worksheet. The calculations are made
automatically once data is entered. The results are stored in spreadsheets
incorporated in the calculator file. The inventory can be updated every year or
every two years, but the inventory report must be updated on the PCC website
every two years.
Operating Budget: The monetary amount is found within the minutes from the
College’s annual board meeting. In years 1996 to 2001, meetings were held in
March, but in years 2002 to 2008 the board meetings were in late May or early
June. To enter the data into the spreadsheet, a blue underlined link labeled
“budget” in the input sheet was opened to expose a linked worksheet that corrects
for inflation. The monetary figures per year were entered in the appropriate year
under column C.
70
Energy Budget: This is the actual amount spent for electricity and natural gas
purchases, from the expenditure records, not the planned budget. The two
monetary amounts were added together and the figures were inserted into the
budget inflation worksheet accessed through the blue link above columns D-F in
the input sheet. Within the separate worksheet, the budget should be entered in
column E for the appropriate year.
Population of Students, Faculty, and Staff: This information was entered in the
input worksheet in columns G-K.
Total Building Space: The total square footage for all buildings was provided
and entered for fiscal year 2008. To get historical information, the square footage
of buildings that have been built or destroyed since 1990 were either added to or
subtracted from total square footage. These totals were added in the input
worksheet in column L.
Research Square Footage: The square feet were inserted in the input worksheet
in column M.
71
Natural Gas: These data are kept in spreadsheet form monthly by the physical
plant in units of MMBtu. This information can be directly entered into the column
AF in the input worksheet.
Fleet Vehicles Gasoline: This section includes information about physical plant,
police, and biology department vans, which use gasoline purchased from an
outside vendor. It also includes the fleet of cars various departments use which
purchase gas at commercial stations. To get information on the physical plant and
police vehicles, the gallons of gasoline the physical plant purchases annually was
collected. For the biology gasoline, a logbook containing all gasoline purchase
was used to obtain a total amount of gasoline use for the biology vehicles for
fiscal year 2008.
Gasoline consumption of staff vehicles was estimated from vehicle
mileage. The Purchasing Representative was able to produce a spreadsheet that
included a list of fleet vehicles with purchase date, starting mileage, and mileage
as of January 2009 for each. I calculated each vehicle’s average mileage per year.
The Benefits Representative provided me with the personal mileage for each
vehicle. I subtracted annual personal miles from the average annual miles to
calculate business mileage. All cars are Ford Tauruses and the EPA website had
an average of city and highway driving of at 20 mpg for this make and model
(www.fueleconomy.gov). The new averages were used and these were
highlighted in yellow. I used the mileage and mpg information to estimate
72
gasoline consumption for each car. This consumption was added to the
consumption of the other fleet vehicles (police, physical plant, and biology) to
arrive at the total fuel quantity used in fiscal year 2008. This amount was entered
into column AP in the input worksheet.
Refrigerants: The three types of refrigerants Austin College used were R-22, R404a, and R-134a. These were entered in pounds under the columns in the input
worksheet of the calendar under the headings HFC-22, HFC-404a, and HFC-134a
(columns AZ and BB). HFC-404a had no leakages in fiscal year 2008 so that
column was left blank.
Fertilizers: Austin College used three different types of fertilizers in fiscal year
2008. The amount of fertilizer was provided in pounds, as well as the percentage
of nitrogen in each fertilizer type. Since three types of fertilizer are used with
different percentages of nitrogen for each, a weighted average was taken to
acquire the percent nitrogen. This percentage was entered into column BG.
Pounds for all three types of fertilizer were added together and entered in the
input worksheet in column BF.
Purchased Electricity: The total kilowatt hours was entered into column BR in
the input worksheet. To select a custom fuel mix, a worksheet accessed through a
blue link in column BR in the input sheet, must be opened. At the bottom of this
73
worksheet, a box must be checked that selects “use custom fuel mix”. The custom
fuel mix worksheet must be opened, which is a green tab next to the input tab, and
the fuel mix in percentages is entered under the appropriate year row and fuel
column. The fuel mix for fiscal year 2008 was natural gas (38%), coal (32%),
nuclear (11%), renewable (10%), and other (9%).
Commuting: The data were collected through an online survey of students, staff,
and faculty. Within the input worksheet, there is a blue link in column BW that
must be opened to enter data on commuting. Within this worksheet, the calculator
requires information on student, faculty, and staff commuting separately. The
information concerning commuting are average miles per gallon (mpg) of
vehicles used for commuting, the percent that commute in a personal vehicle, the
percent of those that drive in a personal vehicle carpool with at least one other
person, trips per week, weeks per year, and miles per trip.
This information was retrieved through a survey I created that was
distributed through SurveyMonkey (www.surveymonkey.com). This survey was
emailed to students, faculty, and staff through the Dean of Faculty, the Vice
President for Student Affairs, and the Director of Human Resources. To estimate
average automobile fuel efficiency, I asked each survey participant to provide the
year, make, and model of the car they drive to campus. Each car was found on the
EPA’s Fuel Economy website (www.fueleconomy.gov) and the average mpg of
city and highway driving for the particular vehicle was recorded. Once all mpg
74
were recorded, an average of the community’s mpg was taken and entered into
column D for students, AS for faculty, and BY for staff. For the percentage of
individuals that drive a personal vehicle, the percentage of total respondents that
drove to school on a regular basis was used, including carpooling individuals.
