The goal of this research was to present a decision-making framework for greenhouse gas (GHG) mitigation strategy selection for local governments based on the development of life cycle GHG mitigation “supply curves”. This approach offers the ability to combine the impacts and cost-effectiveness measurements of numerous GHG mitigation options at the same time. Life cycle GHG emissions accounting considers emissions generated throughout the supply chain of a product or process, and also typically considers system-wide or consequential effects on emissions as well. Life cycle cost analysis (LCCA) and life cycle assessment (LCA) were the two methods used to quanitfy the costs and environmental impacts of the strategies, respectively. Los Angeles (LA) County and Yolo County were selected and the following actions for inclusion in GHG mitigation supply curves for each county were selected:

1. Los Angeles County chose to move forward with quantification of two strategies;

a. Transit bus electrification, which is being undertaken by Foothill Transit, a transit agency that serves not just the unincorporated regions of LA County, but also incorporated regions, and

b.  Implementation of alternative fuel vehicles for LA County fleet

2. Yolo County chose to move forward with quantification of six strategies;

a. Emissions reductions from electricity as a result of switching from PG&E to a community choice aggregation (CCA) entity, Valley Clean Energy (VCE).

b. Bike lanes connecting other cities in Yolo County to Davis for employees not living in Davis.

c. Changes to start and stop, roundabouts, and speed limits in Yolo County affecting vehicle fuel economy.

d. Solar panel canopies installed for electricity generation for electric vehicle charging and lighting on county parking lots.

e. Full depth reclamation versus conventional pavement rehabilitation methods.

This document summarizes the data for each strategy.

The input and output data for each of the strategy listed below as well as the models to process the data are included in its relevant excel file. If any other way of processing the data is used such as coding, the code has been included in the relevant strategy section below. The references to the data sources is cited in the final report.

LA COUNTY - STRATEGIES:

1a. Transit bus electrification, which is being undertaken by Foothill Transit, a transit agency that serves not just the unincorporated regions of LA County, but also incorporated regions

• Bus and battery production data is presented in the excel file “BusProductionLCI.xlsx”.
   
  • Vehicle and battery LCI data is presented in the sheet "Sheet1".
  • Energy and emission LCI results by bus type are presented in the sheet "Sheet2".
  • The equation to calculate emissions by battery size is presented in the sheet "Sheet3" along with the method to arrive at that equation.
     
• Total emissions data was compiled and processed in the excel file “Foothill_Electrification.xlsx”.
   
  • Planned installations of buses per depot and other relevant information are presented in the sheet “Energy Needs”.
  • All costs such as of all fuel types considered, buses, battery, etc, are calculated in the sheet “Costs.”
  • Emissions for bus lifecycle, charging station production, and solar panel production are compiled and calculated in the sheet “Emissions”.

1b. Implementation of alternative fuel vehicles for LA County fleet

• This study consists of 4 Excel files, 3 main Excel files for each of the scenarios, and one file summarizing the results of all the scenarios to develop comparison charts and tables. These files are titled as:
  • The summary file: “AFV for LA Fleet, Summary.xlsx”
  • The model file for the first scenario: “1_AFV for LA, BAU.xlsx”
  • The model file for the second scenario: “2_AFV for LA, All at Once.xlsx”
  • The model file for the third scenario: “3_AFV for LA, Gradual Transition.xlsx”
     
• All the data, assumptions, and modeling approaches for each scenario are available in the corresponding Excel file for that scenario, but the data sources and modeling approach are the same across all three. The main structure of each of the model files include the followings:
  • Historical data on miles per gallon (mpg) of different vehicle categories and model years (MLs) are presented in the sheet “mpgHist” with the data taken from Energy Information Administration (EIA) website (link provided in the sheet),
  • Projections of mpg for different categories between 2020 and 2050 are presented in the sheet “mpgProj” with the data taken from EIA website (link provided in the sheet)
  • The projection of fuel prices for different types of fuel is presented in the sheet “F.Price Projs”. The data are taken from multiple sources, and the website links are provided in the sheet.
  • Historical and projections of vehicle fuel prices are presented in the sheets “VP Hist” and “VP Projs”, respectively, with data taken mostly from the EIA website. The links to data sources are presented in each sheet.
  • The cost of maintenance and repairs for each vehicle category and fuel type combination is presented in the sheet "M&R" with the data sources and assumptions well documented within the sheet.
  • The data required for quantifying the vehicle and fuel cycle impacts are mostly taken from the GREET model by the Argonne National Laboratory, which is presented in the sheet titled “LCA.” Links to data sources are presented where needed.
  • The main modeling effort is conducted in the sheet “Main Model,” where the costs of purchasing, maintaining and repairing vehicles, and the salvage value of the vehicles sold in addition to the cost of fuel are calculated for each year for the entire fleet. The model also calculates similar items for fuel consumption, vehicle cycle environmental impacts, and fuel cycle impacts for each year for the entire fleet.
  • The sheet titled “Results” has two functions:
    • Provide a simple method for the user to modify the main assumption of the model, such as when to change the vehicle (age or mileage) and what alternative fuel technology to use when changing a vehicle.
    • Summarize the results from the sheet “Main Model” in terms of life cycle costs, fuel consumption, and global warming potential (GWP) and putting them into graphs.
       
