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ESTABLISHING A BASELINE: A COMMUNITY GREENHOUSE GAS
EMISSIONS INVENTORY FOR THURSTON COUNTY, WA
by
Robert E. Coleman
A Thesis
Submitted in partial fulfillment
of the requirements for the degree
Master of Environmental Studies
The Evergreen State College
June 2013
©2013 by Robert E. Coleman. All rights reserved.
This Thesis for the Master of Environmental Studies Degree
by
Robert E. Coleman
has been approved for
The Evergreen State College
by
________________________
Dr. Erin Ellis
Member of the Faculty
________________________
Date
ABSTRACT
Establishing a Baseline: A Community Greenhouse Gas Emissions Inventory for
Thurston County, WA
Robert E. Coleman
Global atmospheric concentrations of carbon dioxide (CO2), methane (CH4), and
nitrous oxide (N2O) have increased markedly as a result of human activities since
1750, with CO2 concentrations now exceeding pre-industrial values determined
from ice-cores that span at least 650,000 years. In response, many national and
subnational efforts to reduce greenhouse gas emissions have been initiated with
the intention of combatting the hazardous effects of climate change. Leaders and
community members in Thurston County Washington have identified climate
change as a primary concern for the region’s future and the Thurston County
Planning Department has identified a Community Greenhouse Gas Emissions
Inventory as a necessary exercise to identify and reduce greenhouse gas emissions
in the region. Utilizing the U.S. Community Protocol for Accounting and
Reporting of Greenhouse Gas Emissions, this study estimates the total Metric
Tons of Carbon Dioxide Equivalents (MTCDE) emitted from the built
environment, on-road vehicles, solid waste, wastewater treatment, and livestock
in Thurston County, WA in 2010. Energy consumption in buildings
(approximately 1.4 million MTCDE) and fuel usage in on-road vehicles
(approximately 1.2 million MTCDE) constitute the largest portion of the total
greenhouse gas emissions in Thurston County (approximately 2.8 MTCDE).
Further, energy usage in residential buildings (0.8 million MTCDE) and fuel
usage in passenger vehicles (0.9 million MTCDE) are the two largest individual
sources of greenhouse gas emissions in Thurston County. This information
suggests that in order to drastically reduce greenhouse gas emissions from sources
and activities in Thurston County, local leadership and community members
should focus greenhouse gas emissions reduction efforts on residential buildings
and on-road passenger vehicles.
Table of Contents
List of Figures
vi
List of Tables
vii
Acknowledgements
viii
Introduction
1
Chapter 1: The Need for Carbon Accounting
4
Greenhouse Gas Emissions and Global Climate Change: A
Human Disturbance
4
Effects on the United States, Washington State, and Thurston
County
10
Greenhouse Gas Emissions Inventories at the Subnational
Level
14
Purpose
16
Chapter 2: Effectively Allocating Emissions
18
Current Issues in Allocating Emissions
18
U.S. Community Protocol for the Accounting and Reporting of
Greenhouse Gas Emissions
22
Chapter 3: Methodology
25
Site Description
25
Selection of Estimation Methodology
26
Data Allocation
27
Estimate Calculation Methodology
28
Chapter 4: Results
48
Built Environment Emissions
49
On-road Vehicle Emissions
51
Solid Waste Emissions
52
iv
Wastewater Treatment Emissions
53
Livestock Emissions
54
Chapter 5: Discussion & Conclusion
55
Emissions In Thurston County Relative to Washington State
and King County, WA
55
Implications of Results
57
Limitations of Estimation Methodology
59
Future Research and Interdisciplinary Statement
63
Conclusion
64
Bibliography
66
Appendix A: Table of Estimate Calculations
72
v
List of Figures
Figure 1: Human Enhanced Greenhouse Effect
7
Figure 2: Method for Emissions Estimate from Use of Electricity
34
Figure 3: Method for Emissions Estimate from Transmission and Dist. Losses
35
Figure 4: Method for Upstream Emissions from Electricity Estimate
36
Figure 5: Methods for On-Site Fuel Combustion Emissions Estimate
37
Figure 6: Method for Upstream Emissions from On-site Fuel Combustion
38
Figure 7: Method for Methane Emissions from Landfilled Waste
40
Figure 8: Method for Landfill Process Emissions
41
Figure 9: Method for Landfill Transport Emissions
41
Figure 10: Method for Methane Emissions from Enteric Fermentation
42
Figure 11: Method for Methane Emissions from Digester Gas
43
Figure 12: Method for N2O Emissions from Digester Gas
44
Figure 13:Method for CO2 Emissions from Digester Gas
45
Figure 14: Method for Methane Emissions from Wastewater Lagoons
45
Figure 15: Method for Emissions from Denitrification
46
Figure 16: Method for CO2 Emissions from Methanol Usage
47
Figure 17: Distribution of Emissions from Sources and Activities
49
Figure 18: Distribution of Built Environment Emissions Among Sectors
50
vi
List of Tables
Table 1: Increases in Concentrations of Primary GHGs
7
Table 2: One Hundred Year Global Warming Potentials
29
Table 3: Emissions Sources and Related Estimation Method
29
Table 4: List of Inputs Used for Estimation
31
Table 5: Emission Source Type Quantities and Proportion of Total
48
Table 6: Emission Sources and Quantities for Built Environment
51
Table 7: Emission Sources and Quantities for On-Road Vehicles
52
Table 8: Emissions Sources and Quantities for Solid Waste
52
Table 9: Emissions Sources and Quantities for Wastewater Treatment
53
Table 10: Emissions Sources and Quantities for Livestock Production
54
Table 11: Electricity Resource Mix for eGRID WECC NWPP vs. PSE
61
vii
Acknowledgements
This project would not have been possible without the support and
advisement of Thurston Climate Action Team, especially Tom Crawford, Graeme
Sackrison, Geoff Glass, and Jessica Jensen. In addition, I would like to express
deep gratitude to Dr. Erin Ellis for her excellent and unwavering guidance
through the writing and editing processes of this document. Finally, a sincere
thank you to Farra Vargas with Puget Sound Energy, Thera Black and Bharath
Paladugu with Thurston Regional Planning Council, Peter Guttchen with
Thurston Solid Waste, Laurie Pierce with LOTT Clean Water Alliance, and
Jessica Brandt with InterCity Transit.
viii
Introduction
Our planet is a lonely speck in the great enveloping cosmic dark. In our
obscurity, in all this vastness, there is no hint that help will come from elsewhere
to save us from ourselves.
- Carl Sagan
The Intergovernmental Panel on Climate Change (IPCC) states that global
atmospheric concentrations of carbon dioxide (CO2), methane (CH4), and nitrous
oxide (N2O) have increased markedly as a result of human activities since 1750
and now CO2 levels exceed pre-industrial values determined from ice cores that
span at least 650,000 years (Siegenthaler et al. 2005). Further, global increases in
carbon dioxide concentration are due primarily to fossil fuel use and land use
change, while increases in methane and nitrous oxide concentrations are primarily
due to agriculture (IPCC 2007). All of these gases are greenhouse gases, and as
such have been demonstrated to affect the energy balance of the Earth, with
temperatures increasing as the concentration of these gases increase. In response
to the conclusions drawn by the Intergovernmental Panel on Climate Change,
many national and subnational efforts to reduce greenhouse gas emissions have
been initiated as an attempt to combat the hazardous effects of climate change.
Complete and accurate greenhouse gas emissions inventories are a critical first
step in guiding policy and planning efforts in a direction that will effectively
reduce emissions.
Greenhouse gas emissions inventories have been an integral part of local
and state greenhouse gas emissions reduction strategies and climate action plans
across the United States (Engel 2006). Given that global climate change continues
1
to be addressed at a scale much smaller than the problem itself, the consequences
of developing inventories at the state and local level is a first step towards
combating climate change regardless of the lack of national leadership on this
issue. Further, greenhouse gas emissions inventories have broad applications in
scientific and mathematical modeling, policy-making, environmental regulation
and compliance, as well as environmental stewardship in business and non-profit
endeavors. A community greenhouse gas emissions inventory goes beyond
estimating the emissions resulting from a single entity, and instead incorporates
estimates from all sources and activities within the community that result in
emissions within or outside the community itself (e.g., a power plant that serves a
city but is not located within the city limits). As such, these inventories are a
useful planning tool in developing effective reduction plans that reduce emissions
resulting from sources within the community, as well as activities of the
community that generate emissions elsewhere. This thesis investigates the largest
sources and quantities of greenhouse gas emissions (reported in metric tons of
carbon dioxide equivalents) across Thurston County, and identifies the sources
and activities upon which planners, policy-makers, and individuals should focus
in order to significantly reduce greenhouse gas emissions resulting from
community sources and activities.
The U.S. Community Protocol for the Accounting and Reporting of
Greenhouse Gas Emissions, published by the International Council for Local
Environmental Initiatives (ICLEI) – Local Governments for Sustainability USA,
was used to calculate emission estimates. Given the inherent uncertainty in any
2
emissions estimate, the Community Protocol was selected because it provides
methods for estimating emissions with the best available data. Herein is the first
iteration of a community greenhouse gas emissions inventory for Thurston
County, WA using data for calendar year 2010, including emission estimates for
sources and activities associated with: 1) the built environment (i.e., energy usage
in residential, commercial, and industrial buildings), 2) on-road transportation, 3)
solid waste generation, 4) waste-water treatment, and 5) livestock production
within the geopolitical boundary. Thurston County was selected for this study as
it is home to the state capitol, Olympia, as well as Thurston Climate Action Team
the non-profit organization and proprietor of this inventorying effort.
This thesis is comprised of six chapters. Chapter 1 provides background
information on greenhouse gas emissions, their influences on climate change in
Washington State and the South Puget Sound, the academic discourse on
subnational greenhouse gas emissions inventories, as well as the need for carbon
accounting in Thurston County, WA. Chapter 2 details the effective allocation of
greenhouse gas emissions as discussed in the academic literature, the
methodologies of similar inventorying exercises, as well as the unique aspects of
the U.S. Community Protocol for the Accounting and Reporting of Greenhouse
Gas Emissions (i.e., the Community Protocol). Chapter 3 discusses the methods
used in this study (i.e., the calculation of emissions estimates using the
Community Protocol). Chapter 4 provides a detailed summary of the resultant
greenhouse gas emissions estimates for Thurston County. Chapter 5 is an in-depth
discussion of these results and provides a conclusion to this study.
