No institution-owned, leased, or operated buildings or other holdings that should fall within organizational boundaries are omitted in this report

UWRF used CACP calculator for its greenhouse emission inventory as it is in accordance with GHG Protocol and it is also in compliance with "The Commitment." Many institutions including UWRF have utilized CACP calculator previously to very positive outcomes.

The sources of the emissions coefficients used were the "CACP Campus Carbon Calculator's default emissions coefficients."

Data for UWRF GHG inventory was collected from the institution (UWRF). The data collection and analysis was primarily conducted by Jean Batiste Uwimana (Graduate Student)and reviewed periodically by various university staff. Information emanated from various sources, none of which had been previously queried for this type of information, yielding an excellent view of the gaps that need to be corrected prior to subsequent re-assessments. Data collection as supervised by the university sustainability office director and took approximately a period 12 months.

In 2010, UWRF updated this inventory to include the 2007-08 and 2008-09 academic years. The inaugural 2007 inventory was updated with more comprehensive data and inventories were completed dating back to 1990. During this update, data for the UWRF GHG inventory was collected from the institution (UWRF). The data collection and analysis was primarily conducted by Ian Johnson (Graduate Fellow), Bo Storuzak (Undergraduate Fellow) and Haiya Zhang (Undergraduate Fellow) and reviewed periodically by various University staff.

Some of the data collected for this updated report has been made more readily available than in the inaugural report (2007), while other areas still require more automation to make annual reporting a simpler process.

To provide the most accurate emissions inventory, all emissions sources with data available were included in the calculation.

Data on air travel for faculty, staff, and administrative business inside the country is significantly lacking in the UWRF CACP model because of insufficient data or no data collection at all. This travel data would certainly have a significant impact on total emissions. Data was however collected for student and faculty air travel out of the country for Study Abroad tours form the Global Connections office. Most of this new data was sufficient with the exception of some trips having unknown airport destinations, on which educated guesses were made.

Data on athletic travel, both air and ground, were unable to be obtained, which would also impact total emissions. This information should be available in the athletic department as it is needed for budgetary reasons and thus should be collected for inclusion in future reports.

Data collection gaps also existed in the University’s population data, particularly on full-time and part-time students as well as summer school students. The distinction between faculty and full- and part-time staff was also evident. Reporting populations using these distinctions in the future would offer a better base to estimate commuting data more accurately.

The assumptions used to calculate commuting emissions for UWRF are summarized below:

Students
- 64% commute in personal vehicle
- 5% carpool
- avg. of 3.5 trips per week
- commute 35 weeks/year
- avg. of 15 miles per trip

Faculty/Staff
- 90% commute in personal vehicle
- 8% carpool
- avg. of 4.0 trips per week
- commute 35 weeks/year
- avg of 15 miles per trip


These assumptions were arrived at in various ways:
Students who live in residence halls were assumed to walk or bike to class, while 5% of students (living off campus) were assumed to carpool using a best guess. This left a ‘best guess’ of 64% of students (living off campus) who commute in a personal vehicle. Similarly, a ‘best guess’ of 90% of faculty commute in personal vehicles, while 8% carpool with the remaining 2% living close enough to bike or walk.

As student populations are not divided into full- and part-time, an estimate was made based on a weighted average of trips per week. A best guess of two trips per week for part-time students and four trips per week for full-time students, a weighted average of 3.5 trips per week for the student population was used. Staff and faculty are considered full-time; therefore, an average of 4.0 trips per week was assumed.

A school year consists of 32 weeks per year. With the addition of J-term and summer, 35 weeks per year was used for both students and faculty/staff.

Data collection gaps existed as well in the University’s population data, particularly on full-time and part-time students and summer school students commuting rates and distances. The same commuting data weakness is evident for faculty, staff, and administration.

As student populations are not divided into full-time and part-time, some estimates were made based on a weighted average of trips per week to calculate commuting mileage traveled back and forth to school. With an average of two trips for part-time students and four trips for full-time students, a weighted average of 3.5 trips per week was used. As faculty are considered full time, an average of four trips per week were used.

Miles per trip was an estimate of the likely radius of travel distance of commuters, both those living in town and those commuting from other cities. An average of 15 miles per trip was assumed for both students and faculty/staff. This was largely based on the distance from River Falls to the Twin Cities metropolitan area.

No public transportation options were used to calculate commuting emissions, as no options currently exist in or to River Falls.

Default fuel efficiencies from CACP for commuting methods were used.

With the large amount of estimation and ‘best guesses’ used, commuting data and the associated emissions does not carry a large degree of confidence.

No information provided

Renewable energy certificates are required to be purchased by the state of Wisconsin as part of the University's portfolio.
Additionally, the Student Union at the University have elected to 'tax' themselves through additional segregated fees to facilitate the purchase of REC's equivalent to the energy use of the residence halls and the University Center on campus.

Sequestration values were calculated for the University forests.

No information provided