Bainbridge_GHG Inventory Report_FINAL_20191122_201911271016146596CITY OF BAINBRIDGE ISLAND GREENHOUSE GAS EMISSIONS INVENTORY
FINAL FINDINGS REPORT
2019
CASCADIA CONSULTING GROUP, INC.
Cascadia Consulting Group, Inc.
Tel (206) 343-9759 Fax (206) 343-9819
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CITY OF BAINBRIDGE ISLAND | 2019 | 2
Table of Contents
Acronyms ___________________________________________________________________________ 3
Executive Summary ___________________________________________________________________ 4
Inventory Results ___________________________________________________________________ 6
Introduction ________________________________________________________________________ 11
Greenhouse Gas Inventory Overview __________________________________________________ 12
Roadmap of this Report _____________________________________________________________ 17
Communitywide Emissions ____________________________________________________________ 18
Results __________________________________________________________________________ 19
Data Sources and Methodology _______________________________________________________ 31
Community Contribution Analysis _____________________________________________________ 40
Municipal Operation Emissions _________________________________________________________ 43
Results __________________________________________________________________________ 43
Data Sources and Methodology _______________________________________________________ 52
Municipal Contribution Analysis ______________________________________________________ 58
Consumption-Based Emissions _________________________________________________________ 61
Results __________________________________________________________________________ 61
Data Sources and Methodology _______________________________________________________ 62
Conclusion and Next Steps _____________________________________________________________ 63
References _________________________________________________________________________ 64
Appendix: Tree Carbon Sequestration ______________________________________________________ i
Data Sources and Methodology _________________________________________________________ i
Results ___________________________________________________________________________ iii
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Acronyms
ACS American Community Survey (from the U.S. Census Bureau)
BOD Biochemical oxygen demand (a metric of the effectiveness of wastewater treatment plants)
EIA United States Energy Information Association
EPA United States Environmental Protection Agency
CO2e Carbon dioxide equivalent
GHG Greenhouse gas (limited to CO2, CH4, N2O, and fugitive gases in this inventory)
GWP Global Warming Potential
HFC Hydrofluorocarbon
MTCO2e Metric tons of carbon dioxide equivalent
MOVES Motor Vehicle Emission Simulator model (developed by EPA to quantify emissions from mobile
sources)
MPG Miles per gallon
NONROAD Part of MOVES model developed by EPA to quantify non-road mobile emissions
O&M Operations and Maintenance
ODS Ozone depleting substance
PFC Perfluorocarbon
PSCAA Puget Sound Clean Air Agency
PSE Puget Sound Energy
PSRC Puget Sound Regional Council
SF6 Sulfur hexafluoride
TCR The Climate Registry
USDA United States Department of Agriculture
WARM Waste Reduction Model (model developed by EPA to quantify solid waste emissions)
WSDOT Washington State Department of Transportation
WWTP Wastewater Treatment Plant
VMT Vehicle Miles Traveled
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Executive Summary
Global climate change poses a growing threat and humanitarian climate emergency, and Bainbridge
Island shares the responsibility to reduce greenhouse gas emissions (GHG) to stabilize the global climate
while preparing for the effects of climate change. The City of Bainbridge Island recently completed a
comprehensive greenhouse gas inventory as part of its commitment to reducing emissions and leading
on climate action. Greenhouse gas emission inventories quantify the amount of climate pollution
produced by an entity—in this case, from the Bainbridge Island community and municipal government
operations. As the Bainbridge Island government and community continues to take action to reduce
GHG emissions, these inventories will serve as tools for tracking progress and making improvements
along the way.
Inventory Approaches
This report describes findings from three distinct inventories:
• A community inventory that estimates GHG emissions produced by activities of the Bainbridge
Island community, including residents and businesses. The community GHG inventory includes
emissions due to energy used to power and heat homes and businesses; fuel used by vehicles
running within Bainbridge Island; solid waste that is generated by the community; agriculture
activities; fuel use by off-road equipment and vehicles; and others.
• A municipal inventory that accounts for the GHG emissions resulting from City of Bainbridge
Island government operations. This inventory can help the City understand GHG emissions
stemming from various activities associated with municipal operations, including from municipal
building and facility operation, transportation, solid waste, wastewater, and refrigerant leakage.
• A consumption-based inventory that estimates GHG emissions associated with the consumption
of food, goods, and services within the community, regardless of their origin. For example, this
inventory would not include emissions from the production of locally-manufactured goods that
are consumed entirely outside the community; however, it would include emissions associated
with the production of goods manufactured in another community but consumed by Bainbridge
Island residents, visitors, or businesses. This inventory can be examined in context with the
community inventory to paint a more comprehensive picture of community emissions.
This report also presents findings from additional analyses:
Municipal and communitywide contribution analyses that identify key drivers of observed emission
trends. For example, analysis calculates the impact that a hotter summer or colder winter may have
had on household energy use, and thus, emissions.
A supplemental carbon sequestration analysis that estimates the amount of carbon dioxide that
Bainbridge Island trees absorb—or sequester—from the atmosphere on an annual basis (in
Appendix).
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Inventory Methodology
The GHG inventories summarized in this report account for human-caused emissions of the most
prominent and typical greenhouse gases for communities: carbon dioxide (CO2), methane (CH4), and
nitrous oxide (N2O). To account for the differences in potency among these gases, all emissions are
calculated and reported in units of metric tons of carbon dioxide equivalent (MTCO2e). The inventories
were conducted using widely accepted tools and protocols, including the Local Government Operations
Protocol and U.S. Community Protocol for Accounting and Reporting of Greenhous Gas Emissions.
GHG emissions are inventoried by multiplying annual activity data (e.g. electricity consumption) by
emission factors (greenhouse gas emissions produced per kWh of electricity). For the municipal
operations inventory, we obtained most data from City staff and local documentation such as Puget
Sound Energy's (PSE) billing records, records from local wastewater treatment facilities, and fleet vehicle
fuel use records. For the communitywide inventory, key data sources included electricity consumption
data from PSE, Puget Sound Regional Council (PSRC) modeling outputs for vehicle miles traveled by fuel
type, Bainbridge Disposal tonnage records, and Kitsap County Conservation District estimates of
agricultural landowners and acreage. Where local data were not available, we referenced and
downscaled national data sources such as from the Federal Transit Administration, U.S. Census Bureau,
and the U.S. Department of Agriculture.
Inventory Boundaries
The activities and sectors included in GHG inventories are often classified into three “scopes,” which
represent relative levels of control over an emissions source:
Scope 1 emission sources include those directly caused by an organization’s actions, such as from
owned equipment and facilities.1
Scope 2 emissions are those indirectly associated with purchased electricity, steam, heating, or
cooling.
Scope 3 includes all other indirect emissions that are not covered in Scope 2.
The communitywide and municipal inventories for Bainbridge Island included emissions sources from all
three scopes: Scope 1, Scope 2, and Scope 3. The inventories included all sources required by the
consulted protocols and additional sources, as relevant.
Inventory Years
The inventories summarized in this report cover two representative years, 2014 and 2018. To provide
Bainbridge Island with the most comprehensive, consistent, and relevant information on their GHG
emissions, we selected the most recent year available as an inventory year – 2018. For a comparison
year, we selected 2014 because no major changes in organizational structure or infrastructure occurred
after that year. Additionally, choosing a more recent comparison year increases the likelihood that all
needed data are available and derived using consistent methodologies.
1 Except direct carbon dioxide emissions from biogenic sources.
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INVENTORY RESULTS
Community Emissions
The Bainbridge Island community emitted an estimated 233,998 metric tons of carbon dioxide
equivalent (MTCO2e) in 2018, or 9.4 MTCO2e per Bainbridge Island resident. A high-level comparison
suggests that this per-capita estimate is consistent with that of Kitsap County (9.9 MTCO2e per person),
and lower than per-capita estimates for the U.S., Washington State, King County, and Bellevue. However,
Bainbridge Island’s estimated per-capita emissions are almost twice those of Seattle and Tacoma (Figure
6). The majority of Bainbridge Island community emissions stem from consumption of electricity in
homes and commercial buildings (Figure 4).
Figure 1. Bainbridge Island communitywide emissions in 2018 (total = 233,998 MTCO2e).
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Figure 2. Per-capita GHG emissions comparison.2
Overall, communitywide emissions have increased by 9% since 2014 (Figure 5). Per-capita emissions,
however, only increased 1% over that period, suggesting that population growth contributed to the
observed trends. Changes in electricity fuel source (e.g., renewables versus coal) and growth in
employment also pushed emissions upward, while improvements in vehicle fuel economy, reductions in
the distance each person drives, and declining per-household and per-business energy consumption on
Bainbridge Island softened the extent of those increases.
Figure 3. Bainbridge Island community emissions trends, by year and source.
2 Other jurisdictions may use different data sets, methods, and years for their GHG emission inventories.
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City Government Emissions
Emissions from City of Bainbridge Island activities—which make up about 1% of the total community
emissions—increased 11% from 2014 to 2018, totaling 2,291 MTCO2e in 2018 (Figure 7 and Figure 8).
Major emissions sources included facility electricity consumption (60%) and on-road fleet vehicles (17%).
Emissions from municipal facility electricity and on-road fleet vehicles increased 14% and 7%,
respectively. Just four facilities accounted for 80% of all facility electricity use in 2018: Bainbridge Island
Waste Water Treatment Plant (WWTP), City Hall, Fletcher Bay: Well Field, and Bainbridge Island Public
Works Operations and Maintenance Yard. Among the largest emissions decreases were from streetlights
and traffic signals improvements.
Figure 4. City operations GHG emissions in 2018 (total = 2,291 MTCO2e).
Figure 5. Bainbridge Island city operations emissions trends, by year and source.
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Consumption-based Emissions
The purchasing decisions we make impact the environment. Some types of foods and materials, such as
meat and furniture, can carry a significant GHG emissions burden. For example, meat and dairy cows
emit methane—a potent greenhouse gas. Residents in Bainbridge Island who consume beef contribute
to the emissions from these cows—even if the cows are raised outside the island.
Results from a household-based economic modeling tool suggest that the average Bainbridge Island
household emits 52 MTCO2e a year through their purchasing behaviors.3 There were an estimated 9,404
and 9,798 households on Bainbridge Island in 2014 and 2018, respectively, indicating that total
consumption-based emissions from all households on Bainbridge Island could have reached
approximately 510,000 MTCO2e in 2018. Major drivers include the purchase of meat, furniture, clothing,
home energy, and travel-related expenses such as car fuel and air travel.
Figure 6. Consumption-based emissions per Bainbridge Island household.
3 As indicated from U.C. Berkeley’s CoolClimate Calculator. Outcomes from the consumption-based inventory
analysis are presented at the per-household level because purchasing behavior is typically examined and analyzed
at the household—not individual—level.
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Next Steps
In analyzing the GHG emissions of Bainbridge Island, this report identifies key activities and sectors at
both citywide and municipal operations scales that contribute the largest relative amounts of GHG
emissions. Drawing from the results in this report, activities and operations can then be targeted for
improvement and mitigation. Improving the inventory process, conducting regular inventories, and
incorporating these inventory results into decision-making processes will be critical for evaluating
progress toward emissions reductions targets and for identifying cost-saving opportunities in the future.
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Introduction
This GHG inventory report for the City of Bainbridge Island details estimated GHG emissions from
activities within the city of Bainbridge Island. GHG inventories quantify emissions associated with a
specific “scope”—or boundary condition—over a specific period. By conducting GHG inventories at
regular intervals, they can illuminate trends, accomplishments, and opportunities for improvement. They
also hold governments and communities responsible for their impact on the environment and keep
organizations on track towards reaching climate action goals.
This report describes findings from three distinct inventories (Figure 10):
• A community inventory that estimates GHG emissions produced by activities of the Bainbridge
Island community, including residents and businesses. The community GHG inventory includes
emissions due to energy used to power and heat homes and businesses; fuel used by vehicles
running within Bainbridge Island; solid waste that is generated by the community; agriculture
activities; fuel use by off-road equipment and vehicles; and others.
• A municipal inventory that accounts for the GHG emissions resulting from City of Bainbridge
Island government operations. This inventory can help the City understand GHG emissions
stemming from various activities associated with municipal operations, including from municipal
building and facility operation, transportation, solid waste, wastewater, and refrigerant leakage.
