University of California, Los Angeles
OP-1: Emissions Inventory and Disclosure
| Status | Score | Responsible Party |
|---|---|---|
|
2.42 / 3.00 |
Nurit
Katz Chief Sustainability Officer 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 Climate Registry protocol: http://www.theclimateregistry.org/
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:
UCLA uses an outside firm to conduct third party verification of our inventories.
Documentation to support the GHG inventory verification process:
Scope 1 GHG emissions
| Weight in MTCO2e | |
| Stationary combustion | 224,400 Metric tons of CO2 equivalent |
| Other sources (mobile combustion, process emissions, fugitive emissions) | 2,803 Metric tons of CO2 equivalent |
Total gross Scope 1 GHG emissions, performance year:
227,203
Metric tons of CO2 equivalent
Scope 2 GHG emissions
| Weight in MTCO2e | |
| Imported electricity | 36,393 Metric tons of CO2 equivalent |
| Imported thermal energy | 0 Metric tons of CO2 equivalent |
Total gross Scope 2 GHG emissions, performance year:
36,393
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 | 10,876 Metric tons of CO2 equivalent |
| Commuting | Yes | 44,471.10 Metric tons of CO2 equivalent |
| Purchased goods and services | No | --- |
| Capital goods | No | --- |
| Fuel- and energy-related activities not included in Scope 1 or Scope 2 | No | --- |
| Waste generated in operations | No | --- |
| Other sources | No | --- |
Total Scope 3 GHG emissions, performance year:
55,347.10
Metric tons of CO2 equivalent
A brief description of how the institution accounted for its Scope 3 emissions:
UCLA tracks Scope 3 emissions from air travel and commuting, and reports the data to the UC Office of the President. Air travel calculations use SIMAP - Radiative Forcing (RF) to determine emissions, and commute emissions are calculated with an internal UCLA method, detailed below:
Uniform calculation method for GHG emissions from UC commuting
Developed and approved by the UC Sustainable Transportation Working Group 4/21/11
1. Purpose of calculation:
a. The primary purpose of this definition of a systemwide method of GHG emission calculation for commuting is to be able to report on the amount of GHG emissions from commuting for The Climate Registry (TCR) Scope 3 annual reporting. The Climate Registry does not, as yet, have a protocol for this reporting, so UC is proposing this uniform calculation method for UC use.
b. This information will also be used to report annually to the Systemwide Sustainability Steering Committee, and to the Regents in the Annual Sustainability report.
c. Campuses need to estimate GHG emissions for internal transportation planning purposes with finer grain assumptions than national models. Campuses need to be able to assess the effectiveness of various sustainable transportation program modifications. The model primarily needs to accurately assess existing transportation emissions, rather than projecting future emissions.
2. Need for consistency for systemwide reporting:
We recognize that there are multiple ways that “commute emissions” can be defined and calculated, but for the purpose of consistent systemwide reporting, we need agreement on a single calculation method, and set of definitions so that campuses can be fairly compared. We have identified options for campuses to use variable factors where appropriate which can reflect campus specific information, but not change the basic structure of the calculation.
3. Calculation method is best estimate at this time
The UC Sustainable Transportation Working Group has developed this GHG emission from commuting calculation based on campus experience calculating emissions, an evaluation of existing models, and available data sources. The group will continue to explore best practices in data collection and emission calculation and will revisit this calculation method as needed.
4. Other calculations for other purposes, calculation methods defined by other entities
There are other calculation methods which may be required for other purposes, which may result in different GHG emission calculations, eg for CEQA analysis of future emissions, grants, press outreach, recognition etc. Where there are different calculation methods used, the differences in purpose, differences in assumptions, and differences in outcomes will need to be explained. There are a variety of valid assumptions which can be made, differences in levels of detail required, and differences in areas of uniformity (UC systemwide, or regional uniformity in Air Districts).
Most notably, there are models promulgated by Air Districts for use in estimating GHG emissions from future projects for CEQA evaluation. The URBEMIS model has traditionally been used (see notes below) there is currently a new land use based model, CalEEMod which is similarly land use based, but includes more “downstream” GHG emissions than URBEMIS includes. Both of these models would project “worst case” emissions, based on national trip generation factors which is an appropriate analytical tool for CEQA purposes. Calculating existing emissions on UC campuses can rely on more California specific, and more campus specific information, for more fine grained analysis.