• The summary Excel file titled "AFV for LA Fleet, Summary.xlsx" takes the tables and graphs from the three main model files into a separate Excel file to allow a comparison of the results across different scenarios.

YOLO COUNTY STRATEGIES

2a. Emissions reductions from electricity as a result of switching from PG&E to a community choice aggregation (CCA) entity, Valley Clean Energy (VCE)

• All the data used for analyzing this strategy and the resulting output can be found in the excel file “PG&E_to_VCE.xlsx”.
   
  • The values of fuel pathway LCIs for various potential fuels for electricity can be found in the sheet “LCI”.
  • The varius fuel mixes and the resulting values based on LCI data can be found in the sheet “Power Mix and Emissions”.
  • Emissions for the various fuel mixes, as well as the difference in emissions between the fuel mixes of PG&E and VCE, over the 25 year analysis period are calculated and presented in the sheet “Emissions”.

2b. Bike lanes connecting other cities in Yolo County to Davis for employees not living in Davis

• All the data used for analyzing this strategy and the resulting output of the analyses are listed below and could be found in the excel file “2019_Bike_Study.xlsx”.

• Summary of costs related to materials, construction and maintenance can be found in the sheet “Tab_A”.
• Estimated project costs are listed in the sheet “Table_9”.
• Davis, Woodland and West Sacramento traffic count data can be found in the sheet “Tab_B”.
• Length of the bike paths and lanes for main analysis are in sheet “Tab_C” whereas for sensitivity analysis are in sheet “Table_9”.
• The GHG emissions due to construction and maintenance of the pavement, slurry seal, and aggregate can be found in the sheet “Tab_D”.
• GHG emission reduction due to reduction in vehicle miles travelled (VMT) and GHG emissions due to construction and maintenance of the new bike structures for an analysis period of 25 years could be found in the sheet “Table_7”.
• New bike structure costs and fuel savings due to reduction in VMT over 25 years analysis period can be found in the sheet “Table_8”.
• For sensitivity analysis purposes – GHG emission reduction due to VMT reduction and GHG emissions due to bike structure construction and maintenance over the analysis period of 25 years can be found in the sheet “Table 10”.
• For sensitivity analysis purposes – New bike structure costs and fuel savings due to reduction in VMT over 25 years analysis period can be found in the sheet “Table 11”.

2c. Changes to start and stop, roundabouts, and speed limits in Yolo County affecting vehicle fuel economy

• All the data used for analyzing this strategy and the resulting output of the analyses are listed below and could be found in the excel file “2019_Intersections_Study.xlsx”.
• • The pavement material, cnstruction and maintenance cost along with the LCCA of the intersection and roundabouts are presented in the sheet “Pavement LCCA”.
  • The traffic data is presented in the sheet “Traffic”.
  • Drive cycle for a vehicle at an intersection and a roundabout is shown in the sheet “Drivecycle”.
  • GHG emissions per vehicle class type and total emissions per intersection (for traditional start-stop as well as proposed roundabouts), along with the models are presented in the sheet “Emission”.
  • The annual GHG emissions and annual cost for an existing intersection and proposed roundabout intersection for 25 years analysis period can be found in the sheet (Table_15_16).

2d. Solar panel canopies installed for electricity generation for electric vehicle charging and lighting on county parking lots

• All the data used for analyzing this strategy and the resulting output can be found in the excel file “Yolo_Solar_Canopy.xlsx”.
   
  • Summed emissions and costs data of installation and electricity production over the 25 year lifecycle can be found in the sheet “Emissions + Cost”.
  • Material emissions of the solar canopy can be found in the sheet “LCI”.
  • Information on the parking lots that were analyzed, including addresses, number of parking spaces, and number of installed solar canopies can be found in the sheet “Parking Lot Info”.
  • The calculated number of beams required for installation was calculated in the sheet “Beams Info” based on the number of spaces each canopy covered.

2e. Full depth reclamation versus conventional pavement rehabilitation methods

• All the data, assumptions, and modeling approaches are available in the Excel file titled “FDR_Local Govs.xlsx”.
   
  • The unit prices for all treatments are taken from Caltrans Contract Cost Data Book (CCDB) and are available in the sheet “CCDB”.
  • The sheet “Main Model” includes all the assumptions and modeling approaches implemented in this study and the calculation steps conducted to calculate life cycle impacts and the cost of the different strategies under investigation in this study.
  • The geometric dimensions of the project (length and width) are estimated using Google maps and the limits of the project as obtained through email communication with the project engineer at Yolo County.
  • The environmental impacts are calculated by using life cycle inventory (LCI) data from the UCPRC LCI Database as referenced in the report.
  • Summary results of primary energy demand (PED), global warming potential (GWP), and costs for different maintenance strategies are presented in three separate sheets titled “Summary PED”, “Summary (GWP)” and “Summary Costs” respectively.