This was entered in the separate worksheet into column E for students, AT for
faculty and BZ for staff. For percent that carpool to school on a regular basis, the
respondents that answered that they carpooled were taken as a percent of the total
respondents to the survey. This information was entered in the separate commuter
worksheet into column F for students, AU for faculty, and CA for staff.
All responses regarding trips per week were averaged and entered in the
separate worksheet under the column G for students, AV for faculty, and CB for
staff. The calculator also requires the average number of weeks driven per year.
This figure was estimated based on a question in the survey asking participants to
explain what increments of the year they drove to school on a regular basis. The
options were: fall and spring semesters only, all year round except for school
breaks, and all year round even during school breaks. The weeks per response
type were determined based on the college’s academic calendar. For fall and
spring semester only answers, 30 weeks were estimated. For all year, except
school breaks answers, 40 weeks were estimated. For all year, even during school
breaks, 50 weeks were estimated. The weeks driven were averaged and the
information was entered in the separate commuter worksheet under column H for
students, AW for faculty, CC for staff.
75
Lastly, the survey participants were asked to enter the miles from their
residence to school as estimated by Mapquest (www.mapquest.com). Mapquest
was found to be the most accurate estimate of mileage when compared to
GoogleMaps. The miles per trip from all participants that drive regularly were
averaged and the number was entered in the separate commuter worksheet under
the column I for students, AX for faculty, and CD for staff.
Air travel: This section is split into faculty/staff miles and student miles. The
document produced from budget records contained information on individual
flights, such as the number of passengers from Austin College on each flight,
destination, and the date. This information existed for most entries, but 17% of
budget entries were missing crucial information about the location of the flight
and could not be included. In some entries it was not clear if the item was a
flight at all. Thus, all entries that were missing destinations information
necessary were estimated to average the same distance as the flights with
destinations. The directly financed air travel was adjusted to be increased by
17% to reflect these flights.
From this document, an Excel spreadsheet was created containing columns
for number flying, destination, and distance traveled. An internet offsetting tool,
the carbon footprint calculator of Terrapass, was used to calculate the distance for
each trip (Carbon footprint calculator, http://www.terrapass.com/carbon-footprintcalculator/#air). In the ‘from’ section, Dallas/Ft. Worth International Airport
76
(DFW) was always used. The ‘to’ section was changed according to the specific
location of each flight. The city name or airport code can be used in this section
and both are used interchangeably in the budget.
A separate Excel spreadsheet was created as a reference for destination
distances already calculated. One section contained international cities and
another section contained U.S. cities. For each location calculated with the carbon
footprint calculator, the distance from DFW to the particular city was recorded in
this sheet so the distance would not need to be looked up more than once for each
city. All distances are per round trip. This mileage was then summed for the entire
fiscal year.
Athletic team air travel information provided by the Administrative
Assistant for Athletics included the flight dates, the arrival and departure cities,
and the number of staff and students who traveled. I used the same method of
calculating distance as for the other flights. For each flight, student miles were
totaled and staff miles were totaled. The staff miles were added with the total
flights per year from budget records into column CC in the input worksheet. The
student total miles per year were added into column CD in the input worksheet.
Mileage Reimbursements for Automobile Travel: To calculate total distance,
each monetary sum spent annually on mileage reimbursement from personally
owned vehicles was divided by the IRS standard mileage (appendix 6). These
77
rates are in cents per mile and change each year. This figure was added into
column CI in the input worksheet.
Study Abroad Travel: For each year of January term, an Excel spreadsheet
provided by the Secretary of Academic Affairs provided spreadsheets with travel
locations and the number of professors and students on each trip. A summary
document was created that included the number of students and faculty traveling,
the destination city, and the distance of each round trip flight. Again, the
Terrapass website was used to calculate all distances that had not already been
calculated and put in the reference sheet for distance. In the last column of the
spreadsheet, the number attending multiplied by distance was calculated. For the
January trip to Ghost Ranch in New Mexico, the assumption was made that half
the students on the trip flew and half the students drove in personal vehicles. If the
destination city is not specified in the January term spreadsheet, the capital city of
a country was assumed.
An Excel spreadsheet was provided by the Assistant Director of Study
Abroad for semester and year long study abroad. This document contained the
name of the student who went abroad and the city or country destination. Again, a
summary spreadsheet was created that included destination and distance per trip.
Distances were summed and added to the corresponding years January term total
miles. This total for study abroad travel miles per year was then added to column
CJ in the calculator.
78
Solid Waste: To obtain waste information from the city, a member of the
Physical Plant contacted the City to authorize distribution of data to a student. The
information provided included the size and number of trash receptacles, the
schedule of trash collection, and the year when the collection for each receptacle
was started. This information was used to calculate approximate weight of solid
waste the school creates per year. This number had to be estimated since the trash
is not weighed during the process of being collected and disposed. Average
campus waste is 22.22 cubic yards per ton (CURC Campus Refuse Profile, 1997).
Cubic yards per year for each receptacle were calculated and each of those figures
was divided by 22.22 cubic yards per ton to estimate the number of tons per year
for each container.
