Centre Region Climate Change Action Plan: Phase I
Centre Region
Greenhouse Gas Emissions Inventory
Peter D. Howe
Edited by Brent Yarnal & Howard Greenberg
Department of Geography
The Pennsylvania State University
This report is the collective work of the author and editors, but it relies on extensive information provided by local
governments, agencies, and organizations. Inventorying greenhouse gas emissions is an ongoing process; the
results reported here may change if more accurate data become available.
The Centre Region Climate Change Action Plan Project is funded by a grant from the Pennsylvania Department of
Environmental Protection.
Contact information:
302 Walker Building
Department of Geography
The Pennsylvania State University
University Park, PA 16802
Author
Peter D. Howe, doctoral student: pdh143@psu.edu
Editors
Dr. Brent Yarnal, Professor of Geography and Associate Head: alibar@psu.edu
Howard Greenberg, Research Associate: hjg3@psu.edu
2
Table of Contents
1.
Introduction................................................................................................................................2
1.01 Centre Region Climate Change Action Plan Project
2
1.02 Regional Profile
3
1.03 Greenhouse Gases (GHGs) and Climate Change
5
1.04 Climate Change Impacts in the Centre Region
5
1.05 The Greenhouse Gas Emissions Inventory
7
2.
Emissions Sources by Sector ...................................................................................................... 10
2.01 Local Transportation
10
2.02 Electricity
13
2.03 On-site Fuels
16
2.04 Waste Management
20
2.05 Agriculture and Synthetic Chemicals
23
3.
Total Greenhouse Gas Emissions ............................................................................................... 26
3.01 The Centre Region
26
3.02 Municipalities
29
4.
Emissions Over Time: Historical Estimates and Projections ......................................................... 32
4.01 Historical Estimates of GHG Emissions in 1990
32
4.02 Future Projections of GHG Emissions in 2025
32
4.03 Comparing Past, Current, and Future Emissions
33
5.
Methodology ............................................................................................................................ 34
5.01 Population, housing, and businesses
34
5.02 Transportation
34
5.03 Electricity
36
5.04 On-site fuels
37
5.05 Waste management
39
5.06 Agriculture and synthetic chemicals
41
6.
References ................................................................................................................................ 43
Appendix A: Emissions from Long-Distance Travel ............................................................................ 47
Total Emissions Including Long-Distance Travel
47
Components of the Long-Distance Travel Sector
48
Methodology for Estimating Long-Distance Travel Emissions
50
Appendix B: Example Scenario—A Possible Option for Climate Change Action................................... 51
Scenario: Wind Energy Credits for Households
51
1. Introduction
1.01 Centre Region Climate Change Action Plan Project
The Centre Region Climate Change Action Plan Project (CentreCCAP) is a
collaborative effort of the municipalities of Pennsylvania’s Centre Region, which include the
Borough of State College and the surrounding townships of College, Ferguson, Halfmoon,
and Harris. This document reports the results of Phase 1 of CentreCCAP, a baseline
inventory of greenhouse gas (GHG) emissions for the year 2006 and a projection of
emissions to the year 2025.
CentreCCAP will be completed in five phases:
Phase 1 features a regional GHG emissions inventory for the baseline year 2006.
Projections of GHG emissions to the year 2025 are included in phase 1.
Phase 2 convenes focus groups made up of regional stakeholders; the purpose of the
focus groups is to establish a list of potential mitigation options tailored to the Centre
Region.
Phase 3 features a report that fleshes out the options indentified in Phase 2,
describing the option, pros and cons of the option, measures of successful implementation,
existing programs addressing the option, stakeholders affected by the option, sources of
funding for the option, and additional information.
Phase 4 again convenes focus groups to prioritize the mitigation options, ranking
them as high priority (implementation in 1-2 years), medium priority (implementation in
3-4 years), and low priority (implementation in 5-10 years).
Phase 5 aims to establish GHG reduction goals and develop a formal climate change
action plan; a Climate Change Committee consisting of representatives of the Centre Region
municipal governments will evaluate the potential mitigation options and recommended
priorities, commit to a set of options, and adopt a suit of regional GHG reduction goals, and
turn that set of goals into a formal climate change action plan, which will go out for public
comment and subsequent revision.