• A consumption-based inventory that estimates GHG emissions associated with the consumption
of food, goods, and services within the community, regardless of their origin. For example, this
inventory would not include emissions from the production of locally-manufactured goods that
are consumed entirely outside the community; however, it would include emissions associated
with the production of goods manufactured in another community but consumed by Bainbridge
Island residents, visitors, or businesses. This inventory can be examined in context with the
community inventory to paint a more comprehensive picture of community emissions.
This report also presents findings from additional analyses:
Municipal and communitywide contribution analyses that identify key drivers of observed emission
trends. For example, analysis calculates the impact that a hotter summer or colder winter may have
had on household energy use, and thus, emissions.
A supplemental carbon sequestration analysis that estimates the amount of carbon dioxide that
Bainbridge Island trees absorb—or sequester—from the atmosphere on an annual basis (in
Appendix).
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Figure 7. Conceptual relationship among community, government, and consumption-based inventories for Bainbridge Island.
GREENHOUSE GAS INVENTORY OVERVIEW
Inventory Methodology
The GHG inventories summarized in this report account for human-caused emissions of the most
prominent and typical greenhouse gases for communities: carbon dioxide (CO2), methane (CH4), and
nitrous oxide (N2O). To account for the differences in potency among these gases, all emissions are
calculated and reported in units of metric tons of carbon dioxide equivalent (MTCO2e). The inventories
were conducted using widely accepted tools and protocols, including The Climate Registry’s Local
Government Operations Protocol, ICLEI’s U.S. Community Protocol for Accounting and Reporting of
Greenhous Gas Emissions, and U.C. Berkeley’s CoolClimate Calculator.
GHG emissions are inventoried by multiplying annual activity data (e.g. electricity consumption) by
emission factors (greenhouse gas emissions produced per kWh of electricity). For the municipal
operations inventory, we obtained most data from City staff and local documentation such as Puget
Sound Energy's (PSE) billing records, records from local wastewater treatment facilities, and fleet vehicle
fuel use records. For the communitywide inventory, key data sources included electricity consumption
data from PSE, Puget Sound Regional Council (PSRC) modeling outputs for vehicle miles traveled by fuel
type, Bainbridge Disposal tonnage records, and Kitsap County Conservation District estimates of
agricultural landowners and acreage. Where local data were not available, we referenced and
downscaled national data sources such as from the Federal Transit Administration, U.S. Census Bureau,
and the U.S. Department of Agriculture.
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Inventory Boundaries
The activities and sectors included in GHG inventories are often classified into three “scopes,” which
represent relative levels of control over an emissions source (see Figure 8 and Figure 9):
Scope 1 emission sources include those directly caused by an organization’s actions, such as from
owned equipment and facilities.4
Scope 2 emissions are those indirectly associated with purchased electricity, steam, heating, or
cooling.
Scope 3 includes all other indirect emissions that are not covered in Scope 2.
The communitywide and municipal inventories for Bainbridge Island included emissions sources from all
three scopes: Scope 1, Scope 2, and Scope 3. The inventories included all sources required by the
consulted protocols and additional sources, as relevant.
Figure 8. Sources and boundaries of municipal GHG emissions.5
4 Except direct carbon dioxide emissions from biogenic sources.
5 The Climate Registry. (2010). Local Government Operations Protocol: For the quantification and reporting of
greenhouse gas emissions inventories.
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Figure 9. Sources and boundaries of community GHG emissions.6
6 World Resource Institute (2014). Greenhouse Gas Protocol: Global protocol for community-scale greenhouse gas
emission inventories.
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The tables below summarize sectors included in the municipal and communitywide inventories.
Table 1. Community inventory emissions sources and scope categories.
Emissions Type Required? Scope 1 Scope 2 Scope 3
Residential Energy
Electricity
Propane
Fuel Oil
Commercial Energy
Electricity
Propane
Industrial Energy
Electricity
Propane
Transportation
On-Road Passenger Vehicles
On-Road Freight Vehicles
On-Road Transit Vehicles
Off-Road Vehicles and Equipment
Air Travel
Ferry Travel
Solid Waste, Potable Water, and Wastewater
Solid Waste
Potable Water Use Energy*
Wastewater Treatment
Refrigerant Leakage
Agriculture
* Potable water use energy—energy associated with treating and distributing potable water systems on the Island
(e.g., from pumping stations)—is included in the non-residential energy consumption sector. Energy used for
pumping individual wells is included in the residential energy consumption sector.
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Table 2. Municipal inventory emissions sources and scope categories.
Emissions Type Required? Scope 1 Scope 2 Scope 3
Buildings and Facility Energy
Electricity
Propane
Streetlights and Traffic Signals
Transportation
On-Road Fleet Vehicles
Off-Road Vehicles
Employee Commute
Business Travel
Solid Waste, Potable Water, and Wastewater
Solid Waste
Potable Water Use Energy
Wastewater Treatment
Refrigerant Leakage
Table 3. Consumption-based inventory emissions sources and scope categories.
Emissions Type Required? Scope 1 Scope 2 Scope 3
Consumption-Based Emissions Household Consumption
City Government Consumption
Upstream Energy
Inventory Years
To provide Bainbridge Island with the most up-to-date information on their GHG emissions, we selected
the most recent year available as an inventory year: 2018. For a comparison year, we selected 2014
because no major changes in organizational structure or infrastructure occurred after that year. For
example, the wastewater treatment facility update was completed before 2014, so those changes would
be reflected in the 2014 inventory, enabling a more apples-to-apples comparison with 2018. Other
factors in that deciding the inventory years include:
Data availability: The availability of City data is scarcer further in the past.
Data consistency: Some data were either modeled differently or organized differently in the past
(i.e., methodologies changed over the last decade). Having a more recent baseline better ensures
more of accurate comparison over time.
Relevance: Choosing a more recent comparison inventory year allows for a more productive
assessment of trends over time to inform climate action planning. For example, if the baseline year
of 1990 was chosen it would be difficult to understand distinct drivers of changes between 1990 and
2019 due to the many interim changes that occurred within that time frame.
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ROADMAP OF THIS REPORT
This report is organized into the following sections to assess GHG emissions associated with Bainbridge
Island:
The Communitywide Emissions section presents methodologies and results for community-based
inventory.
The Communitywide Contribution Analysis section explores the drivers of communitywide emission
trends.
The Municipal Operation Emissions section presents methodologies and results for municipal-based
inventory.
The Municipal Contribution Analysis section that explores drivers of municipal operation emission
trends.
The Consumption-Based Emissions section presents methodologies and results from the
consumption-based inventory.
Each inventory section is organized as follows:
Results section presents GHG inventory results for the study years. The results are quantified and,
where relevant, summarized for trends between the two inventory years.
Data Sources and Methodology section details the sources of inventory information by sector, with
calculation methodologies, where relevant. The section also describes any data limitations or
considerations.
The report concludes with a summary of the major trends across all the inventories and future
considerations for climate action planning.
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Communitywide Emissions
The communitywide GHG emissions inventory estimates GHG emissions from individuals, businesses,
and commercial and industrial processes within Bainbridge Island. It also includes emissions associated
with some residential and business activities that occur outside of Bainbridge Island, such as from
electricity generation and solid waste transport to an out-of-state landfill.
Overall communitywide emissions are provided in units of metric tons of carbon dioxide equivalent
(MTCO2e). Table 5 below outlines the various emissions sources included in the communitywide
inventory, along with their corresponding scope. The table also shows which sectors are required by the
U.S. Community Protocol.
Table 4. Community inventory emissions and scope categories.
Emissions Type Required? Scope 1 Scope 2 Scope 3
Residential Energy
Electricity
Propane
Fuel Oil
Commercial Energy
Electricity
Propane
Industrial Energy
Electricity
Propane
Transportation
On-Road Passenger Vehicles
On-Road Freight Vehicles
On-Road Transit Vehicles
Off-road Vehicles and Equipment
Air travel Ferry
Solid Waste, Potable Water, and Wastewater
Solid Waste
Potable Water Use Energy*
Wastewater Treatment
Other Process & Fugitive Emissions
Agriculture
* Potable water use energy—energy associated with treating and distributing potable water systems on the Island
(e.g., from pumping stations)—is included in the non-residential energy consumption sector. Energy used for
pumping individual wells is included in the residential energy consumption sector.
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RESULTS
Overview
Bainbridge Island’s communitywide emissions in 2018 totaled 233,998 MTCO2e—equivalent to 9.4
MTCO2e per resident. Residential energy (37%) was responsible for the greatest proportion of
communitywide emissions, followed by non-residential energy (14%), air travel (13%), and on-road
vehicles (12%) (see Figure 11).
Figure 10. Bainbridge Island community emissions by source, 2018 (total = 233,998 MTCO2e)
Communitywide GHG emissions increased by 9% from 2014 to 2018 (see Figure 12, Table 6, and Figure
13). These increases are primarily due to changes in electricity fuel sources (e.g., proportion of coal in
the utility fuel mix) and growth in population and employment. Improvements in vehicle fuel economy,
reductions in the distance each person drives, and declining per-household and per-business energy
consumption all reduced the extent of this increase. Although communitywide emissions have increased
by 9%, per capita emissions have increased only slightly—by 1% (see Figure 12).
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Figure 11. Bainbridge Island community emissions, by year and source and resident. Major sources are labeled.
Table 5. Communitywide emissions, by sector.
GHG Emissions by Sector (MTCO2e) 2014 2018 Change % Change
Residential Energy 84,885 94,810 9,925 12%
Electricity 75,363 85,898 10,535 14%
Propane & Fuel Oil (Residential, Commercial, and Industrial) 5,912 5,274 -638 -11%
Losses from transmission & distribution 3,610 3,638 28 1%
Non-Residential Energy 31,162 33,277 2,115 7%
Electricity 29,738 31,925 2,187 7%
Losses from transmission & distribution 1,424 1,352 -73 -5%
Transportation 75,315 80,778 5,463 7%
On-Road Passenger & Freight Vehicles 27,448 27,330 -118 0%
On-Road Transit Vehicles 590 781 191 32%
Air Travel 24,023 31,002 6,979 29%
Ferry Travel 14,051 11,334 -2,716 -19%
Other Off-Road Vehicles and Equipment 9,204 10,331 1,127 12%
Solid Waste & Wastewater Treatment 10,503 11,470 968 9%
Solid Waste 8,369 9,289 920 11%
Wastewater Treatment 48 51 3 7%
Septic Tanks 2,086 2,131 45 2%
Other Process & Fugitive Emissions 12,209 13,332 1,123 9%
Agriculture 351 331 -20 -6%
Enteric Fermentation 319 297 -22 -7%
Manure Management 33 34 2 5%
TOTAL 214,425 233,998 19,574 9%
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Figure 12. Bainbridge Island community emissions by source and scope, 2018.
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Residential Energy
Emissions from residential use of electricity, propane7, and fuel oil accounted for 41% (94,810 MTCO2e)
of total communitywide emissions in 2018, a 12% increase from 2014. Residential electricity use alone
makes up 37% of communitywide emissions; it also exceeds non-residential electricity use (see Figure
14).
Figure 13. Community building energy use, by sector and year.
Electricity
Emissions from residential use of electricity increased from 75,363 MTCO2e in 2014 to 85,898 MTCO2e in
2018, a 14% change. One contributing factor is that the consumption of electricity increased slightly
from 184,865,169 kWh in 2014 to 189,165,563 kWh in 2018, an increase of 2%. Additionally, Bainbridge
Island’s population increased 8% from 23,135 to 24,891.
Changes in the electricity fuel mix also contributed to increases in residential electricity emissions (see
Table 7). Puget Sound Energy (PSE) provides power to Bainbridge Island. Approximately two-thirds of the
power is from coal and hydroelectric generation. In 2017, the fuel mix was 38% coal, 33% hydroelectric,
21% natural gas, 6% wind, and 2% nuclear and other sources.8 In 2014, the fuel mix was 35% coal, 36%
hydroelectric, 20% natural gas, 3% wind, and 5% nuclear and other sources. Between 2014 and 2018,
Bainbridge Island residents significantly increased their participation in PSE’s Green Power Program. The
7 Propane amounts were derived from records that do not distinguish between residential, commercial, and
industrial use. Therefore, all Bainbridge Island propane usage—regardless of sector—is included within the residential summary of emissions.