All weights were calculated assuming that the containers were full 100%
of the time. The weight of solid waste at 90% and 80% capacity were also
calculated to perform a sensitivity test to determine the total emissions changes
with these differences in fullness (Table 4). The trash receptacles were estimated
to be about 95% full at the time of collection, except for the two 8 cubic yard
receptacles at the physical plant, which don’t always get picked up on time and
may be overflowing when emptied. It was also estimated that the campus rolloff
trash receptacle is picked up approximately once a month (personal
communication David Merriman, Assistant Director of Physical Plant, November
18, 2008).
79
The city of Sherman uses the Texoma Area Solid Waste Authority, Inc.
(TASWA) landfill. The solid waste tonnages were entered in column CM.
Wastewater: The physical plant keeps total gallons of wastewater the school
generates and that number was put into column CQ in the input worksheet.
Paper: The calculator includes the amount of office paper used on campus and its
recycled content. The school uses uncoated printer paper that has 0% recycled
content. The school used 600 cases of paper during fiscal year 2008 and each case
has 10 reams. Each ream weighs 20 pounds, which is printed on the paper
packaging. The weight of paper per year was calculated and entered into column
CT in the input sheet.
80
Appendix 6: Fleet Vehicle Raw Data for Staff Cars and
Calculations
Raw Data for Fleet Vehicle Information:
Bought
01-02
03-03
02-04
02-04
05-05
05-05
05-05
01-06
02-06
03-07
03-07
03-07
03-08
03-08
03-08
03-08
Mileage
(01/09)
63352
71130
110902
66038
80121
64508
67665
43500
38032
35000
27000
64351
37803
29780
35543
37429
Mileage
(Beginning)
208
8539
8262
8191
10313
10716
10491
9137
5795
12
8
8950
24212
24069
23869
23399
81
Calculations for Fleet Vehicle Data:
mileage since
purchase
years
63144
62591
102640
57847
69808
53792
57174
34363
32237
34988
26992
55401
13591
5711
11674
14030
avg. miles per
year
8
6
5
5
4
4
4
3
3
2
2
2
1
1
1
1
7893
10431.83
20528
11569.4
17452
13448
14293.5
11454.33
10745.66
17494
13496
27700.5
13591
5711
11674
14030
personal miles Business
Gallons per
for 2008
Miles
year
0
7893
394.65
2913
7518.83
375.94
15549
4979
248.95
0
11569.4
578.47
5125
12327
616.35
5380
8068
403.4
1400
12893.5
644.675
850
10604.33
530.216
4729.14
6016.52
300.82
3330
14164
708.2
1500
11996
599.8
6500
21200.5
1060.025
500
13091
654.55
986
4725
236.25
2500
9174
458.7
2362
11668
583.4
82
Appendix 7: Raw Data of Survey Respondents for Commuting
Raw Data of Student Survey Respondents that live off campus and commute.
Year, Make, and Model
2007 Honda Fit
1998 Cheverlet Monte Carlo
2005 Toyota Corolla
1995 Nissan Sentra
Volvo S40
2004 Toyota Yaris
2003 Mitsubishi Outlander
Lexus IS250 2008
1996 chevrolet camaro
2004 Ford F-150 Heritage
2006 Chevy Cobalt
1992 Chevrolet 1500 Pickup
Saturn Vue 2004
2000 Toyota Camry
2002 Honda Civic
Freelander by Land Rover
2003
2004 Dodge Neon
2004 Toyota Solara
1998 Mazda Protege
2002 Chevrolet Monte Carlo
1994 Toyota Camry
Toyota Tacoma 2006
04 Toyota Corolla
2002 Oldsmobile Alero
2005 Ford Focus
1996, Ford, Explorer
2004 Scion xA
Kia Spectre.
2007 Honda Civic
1998 Honda Passport
08 Ford Edge
99 Mazda Millenia
Volkswagen Jetta 99
2005 Ford Escape
2003 Chevrolet Tracker
2002 Honda Accord
2001 Dodge Neon
1998 Mitsubishi eclipse
1997 Chevy Lumina
MPG
Miles
31
21.5
30.5
27
22.5
32
21
22
21.5
16
23.5
17
22
23
32
3.5
3.13
5
5
1
0.2
11
6
15
4
1
1.5
10
2
7
17
25.5
27
26
24
22
21
29.5
25.5
25.5
17
30.5
24.5
30.5
17
20
21
38.5
21
22
23
24
20
21
60
60
63
1
3.12
36.8
5
40
5.22
20
1
0.25
17
14.6
9
4.3
5
0.3
5
7
1
3
10
0.77
trips/week weeks/year
5
50
9
50
7
50
10
50
4
50
8
50
9
50
4
50
5
50
20
50
5
50
25
50
5
50
10
50
13
50
3
1
1
8
4
5
6
5
8
5
20
5
5
9
6
8
0
9
3
6
15
8
5
5
50
50
50
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
Carpool
No
No
No
No
Yes
No
No
No
No
Yes
No
No
No
Yes
No
No
No
No
Yes
No
Yes
No
No
No
No
Yes
Yes
No
No
No
Yes
No
No
No
No
Yes
No
No
No
83
1993 toyota corolla
2006 Nissan Sentra
24
27.5
honda accord 2000
2002 Ford Escort
2006 Volkswagen Jetta
1998 F150
99 Honda Accord
2008 Honda Civic
2005, Nissan Sentra