2
1.02 Regional Profile
The Centre Region, as defined by membership in the Centre Region Council of
Governments, consists of the Borough of State College and the surrounding townships of
College, Ferguson, Halfmoon, Harris, and Patton. The main campus of The Pennsylvania
State University (Penn State) dominates the Centre Region demographically and
economically. Penn State has over 43,000 students, with 13,000 living on campus and most
of the rest distributed between the Borough and townships of the Centre Region. The
campus employs more than 16,000 faculty and staff. The University has its own emissions
inventory and climate change action plan, which will not figure into this inventory because,
although the two entities—Penn State and the Centre Region—have a symbiotic
relationship, they are significantly different physically, demographically, economically, and
governmentally. This difference means that GHG emissions and mitigation plans for the
University and for the Region cannot be commensurate. Although it is important for the
two entities to work together to coordinate their climate change action plans, the Centre
Region must also establish its own plan.
Figure 1-1: The Centre Region
3
The estimated population of the Centre Region, including non-permanent student
residents both on- and off-campus, was nearly 86,000 in 2007. Excluding students, the
permanent Centre Region population is roughly 45,000.
Traditional measures of income and poverty can be misleading when applied to a
community like the Centre Region which has a large student population. The per capita
income for the Centre Region in 2007 was only $19,211 and nearly half, 46.9 percent, of the
population and 9.7 percent of families were below the poverty line. Out of the total
population, 10.6 percent of those under the age of 18, but only 2.2 percent of those 65 and
older were living below the poverty line. Most of those individuals living below the poverty
line were university students or the children of university students. Apart from students,
the Region consists almost exclusively of middle class individuals and families living
traditional middle class lifestyles, with few members of lower- or upper-income groups.
The local economy is a service economy directed towards the employees, students,
and visitors. More than a million people visit the Centre Region annually. The small number
of heavier industries found in the Centre Region left over the last few decades with
economic restructuring. Penn State is the single major employer. Other significant
employers include: high tech firms (AccuWeather, C-COR, and Raytheon Intelligence and
Information Systems); local, state, and federal government; the hospitality industry
(numerous restaurants and hotels); schools, medical facilities, and eldercare; and
supermarkets and “big box” retailers.
Table 1-1-1: Demographic characteristics of the Centre Region
College Ferguson Halfmoon
Population (2006 est.)
9,003
16,207
2,939
Housing units (2006 est.)
3,730
6,760
925
Urban housing units (2000) 2,890
4,237
0
Rural housing units (2000)
323
1,462
802
Per capita income (2007 $)
Source: U.S. Census Bureau 2001, 2006b
Harris
4,686
1,959
1,210
645
Patton
12,799
5,925
4,337
637
State College
39,992
12,554
12,488
0
13,116
Centre Region
85,626
31,853
25,162
3,869
19,211
4
1.03 Greenhouse Gases (GHGs) and Climate Change
GHGs are atmospheric gases that absorb and reemit infrared radiation back to the
surface of the earth. This process is known as the greenhouse effect. As solar radiation
warms the earth’s surface, heat is emitted back into the atmosphere. Some of this heat
passes through the atmosphere and into space, but GHGs trap a portion of this heat and reemit it back toward the earth’s surface. There are many compounds that are considered
GHGs, but the main GHGs are water vapor, carbon dioxide, methane, and nitrous oxide.
Human activities since the Industrial
Revolution have increased the levels of
GHGs in the atmosphere. The majority of
emissions have been due to the burning of
fossil fuels, which represent a source of
stored carbon that was removed from the
atmosphere by organisms living millions of
years in the past. The burning of fossil fuels
returns this carbon to the atmosphere,
increasing concentrations of GHGs. These
increases in greenhouse gases, along with
changes in land cover, alter the balance of
energy in the earth’s climate system. These
human activities have caused increases in
Figure 1-2: Global yearly average temperature from
global average temperatures since the
1880 to 2005. Red bars indicate temperatures above
th
the mean, blue bars are temperatures below the
middle of the 20 century (IPCC
mean. The black line shows carbon dioxide
2007a)(Figure 1-3). Rising levels of GHG
emissions will continue to cause increases in concentration in the atmosphere (GCRP 2009, 17).
global average temperature over the next
century; failing to limit and reduce emissions will lead to escalating and irreversible
changes in climate across the surface of the earth (IPCC 2007a; Solomon et al. 2009).
