| Overall Rating | Gold - expired |
|---|---|
| Overall Score | 70.13 |
| Liaison | John Alejandro |
| Submission Date | March 24, 2021 |
University of San Diego
OP-1: Emissions Inventory and Disclosure
| Status | Score | Responsible Party |
|---|---|---|
|
2.56 / 3.00 |
Trey
McDonald Director of Sustainability and Energy Manager Sustainability |
"---"
indicates that no data was submitted for this field
Part 1. Greenhouse gas emissions inventory
Yes
A copy of the most recent GHG emissions inventory:
A brief description of the methodology and/or tool used to complete the GHG emissions inventory:
The most recent GHG inventory was completed in December 2020 for FY2019. The calculation-based methodologies in A1:F88 Local Government Protocol are used to quantify GHG emissions in each scope and category. For some scope 3 categories that are not covered in the Local Government Protocol, the methods from Corporate Value Chain (Scope 3) are used.
Has the GHG emissions inventory been validated internally by personnel who are independent of the GHG accounting and reporting process and/or verified by an independent, external third party?:
Yes
A brief description of the GHG inventory verification process:
Internal review of the GHG emissions inventory is validated independently by the USD Office of Sustainability. The GHG inventory is conducted by the USD Energy Policy Initiatives Center, a separate entity that is housed in the USD School of Law.
Documentation to support the GHG inventory verification process:
Scope 1 GHG emissions
| Weight in MTCO2e | |
| Stationary combustion | 3,402 Metric tons of CO2 equivalent |
| Other sources (mobile combustion, process emissions, fugitive emissions) | 588 Metric tons of CO2 equivalent |
Total gross Scope 1 GHG emissions, performance year:
3,990
Metric tons of CO2 equivalent
Scope 2 GHG emissions
| Weight in MTCO2e | |
| Imported electricity | 6,554 Metric tons of CO2 equivalent |
| Imported thermal energy | 0 Metric tons of CO2 equivalent |
Total gross Scope 2 GHG emissions, performance year:
6,554
Metric tons of CO2 equivalent
GHG emissions from biomass combustion
0
Metric tons of CO2 equivalent
Scope 3 GHG emissions
| Yes or No | Weight in MTCO2e | |
| Business travel | Yes | 6,637 Metric tons of CO2 equivalent |
| Commuting | Yes | 6,748 Metric tons of CO2 equivalent |
| Purchased goods and services | No | 0 Metric tons of CO2 equivalent |
| Capital goods | No | 0 Metric tons of CO2 equivalent |
| Fuel- and energy-related activities not included in Scope 1 or Scope 2 | Yes | 289 Metric tons of CO2 equivalent |
| Waste generated in operations | Yes | 523 Metric tons of CO2 equivalent |
| Other sources | Yes | 279 Metric tons of CO2 equivalent |
Total Scope 3 GHG emissions, performance year:
14,476
Metric tons of CO2 equivalent
A brief description of how the institution accounted for its Scope 3 emissions:
Scope 3 emissions included in the inventory, and changes from the 2015 inventory, are as follows:
1. Solid Waste Disposal
2. Water and Wastewater
3. Student and Employee Air Travel
• Team Travel is now under student travel (previously under employee travel)
• Ahler’s Center travel miles have popular layover city included,
International Center’s data do not.
• Some domestic trips are included, e.g. Sundance Film Festival.
• Many assumptions included, e.g. some programs just have class # or generic
program name (KSPS domestic internship).
• EPIC & USD not have data on the specific routes and the number and locations
of the layovers for each flight taken by students and employees. Instead,
we estimated an average distance for each flight based on the destination.
For the FY2019 inventory, there was an inconsistency between the data
obtained from the Ahler Center and the International Center regarding the
Graduate Business School’s Study Abroad travels. We assumed the Ahler
Center’s data to be more accurate for our calculations.
4. Student and Employee Commuting
• Different data sources for the calculation
The sources for miles and emission factors for fiscal years 2010-15 and fiscal years 2017-18 are different. Data used to estimate FY2017, FY2018, and FY2019 emissions from student and employee commuting were collected from a survey conducted in 2018. Whereas data from parking permits sold, student and employee address zip codes, and a commuter survey were used to estimate GHG emission calculations for fiscal years 2010-15. The vehicle emission factors for FY 2019 were estimated by multiplying the FY 2018 USD vehicle emission rate with the ratio of San Diego regional 2019 to 2018 CO2e emission rate. The data for San Diego regional passenger cars and small to medium trucks were acquired from the EMFAC 2017 database. EMFAC (EMission FACtor) is a model developed by the California Air Resources Board to estimate the official emissions inventories of on road mobile sources in California.