2000 Chevy impala
94 buick roadmaster
1994 Acura Integra
2004 yellow MiniCooper
2004 Toyota 4runner
2003, honda, crv
2006
24
26
33.5
16
23.5
42.5
27.5
23
19
25
30
18
23
23.5
Ford f150
1998 Buick Century
2003 VW Beetle
2003 ford taurus
1997 Chevrolet Lumina
scion xa 2005
2001 Saturn
2007, toyota, corolla
2003 BMW 325i
2008 Mazda 3
2007 Chrysler PT Cruiser
16
22
23
21
21
30
24
29
20.5
28
19
99 ford explorer
2003 Volkswagon Beetle
Averages:
16.5
23
24.03676
1.5
40
60
0.2
0.75
0.5
0.5
3
5
20
0.6
70
2.51
4
1
1.32
2.5
1
13
1.3
3
2
4.6
0.5
3
55
52
40
2.3
0.73
2
0.5
11.85915
8
40
3
40
1
40
5
20
7
30
6
30
20
30
5
30
14
30
5
30
8
30
5
30
13
30
7
30
15
30
4
30
7
30
3
30
1
30
7
30
7
30
10
30
9
30
6
30
8
30
2
30
1
30
1
30
7
40
10
40
4
30
8
15
7 38.38028169
Yes
No
Yes
No
No
Yes
No
No
No
No
Yes
No
No
No
Yes
Yes
Yes
Yes
No
No
No
No
No
No
No
No
No
No
No
No
Yes
84
Raw Data for Faculty who Commute to Campus
Car
1999 Honda CRV
2008 honda civic
2008 Nissan Sentra
2006, Honda, Civic -- 38 mpg
1999 Dodge Dakota
2008 Honda CRV
1997 Honda Civic
Honda Civic Hybrid 2004
2007 Hyundai Accent
09 Hyundai Sonata
Toyota Camry 2005
Toyota Prius, 2007
1998 Honda Civic
Toyota Corolla 2007
Ford Fusion 2007
2004 Mazda 3i
1998 Ford Explorer Sport
Subaru Outback 2004
2003 Ford Taurus
2009 Toyota Prius
2004 Saturn Ion
1995 plymouth neon
2005 Mazda
2003 Ford F150 Pickup truck
2007 Toyota Corolla
1991 Jeep Wrangler
2002 chevy van
2006 Ford F150
2007 Toyota Prius
2005 Mazda 3
2000 Nissan Xterra
2002 Honda Civic
2006 Pontiac Grand Am
1997 Ford Crown Victoria
1998 nissan altima
miles/gallon
21.5
42.5
29
38
19.5
23.5
32
32.5
30.5
24
24.5
46.5
29
30.5
24.5
27
16.5
22
22
46.5
23
26.5
19.5
16.5
30.5
17
30
16
46
28
19.5
33
21.5
19
24
Miles Trips/Week Weeks/Year
25
5
36
3
7
45
45
4
40
35
5
30
50
5
30
20
6
30
0.5
30
35
4
30
9.3
5
30
5
7
30
4
6
30
4
5
45
40
4
40
35
5
40
35
3
40
5
5
40
9.5
5
40
1.5
6
40
4
6
40
37
5
40
4
5
40
2.5
5
40
5
5
40
25
11
40
9
5
40
0.5
5
40
4
5
40
20
5
40
10
5
40
4.3
5
40
10
5
50
43.5
5
50
40
5
50
1
15
50
2
6
50
2.35
6
50
Carpool?
No
No
No
Yes
No
No
No
No
No
No
No
No
Yes
Yes
Yes
Yes
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
Yes
Yes
No
No
No
85
2003 Pontiac Sunfire
1999 Ford Ranger
Toyota Corolla 2003
Saturn SL 2001
2005 Buick Lacrosse
2007 ford fusion
99 Honda Civic DX 38 mpg
2007 ford escape
1992 Honda civic dl
2000 Toyota Camry
2003 Chevy Pickup
1997 Toyota Corrola
Averages:
25.5
17.5
29.5
29
21
24.5
38
22
29
23
19
24.5
27
15
3.8
1.5
5
3
1.8
24
5
2.5
3.5
22
3.8
14
5
5
5
6
10
5
8
6
6
9
5
5
6
50
50
50
50
50
50
50
50
50
50
40
48
42
No
No
No
No
No
No
No
No
No
No
No
No
86
Raw Data for Staff who Commute to Campus
Year, Make, and Model
1969 Volkswagen Beetle
2005 Chevy Impala
2001 Honda Accord
2005 Honda Accord
2007 Honda civic
Volkswagon golf
Honda CRV 1998
2007 Chevrolet Equinox
1996, ford, taurus
Ford Explorer 2005
2000 Ford F-150 XLT
2000 Honda Accord
2005 Chrysler Town & Country
2008 Toyota RAV4
04 CHev Tahoe
2007 Honda Accord
2000 Mitsubishi Galant
2005 Honda Pilot
Honda Odssey 2000
1998 Dodge Dakota Pick-up
truck
2005 Ford Taurus
2003 Ford Focus
1990 BMW 525i
2000 Chevrolet Impala
camry xle, 1995
1991 Toyota Camry
2002 Ford Taurus
1996 Pontiac Grand Am
2008 Chevrolet HHR
2001 Hyundai Sonata
96 chevy silverado
2005 Ford Expedition
2000 Plymouht Neon
2004 Toyota Accord
2003 ford mustang
2003 Ford Expedition
MPG
Miles
23
24
23
24
30.5
35.5
21
20
21
16
16
23
19
24
15
26
22.5
17.5
19.5
25
4.36
3
45
45
5.56
8
3.06
3
29.5
10
2
15
35
3
6
30
6
8
20.5
21.5
27
19
21
21
24
21
23
25
21
16
14
24
24
20
14
12
3
10.5
3
3
4
1.4
17
2.7
76
10
6
17
35
26
12
1.75
Days/Week Weeks/Year Carpool
5
50 No
10
50 No
5
35 Yes
5
40 No
4
30 No
5
30 No
5
30 No
6
30 No
5
50 No
5
37 Yes
6
50 No
5
40 Yes
3
40 Yes
3
40 Yes
5
40 Yes
40 No
5
40 No
5
40 No
5
40 No
5
6
5
5
5
10
7
10
8
5
5
7
5
6
6
5
5
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
40
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
87
2004 Ford Taurus
2006 Honda Civic
2009 Toyota Camry
2005 SUV
2004 Honda Odyssey (Van)
2007 Toyota FJ Cruiser
2009 lifan 250 M/C
2002 Ford Thunderbird
06 Ford Edge
2007 Ford Edge
2007 Hyundai Sonata
2007 Chevrolet Impala LTZ
2002 Dogde Caravan
Toyota Camry, 1998.