Changes in climate resulting from human activity will have broad and substantial
impacts. Increases in global average temperature will change local climate and weather
patterns across the world, cause sea levels to rise, speed the retreat of glaciers and sea ice,
increase the intensity of extreme weather events, lead to species endangerment and
extinctions, and ultimately reduce agricultural yields (IPCC 2007b). The cumulative effects
of climate change will have widespread social and economic costs (IPCC 2007b). Direct and
indirect effects and their costs will profoundly alter ways of life in communities around the
world.
1.04 Climate Change Impacts in the Centre Region
Residents of Pennsylvania and the Centre Region will experience the effects of
climate change firsthand. During the last century, the average annual temperature in
Pennsylvania rose by .5 degrees F (UCSUSA 2008). Over the next century, rising
temperatures in Pennsylvania are projected to continue and accelerate due to rising levels
of GHGs in the atmosphere (UCSUSA 2008; GCRP 2009; Shortle et al. 2009):
5



Between 2010 and 2039, average annual temperatures in Pennsylvania are
expected to rise by 2.5 degrees F.
Between 2040 and 2060, average temperatures would increase between 4
and 5.5 degrees F, depending on whether emissions continue to rise. By mid
century, Eastern Pennsylvania summers are expected to resemble those in
North Carolina today. Summers in Western Pennsylvania may resemble
those of Kentucky.
Between 2070 and 2099, average annual temperatures would rise by 9.5
degrees F if high rates of GHG emissions continue. Under this scenario, an
average summer day in Pennsylvania would feel between 13 and 15 degrees
warmer at the end of the century than at
present. By the end of the century,
summers in Eastern Pennsylvania may
resemble summers in southern Georgia,
and summers in Western Pennsylvania
are projected to be similar to those in
Alabama.
These projected temperature increases
would also subject the Centre Region to more periods
of extreme heat. The Centre Region currently
experiences less than ten days per year over 90
degrees F. That number is expected to double between
2010 and 2039, and rise to over 40 days per year
between 2040 and 2069 and 65 days per year over 90
degrees F between 2070 and 2099. Under a scenario of
increasing GHG emissions, the Centre Region could
also experience 24 days per year over 100 degrees F
during the last quarter of the 21st century.
Rising temperatures and a changing climate are
expected to create serious challenges for cities in the Figure 1-3: Projected changes in
summer heat index for eastern PA:
northeastern U.S (GCRP 2009). These include:
what summers could feel like under



Declining air quality in urban areas due to higher (red) and lower (orange)
emissions scenarios (image: UCSUSA
air pollution from particulates and
2008, 9).
ground-level ozone, which are exacerbated
by higher temperatures.
Increasing allergy-related diseases due to rising temperatures, altered
precipitation, and increased growth of allergenic-pollen producing plants
such as ragweed and poison ivy.
Threatened infrastructure, including roads, bridges, railways,
communication networks, water systems, and utilities, as the magnitude and
frequency of flooding, drought, and storms changes away from historic
patterns.
6

Shifting demand on energy,
water, and sewer utilities
due to changing
temperatures and more
extreme weather events.
Climate change is also expected to
have considerable impacts on rural areas
in Pennsylvania (UCSUSA 2008; Shortle et
al. 2009), including:






Negative effects on dairy
farming and other livestock
Figure 1-4: Number of days in State College over 90
due to summer heat stress.
degrees F under scenarios of higher and lower GHG
Reduced agricultural
emissions (UCSUSA 2008, 14).
production of corn due to
higher summer temperatures. Warmer winters may also increase infestation
by overwintering insects and diseases.