8 Puget Sound Energy. Electricity Supply. www.pse.com/pages/energy-supply/electric-supply (accessed June 27,
2019). The emissions inventory for 2017 was used because the 2018 inventory was not yet available during the
time of study.
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2018 10% participation rate is among the highest in PSE’s service area. However, due to the complexities
of the electricity grid, the U.S. Community Protocol discourages consideration of renewable energy
participation in calculating communitywide GHG inventories (see text box).
Table 6. Puget Sound Energy (PSE) electricity generation fuel mix for 2014 and 2017.9
Electricity Generation Fuel Type 2014 2017
Biomass 0% 0%
Coal 35% 38%
Cogeneration 4% 0%
Geothermal 0% 0%
Hydro 36% 33%
Landfill Gas 0% 0%
Natural Gas 20% 21%
Nuclear 1% 1%
Other 0% 0%
Petroleum 0% 0%
Solar 0% 0%
Waste 0% 0%
Wind 3% 6%
9 Puget Sound Energy. Electricity Supply. www.pse.com/pages/energy-supply/electric-supply (accessed June 27,
2019). The emissions inventory for 2017 was used because the 2018 inventory was not yet available during the
time of study.
Green Power Purchases
Puget Sound Energy allows electricity users to enroll in a Green Power purchasing program to support
renewable energy generation in the region. When utility customers enroll in this program, they are
not paying for 100% renewable energy to be delivered directly to their home or business, but rather
for their utility to buy a certain amount of renewable energy as part of the utility’s overall fuel mix.
Because utility fuel mixes are used to calculate the GHG emissions of consumed electricity in a
community, the renewable energy purchases made through Green Power programs are already
included in the emissions calculations of the community GHG inventory. Therefore, accounting for
Green Power purchases separately within a GHG inventory risks double-counting the benefits of a
renewable energy system.
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Propane and Fuel Oil
Due to a lack in locally available usage data, consumption of residential propane and fuel oil were
estimated using data from local propane sales tax revenues, the U.S. Energy Information Administration
(EIA), and 2017 American Community Surveys (ACS). These estimations suggest that emissions from
residential use of propane10 and fuel oil totaled 5,912 MTCO2e in 2014 and 5,274 MTCO2e in 2018, an
11% decrease in four years. This decline is primarily due to a decrease in the number of households
using those fuel sources, including for cooking and heating.
Electricity Transmission and Distribution Losses
As electricity travels from where it was generated, such as a hydroelectric dam or wind farm, to
individual homes, businesses, and other buildings, some of the electricity is naturally lost over power
lines and in substations and transformers. The proportion of the total electricity initially generated that is
lost through these processes in a given year and region is known as the “grid loss” factor. This grid loss
proportion can change from year-to-year based on a number of factors, including weather, transmission
distance, power line size, and transmission voltage. Although lost electricity is not ultimately delivered to
the consumer, it still results in the emission of greenhouse gases. We estimate that emissions from
transmitting and distributing residential electricity to Bainbridge Island residents increased slightly from
3,610 MTCO2e in 2014 to 3,638 MTCO2e in 2018—a less than 1% change. These changes are a result of
changes to the amount of electricity consumed and the “grid loss” factor of PSE infrastructure.
Non-Residential Energy
The non-residential energy sector includes greenhouse gas emissions from commercial and industrial
electricity; losses due to the transmission and distribution of that electricity; and energy associated with
treating and distributing potable water (e.g., from pumping stations). Commercial and industrial propane
consumption emissions are included within the residential emissions sector, as the source data did not
distinguish between different use sectors.
Electricity and Transmission and Distribution Losses
Emissions from commercial and industrial electricity accounted for 14% (31,925 MTCO2e) of total
communitywide emissions in 2018, making it the second-largest source along with air travel. Emissions
from commercial and industrial use of electricity increased from 29,738 MTCO2e in 2014 to 31,925
MTCO2e in 2018, a 7% change. The increase in emissions can be partially attributed to the increased
workforce from 8,224 to 8,943 employees, as well as from changes in the electricity fuel mix(see Figure
14 on page 23) Emissions from non-residential electricity transmission and distribution decreased
approximately 5%, from 1,424 MTCO2e in 2014 to 1,352 MTCO2e in 2018. These changes are a result of
changes in the amount of electricity consumed and the “grid loss factor” associated with PSE
infrastructure.
10 Propane amounts were derived from records that do not distinguish between residential, commercial, and
industrial use. Therefore, all Bainbridge Island propane usage—regardless of sector—is included within the
residential summary of emissions.
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Transportation
Transportation contributed over a third of Bainbridge Island community emissions in 2018, making it the
second-largest contributor to the community’s greenhouse gas emissions. In 2014, most transportation
emissions came from passenger and freight vehicles, followed by air travel. However, in 2018, this trend
shifted, with most transportation emissions coming from air travel followed by passenger and freight
vehicles (Figure 15). The rapid growth of Sea-Tac Airport explains this shift: there was a 30% increase in
landings at SeaTac International Airport between 2014 and 2018.11
Figure 14. Community transportation emissions in 2018 (total = 80,778 MTCO2e).
On-Road Vehicles
Most on-road vehicle emissions in Bainbridge Island stem from passenger cars. Downscaled modeling by
the Puget Sound Regional Council suggests that passenger vehicles traveled over 69 million miles in
Bainbridge Island in 2018 (Table 8 and Figure 16).
Table 7. Annual vehicle miles estimated for Bainbridge Island.
Type 2014 2018 Change
Passenger vehicle 66,612,870 69,543,904 4%
Medium truck 3,011,067 2,993,763 -1%
Heavy Truck 708,280 708,118 0%
Transit bus* 394,450 397,634 1%
*Miles for transit buses are in annual revenue miles.
11 Air travel emissions from Bainbridge residents were attributed by downscaling total fuel use at Sea-Tac Airport to
the Bainbridge Island community based on population. More information can be found in the “Data Sources and
Methodology” section of this report.
CITY OF BAINBRIDGE ISLAND | 2019 | 26
Figure 15. Distribution of on-road vehicle miles traveled, by vehicle type.
Transportation data are typically recorded as vehicle miles traveled, or VMT. VMT is the total number of
miles driven by motorized vehicles of specific types. Although the model used to estimate GHG
emissions by VMT and vehicle type does not separately note hybrids and electric vehicles, these vehicles
are subject to the same emissions standards as conventional gasoline or diesel vehicles. As such, hybrid
and electric vehicle VMT are incorporated into the average emissions factors used for each vehicle type
and model year, despite not being reported separately from general passenger vehicles.
Despite a 4% increase in VMT for passenger vehicles between 2014 and 2018, emissions from on-road
vehicles increased minimally—by 0.3%. The increasing average fuel economy of passenger vehicles
accounts for this minimal change (Figure 16).
We estimate that transit vehicle emissions increased 32% between 2014 and 2018, rising from an
estimated 590 MTCO2e in 2014 to 781 MTCO2e in 2018. As reported by Kitsap Transit to the Federal
Transit Administration, annual revenue miles remained relatively constant between the two inventory
years—only increasing 1%. This trend suggests that increased transit emissions may be the result of
incomplete reporting, decreased fuel economy, and/or increased use of high emitting fuels. The report
indicates that Kitsap Transit activities in 2018 included more gasoline use for vanpool vehicles and a shift
to liquified petroleum gas for paratransit (demand response) vehicles.
Off-Road Vehicles & Equipment
This inventory categorizes off-road vehicles and equipment into three categories: ferry travel, air travel,
and other off-road vehicles and equipment. Other off-road vehicles and equipment includes emissions
from vehicles and equipment used for agriculture, construction, lawn/gardening, and recreation such as
boating.
CITY OF BAINBRIDGE ISLAND | 2019 | 27
Ferry Travel
Emissions from ferry travel decreased from 14,051 MTCO2e in 2014 to 11,334 MTCO2e in 2018, an overall
decrease of 19%. This decrease is a result of a large reduction in fuel consumption by Washington State
ferries traveling the Seattle-Bainbridge Island route. In 2014, we estimate that Bainbridge Island’s share
of ferry travel accounted for the consumption of 2.7 million gallons of fuel, compared to 2.2 million
gallons in 2018.
Air Travel
We estimate that air travel contributed 13% to communitywide emissions, making it the largest source
of off-road GHG emissions and second-largest source of emissions overall (tied with non-residential
energy). Emissions from air travel increased 29%, from an estimated 24,023 MTCO2e in 2014 to 31,002
MTCO2e in 2018. This increase is largely attributable to population growth on Bainbridge Island and a
30% increase in total landings at SeaTac International Airport between 2014 and 2018. Our calculations
are based on available jet fuel usage data (from 2015), which were scaled by the proportion of landings
at SeaTac International Airport. Bainbridge Island’s population and businesses make up approximately
0.5% of the four-county area that SeaTac predominantly serves (King, Kitsap, Pierce, and Snohomish
counties).
Other Off-Road Vehicles & Equipment
We estimate that emissions from other off-road equipment accounted for 4% of overall emissions in
Bainbridge Island in 2018 (10,331 MTCO2e). Most of these emissions—which are estimated by scaling
county-level model outputs to Bainbridge Island based on population—are generated by construction
equipment, lawn and garden equipment, and pleasure watercraft.
Solid Waste and Wastewater
Solid Waste
Most emissions from the disposal of solid waste are associated with the release of methane from
decomposing waste in the landfill (see Figure 17 and Table 9). Emissions from waste disposal increased
from 5,527 MTCO2e in 2014 to 6,134 MTCO2e in 2018, an 11% change that is largely due to population
growth and associated increases in tons disposed. Based on waste characterization studies from Kitsap
County, King County, and Washington State, the composition of waste over time remained relatively
constant. Approximately two-thirds of disposed waste is mixed solid waste, and about one-quarter is
food scraps.
All of Bainbridge Island’s waste is transported off-Island, first in trucks to the Olympic View Landfill in
Bremerton then via train to the Columbia Landfill near Arlington, Oregon. We estimate that emissions
from waste transportation increased from 2,352 MTCO2e to 2,611 MTCO2e. This is associated with the
rise in waste collected and transported, which grew from an estimated 22,616 tons in 2014 to 25,102
tons in 2018.
Emissions from equipment used at the landfill to process waste and from yard waste composting make
up a nominal proportion of the Island’s solid waste emissions. We estimate that the diesel-powered
CITY OF BAINBRIDGE ISLAND | 2019 | 28
equipment at Columbia Landfill generated 371 MTCO2e and 412 MTCO2e in 2014 and 2018, respectively.
In 2018, Bainbridge Disposal reported 1,900 tons of yard waste were composted, which generated 132
MTCO2e.
Figure 16. Solid waste emissions in 2018, by source.
Table 8. Summary of solid waste emissions, by process.
Process Emissions (MTCO2e)
2014 2018 Difference
Solid Waste Disposal & Decomposition 5,527 6,134 +607
Yard Waste Composting 119 132 +13
Collection & Transportation to Landfill 2,352 2,611 +258
Processing with Equipment at Landfill 371 412 +41
Total 8,369 9,289 +920
Process Emissions by Weight
(MTCO2e/ton waste)
2014 2018 Difference
Solid Waste Disposal & Decomposition 0.244 0.244 —
Yard Waste Composting 0.070 0.070 —
Collection & Transportation to Landfill 0.104 0.104 —
Processing with Equipment at Landfill 0.016 0.016 —
Total 0.344 0.344 —
CITY OF BAINBRIDGE ISLAND | 2019 | 29
Wastewater Treatment
The combined emissions from wastewater treatment (process and effluent emissions) and fugitive
emissions12 from septic sources contributed to 1% of communitywide emissions in 2018. This small
proportion is associated with an overall 2% increase in emissions from these sources, from 2,134
MTCO2e in 2014 to 2,182 MTCO2e in 2018 (see Table 10). This increase is due to population growth and
the associated increase in waste generated and processed (calculations for emissions from septic tanks
were scaled based on Bainbridge Island population trends and calculating emissions from WWTP also
accounted for population growth).
Table 9. Emissions from wastewater treatment and septic tanks (MTCO2e).