2003 Lincoln Navigator
2003 Toyota Camry
2004 Volvo V70 2.4T
2000 Buick LaSabre
2007 hyundai santa fe
2000 Taurus
Ford Taurus
2005 Toyota Camry
2004 Nissan XTerra
2002 Chevrolet Trailblazer
2000 Chevy Impala
2003 Chevrolet Trail Blazer
2002 NISSAN FRONTIER
PICKUP
2007 Ford Taurus
Chevrolet, Tahoe, 2003
2007 Honda CRV
99 dodge 1500 pickup
2006 Ford Taurus
2000 Grand Marquis
2002 Toyota Camry
03 Toyota
1999 Toyota truck
2006 Toyota Camry XLE
2007 Buick, Ranier
20
30
23
21
19.5
19
90
18.5
22
19.5
25.5
23
20
24
13
25
23
22
21
21.5
21.5
24.5
19
16
21
16
1.7
55
23
10
12
28
1
2.5
3
6
15
14
1
2
3
2.5
30
3.23
6
4
5
5
6
10
2
15
8
5
3
10
4
6
4
5
5
5
5
5
5
20
5
10
5
10
5
7
5
8
6
6
5
6
40
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
No
Yes
Yes
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
19
20
14
23
15
20
18
24
24
20
24
16
12
2.8
5
18
22
3.5
2
20
9
6.11
5
6
10
5
7
5
5
5
20
6
6
5
5
10
50
50
50
50
50
50
50
50
50
50
50
50
No
No
No
No
No
No
No
No
No
No
No
No
88
2008 Hundai Accent
1997 Acura CL
2007, Ford Taurus
1994 Mitsubishi Montero
2007, Toyota, Matrix
2008 Ford Escape
2004 Honda Accord
2005 Chevy Silverado
Averages:
28
22
20
15
27
22
26
17.5
22
29
3
20
4.52
5
18
10
2.75
1
12
6
5
5
8
5
5
5
7
5
6
50
50
50
50
50
50
50
50
50
45
No
No
No
No
No
No
No
No
No
89
Appendix 8: Summary Spreadsheet and Calculations of Flight
Data for fiscal year 2008
#
attending
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Location
Vienna
Germany
London
India
San Antonio
Boston
Austin
Portland, Oregon
Greensboro, NC
Austin
Washington, DC
Memphis, TN
Washington, DC
Washington, DC
San Antonio
Houston
San Antonio
Austin
Greenville, SC
New Orleans
Houston
Lubbock
Spain
NYC
New Orleans
Houston
Houston
Memphis, TN
Chicago
South Padre
Portland, TX
Memphis, TN
Chicago
China
Seattle
Phoenix
Oregon
Washington, DC
Austin
Miles
10,997
10,638
9,473
18,706
494
3,116
380
3,225
1,993
380
2,379
861
2,379
2,379
494
449
494
380
1,720
895
449
562
10,361
2,771
895
449
449
861
1,594
966
710
861
1594
16,210
3,313
1,730
3,225
2,379
380
# attending times miles
10997
10638
9473
18706
988
3116
380
3225
1993
380
2379
861
2379
2379
494
449
494
380
1720
895
449
562
10361
5542
895
449
449
861
1594
966
710
861
1594
16210
3313
1730
3225
2379
380
90
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
New Orleans
Washington, DC
Uruguay
Memphis, TN
Chicago
Calgary, Canada
Salt Lake City
Nova Scotia
Kansas City, MO
Minneapolis, MN
Albuquerque
Washington, DC
Albuquerque
NYC
Canada
London
California
Boston
London
Austin
Washington, DC
St. Louis
Washington, DC
El Paso
Washington, DC
Austin
Houston
Washington, DC
Missouri
Little Rock
Lubbock
Lubbock
Austin
Washington, DC
San Antonio
California
Canada
San Antonio
New Orleans
Atlanta
San Diego
Portland, TX
Chicago
San Diego
Honolulu
Boston
895
2,379
10,756
861
1,594
3,044
1,973
3,929
921
1,705
1,134
2,379
1,134
2,771
3,044
9,473
2,462
3,116
9,473
380
2,379
1,101
2,379
1,099
2,379
380
449
2,379
921
608
562
562
380
2,379
494
2,462
3,044
494
895
1,459
2,335
710
1,594
2,335
7,551
3,116
895
2379
10756
861
1594
3044
1973
3929
921
1705
1134
2379
1134
2771
3044
9473
2462
3116
9473
380
2379
1101
2379
1099
2379
380
449
2379
921
608
562
562
380
2379
494
2462
3044
494
895
1459
2335
710
1594
2335
7551
3116
91
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
El Paso
New Orleans
NYC
San Diego
Taiwan
New Orleans
Nashville
Austin
Ft. Myers, FL
Austin
Atlanta
NYC
Baltimore, MD
Austin
NYC
N/S Carolina
Oxford, UK
NYC
Washington, DC
Galveston
Orlando
Washington, DC
Boston
Galveston
Galveston
NYC
Kalamazoo, MI
Houston
Houston
Chicago
Houston
Houston
Austin
Boston
California
Austin
Austin
Chicago
Boston
Corpus Christi
New Orleans
Washington, DC