Reduced production of fruits, including apples and grapes, due to the
reduction of winter chill periods.
Reductions in snow cover that will negatively affect winter recreation and
associated industries.
Changes in forest composition, such as the elimination of the black cherry
and sugar maple tree from Pennsylvania forests, that would adversely affect
the forest-products industry.
Reduction or elimination of trout and smallmouth bass fisheries in
Pennsylvania streams due to changes in surface water temperature.
Responses to climate change are generally divided between mitigation of the causes
of climate change and adaptation to the effects of climate change. Mitigation can be
achieved through reductions in the rate of GHG emissions. This report, and the scope of
CentreCCAP, is designed to facilitate mitigation at the regional scale.
Global and national policy changes to implement climate change mitigation will
require serious actions by people in all regions of the world to reduce their GHG emissions.
However, there is substantial local variation within countries, states, and regions in the
amounts, types, and sources of GHG emissions. Thus, policies to reduce emissions will need
to be tailored to the context of specific places (Easterling et al. 1998). CentreCCAP aims to
encourage locally relevant policy changes and personal actions that work best for people in
the Centre Region and are substantial contributors to climate change mitigation.
1.05 The Greenhouse Gas Emissions Inventory
Compiling a GHG emissions inventory is the first step in the development of a local
climate change action plan. An emissions inventory is a thorough record of a place’s GHG
emissions for a certain period of time. It is designed to reveal the distribution of emissions
sources for a particular place. Local residents, policymakers, and other stakeholders can
7
then use the information from a GHG emissions inventory to understand the makeup of
local emissions, create plans for emissions reduction, and track the progress of emissions
reduction strategies.
The EPA recommends that inventories track the four major gases that human
activity contributes to the atmosphere: carbon dioxide (CO2), methane (CH4), nitrous oxide
(N2O), and fluorinated gases. Many local and regional inventories omit fluorinated gases
from their accounting due to constraints on local data available regarding their emissions.
This inventory follows the same methodology, recording only the three highest-volume
GHGs: carbon dioxide, methane, and nitrous oxide. Carbon dioxide is the GHG that
contributes the most to global warming. Over six billion tons of carbon dioxide are released
every year by human activities (IPCC 2007a). For comparison, standard accounting of GHG
emissions records all emissions in a standard unit of measure: metric tons of carbon
dioxide equivalent (MTCO2e). For gases other than carbon dioxide, MTCO2e refers to the
amount of total emissions (in metric tons) multiplied by the global warming potential
(GWP) of the gas. They refer to the amount of carbon dioxide emissions by weight that
would produce the same contribution to global warming as a given weight of another GHG.
For example, methane is 21 times more powerful than carbon dioxide in contributing to
global warming, and nitrous oxide is 310 times as powerful (EPA 2009). Thus, the smaller
amounts of these emissions still have a measurable contribution to global warming.
All emissions inventories, whether at the national, regional, or local scale, share the
same techniques. Rather than measuring GHG emissions using satellites or active
monitoring, inventories measure emissions by compiling information about activities that
are known to produce or reduce GHG emissions and multiplying data about these activities
by known amounts of GHGs that are generated or sequestered by each activity. These
known amounts are called emissions coefficients. Emissions coefficients are obtained from
national and international agencies, namely the U.S. Environmental Protection Agency
(EPA) and the Intergovernmental Panel on Climate Change (IPCC). Emissions coefficients
are the amounts of a GHG that are emitted per each unit of activity. For example, the carbon
dioxide emissions coefficient for one barrel of home heating oil is 0.4224. This means that
using one barrel of home heating oil contributes 0.4224 metric tons of carbon dioxide
(MTCO2e) to the atmosphere.
