Default Carbon Intensity Factors. Carbon Intensity Factors for ...
SEEC ClearPath California Reference Sheet – Default Carbon Intensity Factors. Grid Electricity Forecasting changes in GHG generating activities can be challenging. Commercial energy use may be projected to grow at rates similar to projections of business growth or population growth if those are unavailable. For more information on determining what factors to include in forecasts of a variety of sources, you may review past guidance on forecasting from the SEEC program here. The following table contains compound annual growth rates for the decreasing carbon intensity of grid electricity in response to the California Renewable Portfolio Standard. These factors were derived from the CO2 Allocations tab in the E3 GHG Calculator version 3c located at: http://www.ethree.com/public_projects/cpuc2.php. Use the factors below to develop a Forecast Factor Set for Carbon Intensity that corresponds with your utility.
Carbon Intensity Factors for California RPS Utility Anaheim Public Utilities City and County of San Francisco City of Palo Alto Public Utilities Glendale Water & Power Los Angeles Department of Water & Power Pacific Gas & Electric Company PacifiCorp Pasadena Water & Power Riverside Public Utilities Roseville Electric Sacramento Municipal Utility District San Diego Gas & Electric Sierra Pacific Resources Southern California Edison Turlock Irrigation District CA Total
2010-1014 -0.031 -0.031 -0.031 -0.030 -0.024 -0.045 -0.031 -0.030 -0.030 -0.030 -0.037 -0.058 -0.031 -0.028 -0.030 -0.034
2015-2019 -0.024 -0.024 -0.024 -0.031 -0.028 -0.059 -0.024 -0.031 -0.031 -0.031 -0.046 -0.053 -0.024 -0.034 -0.031 -0.034
Note that the RPS and these projected changes only apply up to the year 2020. Beyond that date, users will need to make their own assumptions about further reductions in carbon intensity, due to natural market forces or other factors.
On-Road Transportation Changes in the carbon intensity for each mile driven are expected to decrease due to mandated improvements in vehicle fuel economy. When forecasting emissions from on-road transportation, it is important to consider all the relevant external changes that may be occurring to the particular records you are forecasting. In doing so, you will need to pay close attention to what was included in your inventory records in order to capture likely changes in emissions intensity as a result of changes to the fuel economy of the fleet. Changes in passenger vehicle fuel economy are expected as a result of Pavley I & II regulations. When forecasting emissions from this sector, changes to fuel economy can be accounted for by applying a “Carbon Intensity Factor”. The rate of change you should apply depends on the relative amount of passenger vehicle traffic in your inventory records. Some inventories may only include passenger vehicle traffic only. In these cases, all vehicular travel will become more efficient as a result of the regulations. If your inventory records contain a mix of passenger and commercial or freight traffic, the impact will be slightly less. The values in the table below will help you to make adjustments for either case. VMT Carbon Intensity Factors for Pavley/CAFE Forecast Period Passenger Vehicle Carbon All Traffic Carbon Intensity Intensity Factors Factors -0.007 -0.006 2010-2014 -0.022 -0.017 2015-2019 -0.026 -0.020 2020-2024 -0.023 -0.018 2025-2029 -0.015 -0.012 2030-2034 -0.008 -0.006 2035-2039 -0.003 -0.002 2040-2044 -0.001 -0.001 2045-2049 The values in this table were developed from modeling performed by the USEPA to determine the impact of CAFE standards for the 2017-2025 model years. For these calculations, the benefits calculation output of the EPA OMEGA 1.4.1 Model was examined to determine the on-road calendar year impact of the regulation. Since the Pavely standards have essentially established the path that CAFE will follow, these results should be similar to the impact of Pavely. The impact calculated is presented in terms of relative change and thus should be reasonably applicable to any inventory starting point. Procedure Followed for Developing Pavely Carbon Intensity Factors The OMEGA_Benefits_1.4.1.xls file contains a tab named “Calculations”. Within that tab, there are VMT and fuel consumption information for surviving model year vehicles for each calendar year from 2012 beyond 2050, separated for “cars” and “trucks”. The factors listed in the table above were developed as follows:
Step 1: All calendar year VMT and fuel consumption was summarized for each vehicle type. Step 2: An aggregate fuel economy was calculated for each calendar year. Step 3: Compound annual growth rate at 5 year increments calculated to represent the rate at which carbon intensity of VMT per year would decrease. Step 4: A summary rate of change was then calculated as an average between the Individual rates for cars and trucks, weighted by their proportion of total national level VMT. There are some minor limitations to this analysis. First, the EPA OMEGA model did not include impacts related to diesel passenger vehicles or diesel light trucks due to their relatively low market penetration. The vehicle categories that were included are aggregated to the general vehicle categories of “cars” and “trucks”, rather than the specific vehicle categories used in many other types of emissions calculations. The relative proportion of cars and trucks in the national scale analysis likely differs somewhat from California average as well as local transportation characteristics. Despite these limitations, this analysis provides the best available correction for the impact of the Pavely regulations for use in forecasting and climate action planning. A final correction was introduced for the case of when all VMT has been aggregated together in an inventory versus separate accounting for passenger traffic versus commercial traffic. The impact of the regulation is less when applied to all traffic since it does not impact heavy duty vehicles, which are assumed to largely account for commercial travel. To make this correction factor the following steps were used: Step 1: State-wide average VMT rates for different vehicle types were obtained from EMFAC 2011 for benchmark years at 5 year increments from 2010 to 2035. Step 2: The proportion of Passenger vehicle traffic classes (LDA, LDT1, and LDT2) to all traffic was computed at each interval. The results of this procedure ranged from 78.6% to 79.3%. As a midrange value, 79% was selected as a correction factor for the case of all traffic calculated together. This reflects the expected relative proportion of passenger vehicle traffic to all traffic combined. While this method is somewhat coarse, it is expected to produce better end results than performing the calculation without it. The ratio of passenger vehicle traffic to all traffic may be different in your specific location. Your knowledge of data used in your inventory will be helpful in determining a different value that may be more appropriate, and you are free to modify your carbon intensity factors whenever more precise information is available.