Source Emissions (MTCO2e)
2014 2018 Difference % change
WWTP Process 13 14 +1 +7%
WWTP Effluent 35 37 +2 +7%
Septic Tanks 2,086 2,131 +45 +2%
Total 2,134 2,182 +48 +2%
Other Process & Fugitive Emissions
Emissions from other processes and fugitive sources—including hydrofluorocarbons (HFCs),
perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)–contributed 6% of Bainbridge Island’s
communitywide emissions in 2018.13 Emissions from HFCs—a common refrigerant used in refrigeration
and air conditioning—comprised nearly all of these emissions (99%; 13,234 MTCO2e).
We estimate that emissions from HFCs and PFCs increased 10% between 2014 and 2018, from 12,061
MTCO2e to 13,237 MTCO2e. This increase is driven by population growth, as emissions were scaled down
by population from national-level emissions due to lack of locally available data.
Fugitive emissions from leaks of SF6 in electricity transmission and distribution operating equipment
declined an estimated 36%, from 147 MTCO2e in 2014 to 95 MTCO2e in 2018. Our calculations are based
on data reported by PSE in their 2014 and 2017 GHG inventories, scaled down to the 1% of customers
Bainbridge Island represents within PSE’s service area.
Data on process and fugitive sources such as HFC, PFC, and SF6 emissions at city scales are scarce. The
U.S. EPA’s 2019 Inventory of GHG Sources and Sinks was used as a proxy and the data was scaled to
Bainbridge Island’s population. Estimating emissions from process and fugitive sources can be highly
uncertain. Factors vary between individual pieces of equipment. Even if the leak rate of a piece of
equipment has been tracked carefully, that leak rate can change after the leak is repaired or as the
12 Fugitive emissions are from leaks.
13 Fugitive emissions are those that are not physically controlled but result from the intentional or unintentional
release of GHGs. They commonly arise from the production, processing, transmission, storage and use of fuels or
other substances, often through joints, seals, packing, and gaskets. Examples include HFCs from refrigeration leaks,
SF6 from electrical power distributors, and CH4 from solid waste landfills.
CITY OF BAINBRIDGE ISLAND | 2019 | 30
equipment ages. For example, equipment can leak for two or more years before requiring a recharge, so
emissions over this timeframe are typically not detected until after they occur.
Table 10. Summary of emissions from other processes and fugitive sources.
GHG Emissions (MTCO2e)
2014 2018 Difference % change
HFC 12,058 13,234 +1,176 +10%
PFC 3 3 0 0%
SF6 147 95 -53 -36%
Total 12,209 13,332 +1,123 +9%
Agriculture
The Kitsap County agricultural census reported 11,483 and 12,539 livestock animals in 2012 and 2017,
respectively. To determine what proportion of livestock animals were on Bainbridge Island during these
years, we scaled agricultural census data for Kitsap County to Bainbridge Island based on land area.
Using this methodology, we estimate that Bainbridge Island had 803 and 875 livestock animals in 2014
and 2018; representing a 9% increase in animals between the two years.
While the total animal population increased on the Island, we estimate that the number of cattle
decreased by 12%. This decline drove estimated reductions in enteric fermentation emissions—the
release of methane (CH4) as livestock digest food—of 7%, from 319 MTCO2e in 2014 to 297 MTCO2e in
2018.
Emissions from manure management increased 5%, from 33 MTCO2e in 2014 to 34 MTCO2e in 2018,
driven by the overall increase in livestock animal population.
Table 11. Agricultural acres and population trends, by livestock.
Animal Population
2014 2018 % change
Horses 98 100 +2%
Sheep 41 82 +100%
Goats 35 44 +26%
Cattle 92 81 -12%
Poultry 517 538 +4%
Swine 20 30 +50%
Total 803 875 +9%
CITY OF BAINBRIDGE ISLAND | 2019 | 31
DATA SOURCES AND METHODOLOGY
We followed the U.S. Community Protocol (Version 1.1) to complete the communitywide emissions
inventory for 2014 and 2018, using the U.S. EPA’s GHG Inventory Sources and Sinks Annexes for 2014 and
2019 and the IPCC’s 5th Assessment Report (AR5) for updated GWPs and emissions factors where
available. All emissions were calculated in ClearPath and were based on verified local data when they
were available. When local data were not available, data inputs were scaled down from Kitsap County,
King County, or national datasets. Most data were deemed medium quality due to assumptions about
local data.
Completing this inventory involved acquiring the following data, summarized in Table 13 and detailed in
the followed sections:
Activity data that quantifies levels of activity that generate greenhouse gas emissions, such as
vehicle miles traveled, and tons of waste generated.
Emission factors that translate activity levels into emissions.
Data quality is assessed and reported on a High (H), Medium (M), and Low (L) scale in accordance with
GHG inventory best practices:
A High rating indicates data are detailed and specific to the local geography
A Medium rating indicates data are more general or modeled with robust assumptions and may not
be specific to the local geography, but are downscaled from a slightly broader geography (e.g., state-
level)
A Low rating indicates data are highly modeled, uncertain, or a default value was used based on
national characteristics.
Table 12. Key data sources for the City of Bainbridge Island's communitywide inventory.
Sector Activity Data (AD) AD
Quality
Emissions Factors (EF) EF
Quality
Residential Energy
Electricity • Overall kWh consumption from the
three substations serving the Island
• Residential proportion based on
sample of customer data in 2014
and 2018
H
• PSE reported emissions
factors (PSE Greenhouse Gas
Inventory, 2014 & 2017,
Table 7.1) H
Stationary Fuel
Combustion
• Local propane sales tax information
for Bainbridge Island (2014 and
2018)
• EIA’s average propane price per
gallon of fuel for 2014 and 2018.
M
• Emissions factors provided in
ClearPath program M
Electricity
Transmission &
Distribution Losses
• See “Electricity”
• eGRID Western region grid gross
loss percentage (2014 and 2016) M
• PSE-reported emissions
factors (PSE Greenhouse Gas
Inventory, 2014 & 2017,
Table 7.1)
H
CITY OF BAINBRIDGE ISLAND | 2019 | 32
Sector Activity Data (AD) AD
Quality
Emissions Factors (EF) EF
Quality
Non-Residential Energy
Electricity • kWh consumption from the three
substations serving the Island
• Non-residential proportion based on
sample of customer data in 2014
and 2018
H
• PSE reported emissions
factors (PSE Greenhouse Gas
Inventory, 2014 & 2017,
Table 7.1) H
Electricity Transmission & Distribution Losses
• See “Electricity”
• eGRID Western region grid gross
loss percentage (2014 and 2016) M
• PSE reported emissions
factors (PSE Greenhouse Gas
Inventory, 2014 & 2017,
Table 7.1)
H
Transportation
On-Road Vehicles • Annual miles traveled, by vehicle and fuel type, provided by EPA MOVES analysis of travel model data, for proportion of Kitsap County VMT occurring in Bainbridge Island
• Annual revenue miles traveled and
fuel consumption by type provided
by National Transit Database for
Kitsap County, then scaled down to
Bainbridge Island by population
M
• CO2, CH4, and N2O emission factors are defaults from the U.S. Community Protocol
L
Off-Road Vehicles
& Equipment • Emissions by off-road sector and
fuel type, along with days of use per
year, provided by nonroad module
of the EPA MOVES model, for
proportion of Kitsap County activity
occurring in Bainbridge Island
M
• CO2, CH4, and N2O emission
factors are defaults from the
U.S EPA MOVES nonroad
model L
Air travel • 2015 Jet fuel consumption from Port
of Seattle, scaled to target years by
total landings and to the Island by
population/employment
M
• CO2, CH4, and N2O emission
factor defaults from
ClearPath H
Ferry travel • Ferry fuel price, from EIA, and cost,
from WSDOT M • CO2, CH4, and N2O emission
factor defaults from
ClearPath H
Solid Waste and Wastewater
Solid Waste Generation • Single-family waste tonnages from
Bainbridge Disposal
• Multi-family + commercial tonnages estimated from ratio of single-family to multi-family + commercial from 2015-2016 WA Waste Characterization Study, for Kitsap County
• Landfill methane collection scenario
confirmed “typical” by Columbia
Landfill
• Annual precipitation from National Weather Service, Arlington, OR
M
• Waste characterizations
from 2015-2016 WA Waste
Characterization Study, for
Kitsap County
• Waste characterization was comparable across Port Orchard samples and the Puget Sound-wide data from the aforementioned study; there was also little difference compared to King County compositions, which were assessed as a reference
M
CITY OF BAINBRIDGE ISLAND | 2019 | 33
Sector Activity Data (AD) AD
Quality
Emissions Factors (EF) EF
Quality
Solid Waste
Collection &
Transportation
• Mass of solid waste from Bainbridge
Disposal, with multi-family +
commercial estimated from Kitsap
County ratio of single-family to
multi-family + commercial (see
above)
• Mileage from Google maps
M
• Default EF from ClearPath
L
Yard Waste
Composting • Yard waste tonnage from Bainbridge Disposal for 2018; extrapolated for
2014 using 2014:2018 single-family
solid waste ratio
M
• Default EF from ClearPath
L
Landfill Processing • Mass of solid waste from Bainbridge Disposal, with multi-family + commercial estimated from Kitsap County ratio of single-family to multi-family + commercial (see above)
• Fuel type for equipment confirmed
by Columbia Landfill
M
• Default EF from ClearPath
L
Wastewater Treatment Facility • Wastewater treatment facility
processes determined based on
desktop research and confirmed
with City staff
• Population served by wastewater
treatment facility estimated by
multiplying the number of sewer
connections by the average
household size from ACS
M
• Default EF from ClearPath
• CH4 emissions were not
applicable since the system is
aerobic L
Septic Tanks • Population data estimated based on
number of septic systems reported
to the Department of Health and the
number of sewer connections in the
community. M
• Default EF from ClearPath
• Fugitive emissions calculated
using Community Protocol
WW.11 Alternative Method
for Methane Emissions from
Septic Systems if Only the
Population is Known
L
Refrigerant Leakage
Refrigerant Leakage from Building Heating and Cooling Equipment, and Fugitive Emissions from Electricity Generation & Transmission
• HFC and PFC tonnage from Annex 6
in U.S. EPA GHG Inventory Sources
and Sinks, scaled down to
Bainbridge Island population
• SF6 tonnage and customer data from PSE, scaled down to Bainbridge Island customers
L
• HFC and PFC GWP from IPCC
5th Assessment Report, with
adjustment for climate-
carbon feedback
• SF6 100-Year GWP from U.S. EPA GHG Sources and Sinks
• Emissions calculated using
Community Protocol
Alternative Method BE.7.1.A
H
CITY OF BAINBRIDGE ISLAND | 2019 | 34
Sector Activity Data (AD) AD
Quality
Emissions Factors (EF) EF
Quality
Agriculture
Enteric
Fermentation and
Manure
Management
• Animal population and pastureland
from USDA Agricultural Census, for
Kitsap County
• Agricultural acres with livestock on
Bainbridge Island and waste
management system, from Kitsap
County Conservation District
• Typical animal mass and Bo from
U.S. EPA GHG Inventory Sources &
Sinks, 2017 Annexes
• Volatile solids and excreted nitrogen
from U.S. EPA GHG Inventory
Sources & Sinks, 2014 and 2017
Annexes
• Methane conversion factors from Inventory of U.S. Greenhouse Gas Emissions and Sinks 1990-2017, with annual average temperature from Climate Bremerton
M
• EF, 100-year GWP for CH4 and N2O, and volatilization
nitrogen loss from U.S. EPA
GHG Inventory Sources &
Sinks, 2017 Annexes
• EF for nitrogen volatilization
and runoff/leaching from
U.S. Community Protocol,
Appendix G
• Indirect N2O emissions calculated using U.S Community Protocol, Appendix G
M
The U.S. Community & Local Government Operations Protocols
The U.S. Community and Local Government Operations Protocols were built to provide easily applicable and
accurate community-level and municipal estimates of GHG emissions. These protocols provide a consistent
framework in which to compare emissions from a geographic or operational boundary across time. The U.S.
Community Protocol was designed for community-scale GHG accounting, making it a valuable tool for
counties and cities, and an appropriate choice for the City of Bainbridge Island. The U.S. Community and
Local Government Operations Protocols are widely used, understood, and respected.
These community and municipal inventories follow the U.S. Community and Local Government Operations
Protocol methodologies and deviate from their stated methods only when more precise, local data are
available, per Protocol recommendations. The Local Governments for Sustainability (ICLEI) created the U.S.