An important consideration for GHG inventories at the regional scale is how to
define the scope of activities that generate emissions. GHG emissions are generally divided
between direct and indirect emissions. Direct emissions are those that are generated from a
source controlled by a person or organization. Indirect emissions are those that result from
the activity of a person or organization, but are produced at a source apart from the person
or organization. An example of direct emissions is gasoline used in personal vehicles; an
example of indirect emissions is electricity consumption from an electric utility. Electricity
consumption occurs at points far away from where the electricity is generated. Emissions
could then be attributed to either the location of the power plant or the location of the
electricity consumer. Thus, there are two possible approaches to attributing these
emissions. A supply-based approach would attribute all emissions from the power plant to
the location of the power plant, while an end-use approach would attribute emissions from
8
the power plant to the end-users of its electricity. The difference between these two
approaches presents challenges when compiling emissions inventories within regions,
because regions may have multiple resource, commodity, and energy inputs and outputs
that would lead to drastically different measurements of emissions from the supply-based
or end-use approaches.
The analysis presented in this report is primarily a consumption-based, end-use
approach to measuring GHG emissions. The end-use approach considers both direct and
indirect emissions occurring within a geographic area. It attributes emissions to parties
whose actions lead to the emissions being generated. In other words, people who are
responsible for the actions leading to emissions are recorded as generating those
emissions. The distinction between direct and indirect emissions is commonly subdivided
into three distinct categories: Scope 1, Scope 2, and Scope 3. Scope 1 emissions result from
direct consumption of fuels on-site. Scope 2 emissions are indirect emissions that result
from consumed electricity that is generated in off-site locations. Scope 3 encompasses all
other indirect emissions.
GHG emissions inventories are generally subdivided into sectors representing
distinct categories of emissions (IPCC 2007c; EPA 2009). In accordance with the end-use
approach presented in this report, we categorize emissions into sectors based on their end
use sector. Sectors include: local transportation, electricity, on-site fuels, waste
management, and agriculture and synthetic chemicals. The local transportation,
electricity, and on-site fuels sectors are sub-sectors of the broader energy sector, as defined
by the IPCC and EPA. Local transportation and on-site fuels are direct emissions are
included in Scope 1, while indirect emissions from electricity consumption are included in
Scope 2. The remaining sectors are included in Scope 3: waste management includes both
solid waste and wastewater; agriculture includes emissions from farm animals as well as
synthetic chemicals applied to farm fields and lawns. A final sector, emissions from longdistance travel, is appended at the conclusion of this report. Residing in Scope 1, this sector
includes GHG emissions generated by residents of the Centre Region on their travels
beyond the Centre Region.
Various offices, agencies, and organizations around the Centre Region and
Pennsylvania helped with the collection of data for this report. Specific sources of data are
provided in the methods section of this report.
The next chapter presents the sources of GHG emissions across the Centre Region,
divided into relevant sectors. Chapter 3 presents the overall results of the GHG emissions
inventory for the Centre Region and its component municipalities, and Chapter 4 provides
historical estimates of emissions for the year 1990 and future projections of emissions for
the year 2025. Chapter 5 details the methodology used to calculate emissions within each
sector and the techniques used to forecast and backcast future and past emissions. At the
conclusion of this report, Appendix A provides estimates of the contribution of longdistance travel by Centre Region residents to overall GHG emissions. Appendix B contains a
brief example scenario for reducing the Centre Region’s GHG emissions.
9
2. Emissions Sources by Sector
2.01 Local Transportation
The local transportation sector is a prominent source of GHG emissions in the
Centre Region. This sector encompasses direct fossil fuel combustion in cars, trucks, buses,
and other on-road vehicles driven within the boundaries of the Centre Region
municipalities1.
Fossil fuel consumption for transportation produces carbon dioxide and smaller
quantities of methane and nitrous oxide. In this inventory, we calculated emissions based
on total vehicle miles traveled (VMT) on roads within each Centre Region municipality. We
calculated emissions for three categories of vehicles: cars and light trucks, heavy trucks,
and transit vehicles (buses). This calculation does not include fuel burned while vehicles
are idling in heavy traffic, so it is likely to be a small underestimate of actual emissions.
The local transportation sector includes only emissions from traffic within the
boundaries of the Centre Region (see Appendix A for long-distance travel emissions). In
accordance with the end-use approach in this report, we sought to exclude vehicle travel
that did not originate or terminate within the Centre Region. Section 5.02 details the
methodology used to estimate vehicle miles traveled and emissions from local
transportation.