Austin
Harlingen
Austin
Ft. Myers, FL
1,099
895
2,771
2,335
15,400
895
1,260
380
2,030
380
1,459
2,771
2,428
380
2,771
1,993
9,473
2,771
2,379
449
1,957
2,379
3,116
449
449
2,771
1,798
449
449
1,594
449
449
380
3,116
2,335
380
380
1,594
3,116
710
895
2,379
380
924
380
2,030
1099
895
2771
2335
15400
895
1260
380
2030
380
1459
2771
2428
380
2771
1993
9473
2771
2379
449
1957
2379
3116
449
449
2771
1798
449
449
1594
449
449
380
3116
2335
380
380
1594
3116
710
895
2379
380
924
380
2030
92
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
Washington, DC
Las Vegas
Louisville, KY
El Paso
New Orleans
Burbank, CA
Portland, Oregon
Washington, DC
Albany
Oklahoma
New Orleans
Boston
Austin
El Paso
Denver
Little Rock
Chicago
Chicago
Houston
Houston
Boston
San Antonio
Houston
Austin
Tucson, AZ
Washington, DC
Maryland
San Antonio
Austin
St. Louis
NYC
Austin
Kansas City, MO
Los Angeles
Las Vegas
New Mexico
Atlanta
Washington, DC
Houston
Fredericton,
Canada
Providence, RI
Lubbock
Little Rock
San Francisco
Las Vegas
2,379
2,105
1,463
1,099
895
2,455
3,225
2,379
2,863
351
895
3,116
380
1,099
1,281
608
1,594
1,594
449
449
3,116
494
449
380
1,621
2,379
2,428
494
380
1,101
2,771
380
920
2,462
2,105
1,098
1,459
2,379
449
2379
2105
1463
1099
895
2455
3225
4758
2863
351
895
3116
380
1099
1281
608
1594
1594
449
449
3116
494
449
380
1621
2379
2428
494
380
1101
2771
380
1840
2462
2105
1098
1459
2379
449
3,684
3,051
562
608
2,920
2,105
3684
3051
562
608
2920
2105
93
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
2
2
1
1
1
1
1
1
1
1
1
California
Africa
Washington, DC
Boston
Chicago
San Antonio
Washington, DC
Atlanta
San Diego
Boston
Washington, DC
Baltimore, MD
Midland
Baltimore, MD
Chicago
Tucson, AZ
South Carolina
Germany
Boston
Paris
Nice, France
Chicago
Rochester, NY
Indianapolis
Pakistan
Peru
Newark, NY
Buenoes Aires
Baltimore, MD
Peru
Orlando, FL
St. Louis
Greensboro, NC
Vancouver
Austin
Washington, DC
New Orleans
Philadelphia
Washington, DC
Cincinnati
Pittsburgh
Pittsburgh
Seattle
Denver
Orlando
Baton Rouge
2,920
16,665
2,379
3,116
1,594
494
2,379
1,459
2,335
3,116
2,379
2,428
616
2,428
1,594
1,621
1,720
10,638
3116
9,866
10,630
1,603
2,527
1,522
15,583
7,874
2,738
10,575
2,428
7,874
1,964
1,101
1,993
3,501
380
2,379
895
2,599
2,379
1,621
2,131
2,131
3,313
1,281
1,964
765
2920
16665
2379
3116
1594
494
2379
1459
2335
3116
2379
2428
616
2428
1594
1621
1720
10638
3116
9866
10630
1603
2527
3044
15583
7874
2738
10575
2428
7874
1964
1101
1993
3501
380
4758
1790
2599
2379
1621
2131
2131
3313
1281
1964
765
94
1
1
1
1
1
1
1
1
3
1
1
2
1
1
2
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
1
1
1
1
1
Newark, NY
Roanoke
Pittsburgh
Charlotte, NC
NYC
Tucson, AZ
Houston
NYC
Philadelphia
Birmingham, AL
Newark, NY
NYC
New Orleans
NYC
Washington, DC
Boston
San Jose, CA
Miami
Columbus, OH
NYC
Austin
Boston
Atlanta
Austin
Los Angeles
Boston
Albany
San Luis, CA
Kansas City, MO
Atlanta
Roanoke
NYC
Baltimore, MD
Indianapolis
Columbus, OH
Indianapolis
Raleigh, NC
Chicago
San Diego
Chicago
Baltimore, MD
San Diego
New Orleans
Washington, DC
Mexico City
Washington, DC
2,738
2,019
2,131
1,868
2,771
1,621
449
2,771
2,599
1,191
2,738
2,771
895
2,771
2,379
3,116
2,868
2,239
1,850
2,771
380
3,116
1,459
380
2,462
3,116
2,863
2,712
921
1,459
2,019
2,771
2,428
1,522
1,850
1,522
2,118
1,594
2,335
1,594
2,428
2,335
895
2,379
1,876
2,379
2738
2019
2131
1868
2771
1621
449
2771
7797
1191
2738
5542
895
2771
4758
3116
2868
2239
1850
2771
380
3116
1459
380
4924
3116
2863
2712
921
1459
2019
2771
2428
1522
1850
1522
2118
1594
2335
1594
4856
2335
895
2379
1876
2379
95
2
2
1
1
4
1
1
2
1
1
1
10
1
10
1
9
1
1
2
1
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