USD and EPIC acquired data required to calculate the FY2017 and FY2018 student and employee commute emission through a survey conducted in 2018. We do not have the exact data on commute distance and frequency to calculate the exact emissions. So, we estimated the emission rate for 2019 by scaling the 2017 emission rates by the ratio of San Diego regional 2019 to 2017 CO2e emission rates.
5. Generation of Electricity Consumed in Transmission & Distribution System (T&D System losses)
• More on-site electric generation, less grid purchase, therefore less T&D losses
6. Emissions previously not included in the CAP but can be tracked separately now:
• Athletic buses off-campus refuel
• Direct financed travel - vehicle
1. Solid Waste Disposal
2. Water and Wastewater
3. Student and Employee Air Travel
• Team Travel is now under student travel (previously under employee travel)
• Ahler’s Center travel miles have popular layover city included,
International Center’s data do not.
• Some domestic trips are included, e.g. Sundance Film Festival.
• Many assumptions included, e.g. some programs just have class # or generic
program name (KSPS domestic internship).
• EPIC & USD not have data on the specific routes and the number and locations
of the layovers for each flight taken by students and employees. Instead,
we estimated an average distance for each flight based on the destination.
For the FY2019 inventory, there was an inconsistency between the data
obtained from the Ahler Center and the International Center regarding the
Graduate Business School’s Study Abroad travels. We assumed the Ahler
Center’s data to be more accurate for our calculations.
4. Student and Employee Commuting
• Different data sources for the calculation
The sources for miles and emission factors for fiscal years 2010-15 and fiscal years 2017-18 are different. Data used to estimate FY2017, FY2018, and FY2019 emissions from student and employee commuting were collected from a survey conducted in 2018. Whereas data from parking permits sold, student and employee address zip codes, and a commuter survey were used to estimate GHG emission calculations for fiscal years 2010-15. The vehicle emission factors for FY 2019 were estimated by multiplying the FY 2018 USD vehicle emission rate with the ratio of San Diego regional 2019 to 2018 CO2e emission rate. The data for San Diego regional passenger cars and small to medium trucks were acquired from the EMFAC 2017 database. EMFAC (EMission FACtor) is a model developed by the California Air Resources Board to estimate the official emissions inventories of on road mobile sources in California.
USD and EPIC acquired data required to calculate the FY2017 and FY2018 student and employee commute emission through a survey conducted in 2018. We do not have the exact data on commute distance and frequency to calculate the exact emissions. So, we estimated the emission rate for 2019 by scaling the 2017 emission rates by the ratio of San Diego regional 2019 to 2017 CO2e emission rates.
5. Generation of Electricity Consumed in Transmission & Distribution System (T&D System losses)
• More on-site electric generation, less grid purchase, therefore less T&D losses
6. Emissions previously not included in the CAP but can be tracked separately now:
• Athletic buses off-campus refuel
• Direct financed travel - vehicle
Part 2. Air pollutant emissions inventory
Yes
Annual weight of emissions for::
| Weight of Emissions | |
| Nitrogen oxides (NOx) | 0.98 Tons |
| Sulfur oxides (SOx) | 0.01 Tons |
| Carbon monoxide (CO) | 0.23 Tons |
| Particulate matter (PM) | 0.08 Tons |
| Ozone (O3) | 0 Tons |
| Lead (Pb) | 0.03 Tons |
| Hazardous air pollutants (HAPs) | --- |
| Ozone-depleting compounds (ODCs) | 0 Tons |
| Other standard categories of air emissions identified in permits and/or regulations | 118 Tons |
Do the air pollutant emissions figures provided include the following sources?:
| Yes or No | |
| Major stationary sources | Yes |
| Area sources | No |
| Mobile sources | No |
| Commuting | No |
| Off-site electricity production | No |
None
A brief description of the methodology(ies) the institution used to complete its air emissions inventory:
USD stationary emission sources consist of seven generators, one fire pump, five hot water boilers, and one gasoline dispensing facility. Fuel usage figures are provided to San Diego Air Pollution Control, who uses source test emissions factors to calculate approximate emissions. Test results are from 2019.
Optional Fields
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Gross Scope 2 GHG emissions from imported thermal energy (location-based) :
---
Website URL where information about the institution’s emissions inventories is available:
Additional documentation to support the submission:
---
Data source(s) and notes about the submission:
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The information presented here is self-reported. While AASHE staff review portions of all STARS reports and institutions are welcome to seek additional forms of review, the data in STARS reports are not verified by AASHE. If you believe any of this information is erroneous or inconsistent with credit criteria, please review the process for inquiring about the information reported by an institution or simply email your inquiry to stars@aashe.org.