(a) Emissions sources
Transportation emissions accounted for 146,473 MTCO2e in 2006. Emissions from
cars and light trucks made up the large majority of emissions at 122,591 MTCO2e (86
percent), followed by heavy trucks at 17,169 MTCO2e (12 percent) and buses at 3,569
MTCO2e (2 percent) (Table 2-1).
Table 2-1: Emissions within the local transportation sector (MTCO 2e)
Cars and light trucks
Heavy trucks
Transit vehicles
Total
College
16,926
2,311
651
19,888
Ferguson
32,490
4,437
760
37,686
Halfmoon
6,481
885
0
7,365
Harris
9,199
1,256
108
10,562
Patton
26,769
3,655
598
31,021
State College
33,872
4,625
1,453
39,950
Centre Region
125,735
17,169
3,569
146,473
Emissions from transportation varied considerably across the municipalities of the
Centre Region (Figure 2-1). State College Borough contributed the largest amount of total
emissions, at 39,074 MTCO2e, followed closely by Ferguson Township at 36,846 MTCO2e
and Patton Township at 30,329 MTCO2e. College, Harris, and Halfmoon Townships made
up the smallest share of transportation emissions. Within the transportation sector, the
smallest percentage of emissions generated by cars and light trucks occurred in State
Transportation emissions for vehicles traveling outside of the Centre Region are estimated in Appendix A:
Long Distance Travel.
1
10
College Borough (84 percent); the largest percentage of emissions generated by cars and
light trucks occurred in Halfmoon Township (88 percent).
Figure 2-1: Transportation emissions by sector and municipality
Dividing total emissions by the estimated population in 2006, the local
transportation sector accounted for 1.71 MTCO2e per capita across the Centre Region
(Figure 2-2). State College Borough had the lowest ratio of transportation emissions per
capita, at 1.0 MTCO2e. The remaining municipalities had at least double the per capita
emissions of State College Borough, ranging from 2.21 MTCO2e for College Township to
2.51 MTCO2e for Halfmoon Township.
Figure 2-2: Transportation emissions per capita in 2006
(b) Local characteristics
The majority of trips that are accounted for in the local transportation sector are
commutes to and from work. Across the whole Centre Region, commutes by car or truck
11
driven alone accounted for 58 percent of all commutes in the year 2000; car or truck
carpool commutes represented another 10 percent (U.S. Census Bureau 2001). 21 percent
of workers commuted by bicycle or on foot, and an additional 6 percent took public
transportation (Table 2-3; Figure 2-3).
State College Borough, in addition to having the largest population in the Centre
Region, is adjacent to Penn State University, the largest employer in the region. As such,
State College Borough has, on average, commutes that are shorter than those from outlying
municipalities. In addition, a large percentage of commutes by State College Borough
residents are made on public transportation (9 percent), bicycle (2 percent), or on foot (41
percent).
The disparity in per capita transportation emissions between State College Borough
and the rest of the Centre Region can be explained in part by the large percentage of
workers who commute to work using these low-GHG-producing modes of transportation.
Of the remaining municipalities, Ferguson Township and Patton Township had the largest
percentage of workers commuting by public transportation (6 percent each), and College
Township had the largest percentage of workers commuting on foot (4 percent).
Table 2-2: Mode of commute to work by workers age 16 and over (2000)
College Ferguson Halfmoon Harris Patton
Car or truck: Drove alone 3,079
5,193
1,034
1,798 4,419
Car or truck: carpooled
437
1,018
111
216
843
Public transportation
85
432
2
18
408
Bicycle or walked
180
364
6
54
233
Source: U.S. Census Bureau 2001
State College
6,024
1,145
1,411
6,751
Centre Region
21,547
3,770
2,356
7,588
Figure 2-3: Graph of travel mode for commute to work by workers age 16 and over (2000).
12
2.02 Electricity
Greenhouse gases are emitted during the production of electricity from power plants or
on-site generators that burn fossil fuels. This inventory includes only grid-based electricity
consumption from power plants. We lacked an accurate method for inventorying on-site
generated electricity, which only accounts for a very small portion of electricity consumption.