3
Chapter 1
The Need for Carbon Accounting
The following chapter provides background information on global climate
change, anthropogenic greenhouse gas emissions and their impacts on climate
change, the projected impacts of climate change on the United States, Washington
State, and Thurston County, as well as the development of policies at the local
and regional scale that address climate change. This chapter sets the back-drop
for the purpose of this study, and establishes a foundation for further discussion of
this study’s results and implications related to climate policy development in
Thurston County.
Greenhouse Gas Emissions and Global Climate Change: A Human Disturbance
The greenhouse effect is a term used to describe the trapping of ultraviolet
solar radiation within the Earth’s atmosphere, and the subsequent effect this
trapped radiation has on the Earth’s climate and natural systems. Approximately
one-third of the solar energy that meets the farthest reaches of the Earth’s
atmosphere is reflected directly back to space, while the remaining two-thirds is
absorbed by the surface and atmosphere itself. Short wavelengths of visible light
from the Sun pass through the atmosphere and are absorbed. Re-radiated long
wavelengths of energy are less efficient in escaping the atmosphere leading to
more heating and a higher resultant temperature. The Earth’s greenhouse effect
warms the surface of the planet, making human and non-human life possible, and
trapped thermal radiation is in a constant state of flux between the surface of the
Earth, its land and oceans, and the atmosphere where it is radiated and reradiated.
4
Unfortunately, human activities since the late 18th century, primarily the burning
of fossil fuels and the clearing of forests, have accelerated and intensified the
natural greenhouse effect causing global warming (i.e., climate change) (Figure
1).
Human activities, beginning in the industrial era and continuing into the
present, have made a significant contribution to the concentration of greenhouse
gases in the atmosphere, primarily through the burning of fossil fuels and the
clearing of forest cover. The Kyoto Protocol and the IPCC have identified carbon
dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs),
perfluorocarbons (PFCs), and sulfur hexaflouride (SF6) as the six primary
atmospheric greenhouse gases whose concentrations have been affected by human
activities (IPCC 2007).Since the pre-industrial era, carbon dioxide levels have
increased by over 40 percent (Table 1) and stable isotope analyses of Antarctic ice
cores show that levels are currently higher than any level in the past 650,000
years (Siegenthaler et al. 2005, Figure 2). The intensity and significance of
warming depends on many different mechanisms both human and natural.
Radiative forcing is used to compare how a range of human and natural
factors drive warming or cooling influences on global climate (IPCC 2007). It is a
measure of the influence a factor has in altering the balance of incoming and
outgoing energy in the Earth-atmosphere system and is an index of the importance
of the factor as a potential climate change mechanism. According to the American
Chemistry Society, contemporary interest in radiative forcing is mostly concerned
with the effects of increasing atmospheric concentrations of greenhouse gases.
5
Changes in the atmospheric abundance of greenhouse gases and aerosols alter the
energy balance of the climate system and threaten human and natural systems.
As greenhouse gas concentrations within the atmosphere increase, the
concentration of water vapor within the atmosphere increases due to the inherent
warming, compounding the greenhouse effect and thus creating more warming,
and more water vapor within the atmosphere. According to the IPCC, “this water
vapor feedback may be strong enough to approximately double the increase in the
greenhouse effect due to the added CO2 alone.” Further, if current trends
continue, carbon dioxide concentrations are projected to reach 600 to 1,000 parts
per million by the end of the 21st century (from 278 ppm pre-industrial era), or a
rise of approximately 115 to 250 percent (IPCC 2007). Recently, atmospheric
CO2 concentrations were observed to exceed 400 ppm at the National Oceanic
and Atmospheric Administration Global Monitoring Division’s Mauna Loa
Observatory.
Synthesis of data suggests that “eleven of the last twelve years (19952006) rank among the twelve warmest years” since 1850, and that the 100-year
linear trend highlighted in the AR4 (1906-2005) is larger (0.7 degrees C) in
comparison to the trend observed in the Third Assessment Report’s 100-year
linear trend (1901-2000; 0.6 degrees C). Further, the 50-year linear trend from
1956 to 2005 (0.13 degrees C per decade) is almost two-times that of the 100-year
trend from 1906 to 2005. Similarly, decreases in magnitudes of both snow and ice
are consistent with warming; satellite data show that annual average Arctic sea ice
6
Figure 1: Left - Naturally occurring greenhouse gases—carbon dioxide (CO2),
methane (CH4), and nitrous oxide (N2O)—normally trap some of the sun’s
heat, keeping the planet from freezing. Right - Human activities, such as
the burning of fossil fuels, are increasing greenhouse gas levels, leading to
an enhanced greenhouse effect. The result is global warming and
unprecedented rates of climate change. Retrieved from “What is Climate
Change?,” by Will Elder, 2013, National Park Service,
http://www.nps.gov/goga/naturescience/climate-change-causes.htm.
Table 1: Increases in the concentrations of the primary, long-lived anthropogenic
greenhouse gases according to the IPCC's Fourth Assessment Report
(AR4). These trends indicate that it is very likely that human activities
have accelerated and exacerbated global warming trends. Values reflect
atmospheric concentrations of greenhouse gases in either parts per million
(ppm) or parts per billion (ppb), and are representative of the ratio of the
number of greenhouse gas molecules to the total number of molecules of
dry air (Petit et al. 1999).
Carbon Dioxide
(CO2)
Methane
(CH4)
Nitrous Oxide
(N2O)
Pre-industrial
280 ppm
715 ppb
270 ppb
2005
379 ppm
1774 ppb
319 ppb
7
has shrunk 2.7% per decade since 1978, with decreases of a greater magnitude
(7.4% per decade) in summer (Johannessen et al. 1999). Snow-cap and mountain
glaciers have similarly declined in both the Northern and Southern hemispheres
and surface temperatures of the Arctic’s permafrost layer has generally increased
since the 1980s by up to 3 degrees Celsius (Johannessen et al. 1999).
Global average sea level rose with an average rate of approximately 1.8
millimeters per year from 1961 to 2003 and with an average rate of approximately
3.1 millimeters per year from 1993 to 2003; however, it is unclear if this is due to
decadal variation or an increase in the longer-term trend (Domingues et al. 2008).
Further, thermal expansion of the oceans, i.e., warming of the ocean, has
contributed about 57% of the total estimated rise in sea level with decreases in
glaciers and ice caps contributing about 28% to the total rise, and losses from
polar ice sheets contributing the remaining 15% (Domingues et al. 2008). Since
1750, the uptake of anthropogenic carbon in the world’s oceans has led to
acidification of this precious resource, with an average decrease in pH of 0.1
units, and increasing concentrations of CO2 in the atmosphere have led to further
acidification (Raven et al. 2005).
The Intergovernmental Panel on Climate Change’s (IPCC) Fourth
Assessment Report (AR4) states that “the warming of the global climate system is
unequivocal (AR4).” Further, the report posits that observed changes across all
continents and most oceans show the many natural systems being impacted by
climate change, particularly temperature changes. The IPCC has asserted
anthropogenic greenhouse gas emissions as the primary driver of global climate
8
change, and identifies and outlines observed global trends of climate change,
including increases in global average air and ocean temperatures, widespread
melting of snow and ice, rising global average sea level, ocean acidification as
well as increases in concentrations of greenhouse gases. The effects of these
changes are widespread, impacting all of the world’s continents and most oceans.
The impacts of climate change to human populations differ from continent
to continent, and the IPCC states that “taken as a whole, the range of published
evidence indicates that the net damage costs of climate change are likely to be
significant and to increase over time.” Freshwater availability in Central, South,
East, and Southeast Asia is projected to decrease by the 2050s, while coastal areas
of the continent will be at risk due to increased flooding and death risks associated
with floods and droughts (IPCC 2007). By 2020, between 75 and 250 million
people in African countries are projected to be exposed to increased water stress,
while yields from rain-fed agriculture could be reduced by up to 50 percent in
some regions severely comprising production and food-access (IPCC 2007).
Replacement of tropical forest by savannah in the eastern Amazon, widespread
biodiversity loss through species extinction, and significant changes in water
availability for human consumption, agriculture, and energy generation are
expected in Latin America (IPCC 2007). In Europe, increased risk of inland flash
floods, more frequent coastal flooding, increased erosion from storms and sea
level rise, as well as glacial retreat in mountainous areas and reduced snow cover
will threaten human, ecological, agricultural, and economic systems (IPCC 2007).
In North America, increased frequency, intensity, and duration of heat waves may
9
threaten productivity of existing agricultural systems, however reports also project
a 5 to 20 percent increase in yields of rain-fed agriculture in regions like the
Pacific Northwest that are expected to see lengthening of summer growing
seasons and seasonal rainfall (IPCC 2007). Unfortunately, the impacts of
accelerated warming are not occurring in a timeframe commensurate with the rate
at which anthropogenic greenhouse gas emissions are occurring, and as warming
effects become noticeable, the most vulnerable locations, like coastal regions, will
be the first to experience observable consequences.
Effects of Climate Change on the U.S., Washington State, and Thurston County
Although the threat of climate change is global in nature, climate change
impacts to both natural and human systems are best understood at the regional or
local scale. The Pew Center on Global Climate Change published a compilation
of four case studies on the regional effects of climate change and examined the
similar and differing impacts of climate change on different regions of the United
States. The Climate Impacts Group at The University of Washington has scaleddown global climate change models to produce two scenarios (“A1B”, a moderate
emissions scenario, and “B1”, a low emissions scenario) that provide projected
climate change impacts to the natural systems of the region. These studies and
projections tell a story of how climate change is and will continue to impact the
region. Understanding the ways in which climate change is and will likely impact
Washington State’s and the South Puget Sound’s natural systems is integral to
projecting how those changes will impact humans, environmental, and economic
10
systems of the South Puget Sound, as well as how best to mitigate and adapt to
climate change.
In the four case studies examined by the Pew Center (i.e., Bachelet et al.
2007, Boesch et al. 2007, Ebi et al. 2007, Twilley 2007) evidence is presented that
climate change is already increasing risks like wildfire, sea-level rise, hypoxia,
and extreme weather events in all regions of the United States; these impacts are
projected to become more apparent as the climate continues to shift. In the
Midwest existing heat waves are likely to become more frequent, longer, and
hotter than cities in the region have experienced in the past, potentially leading to
droughts and heat-related mortality (Ebi et al. 2007). In addition to increased
average temperatures, the coastline of the Gulf of Mexico with its low-lying
development, the construction of levees along major rivers that have degraded
coastal wetlands, high pollution levels, and extreme weather events will suffer
from rising sea-levels and associated human-health concerns (Twilley 2007).