Community Protocol in 2013 and the Local Government Operations Protocol in 2010. The U.S. Community
Protocol requires, at a minimum, reporting of the following five activities: 1) Use of electricity by the
community 2) Use of fuel in residential and commercial stationary combustion equipment 3) On-road
passenger and freight motor vehicle travel 4) Use of energy in potable water and wastewater treatment
and distribution 5) Generation of solid waste by the community. These activities are required because they
represent the largest sources of GHG emissions for most communities and are activities that can be
impacted by local government actions. The Local Government Operations Protocol includes similar
reporting requirements with a focus on only those emission sources that are within the government’s
control and are the result of day-to-day operations.
CITY OF BAINBRIDGE ISLAND | 2019 | 35
Residential Energy
Data on electricity use were provided by the utility serving Bainbridge Island, PSE, and for
transmission and distribution losses, by eGRID.
Stationary fuel combustion consisted of residential fuel oil, with data from EIA and the number of
households from ACS.
Propane usage for residential, commercial, and industrial sectors was estimated using local sales tax
data and EIA information on average propane fuel prices per gallon.
Non-Residential Energy
Data on electricity use were provided by the utility serving Bainbridge Island, PSE, and for
transmission and distribution losses, by eGRID. PSE does not track commercial and industrial energy
separately, hence they were combined in this analysis.
Transportation
Vehicle miles traveled were derived from Puget Sound Regional Council’s MOVES analysis of travel
model data and account for all mileage within the Kitsap County boundary regardless of trip origin or
destination. Emissions for Bainbridge Island are assumed proportional to the share of Kitsap County
VMT occurring in Bainbridge Island city limits. Share of average weekday VMT occurring in
Bainbridge Island was calculated from 2014 travel model data and includes all vehicle types.
Bainbridge Island VMT shares represents all trips to/from Bainbridge Island as well as those driving
through the city boundaries. Year 2018 was extrapolated from the rates between 2014 and 2016.
The PSRC data reported VMT and emissions for passenger vehicles, medium trucks, heavy trucks,
and transit. In ClearPath, we reported medium trucks as light trucks.
Annual revenue miles and fuel consumption data for Kitsap County were acquired from the
National Transit Database from the Federal Transit Administration. These data were scaled down to
Bainbridge Island by population.
The Port of Seattle supplied jet fuel consumption data for SeaTac Airport for 2015, of which 0.5-1%
was attributable to Bainbridge Island. SeaTac passenger enplaning surveys and population and
employment statistics were used to assign the above fraction of the total airshed emissions to the
Bainbridge Island community. This allocation methodology means that communities with more
residents and business travelers are assigned a greater proportion of travel-related emissions at
SeaTac airport. We scaled 2015 jet fuel usage to 2014 and 2018 based on the total landings in those
years.
Ferry fuel consumption was derived from EIA data on diesel fuel price and from WSDOT data on the
reported fuel cost for the Bainbridge Island route in fiscal year 2015.
Off-road emissions were calculated from the nonroad module of the EPA MOVES model for 2014
and 2018. The model estimates emissions at the county level, which were then scaled down to
Bainbridge Island by population. Emissions include common non-road equipment, including
construction, agriculture, lawn/gardening, and recreational equipment.
CITY OF BAINBRIDGE ISLAND | 2019 | 36
Solid Waste and Wastewater
Bainbridge Disposal single-family tonnages and Kitsap County waste characterization data, along
with default emissions factors provided in ClearPath, were used to calculate emissions from waste
disposal and composting. Multi-family and commercial tonnages were not directly available and
were estimated using a single-family to multi-family + commercial ratio of 32:68, based on the
transfer station survey data collected for the 2015-2016 Washington Waste Characterization Study.
Waste characterization was comparable across Port Orchard samples and the Puget Sound-wide data
from the aforementioned study; there was also little difference compared to King County
compositions, which were assessed as a reference.
Landfill emissions assumed an 82.5% capture rate, based on Columbia Landfill’s confirmation of a
“typical” collection scenario and ClearPath’s associated capture rates.
Wastewater emission calculations required data from Kitsap County Sewer District #7 and the City of
Bainbridge Island wastewater treatment plants. City and District staff provided the data.
Data required for higher quality calculations in ClearPath, such as BOD5 or population specifically
using septic systems (including unpermitted systems), were not available. Therefore, fugitive septic
tank emissions were estimated based on the number of Bainbridge Island residents not served by a
sewer connection.
Ferry Emissions Attribution
Accounting for emissions related to ferry transportation can be complicated by the fact that ferries
typically travel between multiple jurisdictions. To simplify the methodology for calculating these
emissions, the U.S. Community Protocol recommends allocating portions of the total emissions
related to ferry transportation according to the number of stops located in each jurisdiction. For
example, for the Bainbridge Island-Seattle ferry, this would equate to a 50/50 split of emissions since
there is one ferry stop in each city. This is the calculation approach that was used in this community
inventory.
However, another possible method for attributing emissions to a particular jurisdiction is by ridership
and examining the proportion of ferry riders from each city. To test that the 50/50 allocation was the
correct choice for Bainbridge Island, we performed a sensitivity analysis using a ridership-based
methodology. Using data reported by Washington State, we assumed that where travelers were
heading in the evening on a weekday was likely where they reside. Based on this assumption and
available data, we examined the proportion of total ferry travelers that end in Bainbridge Island in the
evening versus elsewhere. Using this technique, we deduced that 47% of weekday ferry commuters
are residents of Bainbridge Island—a value that is very close to the original 50% estimate.
Given that this proportion strongly aligns with the 50/50 approach recommended by the U.S.
Community Protocol, we ultimately followed the U.S. Community Protocol attribution approach to
align with the robust and established methodology used by other communities in the region.
CITY OF BAINBRIDGE ISLAND | 2019 | 37
Other Process & Fugitive Emissions
Data on fugitive refrigerant HFC and PFC emissions at city scales is scarce. We used the U.S. EPA’s
2019 Inventory of GHG Sources and Sinks and scaled the data to Bainbridge Island by population.
GWP were adjusted to the latest available values in 2014 and 2018, which corresponded to the
values in the 4th and 5th Assessment Reports, respectively.
PSE’s greenhouse gas inventories from 2014 and 2017 provided fugitive electric transmission and
distribution emissions data for SF6. We scaled the data to Bainbridge Island using PSE customer data.
Agriculture
The USDA provides publicly available data on the number of animals by county, which was scaled
down to Bainbridge Island according to the ratio of livestock to land area. Kitsap County
Conservation District provided data on manure management systems. The EPA provides national-
level animal enteric and manure emissions factors, and state-level emissions factors for cattle.
CITY OF BAINBRIDGE ISLAND | 2019 | 38
Considerations
At the time of this inventory, not all communitywide data were available. Many calculations were scaled
from national or county estimates by population. ClearPath’s default emissions factors were used in
cases where local data were not available. There is always a certain level of uncertainty associated with
inventories, given constraints in data availability for most communities. However, the goal of performing
inventories is to attempt to accurately and precisely account for all sources of emissions using best
available data and unbiased methodologies. While ranges of uncertainty are typically not quantified, we
strive to use approaches that produce estimates that are neither conservative nor liberal in their
leanings, and are based on the most locally-specific and reputable data sources.
A list of data limitations and other considerations specific to Bainbridge Island’s communitywide
inventory is provided below.
Multi-family and commercial solid waste tonnage: Since tonnage data was not available, we
assumed a 32:68 ratio of single-family to multi-family and commercial waste, based on Port Orchard
transfer station surveys in 2015.
Yard waste composting tonnage: Bainbridge Disposal data was available for 2018. To derive 2014
yard waste composting tonnage, we calculated the 2018 ratio of single-family tonnage to yard waste
composting tonnage and applied the same ratio to 2014 single-family tonnage.
2018 VMT: PSRC data was available for 2014 and 2016. To derive 2018 VMT, we assumed a linear
rate of increase from 2014 to 2016 to 2018.
2014 and 2018 Annual Revenue Miles: We scaled Kitsap County data to Bainbridge Island according
to population, which may not accurately reflect public transit ridership on Bainbridge Island.
Septic tank fugitive emissions: In the absence of data on BOD5, we used the U.S. Community
Protocol WW.11 Alternative Method to calculate methane emissions when only total population is
known.
HFC and PFC tonnage: National data was available for 2014 and 2017 and was scaled down to
Bainbridge Island by population. We assumed semiconductor manufacture, and the production of
magnesium and aluminum, did not apply to Bainbridge Island and excluded contributions from those
sources. The PFC-Substitution of ODS value provided was “does not exceed 0.05”; 0.04 was used as
an estimate and may be an overestimate.
Air travel: We were not able to obtain fuel use data for 2018, so the air travel emissions were
estimated by using a scaling factor from 2015 fuel use data based on the total landings for 2014 and
2018.
Off-road vehicle and equipment: We used the EPA MOVES model to estimate off-road vehicle and
equipment emissions. The model estimates emissions at the county-level; we scaled Kitsap County
emissions to Bainbridge Island by population.
These considerations should be taken into account when interpreting findings from this inventory. We
also recommend that future inventories seek to address these data limitations, if possible.
CITY OF BAINBRIDGE ISLAND | 2019 | 39
COMMUNITY CONTRIBUTION ANALYSIS
Introduction
In 2014, Bainbridge Island’s 23,135 residents and 9,404 emitted approximately 214,425 MTCO2e. In
2018, the population increased 7% (24,891), the number of households increased 4% (9,798), and
communitywide emissions increased 9% (to 233,998 MTCO2e). Apart from population growth, what
drove that estimated change in emissions? We utilized the Analyzing Drivers of Change in Greenhouse
Gas Emissions Inventories tool available from ICLEI USA to attribute changes in the community
inventories to the economic, social and technological forces that influenced them.14
Results
The communitywide contribution analysis highlighted factors that lead to the most significant changes in
emissions between 2014 and 2018. The analysis revealed that changes to the PSE electricity fuel mix,
increased activity at SeaTac airport (and, thus, higher estimated air travel emissions), and growth in
population and employment all contributed to increases in emissions within the community. Conversely,
downward forces on emissions included reduced ferry fuel use and more efficient driving and energy
use. Figure 18 below shows the influences of the top three drivers on the two inventory years, plus a
category labeled “other”—a compilation of contributors illustrated in Figure 19.
Figure 17. High-level summary of major drivers of communitywide inventory increases and decreases.
14 ICELI USA Analyzing Drivers of Change in Greenhouse Gas Emissions Inventories tool. http://icleiusa.org/ghg-
contribution-analysis/ (Accessed July 1, 2019).
CITY OF BAINBRIDGE ISLAND | 2019 | 40
Figure 18. Detailed depiction of major drivers of inventory increases and decreases.
**Includes effects of population on residential energy, VMT and waste generation.
**After accounting for weather. This change is the net effect of factors that may include occupant behavior,
changes to building types and uses, federal appliance standards, utility programs and new electronic devices.
Specifically, contributors to inventory changes included the following, in order of highest increase to
lowest decrease:
• Electricity fuel mix (+10,542) describes changes to types of resources used to generate
electricity for the community. For example, increased use of renewable sources such as
hydroelectricity and solar and wind power would drive emissions decreases in the electricity fuel
mix. For Bainbridge Island, changes in the PSE electricity fuel mix contributed to increases in
electricity emissions.
• Growth in population (+6,581) includes the impacts of increased housing, driving, and waste
generation from Bainbridge Island’s growing population. Population grew 7.1% from 23,135
in 2014 to 24,891 in 2018.
• Not analyzed (+5,418) describes the emissions from multiple sources—including increases in
emissions from off-road vehicles, air travel, agriculture, wastewater, and refrigerant loss—
that are not explicitly linked to a variable available in the tool. Due to the calculation
CITY OF BAINBRIDGE ISLAND | 2019 | 41
methodology used to estimate emissions from these sources, many of these increases can
be linked to population growth, which was used as a scaling factor to estimate emissions.15
• Growth in employment (+2,583) describes the effect of increased job growth and GDP per
person on emissions. Economic growth leads to larger consumption of goods and services,
therefore resulting in emissions increases.
• Hotter summer (+499) is the increase emissions associated the enlarged strain on various
systems due to hotter temperatures during the summer, such as increased electricity and
energy consumption for residential and commercial cooling. The summer in 2018 was hotter
than in 2014.