The end-use-based accounting system used in this report makes local residents responsible for
indirect emissions from electricity generated outside the region but consumed locally.
Electricity in the Centre Region is provided by Allegheny Power, which transmits
electricity from the Middle Atlanticc regional grid (known as the PJM Interconnection) to
consumers in the Centre Region. Electricity transmitted on the grid is generated from multiple
sources with different compositions and amounts of GHG emissions. Fuels that produce GHG
emissions include coal (the largest source), natural gas, and fuel oil. Nuclear energy and
renewable sources such as wind, solar, and biomass do not increase net GHG emissions.
The electricity emissions of the Centre Region are dependent on the total fuel mix of
power generation across the PJM Interconnection grid. The 2006 fuel mix is reported below. It is
important to note that electricity emissions are closely connected to emissions from on-site fuels
(Section 2.03), since both sectors contribute to building heating.
(a) Emissions sources
Electricity consumption in the Centre Region resulted in emissions of 412,483
MTCO2e during the 2006 (Table 2-3). Allegheny Power reported electricity consumption
for four sectors: residential; commercial and small industrial; large industrial; and street
and area lighting. The majority of emissions were due to electricity demand in the
residential sector, which produced 255,572 MTCO2e (62 percent). Commercial and small
industrial demand produced 155,318 MTCO2e (38 percent), while large industrial
produced 240 MTCO2e (less than 1 percent). Electricity demand from street and area
lighting produced 1,353 MTCO2e (less than 1 percent).
Table 2-3: Emissions within the electricity sector by consumer sector (MTCO2e)
Colleg
Ferguso Halfmoo
Patto
e
n
n
Harris n
26,06
53,03
Residential
27,392 54,371
11,628
6
2
Commercial, small
28,89
industrial
18,189 32,962
4,509
9,551
3
Large Industrial
0
240
0
0
0
Street & area lighting
169
306
9
51
249
35,66
82,17
Total
45,750 87,879
16,146
9
4
State College
Centre Region
83,082
255,572
61,215
0
569
155,318
240
1,353
144,865
412,483
Emissions from electricity varied across municipalities. State College Borough was
the largest consumer of electricity, producing 144,865 MTCO2e, followed by Ferguson and
Patton Townships, which each produced 87,879 MTCO2e and 82,174 MTCO2e, respectively.
College Township electricity demand produced 45,750 MTCO2e, followed by Harris
Township with 35,669 MTCO2e and Halfmoon Township with 16,146 MTCO2e.
13
Figure 2-4: Electricity emissions by sector and municipality
On a per capita basis, the average Centre Region resident’s electricity use resulted in
4.82 MTCO2e emissions in 2006. Per capita electricity emissions varied across
municipalities. State College Borough had the lowest per capita electricity demand,
generating 3.62 MTCO2e. College, Ferguson, and Halfmoon Townships each had between
5.08 and 5.50 MTCO2e per capita emissions. Harris Township had the largest per capita
emissions from electricity, at 7.61 MTCO2e, followed by Patton Township at 6.42 MTCO2e.
The differences in per capita emissions between municipalities can be partly explained by
differences in heating fuel types, age of housing stock, and types of housing units. The next
section, On-site Fuels, details the distribution of fuel types between municipalities.
Figure 2-5: Electricity emissions per capita in 2006
14
(b) Local characteristics
Figure 2-6: Fuel mix for electricity transmitted on the PJM Interconnection grid.
Coal made up the majority of fuel for electricity transmitted over the PJM
Interconnection in 2006, at 58 percent (PJM Environmental Information Services 2007). Other
fossil fuel sources, including natural gas and fuel oil, made up less than 6 percent of total.
Nuclear energy contributed 35 percent of generating capacity, and renewable sources made up 2
percent.
Coal is one of the largest sources of GHG emissions from electricity generation
nationwide (EPA 2009), as well as the largest single contributor to GHG emissions that result
from electricity consumption in the Centre Region. In the Centre Region and its municipalities,
over 95 percent of all electricity emissions are due to combustion of coal (Figure 2-7).
Figure 2-7: Electricity emissions by fossil fuel type.