Development, higher temperatures, increased regional rainfall and nutrient runoff
from farms and communities within the Chesapeake Bay watershed are leading to
hypoxic conditions within the Bay, impacting the ecosystem, its fisheries, and
recreational capacity (Boesch et al. 2007).
The western United States and the Pacific Northwest are likely to
experience many of these impacts. Some examples of impacts include increased
wildfire, reduced snowfall, snowpack, and drier summers (Bachelet et al. 2007).
Nine key indicators and projections of how climate change will impact
Washington and the Pacific Northwest are presented in the Climate Impacts
11
Group’s Washington Climate Change Impacts Assessment Report: increasing
carbon dioxide levels, warmer air temperatures, drier summers and reduced
snowfall, more frequent and severe extreme weather events, rising sea levels,
more acidic marine waters and warmer water temperatures, as well as increasing
severity and frequency of wildfires and flooding events.
The State of Washington Department of Ecology projects that climate
change will affect many human systems and systems upon which humans are
dependent, like forest resources, electricity, municipal water supplies, agriculture,
human health, and shorelines. Impacts to forest resources include loss of
economic viability of forest lands due to affected tree growth rates, fire, and pests,
as well as lost recreational expenditures, and health and environmental costs
related to air pollution and other forest changes (Millar et al. 2007). Climate
change’s impacts on the state’s electrical system, which is highly dependent on
hydropower, will affect both supply and demand and include shifts in the timing
of peak hydropower generation due to increased/decreased seasonal flows, as well
as increased electrical demands in the summer months for cooling needs (Elsner
et al. 2010). The threat to hydropower generation will likely exacerbate the
importation of electrical energy or drive the development of new generation
resources. Municipal water supplies will decline and will increase in cost due to
projected increases in population as well as declines in snowpack and thus
freshwater availability (Miles et al. 2000, Vano et al. 2010). Agriculture in
Washington will likely gain longer growing seasons, but with increased aridity
and reduced water supply alongside increases in water demands (Elsner et al.
12
2010). Shorelines will be affected by sea-level rise and armoring, erosion, and
inundation, while industry associated with aquaculture and port systems will
likely be affected as well (Huppert et al. 2009). Human health will likely suffer
due to increases in human vulnerability to water-borne illness from increases in
precipitation and sea-level rise, cardiovascular disease and death from declining
air quality, aridity and drought, as well as extreme weather events like flooding
and inundation of coastal regions (Climate Impacts Group 2009). Clearly, the
threat of climate change to Washington State will affect ecological and human
systems in Thurston County, particularly shorelines, forests, and human health.
Thurston County is particularly vulnerable to climate change due to susceptibility
to sea level rise, ocean acidification, and wildfire, in addition to economic
dependencies on natural resources, like aquaculture, logging, and hydroelectricity.
However, Thurston County is but a small contributor to global greenhouse gas
emissions.
Unfortunately, the global commons are not governed by a centralized
body and attempts to establish binding international agreements to reduce
anthropogenic greenhouse gas emissions, the primary driver of accelerated global
warming and climate change, have been largely unsuccessful (i.e. the Kyoto
Protocol). But, Washington State and Thurston County are among a growing
number of subnational leaders that are taking climate change preparedness into
their own hands for the sake of Washingtonians, their environment, and the world.
13
Greenhouse Gas Emission Inventories at the Subnational Level
The Intergovernmental Panel on Climate Change has declared global CO2
emissions must be reduced to at least 50% by 2050 to avert the worst threats of
climate change, and with the majority of the world’s population residing in cities,
municipalities and local governments are at the forefront of efforts to reduce
greenhouse gas emissions (IPCC 2007). Although many cities and local
governments have prioritized greenhouse gas emissions inventorying and climate
action planning efforts, there has historically been a lack of both national and
international guidelines for conducting an inventory and developing an action
plan for a city, though the IPCC has published standards for data collection and
estimation of certain emission types. The first international protocol for
community greenhouse gas emissions inventorying was released by the
International Council for Local Environmental Initiatives (ICLEI) - Local
Governments for Sustainability in October of 2012 (ICLEIusa.org). Transnational
networks, like ICLEI, are useful for leveraging increased federal attention to
climate planning activities.
Despite failure of the U.S. government to ratify the Kyoto Protocol, state
and local initiatives to reduce greenhouse gas emissions are bolstering climate
change mitigation and adaptation policy, both regionally and nationally (Engel,
2006). Thirty-two states and Puerto Rico have completed or are developing
strategies to reduce greenhouse gas emissions. Thirty-three states plus
Washington D.C. have enacted Renewable Portfolio Standards that require a
certain percentage of energy sales come from renewable technologies, providing
14
guaranteed reductions in greenhouse gas emissions from point-source emitters
(Environmental Protection Agency 2013). As of November 2012, one thousand
fifty four mayors have adopted the Mayors Climate Action Protection Agreement,
urging cities to adopt the greenhouse gas reduction targets on the timetable
posited by the Kyoto Protocol - a reduction of 7 percent below 1990 levels by the
year 2012 (Engel, 2006).
The benefits of state and local inventorying efforts and climate action
plans are rooted in the ideal of states and local governments as laboratories for
democracy and innovation in governance. Lutsey et al. 2008 outlines the benefits
of these efforts as follows:
i
allowing more experimentation by more policy-makers
ii local tailoring of specific actions to fit more aptly the
environmental preferences of constituents of various states
and locales
iii testing the political response of innovative regulatory and
policy actions
iv and, gaining the benefit of local expertise and experience in
enforcing programs and policies.
These sentiments are echoed more generally in the literature (Fleming et al. 2004,
Satterthwaite 2008). Additionally, the benefit most often referenced is the
potential for state and local initiatives to promote the development of local, state,
and federal climate policy through replication and a bottom-up approach (Rabe
2004, Betsill et al. 2006, Engel et al. 2008). The City of Seattle is a featured
15
community in the EPA’s Climate Showcase Communities Program and its climate
action plan is a model for effective greenhouse gas emissions reductions.
Gelderloos 2013 found that the City of Seattle’s greenhouse gas emissions
reduction strategies were beneficial and that planning at the local level proffered
strengths like accounting for regional variations in climate, as well as economic
and social patterns, in addition to regional authority in policy areas pertinent to
emissions and existing trust of the populace. Similarly, given the rise of global
trends and cultural shifts occurring exclusively in cities it makes sense that
inventorying efforts and action plans would be developed at the local level to
culturally, socially, and politically address climate change.
Purpose
The threat of global climate change is of international concern, and the
impacts of climate change have been identified by the scientific community as
one of the primary threats to humanity and Earth. In addition, the
Intergovernmental Panel on Climate Change’s Fourth Assessment Report (AR4),
published in 2007, indicates that humans are “very likely” the leading cause of
accelerated warming of the atmosphere in the last century. However, the United
States has not implemented comprehensive policies addressing climate change or
its impacts on the global community. Subnational governments in Washington
State are taking progressive actions to not only reduce greenhouse gas emissions,
but to prepare for climate change and its effects. The purpose of this study is to
provide a baseline dataset of emissions estimates for Thurston County, WA, so
that local and regional leadership, as well as the community, might begin to
16
prepare, plan, and measure the effectiveness of greenhouse gas emissions
reductions strategies. The effective allocation of greenhouse gas emissions is
essential to the development of feasible and effective emission reduction plans.
17
Chapter 2
Effectively Allocating Emissions
This chapter builds the case for the selection of the U.S. Community
Protocol for the Accounting and Reporting of Greenhouse Gas Emissions by
reviewing the academic literature relative to the effective allocation of greenhouse
gas emissions and the uncertainty in emissions estimates, the methodologies of
similar inventorying efforts, and outlining the significant attributes of the
Community Protocol that set it apart from existing inventorying methodologies.
Current Issues in Allocating Emissions
Hoornweg et al. 2011 posit that in order to accurately assign responsibility
to cities or regions it is important to consider the fundamental role of the modern
city in the global context: that cities are not only more environmentally efficient
than suburban and rural living at similar levels of affluence, but cities are drivers
of human activity (the primary of global climate change). For this reason, many
scholars have investigated local climate action and posited global climate change
as a global issue that can be addressed through careful and concise “local action”
in cities and other denominations of local government (Kousky et al. 2003,
Fleming et al. 2004, Gupta et al. 2007, Lutsey et al. 2008, Satterthwaite 2008,
Sippel et al. 2009, Larsen et al. 2009). The International Energy Agency reports
in the World Energy Outlook of 2008 that 71% of energy derived CO2 emissions
come from cities in the United States. However, differing estimation
18
methodologies present a significant level of uncertainty in the comparability of
inventories.
There are several methodologies for greenhouse gas emissions inventories;
inventories that are consumption- or production-based, specific to a given
temporal and geographic or organizational boundary, as well as inventories that
incorporate “sinks” of emissions (i.e., the quantity of emissions removed by
natural systems like forests or bodies of water). The selection of a particularly
accounting or estimation methodology is dependent upon the goal of the project
and the intended outcomes of the accounting process. For example, a corporation
may estimate emissions associated with the worldwide operations of the business,
a local government might wish to account for emissions associated with
government operations, while the federal government wonders the quantity of
greenhouse gases emitted versus the quantity stored in natural systems. A
community inventory accounts for all sources and activities that generate
emissions within a given boundary with the goal of facilitating a community-wide
discourse on appropriate avenues for reducing emissions resulting from these
sources and activities.
Assigning responsibility for anthropogenic greenhouse gas emissions
seems to be a tedious task fraught with doubts regarding who should be held
responsible for what emissions. A production versus consumption based inventory
will provide starkly different results (Dodman 2009), one amassing emissions for
which the consumer is accountable the other the producer. For example, a large
fossil-fueled power plant located just outside a city’s limits might provide
19
electricity to the city, but the actual emissions from the power plant are occurring
outside the city limits. Thus, in a production-based inventory, the city would not
be held responsible for the emissions generated at the power plant that in fact
support activities within the city that are dependent on those emissions.