• Colder winter (+366) is the increase emissions associated with the amplified strain on
various systems due to colder temperatures during the winter, such as increased electricity
and energy use for residential and commercial heating. The winter in 2018 was colder than
in 2014.
• Waste generation per person (-386) describes the impacts from change in the amount of
waste disposed per person. In Bainbridge Island, the growth of waste generation was slower
than that of population, which resulted in reduced per-person waste generation.
• Decreased VMT per person (-919) describes changes from people driving more or less in the
community. On average, each Bainbridge Island resident drove fewer miles, resulting in
emissions decreases.
• Decreased on-road emissions per mile (-1,061) represents changes in the amount of
emissions per vehicle mile driven. These changes could be due to better driving behavior or
more fuel-efficient vehicles.
• Decreased energy use per household (-1,687) denotes a decline in the amount of energy
used by the average Bainbridge Island household. This change could be due to more energy
efficient behaviors or appliances.
• Decreased commercial energy use per job (-3,754) incorporates the fact that job growth has
increased, but a large conversion of energy efficient standards has been made throughout
the commercial sector resulting in a decrease in emissions.
15 These sources are classified as “not analyzed” because population is used as a scaling factor to estimate
emissions for these sources, and therefore population growth is already “baked into” the estimation. Thus, it would
be inappropriate to group these sources with the “growth in population” driver.
CITY OF BAINBRIDGE ISLAND | 2019 | 42
Municipal Operation Emissions
The municipal operation emissions inventory accounts for the GHG emissions resulting from Bainbridge
Island City government operations. Bainbridge Island’s government provides a range of municipal
services including police, streets, planning, zoning, and general administration services. The City also
operates the water and wastewater utilities for a portion of the island.
Table 14 below provides an outline of the various emissions sources included in the municipal inventory,
paired with their respective Scope. The table also specifies which sectors are required by the Local
Government Operations Protocol.
Table 13. Municipal inventory emissions and scope categories.
Emissions Type Required? Scope 1 Scope 2 Scope 3
Buildings and Facilities Energy
Electricity
Stationary Fuel Consumption
Streetlights and Traffic Signals
Transportation
On-Road Fleet Vehicles
Off-Road vehicles
Employee Commute
Business Travel
Solid Waste, Potable Water, and Wastewater
Solid Waste
Wastewater Treatment
Refrigerant Leakage
RESULTS
Overview
Bainbridge Island’s 2014 municipal-based GHG inventory totaled 2,067 MTCO2e. Municipal emissions in
2018 increased 11% to 2,291 MTCO2e. Major emissions sources in 2018 included facility electricity
consumption (60%) and on-road fleet vehicles (17%) (see Table 15).
Transportation and electricity also contributed some of the largest increases in emissions from 2014 to
2018. Municipal facility electricity and on-road fleet vehicles increased by 14% and 7%, respectively. Just
four facilities accounted for 80% of all facility electricity use: Bainbridge Island Waste Water Treatment
Plant (WWTP), City Hall, Fletcher Bay: Well Field, and Bainbridge Island Public Works Operations and
Maintenance Yard. There were a few sectors with decreases in emissions, the largest of which was from
streetlight and traffic signal improvements.
CITY OF BAINBRIDGE ISLAND | 2019 | 43
Table 14. Municipal GHG emissions by year, sector, and scope.
GHG Emissions (MTCO2e)
Sector Scope 2014 2018
Building Propane 1 40 40
On-Road Fleet Vehicles 1 359 385
Off-Road Vehicles 1 77 63
Refrigerant Loss 1 18 18
Wastewater Treatment Plant 1 40 43
Electricity 2 1,212 1,383
Street Lights & Traffic Signals 2 103 91
Solid Waste Generation 3 59 84
Employee Commute 3 160 184
Business Travel 3 - -
Total 2,067 2,291
Figure 19. Municipal emissions, by source and scope, for 2018 (total = 2,291 MTCO2e).
CITY OF BAINBRIDGE ISLAND | 2019 | 44
Figure 20. Bainbridge Island municipal emissions, by year and source.
Buildings and Facilities Energy
The City of Bainbridge Island operates several government administration buildings, including City Hall,
the Police Station, the Municipal Court, and a maintenance yard, as well as several community spaces, a
wastewater treatment facility, and the streetlights and traffic signals throughout the City. This section
details the GHG emissions resulting from the consumption of energy at these buildings and facilities. The
types of energy consumed at these locations include electricity, provided by Puget Sound Energy, and
propane, which is combusted in stationary equipment on-site.
In 2018, energy consumption at City of Bainbridge Island buildings and facilities accounted for 66% of
total municipal GHG emissions. Building electricity usage accounted for the bulk of emissions,
comprising 89% and 91% of the energy sector’s emissions in 2014 and 2018, respectively (see Figure 22).
From 2014 to 2018, building and facility electricity emissions grew by 14%, primarily due to fluctuations
in the electricity utility fuel mix (see Electricity section below). The following sections provide greater
detail on trends for the three sources of building and facility energy use: electricity, stationary fuel
combustion, and streetlights and traffic signals.
CITY OF BAINBRIDGE ISLAND | 2019 | 45
Figure 21. Bainbridge Island municipal buildings and facilities energy emissions.
2014
(Total = 1,354 MTCO2e)
2018
(Total = 1,513 MTCO2e)
Electricity
Electricity usage contributed the largest portion of GHG emissions within the City’s buildings and
facilities sector, resulting in the emission of 1,212 MTCO2e in 2014 and 1,383 MTCO2e in 2018. Between
2014 and 2018, electricity emissions grew by 14%. However, electricity usage in kWh only grew by 4%
within this same time period. This indicates that the growth in emissions between 2014 and 2018 was
primarily due to fluctuations in the electricity utility fuel mix (i.e., changes in the proportion of fossil fuel
sources used by the utility to generate electricity in a given year) rather than substantial increases in
electricity usage.
The two facilities with the greatest electricity usage in both years were the wastewater treatment facility
(WWTP) and City Hall. These two facilities also experienced the greatest reductions in electricity usage
between 2014 and 2018, demonstrating that the City is continuing to make progress on energy efficiency
and conservation in the highest consumption facilities (see Figure 23 Figure 24 below). One way the City
has reduced electricity usage at City Hall is through on-site solar electricity production: the solar panels
at City Hall produced 71,300 kWh and 74,500 kWh of solar electricity in 2014 and 2018, respectively.
Figure 22. Top electricity-using facilities in 2018.
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Figure 23. Facilities with the greatest electricity consumption increases between 2014 and 2018.
Figure 24. Facilities with the greatest electricity consumption decreases between 2014 and 2018.
Stationary Fuel Combustion
Stationary fuel (propane) combustion was the lowest contributor to building-related municipal GHG
emissions in both 2014 and 2018. Between both years, emissions remained constant at 40 MTCO2e. The
only source for stationary fuel combustion is the Public Works Operations and Maintenance shop, which
consumed an estimated 7,077 gallons of propane for heating. The number of gallons consumed
remained constant from 2014 to 2018 and therefore resulted in no change in emissions.
Streetlights and Traffic Signals
The second largest contributor to GHG emissions 2018 were streetlights and traffic signals. Between
2014 and 2018, the City of Bainbridge Island increased the number of streetlights from 328 to 343.
However, the emissions produced and electricity consumed by the streetlights has decreased by 12%.
This decrease can be attributed to the City’s increased use of energy efficient bulbs.
CITY OF BAINBRIDGE ISLAND | 2019 | 47
Transportation
Transportation sector emissions are the third largest contributor to the City of Bainbridge Island’s
municipal emissions. This section details the GHG emissions resulting from the consumption of gasoline,
diesel, biodiesel, and propane in various vehicles. These vehicles are a part of numerous city operations,
such as emergency services, landscaping, and government travel.
In 2018, the transportation sector contributed 28% of all emissions, totaling 663 MTCO2e. The City of
Bainbridge Island utilizes fuel for different vehicles such as boats, pickup-trucks, dump trucks,
construction equipment, and patrol vehicles (see Figure 26). Municipal fuel consumption and emissions
increased between 2014 and 2018, and there was a small decrease in fuel economy. Between 2014 and
2018, average municipal fuel economy decreased from 13 mpg to 12 mpg (see Figure 27).
Figure 25. City of Bainbridge Island fleet vehicle emissions, by type.
2014
(Total = 436 MTCO2e)
2018
(Total = 449 MTCO2e)
* Refers to police department fuel purchased outside of O&M. This data is not connected to specific vehicle types.
CITY OF BAINBRIDGE ISLAND | 2019 | 48
Figure 26. Municipal fleet fuel consumption and average fuel economies, by year.
On-Road Fleet Vehicles
On-road vehicles made up the majority of transportation emissions in 2014 and 2018. Emissions come
from on-road fleet vehicles driving on roadways within the community. In 2018, on-road vehicles
consisted of 61% of all transportation sector emissions. We estimate that municipal on-road vehicles
produced 359 MTCO2e and 385 MTCO2e in 2014 and 2018, respectively. The 2003 Volvo Vactor Sewer
Cleaner consumed the greatest amount of fuel both years (1,518 gallons of diesel in 2014 and 2,673
gallons in 2018). The Patrol/Interceptor vehicles sector contained the largest number of fuel-consuming
vehicles. Figure 28 presents the top-10 fuel consuming vehicles in 2018.
Figure 27. Top 10 fuel-consuming fleet vehicles, 2018.
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Off-Road Vehicles
Off-road equipment, such as lawnmowers, boats, and forklifts, contribute another 10% of transportation
sector emissions in 2018. There was a 17% reduction in emissions between 2014 and 2018, from 77
MTCO2e to 63 MTCO2e. Reductions in emissions are from reduced fuel consumption, decreasing from
7,730 gallons in 2014 to 6,474 gallons in 2018.
Employee Commute
Employee commute includes single-occupancy vehicles (SOV), vanpools and carpools. In 2014, employee
commuting produced an estimated 160 MTCO2e from 486,922 VMT. There were 106 full-time equivalent
municipal employees, resulting in 1.51 MTCO2e emitted per employee. The emissions increased in 2018
to 184 MTCO2e. This was a consequence of an increase in VMT to 646,027. In 2018, there were 119 full-
time equivalent employees for the city with only a small increase to 1.55 MTCO2e per person.
Solid Waste and Wastewater
Waste sector includes emissions from solid waste generation and biological process emissions related to
wastewater treatment—detailed below.
Solid Waste
Solid waste is comprised of municipal landfill waste and municipal diverted waste (recycling, cardboard,
and yard waste). We estimate that emissions from waste increased from 59 MTCO2e in 2014 to 84
MTCO2e in 2018. Much of this increase can be attributed to additional service at the Waterfront Park and
downtown areas. An increase in foot traffic in the Winslow downtown area, as well as the reconstruction
of the Waterfront Park and City Dock, required the installation of more waste receptacles in these areas.
We estimate that 147 tons of waste was sent to the landfill in 2014 and that amount increased to 209
tons in 2018.
Between 2014 and 2018, the amount of diverted waste increased from 8.6 tons to 28.8 tons. Yard waste
in particular, increased from 2.1 tons in 2014 to 3.9 tons in 2018. This increase in yard waste composting
contributed to a slight increase in emissions within the diverted waste category, from 0.15 MTCO2e to
0.27 MTCO2e (Figure 29).
CITY OF BAINBRIDGE ISLAND | 2019 | 50
Figure 28. Municipal solid waste disposal trends.
Wastewater Treatment
The City owns and operates the Winslow Wastewater Treatment Plant and operates collection for the
South Island Sewer System. The Winslow Sewer System serves the historic downtown Winslow area and
the South Island Sewer System serves the Lynwood Center, Point White, Pleasant Beach, Emerald
Heights, Blakely School, and Rockaway Beach neighborhoods. The collection systems have a combined
infrastructure that includes emergency generators, manholes, residential grinder pumps and sewage
pump stations.
In 2018, emissions from wastewater treatment totaled an estimated 43 MTCO2e. This was an 7%
increase from 2014 when emissions were 40 MTCO2e. This can be attributed to the increase in
population served from 4,743 in 2014 to 5,079 in 2018.16
Refrigerant Leakage
Leaks in refrigeration systems cause emissions of potent greenhouse gases. These losses can occur in
domestic refrigeration, commercial refrigeration, industrial refrigeration, chillers, and
residential/commercial air conditioning units. Refrigerant gases differ in their Global Warming Potential
(GWP)—the amount of heat a greenhouse gas traps in the atmosphere relative to carbon dioxide.