1
3
1
2
Corpus Christi
Kansas City, MO
Salt Lake City
Chicago
Chicago
San Diego
Ithaca, NY
Nashville
Baltimore, MD
Amarillo
Chicago
Chicago
Little Rock
Chicago
Houston
Chicago
Washington, DC
Roanoke
Greenville, SC
Corpus Christi
Las Vegas
Seattle
San Diego
New Mexico
Burbank, CA
Islip, NY
Florida
New Orleans
Houston
San Antonio
Austin
El Paso
Albuquerque
Houston
Houston
San Antonio
Austin
Brownsville
Houston
710
921
1,973
1,594
1,594
2,335
2,600
1,260
2,428
625
1,594
1,594
608
1,594
449
1,594
2,379
2,019
1,720
710
2,105
3,313
2,335
1,098
2,455
2,850
2,239
895
449
494
380
1,099
1,134
449
449
494
380
966
449
Sum for 2008:
1420
1842
1973
1594
6376
2335
2600
2520
2428
625
1594
15940
608
15940
449
14346
2379
2019
3440
710
2105
3313
2335
1098
4910
2850
2239
895
449
494
380
1099
1134
449
449
494
1140
966
898
787077
96
Appendix 9: Sports Air Travel Summary Document and
Calculations for fiscal year 2008
Players Staff
Destination
23
1 Birmingham, AL
23
1 Indiannapolis, IN-one way
23
1 Louisville, KY-one way
23
1 Colorado Springs, CO
23
1 Birmingham, AL
23
1 Indiannapolis, IN-one way
23
1 Louisville, KY-one way
52
11 Louisville, KY
52
11 Nashville, TN
52
11 Indiannapolis, IN
14
2 Greensboro, NC
16
2 Colorado Springs, CO
16
2 Lexington, KY
14
1 Colorado Springs, CO
14
1 Memphis, TN-one way
14
1 Birmingham, AL-one way
12
4 Colorado Springs, CO
12
4 Memphis, TN-one way
12
4 Birmingham, AL-one way
20
4 Indiannapolis, IN
Mileage
Students/ miles Staff/miles
1191
27393
1191
761
17503
761
731
16824
731.5
1184
27232
1184
1191
27393
1191
761
17503
761
731
16824
731.5
1463
76076
16093
1260
65520
13860
1522
79144
16742
1993
27902
3986
1184
18944
2368
1567
25072
3134
1184
16576
1184
430
6027
430.5
595
8337
595.5
1184
14208
4736
430
5166
1722
595
7146
2382
1522
30440
6088
Sum of
Sum of Student Adult
Miles:
Miles:
531231
79872
97
Appendix 10: Summary Document for Raw Data for January
term Trips for fiscal year 2008
#
#
students faculty Location
28
2 Greece
Dresden,
4
0 Germany
Munich,
1
0 Germany
Berlin,
5
1 Germany
Hamburg,
1
0 Germany
32
2 Peru, Bolivia
15
2 India
36
2 Turkey
23
1 Scotland
26
1 Japan
28
2 Australia
12
1 Spain
19
1 Costa Rica
Brazil and
18
1 Uruguay
7
1 Guatemala
14
1 Jamaica
19
1 Egypt
4
0 Mexico
10
1 Abiquii, NM
Washington,
10
1 DC
10
1 NYC
1
0 Costa Rica
1
0 Colorado
12
0 India
3
0 Ethiopia
2
0 Kenya
1
0 Costa Rica
1
0 Pakistan
1
0 Chile
1
0 El Salvador
Mileage for round
trip
Number attended/miles
12,471
374130
10,546
42184
10,638
10638
10,398
62388
10,088
7,874
18,706
13,419
8,928
12,819
17,148
9,879
3,559
10088
267716
318002
509922
214272
346113
514440
128427
71180
10,457
4,886
3,091
13,851
2,198
1,098
198683
39088
46365
277020
8792
6039
2,379
2,771
3,559
1,281
18,706
16,665
17,474
3,559
15,583
9,768
2,833
26169
30481
3559
1281
224472
49995
34948
3559
15583
9768
2833
98
Appendix 11: Summary Document for Raw Data for Study
Abroad Semester and Year Long Trips for fiscal year 2008
#
students
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Country
France
Scotland
Austria
Argentina
China
Spain
Japan
France
Argentina
Mexico
China
France
Japan
Italy
Costa Rica
Japan
Scotland
Spain
Austria
Japan
Latin America
Argentina
Japan
Austria
Austria
Australia
Chile
Argentina
Italy
Dominican Republic
Argentina
Ecuador
England
Spain
Italy
Spain
Australia
Japan
Spain
Number attending/
Mileage
miles
9866
9866
8928
8928
10997
10997
10575
10575
13906
13906
9879
9879
13140
13140
10301
10301
10575
10575
1854
1854
13906
13906
Grenoble
10347
10347
Toyko
12819
12819
Rome
11194
11194
3559
3559
Nagoya
13140
13140
Edinburgh
9001
9001
Granada
10099
10099
Vienna
10997
10997
Toyko
12819
12819
Mexico/Peru/Argentina
10575
10575
Buenos Aires
10575