Neither a consumption or production-based inventory is necessarily
superior to the other, however, the geographic or organizational boundary used to
conduct the inventory is a determinant of which methodology is used; at the
national or state level a production-based inventory makes sense as the majority
of the energy produced within the state or country is used within the state or
country. The Washington State Greenhouse Gas Emissions Inventory and the
Inventory for U.S. Greenhouse Gas Emissions and Sinks use a production-based,
while smaller scale inventories utilize a consumption-based methodology. King
County, WA utilized a consumption-based accounting approach for their GHG
emissions inventories. However, these differing methodologies focus on similar
emission source types, like the built environment, transportation, solid waste,
wastewater treatment, and livestock and agricultural emissions.
Ramaswami et al. 2008 propose the need for methodologies that allocate
emissions to the consumer of the good or service provided by the emissions
source to more appropriately allocate emissions from surface and airline travel
across co-located cities in larger metropolitan regions and to quantify the
embodied energy of key urban materials, like food, water, fuel, and concrete
enabling cities to separately report the greenhouse gas impact associated with
direct end-use of energy by cities. The difficulties associated with assigning
20
responsibility for anthropogenic greenhouse gas emissions might be alleviated by
standardization across reporting frameworks to minimize double-counting and
unallocated emissions. The result of double-counting emissions is an inventory
that over-reports emission estimates and thus limits the applicability of the
inventory to a reduction strategy or modeling and forecasting effort. Similarly,
unallocated emissions result in an inventory that under-reports emission estimates
further limiting effective reduction strategizing.
Rypdal and Winiwarter 2001 discuss difficulty in GHG reduction
strategizing in terms of the level of uncertainty in inventory estimates. According
to Rypdal and Winiwater 2001, uncertainty in emissions estimates range from 5 to
20% in well-developed inventories from the five countries they examined. Further
they state that this range reflects differences in source mix with CO2 typically
having less uncertainty relative to emissions from CH4 and N2O. For example,
uncertainty in nitrous oxide emissions from agricultural soils and uncertainties in
CO2 emissions are a few percent in all countries, whereas uncertainty for CH4
ranges between 20–40%. They conclude that in any inventorying effort a keen
discussion or estimate of uncertainty in data or calculation is important, given the
inherent uncertainty in an estimation methodology and the possibility of needed
recalculations or expansion of an inventories scope (i.e., including more sources
and activities generating emissions).
21
U.S. Community Protocol for the Accounting and Reporting of Greenhouse Gas
Emissions
For this greenhouse gas emissions inventorying effort ICLEI’s U.S.
Community Protocol for the Accounting and Reporting of Greenhouse Gas
Emissions was selected as a guide as it establishes requirements and recommends
best practices for developing community GHG emissions inventories. The
Community Protocol is designed to:
enable local governments to estimate and report on GHG emissions
associated with their communities in order to measure progress toward
GHG emission reduction goals
use best practice methods that align, where possible, with nationally
and internationally recognized GHG accounting and reporting
principles, as well as with emerging reporting processes or registries
provide local governments with an assessment of GHG emissions
associated with their communities so that they – and others – can make
more informed decisions about where and how to pursue GHG
emissions reduction opportunities
help local governments engage with residents, businesses, and other
stakeholders about opportunities in their communities for reducing
GHG emissions
advance consistent, comparable, and relevant quantification of GHG
emissions and appropriate, transparent, and policy-relevant reporting
22
of GHG emissions to allow communities to compare their baseline
emissions.
In particular the Community Protocol includes many innovations that are different
from existing accounting and reporting methodologies, including:
the drawing of distinctions between emission sources that may be
located in a community and activities of the community that result in
GHG emissions elsewhere
five required Basic Emissions Generating Activities for all
communities: the built environment, on-road transportation, solid
waste generation and disposal, wastewater treatment, and livestockrelated emissions
a focus on a required process that helps communities achieve their
emissions management goals in a variety of contexts
detailed accounting guidance to aid data collection and emission
calculations
emphasis on line item reporting of emissions numbers with guidance
on aggregation where appropriate and how to avoid double counting
inclusion of life cycle accounting methods of upstream emissions
from: electricity use, stationary fuel use, transportation fuels, and
materials and services used in the community
In contrast to GHG emissions reports that might be developed for individual
organizations or projects (e.g., by a company reporting on its own emissions to a
carbon registry), community GHG emissions inventories convey information
23
about emissions associated with entire geopolitically defined communities. They
are neither exclusive of emissions separately reported by organizations in the
community, nor simply the sum of emissions reported by individual organizations
or households. Rather, community inventories provide new ways of
understanding the collective GHG emissions stories associated with a community.
They are primarily created from community‐wide data sets (e.g., total energy use,
total miles driven, total waste produced). While no community inventory is fully
comprehensive (some emissions cannot be estimated due to a lack of valid
methods, a lack of emissions data, or for other reasons), community inventories
often aim to provide as complete a picture of GHG emissions associated with a
community as is feasible.
24
Chapter 3
Methodology
Site Description
Thurston County is located at the southern-most point of Puget Sound in
western Washington and is one of the smallest counties in Washington State. The
county covers a total of 736 square miles, approximately 14% of which is
incorporated in cities and towns. Topographically, the area ranges from coastal
lowlands to prairie flatlands and the foothills of the Cascade Range. The county
neighbors Mason, Pierce, Lewis, and Grays Harbor counties to the north, east,
south, and west, respectively.
Boasting a population of roughly 252,264 in 2010, and an average annual
population growth of 2%, Thurston County has been one of the fastest-growing
counties in the state since the 1960s. Most of the observed population growth in
Thurston County is a result of in-migration, or the movement of individuals from
outside the region into the region. Further, Thurston Regional Planning Council
estimates the county population will continue to grow to 400,000 residents by
2040. The potential impacts of such population growth and associated
development on the environment and greenhouse gas emissions are cause for
concern, further justifying the need for regular carbon accounting in order to
coordinate and measure impact reduction plans.
25
Selection of Estimation Methodology
Given the many ways that communities contribute to greenhouse gas
emissions and the many methodologies available to estimate emissions, the U.S.
Community Protocol for Accounting and Reporting Greenhouse Gas Emissions
(i.e., Community Protocol, http://www.icleiusa.org/tools/ghgprotocol/community-protocol) was selected as the primary guide for estimating
community-wide greenhouse gas emissions within the geopolitical boundary of
Thurston County Washington. The Community Protocol is a national standard
developed by ICLEI-USA (International Council for Local Environmental
Initiatives), now known as Local Governments for Sustainability USA, to inspire
and guide U.S. local governments to account for and report on greenhouse gas
emissions associated with the communities they represent. The development of
the Community Protocol was funded by Pacific Gas and Electric Company, the
State of Oregon Department of Environmental Quality, and through a National
Science Foundation grant from the Research Coordination Network led by Dr.
Anu Ramaswami at University of Colorado Denver. The Community Protocol
was vetted by industry experts working in local, state, and federal governments,
as well as universities, non-governmental organizations, and private corporations
across the United States and Canada. By addressing six internationally recognized
greenhouse gases regulated under the Kyoto Protocol (CO2, CH4, N2O,
Hydrofluorocarbons (HFCs), Perfluorocarbons (PFCs), and Sulfur hexafluoride
(SF6)) across five basic emission types (built environment, transportation and
26
other mobile sources, solid waste, water and wastewater, and agriculture), the
protocol can be used to estimate the quantity of GHG emissions associated with
community sources and activities during a chosen analysis year using a
consumption based methodology.
Data Allocation
The quantities of CO2, CH4, and N2O emitted for each of the five basic
emission types were estimated for 2010 based on the best available data. Data for
this inventory was allocated during the months of January and February of 2013,
in partnership with Thurston Climate Action Team, Thurston County, and
Thurston Regional Planning Council. Aggregate use of natural gas and electricity
in residential, commercial, and industrial units within the geopolitical boundary of
Thurston County were obtained from Puget Sound Energy. Additionally,
estimates for a small percentage of residential on-site fuel usage not served by
Puget Sound Energy (i.e., fuel oil, propane, liquefied petroleum gas, and wood)
were obtained utilizing the Energy Information Administration’s State Energy
Data System (SEDS). Values for the amount of fuel oil, propane, liquefied
petroleum gas, and wood were obtained by scaling-down consumption estimates
from the Energy Information Administration’s (EIA) State Energy Database
System (SDES). Thurston County Solid Waste provided aggregate solid waste
volumes generated within the geopolitical boundary and collected at countyowned sites. Estimates for livestock production (i.e., dairy and beef cows, swine,
and sheep) were obtained from the United States Department of Agriculture’s
27
Agricultural Census of 2007. Emissions from the operation of wastewater
treatment facilities located within the community were estimated based on data
provided by the Lacey, Olympia, Tumwater, Thurston (LOTT) Clean Water
Alliance and Thurston Regional Planning Council’s Profile 2012. Emissions from
on road vehicles operating within the community were estimated based on
Vehicle Miles Traveled (VMT) data supplied by Thurston Regional Planning
Council’s Travel Demand Model and Annual Vehicle Miles Traveled data from
the Highway Performance Monitoring System (HPMS) database.
Estimate Calculation Methodology
Microsoft Excel was used to create a calculator that incorporated
estimation methods provided by the Community Protocol (Table 3) and user
inputs (Table 4). Metric Tons of Carbon Dioxide Equivalents (MTCDE) were
calculated either directly with an equation supplied by the Community Protocol or
by converting individual estimates for each of the three greenhouse gases
(provided in units of metric tons of the particular gas) into Carbon Dioxide
equivalents using 100 year Global Warming Potential (Table 2) and summing.
𝑀𝑇𝐶𝐷𝐸 = [(𝑚𝑡 𝐶𝑂2 × 𝐺𝑊𝑃𝐶𝑂2 ) + �𝑚𝑡 𝐶𝐻4 × 𝐺𝑊𝑃𝐶𝐻4 �
+ �𝑚𝑡 𝑁2 𝑂 × 𝐺𝑊𝑃𝑁2 𝑂 �]
Where the variable in metric tons (e.g., mt CO2) represents the value obtained
from the estimation methodology and the variable Global Warming Potential
(GWP) represents the value obtained from Table 2.
28
Table 2: One-hundred year Global Warming Potentials (GWP) for greenhouse
gases. Carbon Dioxide (CO2) has a GWP of 1 since it is the baseline unit
to which all other greenhouse gases are compared.