Emissions from R-22 leaks, for example, are especially impactful: they have a GWP 1,760, which means
that they are over one thousand times more damaging than carbon dioxide. The City’s heating and
cooling systems largely use R-22, which we estimate produces 18 MTCO2e per year.
16 Service populations were estimated at 25% of the total Bainbridge Island population, as estimated by Bainbridge
Island City staff.
CITY OF BAINBRIDGE ISLAND | 2019 | 51
DATA SOURCES AND METHODOLOGY
The municipal emissions inventory involved acquiring the following data types, summarized in Table 16
and detailed in the following sections:
Activity data that quantifies levels of activity that generate GHG emissions, such as miles traveled,
and kWh of electricity consumed.
Emissions factors that translate activity levels into emissions (e.g., MgCO2e per kWh).
Data quality is assessed and reported on a High (H), Medium (M), and Low (L) scale in accordance with
GHG inventory best practices:
A High rating indicates data are detailed and specific to the local geography
A Medium rating indicates data are more general or modeled with robust assumptions and may not
be specific to the local geography, but are downscaled from a slightly broader geography (e.g., state-
level)
A Low rating indicates data are highly modeled, uncertain, or a default value was used based on
national characteristics.
Table 15. Key data sources for the City of Bainbridge Island's municipal inventory.
Sector Activity Data (AD) AD
Quality
Emissions Factors (EF) EF
Quality
Buildings and Facilities Energy
Electricity • kWh consumption compiled
from PSE bills H • PSE reported emissions factors
(PSE Greenhouse Gas Inventory,
2014 & 2017, Table 7.1) H
Stationary Fuel Combustion • Gallons of propane used for
heating compiled based on
municipal purchasing
information provided by
O&M
M
• Emissions factors provided in
ClearPath program M
Streetlights and Traffic Signals • Quantity, type, and wattage
of each streetlight and traffic
signal transcribed from PSE
bills
• Installed wattage used to
estimate electricity
consumption in kWh
M
• PSE reported emissions factors
(PSE Greenhouse Gas Inventory,
2014 & 2017, Table 7.1) H
Transportation
CITY OF BAINBRIDGE ISLAND | 2019 | 52
Sector Activity Data (AD) AD
Quality
Emissions Factors (EF) EF
Quality
On-Road Fleet
Vehicles • Fuel volumes by vehicle and
type, along with annual miles
traveled, provided by Public
Works staff
• Where fuel volumes and
miles traveled were
unavailable for specific
vehicles, the total quantity of
fuel purchased was provided
(with no vehicle information
associated)
H
• CO2 emission factors provided in
ClearPath program
• CH4 and N2O average emissions
factors for each vehicle and fuel
type were calculated based on the
model year composition of the
municipal fleet vehicles
• Emissions factors used in these
calculations were derived from
the EPA (2017) Inventory of U.S.
Greenhouse Gas Emissions and
Sinks (Climate Leadership
Resource)
H
Off-Road Vehicles • Fuel volumes by vehicle and type, along with annual hours of use, provided by Public Works staff
• Where fuel volumes were
unavailable for specific
vehicles, the total quantity of
fuel purchased was provided
(with no vehicle information
associated)
H
• Emissions factors provided in ClearPath program
• Emissions factors for off-road
vehicle/equipment propane use
were missing from the ClearPath
program; these emissions were
calculated separately using
emissions factors derived from
the EPA (2017) Inventory of U.S.
Greenhouse Gas Emissions and
Sinks (Climate Leadership
Resource)
M
Employee Commute • MTCO2e obtained from
Commute Trip Reduction
survey conducted by WSDOT M • N/A; value converted to MTCO2e
by WSDOT N/A
Solid Waste and Wastewater
Solid Waste
Generation
• Bin sizes, pickup frequency,
and waste type were
transcribed from solid waste
bills
• Estimated cubic yards of
waste were then converted
to tons using EPA solid waste
weight conversions
• This methodology assumes
all waste pickup containers
were full
L
• Waste characterizations from King
County multifamily and
commercial buildings used to
estimate Bainbridge Island
municipal waste composition
• ClearPath default emissions
factors used to estimate all future
methane emissions resulting from
the decomposition of each waste
type
L
Wastewater Treatment Facility • Wastewater treatment
facility processes determined
based on desktop research
and confirmed with city staff
• Population served by wastewater treatment facility estimated by multiplying the number of sewer connections (city staff) by the average household size (ACS)
M
• Local Government Operations
Protocol equations 10.8 and 10.10
used to calculate N2O emissions
• CH4 emissions were not applicable since the system is aerobic L
Refrigerant Leakage
CITY OF BAINBRIDGE ISLAND | 2019 | 53
Sector Activity Data (AD) AD
Quality
Emissions Factors (EF) EF
Quality
Refrigerant
Leakage from
Building Heating and Cooling
Equipment
• List of heating/cooling
equipment provided by city
staff
• Equipment categorized by
type and refrigerant used
L
• Emissions calculated using
Equation 6.35 and the default
factors in Table 6.4 of the Local
Government Operations Protocol L
CITY OF BAINBRIDGE ISLAND | 2019 | 54
Buildings and Facilities Energy
We acquired electricity consumption data by hand transcribing individual monthly PSE electricity
bills for the City of Bainbridge Island’s municipal operations. City staff photocopied and provided
these bills.
In 2018, gallons of propane used to heat the maintenance shop were tracked in City records.
However, only cost information was tracked in 2014. Based on the comparison of cost information
between the two years, City staff estimated the propane use at this facility was the same in 2014 and
2018.
Propane usage in an emergency generator at the Senior Center was omitted from the 2014 and 2018
inventories. In 2014, the generator was not maintained by the City and in 2018 the generator was
not used.
We estimated the total electricity usage of streetlights and traffic signals operated by the City of
Bainbridge Island by counting the number, wattage, and types of streetlights and traffic signals
included in the individual monthly PSE electricity bills. We used Equation 6.15 in the Local
Government Operations Protocol to convert wattage to estimated electricity consumption in kWh.
We assumed an average daily operating time of 12 hours for streetlights and 8 hours for traffic
signals.
Transportation
We categorized the list of on-road and off-road vehicles and equipment into standard vehicle types
(i.e., passenger car, light-duty truck, heavy-duty truck, etc.) based on provided vehicle descriptions
and make/model information. We totaled fuel gallons and vehicle miles traveled by each vehicle
category and type of fuel. CO2 emissions were derived based on usage volumes by type of fuel and
ClearPath default emissions factors. CH4 and N2O emissions were derived based on miles traveled by
vehicle category and fuel type. We used CH4 and N2O emissions factors for each vehicle category-fuel
type combination originally derived from the EPA (2017) Inventory of U.S. Greenhouse Gas Emissions
and Sinks and modified these factors to reflect the municipal fleet age composition.
One forklift within the municipal fleet used propane. However, propane is not an available fuel type
for off-road equipment in the ClearPath program. Therefore, we calculated propane emissions
outside of ClearPath using emissions factors derived from the EPA (2017) Inventory of U.S.
Greenhouse Gas Emissions and Sinks.
We obtained total emissions (in MTCO2e) associated with employee commuting from the Commute
Trip Reduction Survey conducted by WSDOT.
Solid Waste and Wastewater
We acquired waste generation data by hand transcribing individual monthly Bainbridge Disposal bills
for the City of Bainbridge Island’s municipal operations. City staff photocopied and provided these
bills.
Waste bills generally indicated the disposal bin volume, the pickup frequency, and the waste stream
(i.e., recycling, yard waste, trash, etc.). We assumed that waste bins were full at time of pickup and
CITY OF BAINBRIDGE ISLAND | 2019 | 55
that waste described as recycling or cardboard was recycled, waste described as yard waste was
composted, and waste described as trash was landfilled. We converted annual volumes of waste by
type into tons of waste by type using EPA solid waste weight conversions. We then used King County
waste composition information and ClearPath default emissions factors to estimate emissions
associated with waste generation and composting.
We estimated wastewater treatment N2O emissions using Equation 10.7 and 10.10 of the Local
Government Operations Protocol. Population served was estimated by Bainbridge Island City staff.
Default nitrogen load information was used since local data was not available.
Refrigerant Leakage
We acquired a list of heating/cooling equipment used in municipal buildings from Bainbridge staff.
We did an online search of the equipment models and serial numbers to determine how to best
categorize each piece of equipment. Using these categorizations, we estimated emissions from
refrigerant leakage using Equation 6.35 and Table 6.4 of the Local Government Operations Protocol.
CITY OF BAINBRIDGE ISLAND | 2019 | 56
Considerations
There is some degree of uncertainty in any GHG inventory. This uncertainty can come from incomplete
data, but it can also result from uncertainty in the methodology or emissions factors used in calculating
units of activity (e.g. gallon of fuel, kilowatt-hour of electricity, short ton of solid waste) into
CO2-equivalent emissions. These considerations should inform future inventory and reporting efforts,
including prioritization of additional data collection, understanding of inventory results, and in the
development of mitigation goals and monitoring systems.
Considerations for the municipal operations inventory include:
Electricity consumption: The hand transcribing of electricity and waste bills introduces a greater
potential for human error.
Streetlight and traffic signal daily operations: Assumptions made on average daily operating time
could affect electricity consumption amounts.
Employee commuting emissions: WSDOT modeled the Commute Trip Reduction Survey, therefore
the methodology, such as emissions factors assumed for passenger vehicles, could be different from
those used for community passenger vehicles.
Municipal vehicle fleet: Some municipal feel vehicles and equipment are fueled by bulk fuel
purchases or mobile fueling tanks. In these instances, we had to estimate vehicle miles traveled and
vehicle composition, potentially affecting the CH4 and N2O calculations.
Solid waste generation: Disposal frequency can be difficult to determine from solid waste bills—
which was the only data available to deduce solid waste disposal amounts. We also lacked data on
the amount of waste included in each disposal bin at the time of pickup, we assumed all bins were
full. The hand transcribing of waste bills introduces a greater potential for human error.
Solid waste characterization: Bainbridge Island lacked a local waste characterization study,
therefore, we applied King County waste characterization data to estimate the relative proportions
of different materials in the waste stream. The waste composition for Bainbridge Island may be
different than for King County.
Wastewater treatment: Due to limitations in local data availability, the calculations used were
default national values based on the treatment method.
CITY OF BAINBRIDGE ISLAND | 2019 | 57
MUNICIPAL CONTRIBUTION ANALYSIS
Introduction
In 2014, total municipal emissions were 2,067 MTCO2e. In 2018, total emissions increased to 2,291
MTCO2e, resulting in a 11% (223 MTCO2e) increase from the 2014 inventory. We employed the Analyzing
Drivers of Change in Greenhouse Gas Emissions Inventories tool available from ICLEI USA to attribute
changes in the municipal inventories to the economic, social and technological forces that caused
them.17 The primary goal of this tool is to provide a methodology for discovering the drivers for change
between the two inventory years.
Results
The contribution analysis revealed the factors that led to the net increase in emissions between 2014
and 2018. In summary, a lower-renewables electricity fuel mix as reported by Puget Sound Energy,
increased water treatment electricity use, and increased use of fleet vehicles all contributed to emissions
increases. Reductions were due to more carbon-efficient employee commuting, more energy-efficient
streetlights, and increased fuel economy of the vehicle fleet. Figure 30 shows the influences of major
forces on the inventory between 2014 and 2018, and Figure 31 presents a more detailed depiction.
Figure 29. High-level summary of major drivers of government operations inventory increase and decreases.
17 ICELI USA Analyzing Drivers of Change in Greenhouse Gas Emissions Inventories tool. http://icleiusa.org/ghg-
contribution-analysis/ (Accessed July 1, 2019).
CITY OF BAINBRIDGE ISLAND | 2019 | 58
Figure 30. Detailed depiction of contributions to change for Bainbridge Island government operations GHG emissions.
Contributors to inventory changes included the following, in order from highest increases to lowest
decreases:
• Electricity fuel mix (+131 MTCO2e) describes changes to types of resources used to generate
electricity for the community. For example, increased use of renewable sources such as
hydroelectricity and solar and wind power would drive emissions decreases in the electricity fuel
mix. For Bainbridge Island, changes in the PSE electricity fuel mix contributed to increases in
electricity emissions.