The URBEMIS model is frequently used and required by Air districts for calculating GHG emissions from future projects for CEQA analysis. In comparing the URBEMIS model and the proposed uniform calculation method (internal benchmark tool), the key difference that affects the outcome is that URBEMIS allocates portions of multi-stop trips to the final destination. For example, if a person drives from home (a) to a childcare center (any intervening stop) (b) and then to work (c), the URBEMIS model would only allocate the GHG from (b) to (c) portion of the trip to (c). In using this allocation, UCSF found that this resulted in a trip length of 1/3 the trip length estimated via the proposed uniform calculation method.
There may be future reporting requirements that define a different calculation method from the one articulated here. The Sustainable Transportation Working Group will revisit this issue at such time as The Climate Registry defines a calculation method, or other relevant models are promulgated by regulatory agencies.
5. What to report:
GHG emissions from commuting
Include: residential students in population
Campuses want to be able to calculate the reduction in GHG emissions from having students live on campus.
Exclude for now: commercial/service trips and visitors. Since the focus of this calculation is on regular commuting, these other types of trips should not be included. Most campuses do not have accurate information for these trips. Campuses can include this type of trip in other GHG emission calculations if desired, but specify trip types included.
6. How to calculate:
Inputs:
a. Mode split – use the mode split information from the most recent transportation survey or cordon count.
b. Vehicle trips/day – assume 2 trips/day (in and out) unless other information available.
c. Average miles per gallon by vehicle type:
20 mpg – national EPA average for passenger vehicles
There are a variety of different mpg for different vehicle types (eg 22.6 mpg for passenger vehicles, and 18.1 for SUVs). Using a more detailed mpg figure would require campuses to determine the vehicle mix of their population, which is not reliably available. Campuses may ask for vehicle type in surveys, so this is a reliable source for type of vehicle, but people tend to overestimate their mpg.
We expect that the California average miles per gallon would be higher than the national average, but have not been able to get a reliable source for statewide average.
As California implements its Low Carbon Fuel Standard, this factor will change.
d. Vehicle miles traveled (Average trip length x number of trips)
Data sources:
Self report from transportation survey, or estimate from zip code information.
e. Fuel consumption – calculation: # of trips x average trip length divided by average miles per gallon
f. # of work days/year –
The UC Systemwide # of work days/year for faculty and staff is 261
The UC Systemwide # of instruction days/year for students is 146.
These numbers are not adjusted for vacation and sick leave. Campuses can adjust these figures based on campus specific information.
Faculty staff adjustment is expected to be in the range of 11-18%
Student adjustment is expected to be in the range of 7.5-15%
g. Annual CO2 emissions – calculation: Gallons consumed per year x emission factor per gallon
h. Emissions per GALLON consumed
Use the Emission factors in CCAR Table C.3, which is based on US EPA Inventory of Greenhouse Gas Emissions and Sinks 1990-2005 (Attached)
The emissions per gallon has the miles per gallon rate included within it.
i. Emissions per MILE traveled (DOE)
CO2 per MILE, DOE also has factors for CH4 and N20 built into calculator to get a total CO2. There are a variety of emission factors per mile which could be used, but it is unclear what miles per gallon figures are integrated into this figure. Campuses will use miles per gallon. LBNL is required by DOE to use their calculator which is based on emissions per mile.
7. When to report: July 30 each year. LBNL reports Dec 1 each year
8. Proposed method of calculating amount of GHG REDUCED
Calculate GHG production if EVERYONE drove alone to campus, then subtract actual production, to get metric tons reduced.
While this calculation method may overstate the number of people who will drive to campus, it has the advantage of calculating the overall benefit of Transportation Demand Management programs, and may be helpful in determining the cost per unit of GHG emitted.
Attachments
1. Calculator spreadsheet
2. CCAR Carbon Dioxide Emission Factors for Transport Fuels
G/PD/Sustainability/Sustainable Transportation/GHG emission reduction/CCAR_Protocol_3 1 Jan 2009- Mobile Source.pdf
G:\PD\Sustainability\Sustainable Transportation\GHG emission reductions\Final uniform calculation method for GHG emissions from commuting.doc
Uniform calculation method for GHG emissions from UC commuting
Developed and approved by the UC Sustainable Transportation Working Group 4/21/11
1. Purpose of calculation:
a. The primary purpose of this definition of a systemwide method of GHG emission calculation for commuting is to be able to report on the amount of GHG emissions from commuting for The Climate Registry (TCR) Scope 3 annual reporting. The Climate Registry does not, as yet, have a protocol for this reporting, so UC is proposing this uniform calculation method for UC use.
b. This information will also be used to report annually to the Systemwide Sustainability Steering Committee, and to the Regents in the Annual Sustainability report.
c. Campuses need to estimate GHG emissions for internal transportation planning purposes with finer grain assumptions than national models. Campuses need to be able to assess the effectiveness of various sustainable transportation program modifications. The model primarily needs to accurately assess existing transportation emissions, rather than projecting future emissions.