Greenhouse Gas
100 year GWP
Carbon Dioxide (CO2)
1
Methane (CH4)
21
Nitrous Oxide (N2O)
310
The Community Protocol provides equations that a user can input communitybased variables in order to calculate individual greenhouse gas values or MTCDE
for a given emission source or activity. The following tables detail which
equations were used (with specific equation numbers referring to equations found
within the Community Protocol) to calculate emissions associated with a
particular source or activity (Table 3), and the user inputs used within those
equations (Table 4).
Table 3: Emissions sources and related estimation method used to calculate
greenhouse gas emission based on the Community Protocol. The right
column details which equations were used (with specific equation
numbers referring to equations found within the Community Protocol) to
calculate emissions associated with a particular source or activity listed in
the column on the left.
Emission Source
Estimation Method Used
Built Environment Emission Activities and Sources
Emissions from stationary
BE.1.1, Equations BE.1.1.1,
combustion of natural gas in
BE.1.1.2, BE.1.1.4, BE.1.1.6
residential, commercial, and industrial
units
Emissions from stationary
BE.1.2, BE.1.1
combustion of fuel oil, propane/LPG,
and wood in residential units
29
Emissions from use of electricity in
BE.2.1, Equation BE.2.2
residential, commercial, and industrial
units
Emissions from electricity
BE.4.1, Equation BE.4.1.1
transmission and distribution losses
Upstream emissions from energy use BE.5.1, Equation BE.5.1.1; BE.5.2A
Transportation and Other Mobile Emission Activities
Emissions from passenger vehicles
TR.1.B, Equations TR.1.B.2,
TR.1.B.3
Emissions from freight and service
TR.2.A, Equations TR.2.A.1,
trucks
TR.2.A.2
Solid Waste Emission Activities and Sources
Methane emissions from community- SW.4.1
generated waste sent to landfills
Process emissions associated with
SW.5
landfilling
Collection and transportation
SW.6
emissions
Agricultural Livestock Emission Activities and Sources
Methane emissions from enteric
A.1
fermentation
Wastewater and Water Emission Activities and Sources
Stationary methane emissions from
WW.1.a
combustion of digester gas
Stationary nitrous oxide emissions
WW.2.a
from combustion of digester gas
Stationary carbon dioxide emissions
WW.3
from digester gas combustion
Process methane emissions from
WW.6
wastewater treatment lagoons
Process nitrous oxide emissions from WW.7
wastewater treatment plants with
nitrification or denitrification
Process carbon dioxide emissions
WW.9
from the use of fossil-fuel-derived
methanol for biological nitrogen
removal
30
Table 4: List of user input descriptions, values, and related emission
source/activity. These values were the user inputs utilized to calculate
emission estimates for the various emission sources and activities.*Values
are obtained by scaling-down consumption estimates from the Energy
Information Administration’s (EIA) State Energy Database System
(SDES)
Input Description
Input Value
Built Environment
Use of electricity in residential
units
1,266,273,211
(kWh)
Use of electricity in commercial
units
920,512,299
(kWh)
Use of electricity in industrial
units
136,413,709
(kWh)
Use of electricity in street
lighting
4,419,884
(kWh)
Use of natural gas in residential
units
31,268,416
(therms)
Use of fuel oil in residential units
248,428*
(MMBtu)
Use of propane/LPG in
residential units
26,169*
(MMBtu)
Use of wood in residential units
125,965*
(MMBtu)
Use of natural gas in commercial
units
15,994,387
(therms)
Use of natural gas in industrial
units
4,007,881
(therms)
Emission Source/Activity
Consumption of
electricity, Transmission
and Distribution Losses,
Upstream emissions from
electricity use
Consumption of
electricity, Transmission
and Distribution Losses,
Upstream emissions from
electricity use
Consumption of
electricity, Transmission
and Distribution Losses,
Upstream emissions from
electricity use
Consumption of
electricity, Transmission
and Distribution Losses,
Upstream emissions from
electricity use
Onsite combustion of fuel,
Upstream emissions from
fuel use
Onsite combustion of fuel,
Upstream emissions from
fuel use
Onsite combustion of fuel,
Upstream emissions from
fuel use
Onsite combustion of fuel,
Upstream emissions from
fuel use
Onsite combustion of fuel,
Upstream emissions from
fuel use
Onsite combustion of fuel,
Upstream emissions from
31
Input Description
Input Value
Emission Source/Activity
fuel use
Transportation and Other Mobile Units
Vehicle Miles Traveled estimate
Use of fuel in passenger
2,341,013,000
cars
Use of fuel in heavy-duty
Vehicle Miles Traveled estimate 2,341,013,000
freight vehicles
Solid Waste
Methane emissions from
Tons of waste sent to landfill
165,191 tons
community-generated
waste sent to landfills
Process emissions
Tons of waste sent to landfill
165,191 tons
associated with landfilling
Collection and
Tons of waste sent to landfill
165,191 tons
transportation emissions
Agricultural Livestock
Methane emissions from
enteric fermentation and
5,165
Quantity of beef cows
manure, direct and indirect
individuals
nitrous oxide emissions
from manure
Methane emissions from
enteric fermentation and
5,451
Quantity of dairy cows
manure, direct and indirect
individuals
nitrous oxide emissions
from manure
Methane emissions from
enteric fermentation and
777
Quantity of swine
manure, direct and indirect
individuals
nitrous oxide emissions
from manure
Methane emissions from
enteric fermentation and
1,838
Quantity of sheep
manure, direct and indirect
individuals
nitrous oxide emissions
from manure
Wastewater Treatment
Digester annual average daily
138,369 ft3
LOTT Digester emissions
Biogas
Fraction of CH4 in biogas
70%
LOTT Digester emissions
BOD5
23,162 lbs
LOTT Process emissions
BOD5 removed
11,544 lbs
LOTT Process emissions
Population served by LOTT
102,000
LOTT Process emissions
LOTT Emissions from
31,029
Annual methanol consumption
methanol use in biological
gallons
treatment of wastewater
32
Emission sources and activities associated with the built environment
include the consumption of electricity, electricity transmission and distribution
losses, onsite combustion of fuel, and upstream emissions (i.e., emissions from
production/extraction) from electricity and fuel usage. Aggregate values for the
consumption of electricity in residential, commercial, industrial, and street
lighting units were used to calculate emissions associated with the generation of
the electrical energy consumed (Figure 2) as well as transmission and distribution
losses (Figure 3) and upstream emissions resulting from the use of electricity
(Figure 4). Aggregate values for the consumption of fuel in residential,
commercial, and industrial units were used to calculate associated emissions
(Figure 5) and upstream emissions resulting from the use of fuel (Figure 6).
33
Figure 2: Method for estimating individual GHG emissions from the use of
electricity, where “electricity” represents the use of electricity in
residential, commercial, or industrial units from Table 4 and “emission
factor” represents the emission factor listed for the NWPP sub-region for
the particular gas in Table B.10 of Appendix C of the Community
Protocol. Retrieved from “U.S. Community Protocol for Accounting and
Reporting Greenhouse Gas Emissions,” Developed by ICLEI Local
Governments for Sustainability – USA, 2012.
34
Figure 3: Method for estimating GHG emissions resulting from transmission and
distribution losses, where “community electricity use” represents the use
of electricity in residential, commercial, or industrial units from Table 4,
“grid loss factor” represents the value listed for the western region in
Table B.12 of Appendix C of the Community Protocol, and “CO2e
emission factor” represents the value listed for the NWPP sub-region for
CO2e in Table B.10 of Appendix C of the Community Protocol. Retrieved
from “U.S. Community Protocol for Accounting and Reporting
Greenhouse Gas Emissions,” Developed by ICLEI Local Governments for
Sustainability – USA, 2012.
35
Figure 4: Method for estimating upstream GHG emissions associated with
electricity used within a community, where “total electricity use”
represents the use of electricity in residential, commercial, or industrial
units from Table 4 and “regional upstream emissions factor” represents the
value listed for the western region in Table B.18 of Appendix C of the
Community Protocol. Retrieved from “U.S. Community Protocol for
Accounting and Reporting Greenhouse Gas Emissions,” Developed by
ICLEI Local Governments for Sustainability – USA, 2012.
36
Figure 5: Method for estimating emissions from on-site combustion of fuels in
residential, commercial, and industrial units, where “fuel use” represents
the use of the particular fuel in residential, commercial, or industrial units
from Table 4 and “emissions factor” represents the value listed for the
particular fuel in Tables B.2 and B.3 of Appendix C of the Community
Protocol. Retrieved from “U.S. Community Protocol for Accounting and
Reporting Greenhouse Gas Emissions,” Developed by ICLEI Local
Governments for Sustainability – USA, 2012.
37
Figure 6: Method for estimating upstream emissions associated with on-site fuel
use in residential, commercial, and industrial units, where “total fuel use”
represents the use of natural gas in residential, commercial, or industrial
units from Table 4, “conversion factor” represents the factor used to match
the units used in Table B.13 of Appendix C of the Community Protocol,
and “upstream EF” represents the fuel-specific value listed in Table B.13
of Appendix C of the Community Protocol. Retrieved from “U.S.
Community Protocol for Accounting and Reporting Greenhouse Gas
Emissions,” Developed by ICLEI Local Governments for Sustainability –
USA, 2012.
38
Emissions activities and sources associated with on-road transportation
and other mobile units include the use of fuel in on-road passenger and freight
vehicles, as well as the use of fuel in public transit vehicles. On-road passenger
and freight vehicle emissions were calculated by using the formula:
�(
𝑉𝑀𝑇 × %𝑣𝑒ℎ𝑖𝑐𝑙𝑒 𝑡𝑦𝑝𝑒
× 𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝐹𝑎𝑐𝑡𝑜𝑟𝑓𝑢𝑒𝑙 𝑡𝑦𝑝𝑒 )
𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑀𝑃𝐺𝑣𝑒ℎ𝑖𝑐𝑙𝑒 𝑡𝑦𝑝𝑒
Where VMT represents the Vehicle Miles Traveled estimate for passenger or
heavy-duty vehicles listed in Table 4, %vehicle type represents the default vehicle
mix value listed in Table TR.1.3 in Appendix D of the Community Protocol,
Average MPGvehicle type represents the default fuel efficiency by vehicle type
listed in Table TR.1.5 in Appendix D of the Community Protocol, and
Emission Factorfuel type represents the fuel-specific value listed in Table TR.1.6
in Appendix D of the Community Protocol. Emissions from public transit vehicles
were obtained from InterCity Transit’s 2010 greenhouse gas emissions inventory.
