Greenhouse gas reduction opportunities for local governments: a quantification and prioritization framework

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.

Methods
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.

本研究的目标是为地方政府的温室气体（Greenhouse Gas, GHG）减排策略选择构建决策框架，其基础为全生命周期温室气体减排“供给曲线”的开发。该方法可同时整合多种温室气体减排方案的影响与成本效益评估结果。全生命周期温室气体排放核算会考量产品或流程全供应链产生的排放，通常也会涵盖系统层面或相关的排放连带效应。本研究采用全生命周期成本分析（Life Cycle Cost Analysis, LCCA）与全生命周期评估（Life Cycle Assessment, LCA）两种方法，分别量化各策略的成本与环境影响。研究选取了洛杉矶县（Los Angeles County, LA）与约洛县（Yolo County）作为案例，并为两县的温室气体减排供给曲线筛选了以下纳入策略：

1. 洛杉矶县选取了两项策略开展量化研究：
a. 公交巴士电动化：该项目由山麓公交局（Foothill Transit）主导实施，其服务范围不仅覆盖洛杉矶县的未建制区域，也涵盖已建制的行政区域；
b. 洛杉矶县公务车队替代燃料车辆部署。

2. 约洛县选取了六项策略开展量化研究：
a. 从太平洋天然气和电力公司（PG&E）转型至社区选择聚合（Community Choice Aggregation, CCA）实体Valley Clean Energy（VCE）所带来的电力减排；
b. 连接约洛县其他城市与戴维斯市的自行车道，服务非戴维斯本地居住的通勤员工；
c. 约洛县内的启停规则、环岛设置与限速调整，以优化车辆燃油经济性；
d. 县属停车场安装太阳能光伏车棚，用于电动汽车充电与场地照明的电力生产；
e. 全深度再生修复与传统路面翻新工艺的对比分析。

本文件汇总了各项策略的相关数据。

### 研究方法
下述各项策略的输入输出数据，以及用于处理数据的模型，均存储于对应的Excel文件中。若采用其他数据处理方式（如代码实现），相关代码已收录于下方对应策略的章节中。数据来源的参考文献已在最终报告中列明。

#### 洛杉矶县策略
1a. 山麓公交局主导的公交巴士电动化（服务范围覆盖洛杉矶县未建制区域与已建制行政区域）
巴士与电池生产数据存储于Excel文件"BusProductionLCI.xlsx"中：
- 车辆与电池生命周期清单（Life Cycle Inventory, LCI）数据存储于"Sheet1"工作表；
- 不同巴士类型的能源与排放LCI结果存储于"Sheet2"工作表；
- 电池尺寸相关的排放计算公式及推导方法存储于"Sheet3"工作表。
总排放数据的整理与处理存储于Excel文件"Foothill_Electrification.xlsx"中：
- 各场站的巴士规划安装量与其他相关信息存储于"Energy Needs"工作表；
- 各类燃料、巴士、电池等的全部成本核算存储于"Costs"工作表；
- 巴士全生命周期、充电站生产与太阳能面板生产的排放数据汇总与计算存储于"Emissions"工作表。

1b. 洛杉矶县公务车队替代燃料车辆部署
本研究包含4个Excel文件：3个为各场景的主模型文件，1个为汇总所有场景结果以生成对比图表与表格的汇总文件。文件命名如下：
- 汇总文件："AFV for LA Fleet, Summary.xlsx"
- 首个场景的模型文件："1_AFV for LA, BAU.xlsx"
- 第二个场景的模型文件："2_AFV for LA, All at Once.xlsx"
- 第三个场景的模型文件："3_AFV for LA, Gradual Transition.xlsx"
各场景的全部数据、假设与建模方法均存储于对应场景的Excel文件中，且三个场景采用统一的数据源与建模逻辑。各模型文件的核心结构如下：
- 不同车辆类别与车型年的历史英里每加仑（Miles Per Gallon, mpg）数据存储于"mpgHist"工作表，数据来源于美国能源信息署（Energy Information Administration, EIA）官网（工作表中附链接）；
- 2020至2050年不同车辆类别的mpg预测数据存储于"mpgProj"工作表，数据来源于EIA官网（工作表中附链接）；
- 各类燃料的价格预测数据存储于"F.Price Projs"工作表，数据来源于多源渠道，工作表中附相关网站链接；
- 车辆燃油价格的历史数据与预测数据分别存储于"VP Hist"与"VP Projs"工作表，数据主要来源于EIA官网，各工作表中附数据源链接；
- 不同车辆类别与燃料类型组合的维保成本数据存储于"M&R"工作表，数据源与假设已在工作表内详细说明；
- 车辆与燃料循环影响量化所需数据主要来源于阿贡国家实验室（Argonne National Laboratory）的GREET模型，相关内容存储于"LCA"工作表，必要处附数据源链接；
- 核心建模工作在"Main Model"工作表中完成，该工作表将逐年核算整个车队的车辆购置、维保成本，车辆残值以及燃料成本，同时逐年核算整个车队的燃料消耗量、车辆生命周期环境影响与燃料生命周期影响。
- "Results"工作表具备两项功能：
1. 为用户提供简便的模型主假设修改入口，例如车辆更换节点（按使用年限或行驶里程）与车辆更换时选用的替代燃料技术；
2. 汇总"Main Model"工作表的结果，包括全生命周期成本、燃料消耗量与全球变暖潜势（Global Warming Potential, GWP），并以图表形式呈现。
名为"AFV for LA Fleet, Summary.xlsx"的汇总文件将三个主模型文件中的表格与图表整合至单个文件中，便于不同场景间的结果对比。