2. Need for consistency for systemwide reporting:
We recognize that there are multiple ways that “commute emissions” can be defined and calculated, but for the purpose of consistent systemwide reporting, we need agreement on a single calculation method, and set of definitions so that campuses can be fairly compared. We have identified options for campuses to use variable factors where appropriate which can reflect campus specific information, but not change the basic structure of the calculation.
3. Calculation method is best estimate at this time
The UC Sustainable Transportation Working Group has developed this GHG emission from commuting calculation based on campus experience calculating emissions, an evaluation of existing models, and available data sources. The group will continue to explore best practices in data collection and emission calculation and will revisit this calculation method as needed.
4. Other calculations for other purposes, calculation methods defined by other entities
There are other calculation methods which may be required for other purposes, which may result in different GHG emission calculations, eg for CEQA analysis of future emissions, grants, press outreach, recognition etc. Where there are different calculation methods used, the differences in purpose, differences in assumptions, and differences in outcomes will need to be explained. There are a variety of valid assumptions which can be made, differences in levels of detail required, and differences in areas of uniformity (UC systemwide, or regional uniformity in Air Districts).
Most notably, there are models promulgated by Air Districts for use in estimating GHG emissions from future projects for CEQA evaluation. The URBEMIS model has traditionally been used (see notes below) there is currently a new land use based model, CalEEMod which is similarly land use based, but includes more “downstream” GHG emissions than URBEMIS includes. Both of these models would project “worst case” emissions, based on national trip generation factors which is an appropriate analytical tool for CEQA purposes. Calculating existing emissions on UC campuses can rely on more California specific, and more campus specific information, for more fine grained analysis.
The URBEMIS model is frequently used and required by Air districts for calculating GHG emissions from future projects for CEQA analysis. In comparing the URBEMIS model and the proposed uniform calculation method (internal benchmark tool), the key difference that affects the outcome is that URBEMIS allocates portions of multi-stop trips to the final destination. For example, if a person drives from home (a) to a childcare center (any intervening stop) (b) and then to work (c), the URBEMIS model would only allocate the GHG from (b) to (c) portion of the trip to (c). In using this allocation, UCSF found that this resulted in a trip length of 1/3 the trip length estimated via the proposed uniform calculation method.
There may be future reporting requirements that define a different calculation method from the one articulated here. The Sustainable Transportation Working Group will revisit this issue at such time as The Climate Registry defines a calculation method, or other relevant models are promulgated by regulatory agencies.
5. What to report:
GHG emissions from commuting
Include: residential students in population
Campuses want to be able to calculate the reduction in GHG emissions from having students live on campus.
Exclude for now: commercial/service trips and visitors. Since the focus of this calculation is on regular commuting, these other types of trips should not be included. Most campuses do not have accurate information for these trips. Campuses can include this type of trip in other GHG emission calculations if desired, but specify trip types included.
6. How to calculate:
Inputs:
a. Mode split – use the mode split information from the most recent transportation survey or cordon count.
b. Vehicle trips/day – assume 2 trips/day (in and out) unless other information available.
c. Average miles per gallon by vehicle type:
20 mpg – national EPA average for passenger vehicles
There are a variety of different mpg for different vehicle types (eg 22.6 mpg for passenger vehicles, and 18.1 for SUVs). Using a more detailed mpg figure would require campuses to determine the vehicle mix of their population, which is not reliably available. Campuses may ask for vehicle type in surveys, so this is a reliable source for type of vehicle, but people tend to overestimate their mpg.
We expect that the California average miles per gallon would be higher than the national average, but have not been able to get a reliable source for statewide average.
As California implements its Low Carbon Fuel Standard, this factor will change.
d. Vehicle miles traveled (Average trip length x number of trips)
Data sources:
Self report from transportation survey, or estimate from zip code information.
e. Fuel consumption – calculation: # of trips x average trip length divided by average miles per gallon
f. # of work days/year –
The UC Systemwide # of work days/year for faculty and staff is 261
The UC Systemwide # of instruction days/year for students is 146.
These numbers are not adjusted for vacation and sick leave. Campuses can adjust these figures based on campus specific information.
Faculty staff adjustment is expected to be in the range of 11-18%
Student adjustment is expected to be in the range of 7.5-15%
g. Annual CO2 emissions – calculation: Gallons consumed per year x emission factor per gallon
h. Emissions per GALLON consumed
Use the Emission factors in CCAR Table C.3, which is based on US EPA Inventory of Greenhouse Gas Emissions and Sinks 1990-2005 (Attached)
The emissions per gallon has the miles per gallon rate included within it.
i. Emissions per MILE traveled (DOE)
CO2 per MILE, DOE also has factors for CH4 and N20 built into calculator to get a total CO2. There are a variety of emission factors per mile which could be used, but it is unclear what miles per gallon figures are integrated into this figure. Campuses will use miles per gallon. LBNL is required by DOE to use their calculator which is based on emissions per mile.