• Water treatment kWh/gallon (+66 MTCO2e) includes changes in the energy efficiency of processing
wastewater.
• Vehicle fleet total VMT (+61 MTCO2e) describes the increased emissions due to a rise in total vehicle
miles traveled for municipally owned vehicles.
• Other increases (+103 MTCO2e) is a compilation of changes in: population served by water
treatment, number of employees commuting, waste generation per employee, and number of
streetlights.
• Employee commute MTCO2e/mile (-25 MTCO2e) represents more efficient commuting behaviors,
possibly by changes in mode, distance, or vehicle efficiency.
• kWh per street light (-25 MTCO2e) incorporates the fact that streetlight and traffic signal numbers
have increased, but a large conversion to LED prior to 2018 reduced electricity use and emissions.
CITY OF BAINBRIDGE ISLAND | 2019 | 59
• Vehicle fleet CO2e/mile (-48 MTCO2e) is the reduction in emissions associated with reduced gasoline
consumption in newer vehicles meeting more stringent federal standards, as well as the retiring of
older, less fuel-efficient vehicles.
• Other decreases (-21 MTCO2e) includes decreased emissions from changes in the type of heating
fuels used and less wastewater produced per-person.
CITY OF BAINBRIDGE ISLAND | 2019 | 60
Consumption-Based Emissions
The purchasing decisions we make impact the environment. Some types of foods and materials, such as
meat and furniture, can carry a significant GHG emissions burden. For example, meat and dairy cows
emit methane—a potent greenhouse gas. Residents of Bainbridge Island who consume beef contribute
to the emissions from these cows—even if the cows are raised outside the island. This section presents
estimated emissions associated with the purchasing decisions made by Bainbridge Island households.
Consumption-based emissions are provided on a per-household basis because a household is the
economic unit used in the underlying analyses (in other words, the analytical approach is based on
household, not individual, purchasing trends and decisions). For example, food and home goods are
generally purchased by one person for the use of their entire household.
RESULTS
Overview
Results from a household-based economic modeling tool suggest that the average Bainbridge Island
household emits 52 MTCO2e a year through their purchasing behaviors.18 There were an estimated 9,404
and 9,798 households on Bainbridge Island in 2014 and 2018, respectively, indicating that total
consumption-based emissions from all households on Bainbridge Island could have reached
approximately 510,000 MTCO2e in 2018. Major drivers include the purchase of meat, furniture, clothing,
home energy, and travel-related expenses such as car fuel and air travel (see Figure 32 and Figure 33).
Figure 31. Estimated 2018 consumption-based emissions for Bainbridge Island (total = 509,496 MTCO2e).
18 As indicated from U.C. Berkeley’s CoolClimate Calculator. Outcomes from the consumption-based inventory
analysis are presented at the per-household level because purchasing behavior is typically examined and analyzed
at the household—not individual—level.
CITY OF BAINBRIDGE ISLAND | 2019 | 61
Figure 32. Estimated annual individual household consumption-based emissions for Bainbridge Island residents (total = 52
MTCO2e/year).
DATA SOURCES AND METHODOLOGY
Because consumption-based inventories are inevitably coarse in scale compared to other inventory
sectors, we used readily available sources to estimate Bainbridge Island’s consumption-based emissions.
Specifically, we used UC Berkeley’s CoolClimate Calculator, which employs an Economic Input-Output Life
Cycle Assessment model (EIO-LCA), designed by Carnegie Mellon University, and the Comprehensive
Environmental Database Archive to calculate consumption-based emissions. This model employs an
economy-wide model of cradle-to-grave emissions of all major greenhouse gases for over 400 economic
sectors of the economy.
Considerations
The CoolClimate Calculator largely uses national-level data to estimate emissions associated with
purchased goods and services. This means that more locally-specific emissions factors—such as those
associated with the electricity we purchase—are not incorporated. For Bainbridge Island, that may mean
that the calculator is slightly overestimating household emissions, since the Puget Sound Energy
electricity fuel mix is different than the national average. However, the calculator does use regionally-
specific economic data to characterize spending habits.
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Conclusion and Next Steps
These GHG inventories provide a solid and informative foundation for taking climate action:
The Bainbridge Island community now understands its major contributors of GHG emissions—
residential electricity, non-residential electricity, on-road vehicles, and air travel—revealing major
sectors to focus climate action efforts. Conducting inventories for two years also revealed emissions
trends: a 9% increase between the two inventory years as well as increased emissions in almost all
sectors. The community could consider approaches for addressing emissions sources that are
increasing, such as increasing electric vehicle uptake, incentivizing alternatives to air travel,
continuing to increase building use efficiency, and reducing growth. The contribution analysis also
provided insight into the underlying drivers of these trends: we learned that continuing to push for
lower-emissions electricity sources will be important for lowering Bainbridge Island’s climate impact.
The City of Bainbridge Island now understands its key drivers of greenhouse gas emissions—
transportation, electricity, and wastewater treatment—which highlight key areas for reduction. The
inventories for the two years demonstrated an upward trend in emissions, similar to the community
inventory. Between 2014 and 2018, a 11% increase in emissions occurred. The municipal
contribution analysis highlighted the drivers of these trends: changes in electricity fuel mix, water
treatment operations, and vehicle fleet usage. The City of Bainbridge Island did see small reductions
in streetlight and traffic signal use and fleet vehicle fuel economy. The City can consider actions for
reducing emissions from increasing sources, such as transferring to a low-carbon electricity fuel mix
and decreasing the amount of vehicle travel.
Bainbridge Island households learned the impact of spending habits—an estimated 52 MTCO2e of
emissions per year, on average. The consumption-based inventory also exposed key contributors to
that footprint: meat consumption, travel expenses, and the purchase of furniture, clothing, and
energy. Bainbridge households could consider behavior changes to lower these emissions, such as
switching to a low-carbon diet-which includes more vegetables, fruits and whole grains; utilizing
alternative forms of travel; and purchasing second-hand goods.
This foundational work also illuminated opportunities for improving and expanding future inventories.
We were not able to obtain data related to commercial propane use, for example. The City can continue
to work with local propane vendors to start collecting these data and, eventually, begin incorporating
this important emissions source into the city’s inventory. These and other improvements will not only
paint a fuller picture of the community’s overall environmental impact but can also motivate businesses
and individuals to better understand their personal carbon footprint and identify pathways for reducing
that impact.
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References
Intergovernmental Panel on Climate Change. (2014). Fifth Assessment Report.
https://www.ipcc.ch/assessment-report/ar5/ (accessed June 29, 2019).
King County Waste Monitoring Program. (2015). 2015 King County Waste Characterization and Customer
Survey Report.
Puget Sound Energy. (2015). 2014 Greenhouse Gas Inventory.
Puget Sound Energy. (2018). 2017 Greenhouse Gas Inventory.
The Climate Registry. (2010). Local Government Operations Protocol: For the quantification and reporting
of greenhouse gas emissions inventories.
U.S. Department of Agriculture. (2012). National Agricultural Statistics Service.
https://www.nass.usda.gov/AgCensus/ (accessed June 29, 2019).
U.S. Department of Agriculture. (2017). National Agricultural Statistics Service.
https://www.nass.usda.gov/AgCensus/ (accessed June 29, 2019).
U.S. Environmental Protection Agency. (2014). Inventory of U.S. Greenhouse Gas Emissions and Sinks
1990-2014.
U.S. Environmental Protection Agency. (2017). Inventory of U.S. Greenhouse Gas Emissions and Sinks
1990-2017.
Washington State Department of Ecology. (2018). 2015-2016 Washington Statewide Waste
Characterization Study. Publication 16-07-032. 157 pp.
Washington State Department of Transportation. (2017). Commute Trip Reduction Survey.
https://www.wsdot.wa.gov/sites/default/files/2007/03/05/2018-07-12_Calculating_GHG.PDF
(accessed June 29, 2019).
World Resource Institute (2014). Greenhouse Gas Protocol: Global protocol for community-scale
greenhouse gas emission inventories.
CITY OF BAINBRIDGE ISLAND | 2019 | i
Appendix: Tree Carbon Sequestration
While inventories focus on emissions of greenhouse gases into the atmosphere, vegetation such as trees
and grasslands can sequester—or absorb—carbon dioxide from the atmosphere. Land use changes, such
as development of open and working forest and agricultural lands, can affect this process. To illustrate
and better understand this benefit, we sought to quantify the extent to which existing trees in
Bainbridge Island sequester carbon from the atmosphere.
It is important to note that while vegetation on Bainbridge Island is taking carbon dioxide out of the
atmosphere, this process does not offset or counteract emissions of greenhouse gases from the
community, as quantified in the other sections of this report. Such land carbon “offsets” can only be
achieved through rigorous and verifiable changes in land management that result in a net increase in
carbon sequestration as compared to a pre-established baseline. This analysis does not quantify such
activities, but rather offers some insight into the ecosystem services the trees and natural and working
forests of Bainbridge Island provide, and the potential losses of services that could result from their
development or removal.
DATA SOURCES AND METHODOLOGY
We utilized the i-Tree Canopy software to estimate annual tree carbon sequestration on Bainbridge
Island. The software facilitates a supervised random sampling using Google Maps aerial photography.
Specifically, the software walks users through the following steps:19
Define the project area using Google Maps aerial photography (see Figure 35).
Select project location using dropdown menus. This step characterizes per-acre carbon
sequestration based on anticipated vegetation types (e.g., types of trees) typical in that location. For
Bainbridge Island, the selected location was Kitsap County (see Figure 36).
Conduct random sampling. i-Tree Canopy shows a magnified image from the project area with a
point identified with crosshairs (see Figure 37). The user then identifies whether the crosshairs are
on a tree or “non-tree” area.
Repeat random sampling. The tree/non-tree identification is repeated multiple times to increase
statistical precision of the estimated percent tree canopy cover of the project area. For this exercise,
we classified 100 random samples.
Analyze results. i-Tree Canopy uses the random sampling to provide an estimate of overall percent
tree canopy cover and resultant tree carbon benefits. The estimate carries a level of uncertainty
(results are indicated by a mean value +/- one standard error). This uncertainty stems from
limitations associated with the sampling approach.
19 More information regarding the methodology used by i-Tree Canopy can be found at
https://canopy.itreetools.org/resources/iTree_Canopy_Methodology.pdf.
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Figure 33. Defining the project area within i-Tree Canopy.
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RESULTS
Outcomes from the i-Tree Canopy analysis suggest that 51% of the Bainbridge Island land mass was
covered with trees in 2018.20 Those trees sequester an estimated 58,727 MTCO2e from the atmosphere
every year.21 This value appears to have decreased slightly since 2014; sampling of historical aerial
imagery suggests a tree canopy cover of 55% in 2014 (equivalent to an estimated 63,334 MTCO2e annual
sequestration rate).22 This change in tree canopy cover would result in an estimated net loss of 4,607
MTCO2e in carbon sequestration benefits annually.
Figure 34. Estimated tree canopy cover on Bainbridge Island in 2018, using random sampling from the i-Tree Canopy
software.23
20 Value depicted as mean estimate, with 95% confidence interval of 41.2% to 60.8%.
21 Assumes a sequestration rate of 10,010 lbs. CO2/acre/year. Source: i-Tree Canopy v.6.1.
22 Value depicted as mean estimate, with 95% confidence interval of 45.3% to 64.7%.
23 https://canopy.itreetools.org/
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Figure 35. Selected project location for the Bainbridge Island study.
Figure 36. Example of random sampling classification exercise.
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Considerations
This carbon sequestration analysis represents a high-level estimate of annual land carbon sequestration
on Bainbridge Island. Data limitations and other considerations include the following:
Omission of non-tree vegetation: This approach assumes that non-tree vegetation does not
sequester carbon, which is not the case. This analysis does not include carbon benefits from non-
tree vegetation such as agriculture, pasture, and shrubs.
Tree generalization: This approach does not explicitly differentiate between tree types, but assumes
that all trees sequester an average, representative amount of carbon every year.
Statistical sampling: This approach extrapolates a statistical sampling of an area, rather than analyze
the area in its entirety, which inevitably results in some level of statistical uncertainty and
imprecision.