#### 约洛县策略
2a. 从PG&E转型至社区选择聚合实体Valley Clean Energy（VCE）所带来的电力减排
本策略分析所用的全部数据与分析结果均存储于Excel文件"PG&E_to_VCE.xlsx"中：
- 各类电力潜在燃料的燃料路径LCI数据存储于"LCI"工作表；
- 基于LCI数据的各类燃料组合及对应结果存储于"Power Mix and Emissions"工作表；
- 25年分析期内各类燃料组合的排放数据，以及PG&E与VCE燃料组合的排放差值均存储于"Emissions"工作表。

2b. 连接约洛县其他城市与戴维斯市的自行车道，服务非戴维斯本地居住的通勤员工
本策略分析所用的全部数据与分析结果均存储于Excel文件"2019_Bike_Study.xlsx"中，具体如下：
- 材料、施工与维保相关的成本汇总存储于"Tab_A"工作表；
- 项目预估成本列于"Table_9"工作表；
- 戴维斯、伍德兰与西萨克拉门托的交通流量数据存储于"Tab_B"工作表；
- 主分析所用的自行车道与路径长度存储于"Tab_C"工作表，敏感性分析所用的相关数据存储于"Table_9"工作表；
- 路面、封层与骨料的施工及维保产生的温室气体排放数据存储于"Tab_D"工作表；
- 25年分析期内，因车辆行驶里程（Vehicle Miles Travelled, VMT）减少带来的温室气体减排量，以及新建自行车设施的施工与维保产生的温室气体排放数据存储于"Table_7"工作表；
- 25年分析期内，新建自行车设施成本与VMT减少带来的燃料节约量存储于"Table_8"工作表；
- 敏感性分析所用：25年分析期内VMT减少带来的温室气体减排量，以及自行车设施施工与维保产生的温室气体排放数据存储于"Table 10"工作表；
- 敏感性分析所用：25年分析期内新建自行车设施成本与VMT减少带来的燃料节约量存储于"Table 11"工作表。

2c. 约洛县内的启停规则、环岛设置与限速调整，以优化车辆燃油经济性
本策略分析所用的全部数据与分析结果均存储于Excel文件"2019_Intersections_Study.xlsx"中：
- 路面材料、施工与维保成本，以及交叉口与环岛的全生命周期成本分析（LCCA）数据存储于"Pavement LCCA"工作表；
- 交通数据存储于"Traffic"工作表；
- 车辆在交叉口与环岛的行驶循环数据存储于"Drivecycle"工作表；
- 不同车辆类别的单位排放、各交叉口的总排放（包括传统启停模式与拟建环岛模式）及对应模型存储于"Emission"工作表；
- 25年分析期内，现有交叉口与拟建环岛交叉口的年温室气体排放量与年成本数据存储于"Table_15_16"工作表。

2d. 县属停车场安装太阳能光伏车棚，用于电动汽车充电与场地照明的电力生产
本策略分析所用的全部数据与分析结果均存储于Excel文件"Yolo_Solar_Canopy.xlsx"中：
- 25年全生命周期内的安装与电力生产的总排放与成本数据存储于"Emissions + Cost"工作表；
- 太阳能车棚的材料排放数据存储于"LCI"工作表；
- 本次分析涉及的停车场信息，包括地址、停车位数量与已安装太阳能车棚数量存储于"Parking Lot Info"工作表；
- 基于每个车棚覆盖的停车位数量计算所需支架梁数量的相关内容存储于"Beams Info"工作表。

2e. 全深度再生修复与传统路面翻新工艺的对比分析
本策略的全部数据、假设与建模方法均存储于Excel文件"FDR_Local Govs.xlsx"中：
- 所有处理工艺的单位单价取自加州交通局（Caltrans）合同成本手册（Contract Cost Data Book, CCDB），相关数据存储于"CCDB"工作表；
- "Main Model"工作表包含本研究采用的全部假设与建模方法，以及用于计算不同策略全生命周期影响与成本的计算步骤；
- 项目几何尺寸（长度与宽度）通过谷歌地图估算，并结合与约洛县项目工程师的邮件沟通获取的项目范围确定；
- 环境影响计算采用美国加州大学帕克研究中心（UCPRC）生命周期清单数据库的LCI数据，相关引用已在报告中说明；
- 不同维保策略的一次能源需求（Primary Energy Demand, PED）、全球变暖潜势（GWP）与成本的汇总结果分别存储于"Summary PED"、"Summary (GWP)"与"Summary Costs"三个独立工作表中。