10575
Toyko
12819
12819
Vienna
10997
10997
Salzburg
10763
10763
17148
17148
Valparaiso
9768
9768
Buenos Aires
10575
10575
Florence
10945
10945
Santiago
3738
3738
Buenos Aires
10575
10575
5161
5161
London
9473
9473
Madrid
9903
9903
Florence
10945
10945
Salamanca
9903
9903
Bond Univ
16598
16598
Nagoya
13140
13140
Barcelona
10361
10361
City
Paris
Glasgow
Vienna
Buenos Aires
Beijing
Seville
Nagoya
Lyon
Buenos Aires
Xalapa
99
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Spain
Japan
France
Japan
Mexico
Samoa
Austria
Chile
Australia
Spain
Argentina
Spain
Chile
Spain
Chile
France
Spain
England
France
Japan
Mexico
Mexico
EU
Mexico
Sevilla
Toyko
Grenoble
Nagoya
Xalapa
Vienna
Valparaiso
Bond Univ
Sevilla
Mendoza
Granada
Valparaiso
Sevilla
Valparaiso
Paris
Salamanca
York
Paris
Toyko
9879
12819
10347
13140
1854
11754
10997
9768
16598
9879
9793
10099
9768
9879
9768
9866
9903
9240
9866
12819
2059
2059
9473
1854
Sum of
SA miles
in 2008:
9879
12819
10347
13140
1854
11754
10997
9768
16598
9879
9793
10099
9768
9879
9768
9866
9903
9240
9866
12819
2059
2059
9473
1854
635345
100
Appendix 12: Calculations of Solid Waste Averages
Cubic
Per
cubic yards per
Date
Trash Containers Yards
per week
year
year
Tons per year started
Apartments
6
2
104
624
28.08 Sep-05
Cafeteria
4
6
312
1248
56.17 Sep-05
Cafeteria
4
5
260
1040
46.80 Sep-05
Physical Plant
8
6
312
2496
112.33 Aug-05
Physical Plant
8
5
260
2080
93.61 Aug-05
Physical Plant
Roll Off
30 2 per month
12
360
16.20 Aug-05
Total tons per
year at 100%
full:
353
Total tons per
year at 90% full:
318
Total tons per
year at 80% full:
283
Recycling
Containers
Apartments
Apartments
Cafeteria
Physical Plant
Cubic
yards
Per
year
per week
8
8
8
8
1
1
5
5
52
52
260
260
cubic yards per
Date
year
tons per year
started
416
18.72 Oct-05
416
18.72 Oct-05
2080
93.61 Sep-05
2080
93.61 Aug-05
Total Tons per
year at 100%
225
Total Tons per
year at 90%
202
Total Tons per
year at 80%
180
101
Appendix 13: Summary of Recommendations for Record Keeping
Improvements with pertinent Staff/Faculty member
Source Type
Air Travel
Air Travel
Air Travel
Air Travel
(January Term)
Staff/Faculty
Member
Director of the
Business Office
Director of the
Business Office
Director of the
Business Office
and Accounts
Payable
Accountant
Secretary for
Academic Affairs
Air Travel
(Semester and
Year Long Study
Abroad)
Assistant Director
of Study Abroad
Commuting
Survey
Fleet Vehicle
Personal Mileage
Director of Human
Resources
Benefits
Representative
Fleet Vehicles
Purchasing
Representative
Solid Waste
Director of
Physical Plant
Solid Waste
Director of
Physical Plant
Recommendation
Keep flights separate from other
budget entries in voucher records.
Keep purchasing card entries that are
flights in a separate document with
specified destinations and passengers
when they are entered.
Each voucher entry should include the
destination and number of Austin
College passengers in the description
area.
Create a summary document for each
January that includes the number of
passengers for each trip, including
professors and students, and the
destination country and city
Create a summary document that
includes each city and country
destination and the number of Austin
College students that traveled there
annually.
Distribute a paper copy of commuting
survey to staff without email addresses.
Collect personal mileage at beginning
and end of each fiscal year for each
fleet vehicle.
Collect mileage at beginning and end
of each fiscal year for each fleet
vehicle.
Collect information from the city
directly, per the request of the
inventory creator.
Find an average weight per bag and
inventory the amount of bags used
annually to estimate trash creation.