Emission sources and activities associated with the generation and
disposal of solid waste include methane emissions from community-generated
waste sent to landfills (Figure 7), process emissions associated with landfilling
waste (Figure 8), and rail transportation emissions (Figure 9).
39
Figure 7: Method for estimating methane emissions from community-generated
waste sent to landfills, where GWPCH4 represents the global warming
potential value of methane (i.e., 21), M represents the tons of waste sent to
the landfill listed in Table 4, Pi represents the default value of 1 for
landfilled waste (i.e., all waste included in M is landfilled), CE represents
the default Landfill Gas collection efficiency factor of 0.75 ,and EFi
represents the default emissions factors for mixed municipal solid waste
listed in Table SW.5 of Appendix E of the Community Protocol. Retrieved
from “U.S. Community Protocol for Accounting and Reporting
Greenhouse Gas Emissions,” Developed by ICLEI Local Governments for
Sustainability – USA, 2012.
40
Figure 8: Method for estimating process emissions from community-generated
waste sent to landfills, where M represents the tons of waste sent to the
landfill listed in Table 4 and EFP represents the diesel value for fuel (i.e.,
0.0164). Retrieved from “U.S. Community Protocol for Accounting and
Reporting Greenhouse Gas Emissions,” Developed by ICLEI Local
Governments for Sustainability – USA, 2012.
Figure 9: Method for estimating rail transportation emissions from communitygenerated waste sent to landfills, where M represents the tons of waste
sent to the landfill listed in Table 4, MT represents the estimated 200 miles
waste travels by rail to the landfill, and EFT represents the default value of
0.00014 for diesel locomotives. Only rail transportation emissions are
estimated as collection emissions are captured in the on-road vehicle
estimate. Retrieved from “U.S. Community Protocol for Accounting and
Reporting Greenhouse Gas Emissions,” Developed by ICLEI Local
Governments for Sustainability – USA, 2012.
41
Emissions sources and activities associated with domesticated animal
production include methane emissions from enteric fermentation. In this
inventory, only emissions from enteric fermentation are reported as the
availability of data related to manure management practices in Thurston County is
not readily available. Beef cows, dairy cows, swine, and sheep populations were
included in methane emissions estimates resulting from enteric fermentation
(Figure 10).
Figure 10: Method for estimating methane emissions from enteric fermentation,
where “animal population” represents species-specific population
estimates listed in Table 4, EF represents the species-specific emissions
factor listed in tables A.1.1 and A.1.2 in Appendix G of the Community
Protocol, and GWPCH4 represents the global warming potential for
methane (21). Retrieved from “U.S. Community Protocol for Accounting
and Reporting Greenhouse Gas Emissions,” Developed by ICLEI Local
Governments for Sustainability – USA, 2012.
42
Emission sources and activities associated with wastewater treatment at
the LOTT Clean Water Alliance Budd Inlet Treatment Plant include digester
operation (Figure 11, 12, 13), lagoon (Figure 14, 15) and biological (Figure 16)
wastewater treatment processes.
Figure 11: Method for estimating methane emissions from devices designed to
combust digester gas, where “digester gas” represents the average daily
biogas production listed in Table 4, and fCH4 represents the fraction of
CH4 contained in each unit of biogas (0.70). Retrieved from “U.S.
Community Protocol for Accounting and Reporting Greenhouse Gas
Emissions,” Developed by ICLEI Local Governments for Sustainability –
USA, 2012.
43
Figure 12: Example method for estimating nitrous oxide emissions from the
combustion of digester gas, where “digester gas” represents the average
daily biogas production listed in Table 4, and fCH4 represents the fraction
of CH4 contained in each unit of biogas (0.70), all other values as listed in
this figure. Retrieved from “U.S. Community Protocol for Accounting and
Reporting Greenhouse Gas Emissions,” Developed by ICLEI Local
Governments for Sustainability – USA, 2012.
44
Figure 13: Method for estimating carbon dioxide emissions from digester gas
combustion, where “digester gas” represents the average daily biogas
production listed in Table 4 and BTUCO2 represents the default value of
0.000841. Retrieved from “U.S. Community Protocol for Accounting and
Reporting Greenhouse Gas Emissions,” Developed by ICLEI Local
Governments for Sustainability – USA, 2012.
Figure 14: Method for estimating methane emissions from wastewater treatment
lagoons, where “BOD5load” represents BOD5 listed in Table 4 and “FP”
represents BOD5 removed listed in Table 4. Retrieved from “U.S.
Community Protocol for Accounting and Reporting Greenhouse Gas
Emissions,” Developed by ICLEI Local Governments for Sustainability –
USA, 2012.
45
Figure 15: Method for estimating emissions from denitrification, where P
represents population served by LOTT listed in Table 4. Retrieved from
“U.S. Community Protocol for Accounting and Reporting Greenhouse Gas
Emissions,” Developed by ICLEI Local Governments for Sustainability –
USA, 2012.
46
Figure 16: Method for estimating carbon dioxide emissions from methanol usage
in the biological treatment of wastewater, where “methanol load”
represents annual methanol consumption listed in Table 4. Retrieved from
“U.S. Community Protocol for Accounting and Reporting Greenhouse Gas
Emissions,” Developed by ICLEI Local Governments for Sustainability –
USA, 2012.
47
Chapter 4
Results
In calendar year 2010 sources and activities producing greenhouse gas
emissions in Thurston County, WA emitted roughly 2.78 million metric tons of
carbon dioxide equivalents (MTCDEs) (Table 5, Figure 17), including emissions
from the built environment, on-road vehicles (i.e., passenger, heavy-duty, and
public transit vehicles), the generation and disposal of solid waste, wastewater
treatment, and livestock production. The built environment was the largest
emission source type generating approximately 1.44 million MTCDE (52%),
whereas on-road vehicles were the second largest emission source type producing
approximately 1.23 million MTCDE (44%). The generation and disposal of solid
waste by the community emitted approximately 54,000 MTCDE (2%), whereas
emissions related to the primary wastewater treatment facility within the county
was approximately 31,000 MTCDE(1%), and livestock produced the least amount
of emissions, roughly 21,000 MTCDE (1%).
Table 5: Emission source type quantities, and percentage of total emissions.
Values are in Metric Tons of Carbon Dioxide Equivalents (MTCDE).
Emission Source Type
Built Environment
On-Road Vehicles
Solid Waste
Livestock
Wastewater Treatment
Total
Per Capita Emissions
MTCDE
1,444,406
1,230,054
54,166
21,289
31,508
2,781,423
11.03
%
52%
44%
2%
1%
1%
100%
48
Livestock
1%
Solid Waste
2%
On-Road
Vehicles
44%
Wastewater
Treatment
1%
Built
Environment
52%
Figure 17: Distribution of percentages of metric tons of carbon dioxide
equivalents emitted in 2010 from community sources and activities in
Thurston County, WA. Thurston County produced approximately 2.78
million metric tons of carbon dioxide equivalents in calendar year 2010,
including emissions from the built environment, on-road transportation,
solid waste, water and wastewater treatment, and livestock production.
Built Environment Emissions
Emissions resulting from the use of fuel and electricity in the built
environment account for the largest portion of emissions in the county (Figure
17). Diving further into the distribution of emissions within the built environment
reveals that the residential sector accounts for the most built environment
emission and the second largest single source of emissions count-wide (Figure
18).
49
900,000
800,000
700,000
600,000
500,000
400,000
300,000
200,000
100,000
0
Residential
Commercial
Industrial
Street Lighting
MTCDE
Figure 18: Distribution of built environment emissions in metric tons of carbon
dioxide equivalents among residential, commercial, industrial and street
lighting units. Emissions associated with the built environment in
Thurston County were largest in residential buildings.
The use of electricity within the county accounts for sixty percent of built
environment emissions (Table 6), while the use of fuel, primarily natural gas,
accounts for roughly twenty percent (Table 6). Upstream emissions involved in
the generation of the electricity consumed by the community account for
approximately ten percent (Table 6) of built environment emissions. Emissions
from electricity transmission and distribution losses and upstream emissions
associated with the production and distribution of natural gas account for five and
four percent of the built environment total, respectively (Table 6).
50
Table 6: Emission source quantities and percentage of total for emissions from the
built environment. Values are in Metric Tons of Carbon Dioxide
Equivalents (MTCDE).
Emissions Source
Use of Electricity
Use of Fuel
Upstream Electricity Use
Transmission and Distribution Losses
Upstream Fuel Use
Total
MTCDE
869,353
293,597
145,476
71,373
64,606
1,444,406
%
60%
20%
10%
5%
4%
100%
On-road Vehicle Emissions
On-road vehicle emissions account for approximately 44% of total
emissions in Thurston County, WA in 2010, and are the second largest emission
source type county-wide (Table 7). Emissions resulting from on road vehicles
operating within the county boundary were larger in passenger vehicles (962,360
MTCDE) than in heavy-duty freight vehicles (258,696 MTCDE), and public
transit emissions were the smallest source (8,997 MTCDE). Passenger vehicles
account for seventy-eight percent of emissions from on-road transport and are the
largest single-source of emissions county-wide, while heavy-duty freight vehicles
account for twenty-one percent of on-road transportation emissions, and public
transit accounts for approximately 1% of on-road transportation emissions.
51
Table 7: Emission source quantities and percentage of total for emissions from
on-road vehicles. Values are in Metric Tons of Carbon Dioxide
Equivalents (MTCDE).
Emission Source
Passenger vehicles
Heavy Duty Freight vehicles
Public Transit (Gasoline)
Public Transit (Diesel)
Total
MTCDE
962,361
258,697
1,842
7,154
1,230,054
%
78%
21%
>1%
>1%
100%
Solid Waste Emissions
Eighty-six percent of solid waste emissions are a result of methane
emissions from the community-generated waste that is landfilled (Table 8).
Emissions associated with the landfilling process (i.e., biological decomposition)
and equipment account for 5% of emissions (Table 8). Rail and truck emissions,
separate from on-road vehicle emissions, from transporting waste from the
Thurston County Waste and Recovery Center to the Roosevelt Regional Landfill
in Roosevelt, WA (4,625 MTCDE) makeup the remaining 9% of solid waste
emissions (Table 8).