Carbon Intensity Factors for California RPS Utility Anaheim Public Utilities City and County of San Francisco City of Palo Alto Public Utilities Glendale Water & Power Los Angeles Department of Water & Power Pacific Gas & Electric Company PacifiCorp Pasadena Water & Power Riverside Public Utilities Roseville Electric Sacramento Municipal Utility District San Diego Gas & Electric Sierra Pacific Resources Southern California Edison Turlock Irrigation District CA Total
2010-1014 -0.031 -0.031 -0.031 -0.030 -0.024 -0.045 -0.031 -0.030 -0.030 -0.030 -0.037 -0.058 -0.031 -0.028 -0.030 -0.034
2015-2019 -0.024 -0.024 -0.024 -0.031 -0.028 -0.059 -0.024 -0.031 -0.031 -0.031 -0.046 -0.053 -0.024 -0.034 -0.031 -0.034
Note that the RPS and these projected changes only apply up to the year 2020. Beyond that date, users will need to make their own assumptions about further reductions in carbon intensity, due to natural market forces or other factors.
On-Road Transportation Changes in the carbon intensity for each mile driven are expected to decrease due to mandated improvements in vehicle fuel economy. When forecasting emissions from on-road transportation, it is important to consider all the relevant external changes that may be occurring to the particular records you are forecasting. In doing so, you will need to pay close attention to what was included in your inventory records in order to capture likely changes in emissions intensity as a result of changes to the fuel economy of the fleet. Changes in passenger vehicle fuel economy are expected as a result of Pavley I & II regulations. When forecasting emissions from this sector, changes to fuel economy can be accounted for by applying a “Carbon Intensity Factor”. The rate of change you should apply depends on the relative amount of passenger vehicle traffic in your inventory records. Some inventories may only include passenger vehicle traffic only. In these cases, all vehicular travel will become more efficient as a result of the regulations. If your inventory records contain a mix of passenger and commercial or freight traffic, the impact will be slightly less. The values in the table below will help you to make adjustments for either case. VMT Carbon Intensity Factors for Pavley/CAFE Forecast Period Passenger Vehicle Carbon All Traffic Carbon Intensity Intensity Factors Factors -0.007 -0.006 2010-2014 -0.022 -0.017 2015-2019 -0.026 -0.020 2020-2024 -0.023 -0.018 2025-2029 -0.015 -0.012 2030-2034 -0.008 -0.006 2035-2039 -0.003 -0.002 2040-2044 -0.001 -0.001 2045-2049 The values in this table were developed from modeling performed by the USEPA to determine the impact of CAFE standards for the 2017-2025 model years. For these calculations, the benefits calculation output of the EPA OMEGA 1.4.1 Model was examined to determine the on-road calendar year impact of the regulation. Since the Pavely standards have essentially established the path that CAFE will follow, these results should be similar to the impact of Pavely. The impact calculated is presented in terms of relative change and thus should be reasonably applicable to any inventory starting point. Procedure Followed for Developing Pavely Carbon Intensity Factors The OMEGA_Benefits_1.4.1.xls file contains a tab named “Calculations”. Within that tab, there are VMT and fuel consumption information for surviving model year vehicles for each calendar year from 2012 beyond 2050, separated for “cars” and “trucks”. The factors listed in the table above were developed as follows:
Step 1: All calendar year VMT and fuel consumption was summarized for each vehicle type. Step 2: An aggregate fuel economy was calculated for each calendar year. Step 3: Compound annual growth rate at 5 year increments calculated to represent the rate at which carbon intensity of VMT per year would decrease. Step 4: A summary rate of change was then calculated as an average between the Individual rates for cars and trucks, weighted by their proportion of total national level VMT. There are some minor limitations to this analysis. First, the EPA OMEGA model did not include impacts related to diesel passenger vehicles or diesel light trucks due to their relatively low market penetration. The vehicle categories that were included are aggregated to the general vehicle categories of “cars” and “trucks”, rather than the specific vehicle categories used in many other types of emissions calculations. The relative proportion of cars and trucks in the national scale analysis likely differs somewhat from California average as well as local transportation characteristics. Despite these limitations, this analysis provides the best available correction for the impact of the Pavely regulations for use in forecasting and climate action planning. A final correction was introduced for the case of when all VMT has been aggregated together in an inventory versus separate accounting for passenger traffic versus commercial traffic. The impact of the regulation is less when applied to all traffic since it does not impact heavy duty vehicles, which are assumed to largely account for commercial travel. To make this correction factor the following steps were used: Step 1: State-wide average VMT rates for different vehicle types were obtained from EMFAC 2011 for benchmark years at 5 year increments from 2010 to 2035. Step 2: The proportion of Passenger vehicle traffic classes (LDA, LDT1, and LDT2) to all traffic was computed at each interval. The results of this procedure ranged from 78.6% to 79.3%. As a midrange value, 79% was selected as a correction factor for the case of all traffic calculated together. This reflects the expected relative proportion of passenger vehicle traffic to all traffic combined. While this method is somewhat coarse, it is expected to produce better end results than performing the calculation without it. The ratio of passenger vehicle traffic to all traffic may be different in your specific location. Your knowledge of data used in your inventory will be helpful in determining a different value that may be more appropriate, and you are free to modify your carbon intensity factors whenever more precise information is available.