7. When to report: July 30 each year. LBNL reports Dec 1 each year
8. Proposed method of calculating amount of GHG REDUCED
Calculate GHG production if EVERYONE drove alone to campus, then subtract actual production, to get metric tons reduced.
While this calculation method may overstate the number of people who will drive to campus, it has the advantage of calculating the overall benefit of Transportation Demand Management programs, and may be helpful in determining the cost per unit of GHG emitted.
Attachments
1. Calculator spreadsheet
2. CCAR Carbon Dioxide Emission Factors for Transport Fuels
G/PD/Sustainability/Sustainable Transportation/GHG emission reduction/CCAR_Protocol_3 1 Jan 2009- Mobile Source.pdf
G:\PD\Sustainability\Sustainable Transportation\GHG emission reductions\Final uniform calculation method for GHG emissions from commuting.doc
Part 2. Air pollutant emissions inventory
Yes
Annual weight of emissions for::
| Weight of Emissions | |
| Nitrogen oxides (NOx) | 84.78 Tons |
| Sulfur oxides (SOx) | 1.10 Tons |
| Carbon monoxide (CO) | 61.44 Tons |
| Particulate matter (PM) | 21.67 Tons |
| Ozone (O3) | 16.86 Tons |
| Lead (Pb) | 0.00 Tons |
| Hazardous air pollutants (HAPs) | --- |
| Ozone-depleting compounds (ODCs) | --- |
| Other standard categories of air emissions identified in permits and/or regulations | 0 Tons |
Do the air pollutant emissions figures provided include the following sources?:
| Yes or No | |
| Major stationary sources | Yes |
| Area sources | Yes |
| 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:
The South Coast Air Quality Management District's (SCAQMD’s) Annual Emission Reporting (AER) program was developed to track emissions of air contaminants from permitted facilities. Fees for emissions of air contaminants are assessed based on reported data. Under the SCAQMD program, emitters pay in accordance with total emissions and the fees are used toward air pollution control efforts. The aim is for the fee to act as an incentive to lower emissions.
The data collected under the auspices of the AER is used to update the comprehensive emissions inventory for the SCAQMD, which includes Orange County, the non-desert portions of Los Angeles and San Bernardino counties, and the Riverside county areas west of the Palo Verde Valley.
UCLA collects emissions data from numerous departments on and off campus. The primary sources of data are Co-Generation, Utilities, Refrigerant Management, Paint Shop, Facilities Management for boilers and emergency generators, ASUCLA, The Wilshire Center, Hazardous Waste Collection and Management, Hospital (RRMC and CHS) formaldehyde and solvent use, lab solvent and formaldehyde use and Fleet and Transportation Services. These data are aggregated by Environmental Compliance at EH&S and emission factors applicable to the process are assigned. Data are entered in the SCAQMD AER web reporting tool which automatically calculates the fees associated with all permitted and non-permitted emissions. Campus use records are collected from various business units for diesel, natural gas, refrigerants, adhesives, solvents, lab chemicals, generator run hours, etc. and entered into the SCAQMD AER online program.
The data collected under the auspices of the AER is used to update the comprehensive emissions inventory for the SCAQMD, which includes Orange County, the non-desert portions of Los Angeles and San Bernardino counties, and the Riverside county areas west of the Palo Verde Valley.
UCLA collects emissions data from numerous departments on and off campus. The primary sources of data are Co-Generation, Utilities, Refrigerant Management, Paint Shop, Facilities Management for boilers and emergency generators, ASUCLA, The Wilshire Center, Hazardous Waste Collection and Management, Hospital (RRMC and CHS) formaldehyde and solvent use, lab solvent and formaldehyde use and Fleet and Transportation Services. These data are aggregated by Environmental Compliance at EH&S and emission factors applicable to the process are assigned. Data are entered in the SCAQMD AER web reporting tool which automatically calculates the fees associated with all permitted and non-permitted emissions. Campus use records are collected from various business units for diesel, natural gas, refrigerants, adhesives, solvents, lab chemicals, generator run hours, etc. and entered into the SCAQMD AER online program.
Optional Fields
---
Gross Scope 2 GHG emissions from imported thermal energy (location-based) :
0
Metric tons of CO2 equivalent
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:
Additional information available at https://ehs.ucla.edu/eosp/environmental-compliance
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.