Table 8: Emission source quantities and percentage of total for emissions from the
generation and disposal of solid waste. Values are in Metric Tons of
Carbon Dioxide Equivalents (MTCDE).
Emission Source
Methane emissions
Process emissions
Transportation emissions
Total
MTCDE
46,831
2,710
4,625
54,166
%
86%
5%
9%
100%
52
Wastewater Treatment Emissions
Emissions from the operation of the primary wastewater treatment facility
within the county (Lacey Olympia Tumwater Thurston (LOTT) Clean Water
Alliance Budd Inlet Treatment Plant) were comprised of process emissions,
emissions from burning methane gas from the onsite digesters, and emissions
resulting from the use of methanol to biologically treat waste (Table 5). Process
emissions account for 62% of emissions at the primary wastewater treatment
plant, 37% of emissions were from the onsite burning of captured methane gas,
and approximately 1% of emissions were a result of methanol use in the
biological treatment of waste (Table 9).
Table 9: Emission source quantities and percentage of total for emissions from
wastewater treatment at the LOTT Clean Water Alliance Budd Inlet
Treatment Plant. Values are in Metric Tons of Carbon Dioxide
Equivalents (MTCDE).
Emission Source
Digester Emissions
Process Emissions
Methanol Emissions
Total
MTCDE
11,759
19,623
124
31,506
%
37%
62%
1%
100%
53
Livestock Emissions
Methane emissions resulting from domesticated animal production within
the county-boundary were divided among beef cows, dairy cows, sheep, and
swine (Table 6). Fifty-one percent of emissions from domesticated animal
production were from beef cows, 48% from dairy cows, 1% from sheep, and less
than 1% from swine (Table 10).
Table 10: Emission source quantities and percentage of total for emissions from
livestock production. Values are in Metric Tons of Carbon Dioxide
Equivalents (MTCDE).
Emission Source
Dairy Cows
Beef Cows
Swine
Sheep
Total
MTCDE
10,196
10,760
24
309
21,289
%
48%
51%
<1%
1%
100%
54
Chapter 5
Discussion & Conclusion
Emissions in Thurston County Relative to Washington State and King County, WA
In 2010, Thurston County emitted roughly 2.78 million metric tons of
carbon dioxide equivalents, roughly 2.5% of the total emissions in Washington
State for the same year (i.e., Washington State emitted roughly 103 million metric
tons of carbon dioxide equivalents in 2010, Washington State Department of
Ecology 2007). Given the population of Thurston County (252,264) and the total
estimated emissions for the county (2,781,423 Metric Tons of Carbon Dioxide
Equivalents (MTCDE)), per capita CO2 emissions in 2010 are roughly 11
MTCDE. The Washington State Department of Ecology reported in 2007 that on
a per capita basis, Washington residents emit about 15 MTCDE annually; much
lower than the national per capita average for 2012 of 25 MTCDE (EPA 2013),
largely due to the state’s abundant hydroelectricity. Further, emission estimates
for King County, WA, the nearest county in Washington that has completed a
similar inventory, are estimated at roughly 16% of total emissions in Washington
State (roughly 16.6 million MTCDE), with a per capita estimate of
approximately 8.6 MTCDE (Erickson and Chandler 2012).
Thurston County is on par with the state for both per capita emissions and
the proportion of emissions resulting from transportation (approximately 44%).
The principal source of Washington’s GHG emissions is transportation,
accounting for roughly 47% of total state gross GHG emissions in 2005
(Washington State Department of Ecology 2007). Although transportation does
55
make up a large fraction of both Washington’s emissions and Thurston County’s
emissions – again largely as a result of the state’s abundant hydroelectricity – on a
per capita basis, both produce emissions that are similar to the US average for
transportation (Washington State Department of Ecology 2007) roughly 5
MTCDE per capita (EPA 2013).
Per capita emissions in Thurston County are slightly higher than those
reported in King County, WA (approximately 8.6 MTCDE per capita). Emissions
in Thurston County in 2010 from fuel consumption in residential, commercial,
and industrial units are a small proportion of total emissions (approximately 11%)
in comparison to Washington State (20%), and the consumption of electricity
comprises a greater proportion of total emissions (approximately 31% to the
State’s 20%) (Washington State Department of Ecology 2007). Thurston County
per capita emissions from the built environment are higher (roughly 5.6 MTCDE
per person) than that of King County (roughly 4 MTCDE per person) (Erickson
and Chandler 2012). Further, per capita transportation emissions in Thurston
County are higher (4.7 MTCDE per person) than that of King County (4 MTCDE
per person). These differences may be explained in part by per-person decreases
in vehicle travel and residential energy that have been observed in King County
since 2003, suggesting that regional efforts to create pedestrian and transitoriented communities and more energy-efficient buildings may be beginning to
yield results (Erickson and Chandler 2012).
Agricultural related emissions in Thurston County differ significantly
from the state average. Agricultural activities (i.e., manure management, fertilizer
56
use, and livestock) in Washington account for 6% of state emissions (Washington
State Department of Ecology), while in Thurston County they account for 1% of
emissions. This difference is likely due to the sources and activities included at
the state level that are excluded from the county-level analysis (i.e., manure
management and fertilizer use), as well as the relatively larger proportion of
agricultural land in the eastern region of Washington than that of western
Washington. Further, farmland in Thurston County accounts for only 17% of
land-use (TRPC 2012), while it accounts for 33% of land-use state-wide (USDA
2009).
Implications of Results
The estimated greenhouse gas emissions values obtained using the
Community Protocol indicate the most significant sources of greenhouse gas
emissions in Thurston County, WA in 2010 were the use of fuel in on-road
transportation operating within the geopolitical boundary and energy usage in
residential, commercial, and industrial buildings and properties. The use of fuel in
on-road passenger vehicles represents the largest single source of emissions. The
results obtained suggest both local governments and community members in
Thurston County, WA should focus greenhouse gas emissions reduction efforts
on sources and activities associated with on-road transportation and the built
environment.
Given the limitations of local government’s ability to impact emissions
associated with on-road vehicles themselves (i.e., fuel efficiency), GHG reduction
57
efforts in the transportation realm should focus on reducing the quantity of
vehicles on the road through increased access and prevalence of public transit
options as well as pedestrian options like greenbelts. King County has achieved
steady reductions in transportation related emissions by increasing availability
and access to public transit options (Erickson and Chandler 2012). One
opportunity would be the provision of public transit options that extend the reach
of existing public transit infrastructure in the cities of Olympia, Lacey, and
Tumwater to connect incorporated and unincorporated portions of Thurston
County.
Increased attention should also be paid to residential energy efficiency
opportunities. Emissions resulting from the built environment are largely
attributable to the use of electricity and fuel in residential units. Both
governmental and individual efforts to reduce greenhouse gas emissions should
focus on residential units, specifically on efficient use of electricity among
residential units. King County has observed successes in reducing emissions
related to energy consumption in buildings through ongoing efforts to increase
energy performance of existing buildings, as well as encouraging fuel switchinig
from less-efficient oil to more-efficient natural gas. Further increased urbanization
in King County and the growing fraction of residents that live in less energyintensive multifamily housing may contribute to decreases in energy consumption
in buildings (Erickson and Chandler 2012). These options are feasibility for
Thurston County, and provide basic opportunities to reduce emissions from
buildings.
58
Emissions resulting from generation and disposal of solid waste, as well as
wastewater treatment may be relatively fixed in Thurston County given existing
efforts to reduce landfilled waste and minimize the environmental impact of
wastewater treatment processes. Wastewater treatment processes at the Budd Inlet
Treatment Plant, the primary wastewater treatment facility in Thurston County,
already utilizes anaerobic digestion of solids and methane capture to heat and
power its facilities, which is an extremely effective way to reduce GHG emissions
associated with wastewater treatment. Dissimilarly, there may be opportunities for
reductions in methane emissions from livestock production on farms in Thurston
County, given the rise of anaerobic digester technologies and improved
methodologies for manure management. However, the relatively small proportion
of emissions resulting from livestock production and the economic challenge
presented by low rates for electricity limit the applicability of these expensive
technologies on farms in Washington State (Redfern 2013).
Limitations of Estimation Methodology
Although the observed results are based on a vetted and accepted
greenhouse gas emissions estimation methodology, these results are constrained
by a number of factors. There are three primary sources of uncertainty that need
to be addressed due to the methodology chosen in this study, and a discussion of
these sources is presented below. Uncertainty arises from 1)the use of emission
factors for the Northwest sub-region of the Emissions & Generation Resource
Integrated Database (eGRID) in the estimation of emissions from electricity usage
in place of utility-specific emissions factors, 2) the estimation of upstream
59
emissions, and 3) the estimation of passenger vehicle emissions all present
challenges to the accuracy of aggregate emission estimates as well as per capita
emissions estimates.
The eGRID is a comprehensive source of data on the characteristics of
resource mixes for all electric power generated in the United States, and is a
source for estimating greenhouse gas emissions from electricity using eGRID
subregion emission factors for the northwest (i.e., the Western Electricity
Coordinating Council (WECC) Northwest (NWPP)). The Community Protocol
prefers the use of utility-specific emission factors; however, this data is not
readily available from Puget Sound Energy (PSE), which is the source of the
energy data used in this study. However, the WECC eGRID sub-region average
emission factors do provide adequate results as the fuel mix proportions between
PSE and the NWPP do not significantly differ (Table 11). The most significant
difference in estimates based upon the NWPP versus a utility-specific emission
factor would be an underestimation of emissions.
Upstream emissions refer strictly to the process of producing fuels.
Upstream emissions do not include GHG emissions associated with construction,
maintenance, and decommissioning of infrastructure, or the emissions associated
with management of wastes, such as spent nuclear fuels. The Community
Protocol recommends using the Department of Energy’s National Renewable
Energy Laboratory (NREL) average emissions factors derived from its Fuels and
Energy Pre-combustion Life Cycle Inventory (LCI) database, which was the
procedure followed in this study. The uncertainty associated with this
60
61
Puget Sound Energy
PSE
*Biomass, landfill gas, petroleum, waste and wind.
WECC Northwest
NWPP
Sub-region or Utility Sub-region / Utility Name
32
29.8
Coal
-
0.3
Oil
30
15.2
Gas
-
0.15
-
1.09
36
46.5
1
2.46
-
3.8
-
-
-
0.55
1*
0.12
Other Fossil Biomass Hydro Nuclear Wind Solar Geothermal Other
2009 Generation Resource Mix (%)
Table 11: Electricity resource mix for the eGRID WECC Northwest Sub-region in relation to Puget Sound Energy.
methodology is inherent in the application of these average values to any
particular locality. These factors, while widely applicable as national averages do
not allow the user to account for differences that could exist if the exact source of
a fuel, and technologies and processes used to extract and refine it, is known. The
recent increase in unconventional extractions methods (i.e., hydrolic fracturing, or
“fracking”) complicates this matter further. “Fracking” for natural gas is known to
increase methane leakage, causing higher upstream emissions as compared to
other forms of natural gas extraction. Similarly, gasoline and other petroleum
products derived from tar sands or other “heavy oil” deposits require significantly
more energy inputs to extract and refine than is the case with traditional liquid
deposits. This increases the amount of secondary fuels required to produce each
unit of primary fuel that was refined from one these unconventional deposits. The
Community Protocol does not account for energy-intensive extraction methods,
and thus may underestimate emissions from the use of natural gas that may be
derived from these sources. Further, due to a lack of available data, upstream
emissions from some fuel types are not considered in this method, such as
biomass. Also, data on secondary fuel use associated with the production of many
fuel types beyond the most common (natural gas, coal, and fuel oil) are not widely
available and not currently included in the Community Protocol.
The Community Protocol provides a framework for estimating emissions
from on-road transit, however, local estimates of GHG emissions from vehicles
differs from state-level and national-level accounting because of the high
proportion of cross-boundary travel, and the unique authority and influence local
62
governments possess over transportation and land use. Typically, state and
national estimation methods utilize the aggregate amount of fuel dispensed, which
does not serve local entities well as vehicles typically travel between multiple
jurisdictions on a single tank of fuel (Ramaswami et al. 2008) . Similarly,
methods based solely on vehicle travel within the community’s geographic
boundaries also produce inaccurate results also due to the high proportion of
cross-boundary traffic. This inventory attempts to address this issue by using
Thurston Regional Planning Council’s Travel Demand Model, and excluding all
modeled trips that do not originate or terminate within the Thurston County
geopolitical boundary. However, local variations in vehicle fuel efficiency and
fuel type further complicate emission estimates, and adjustments based on known
local data are difficult to obtain as state departments that manage the registration
of motor vehicles do not produce it; for this reason the national traffic mix
proportions provided by the Community Protocol were applied to the modeled
regional Vehicle Miles Traveled (VMT) estimate.
Future Research and Interdisciplinary Statement
Future efforts related to greenhouse gas emission estimates for Thurston
Climate Action Team and Thurston County should focus on producing an
inventory for the 1990 calendar year in order to establish reduction targets that are
in line with existing targets for state agencies outlined in RCW 70.235.020 – the
law defining Greenhouse gas emissions reduction targets for Washington State. In
addition, subsequent inventories should be completed on an annual basis to track
63
progress and trends over time. Further, future iterations of this study should strive
to incorporate utility-specific emission factors for Puget Sound Energy and
regionally accurate vehicle fuel types and efficiencies and traffic mix proportions.
These provisions will result in an inventory with greater accuracy and
completeness for the region.
These future efforts are significant to and highlight the interdisciplinary
nature of this study. Community greenhouse gas emissions inventories are an
important component of subnational greenhouse gas emissions reduction
strategies, and this inventory is a first-step in developing plans and policies that
will truly reduce emissions. The estimates herein provide a basis from which
planners and policymakers can plan, initiate, and measure emission reduction
efforts.
Conclusion
Thurston County is particularly vulnerable to climate change due to
susceptibility to sea level rise, ocean acidification, and wildfire, in addition to
economic dependencies on natural resources, like aquaculture, logging, and
hydroelectricity. Climate change is projected to affect many human systems and
systems upon which humans are dependent in Washington State, like forest
resources, electricity, municipal water supplies, agriculture, human health, and
shorelines. Climate change’s impacts on the state’s electrical system, which is
highly dependent on hydropower, will affect both supply and demand and include
shifts in the timing of peak hydropower generation due to increased/decreased
seasonal flows, as well as increased electrical demands in the summer months for
64
cooling needs (Elsner et al. 2010). The threat to hydropower generation will likely
exacerbate the importation of electrical energy or drive the development of new
generation resources, likely increasing greenhouse gas emissions in the region.
Agriculture in Washington will likely gain longer growing seasons, with
increased aridity and reduced water supply alongside increases in water demands
driving further increases in emissions.
Greenhouse gas emissions inventories are an integral part of local and
state greenhouse gas emissions reductions plans across the United States as global
atmospheric concentrations of carbon dioxide are reaching unprecedented levels.
However, Thurston County is but a small contributor to global greenhouse gas
emissions. In relation to global climate change, the importance of community
greenhouse gas emissions inventories on a much broader scale involves the
development of plans and policies that will result in marked reductions of
greenhouse gas emissions locally, but also reduction strategies that are applicable
and replicable on a national, and even global, scale.
65
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https://fortress.wa.gov/ecy/publications/publications/1002046.pdf
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Appendix A: Table of Emission Estimates
Thurston County
Emission Source Type
Built Environment
On-Road Vehicles
Solid Waste
Agriculture/Livestock
Wastewater Treatment
Total
Per Capita Emissions
MTCDE
1,444,406
1,230,054
54,166
21,289
31,508
2,781,423
11.03
%
52%
44%
2%
1%
1%
100%
user input range
estimated values
calculating range
do nothing
bold type for source totals
KEY
BUILT ENVIRONMENT
Use of fuel in residential, commercial, and industrial stationary combustion equipment
Natural Gas (therms) Natural Gas (MMBtu) Fuel Oil (MMBtu) Propane/LPG (MMBtu)
Wood (MMBtu)
31,268,416
3,126,842
248,428
26,169
125,965
15,994,387
1,599,439
4,007,881
400,788
Residential
Commercial
Industrial
Upstream emissions from use of natural gas in residential, commercial, and industrial stationary equipment
Natural Gas (therms) Natural Gas (ft^3)
Natural Gas (m^3)
mt CH4
mt N2O
31,268,416
3,126,841,600
88,542,148
15,994,387
1,599,438,700
45,290,986
4,007,881
400,788,100
11,349,036
Total
Residential
Commercial
Industrial
Use of electricity in lighting(ext), residential, commercial, and industrial buildings
Electricity (kWh)
Electricity (MWh)
mt CO2
mt CH4
4,419,884
4,419.88
3,620,813
67.58
1,266,273,211
1,266,273.21
1,037,343,677
19,361.32
920,512,299
920,512.30
754,092,880
14,074.63
136,413,709
136,413.71
111,751,475
2,085.77
Lighting (ext)
Residential
Commercial
Industrial
mt CO2
mt CH4 mt N2O MTCDE
197,583
58
1.01 187,307
84,802
8
0.16
85,020
21,250
0.40
0.04
21,271
Total 293,597
MTCDE
39,401
20,154
5,050
64,606
mt N2O
MTCDE
55.25
1,650.80
15,828.42 472,946.15
11,506.40 343,806.33
1,705.17 50,949.78
Total 869,353.05
Electricity Transmission and Distribution Losses emissions from the use of electricity in lighting(ext), residential, commercial, and industrial buildings
Electricity (kWh)
Electricity (MWh)
4,419,884
4,419.88
1,266,273,211
1,266,273.21
920,512,299
920,512.30
136,413,709
136,413.71
Lighting (ext)
Residential
Commercial
Industrial
mt CO2
mt CH4
mt N2O
Total
MTCDE
135.53
38,828.59
28,226.29
4,182.95
71,373.36
Upstream Emissions from the use of electricity in lighting(ext), residential, commercial, and industrial buildings
Electricity (kWh)
4,419,884
1,266,273,211
920,512,299
136,413,709
Lighting (ext)
Residential
Commercial
Industrial
mt CO2
mt CH4
mt N2O
Total
MTCDE
276.24
79,142.08
57,532.02
8,525.86
145,476.19
SOLID WASTE
Generation and disposal of solid waste by the community using total volume of waste generated in Thurston County
Tons
mt CO2
CH4 in MTCDE
N2O in MTCDE
MTCDE
Methane emissions from community-generated waste
sent to landfills
165,191.00
Process emissions associated with landfilling
165,191.00
Transportation emissions
165,191.00
46,831.65
46,831.65
2,709.13
4,625.35
Total
54,166.13
Domesticated animal production, using USDA Agricultural Census 2007 figures
Quantity
mt CO2
mt CH4
mt N2O
5,165
485.5100
5,451
512.3940
777
1.17
1,838
14.70
Total
MTCDE
10,195.71
10,760.27
24.48
308.78
21,289.24
AGRICULTURE/LIVESTOCK
Dairy Cows (individuals)
Beef Cows (individuals)
Swine (individuals)
Sheep (individuals)
WASTEWATER TREAMENT
Emissions from operation of primary wastewater treatment facility located in the community
Volume
MTCDE
CH4 in MTCDE
N20 in MTCDE
Total MTCDE
3)
LOTT - Digester Annual Average Daily Gas (ft
LOTT - Fraction of CH4 in biogas (annual average)
LOTT - Digester Emissions
LOTT - lbs BOD/day
LOTT - kg BOD/day
LOTT - lbs BOD/day removed
LOTT - kg BOD/day removed
LOTT - Fraction kg BOD/day removed
LOTT - Population Served
LOTT - Process Emissions
LOTT - Annual Methanol consumption (gallons)
LOTT - Emissions from Methanol Use
138,369
70%
2,213.16
2,443.93
7,102.68
11,759.78
19,402.0453
221.3
19,623.3853
Total
124.3410
31,507.50
Emissions from Passenger vehicles
On road vehicles operating within the community, excluding public transit
VMT
kg CO2
g CH4
g N2O
938,155,810.87
63,272,899.36
73,793,411.79
2,341,013,000
MTCDE
962,360.50
Emissions from Heavy Duty Freight vehicles
2,341,013,000
23,162
10,506
11,544
5,236
0.49840
102,000
31,029
100.84425
124.3410
ON-ROAD VEHICLES
258,656,133.75
129,201.40
121,601.32
Emissions from Public Transit (Gasoline)
258,696.54
1,842.75
Emissions from Public Transit (Diesel)
7,154.29
Total
1,230,054.08
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