15
2.03 On-site Fuels
Homes, businesses, and municipal buildings burn fossil fuels on-site for space
heating, water heating, and other purposes. Fuels such as utility natural gas, propane, fuel
oil, kerosene, and coal are consumed for such uses. The direct consumption of these fuels
generates GHG emissions in various ratios, depending on the type of fuel consumed.
Electricity used for space and water heating is counted as an indirect emissions source and
included in the previous section.
Utility natural gas and fuel oil make up the majority of fuels consumed on-site for
heating (see section b, below). Columbia Gas of Pennsylvania is the utility that distributes
natural gas in the Centre Region. Numerous smaller companies distribute fuel oil and
propane.
Fossil fuel combustion produces CO2 emissions as well as smaller amounts of CH4
and N2O from fuel impurities and incomplete combustion. This inventory uses data from
the U.S. Census Bureau, the Energy Information Administration, and Columbia Gas to
estimate GHG emissions in homes, businesses, and other buildings (see section 5.04 for
detailed methodology). This section utilizes the fuel types denominated by the U.S. Census
Bureau for household heating fuel. The four fuel types that produce GHGs are: utility
(natural) gas; bottled, tank or LP gas (propane); fuel oil, kerosene, etc.; and coal or coke.
(a) Emissions sources
Direct emissions from on-site fuels produced 113,678 MTCO2e in 2006 across the
Centre Region (Table 2-4). The majority of emissions were due to the burning of fuel oil for
heating, which produced 65,124 MTCO2e, 57 percent of all on-site fuels emissions. Natural
gas was the second-greatest contributor to on-site fuels emissions, creating 41,302 MTCO2e
(36 percent) in the Centre Region. Bottled, tank, or LP gas contributed a much smaller
5,868 MTCO2e (5 percent), followed by coal or coke with 1,385 (1 percent).
Table 2-4: Emissions within the on-site fuels sector by fuel type (MTCO2e)
College Ferguson Halfmoon Harris Patton
Natural gas
2,788
10,705
0
205
7,770
Bottled, tank, or LP gas 576
1,033
590
444
473
Fuel oil, kerosene, etc. 11,859 14,605
3,333
7,778 6,938
Coal or coke
157
327
336
209
259
Total
15,380 26,670
4,259
8,636 15,440
State College
19,834
2,751
20,611
97
43,293
Centre Region
41,302
5,868
65,124
1,385
113,678
By consumer sector, fuels consumed in residences made up the majority of on-site
fuels emissions in the Centre Region (Table 2-5). Residential on-site fuels emissions were
83,314 MTCO2e (73 percent), while commercial and industrial emissions were 30,364
MTCO2e (37 percent).
Table 2-5: On-site fuels emissions by consumer sector
College Ferguson Halfmoon
Residential
10,475 20,372
2,776
Commercial & Industrial 4,904
6,299
1,483
Total
15,380 26,670
4,259
Harris
5,501
3,136
8,636
Patton
13,950
1,490
15,440
State College
30,241
13,052
43,293
Centre Region
83,314
30,364
113,678
Figure 2-8: On-site fuels emissions by fuel type
Figure 2-9: Per capita on-site fuels emissions in 2006
(b) Local characteristics
Despite the fact that there were fewer households utilizing natural gas than fuel oil
for heating (Table 2-6), fuel oil remained the largest contributor to GHG emissions in the
on-site fuels sector. Natural gas burns more efficiently and generates fewer GHG emissions
per unit of heat than fuel oil, meaning fewer per household emissions. 29 percent of
housing units in the Centre Region use natural gas for their primary heating fuel, while only
22 percent use fuel oil.
17
Table 2-6: Household heating fuel by number of housing units
College Ferguson Halfmoon Harris
Natural gas
451
1,727
0
37
Bottled, tank, or LP gas 55
104
56
46
Fuel oil, kerosene, etc. 976
1,332
272
671
Coal or coke
41
90
86
59
Electricity
1,460
2,078
305
827
Wood
54
145
46
77
Other fuel
32
18
4
25
No fuel used
0
17
0
10
Source: U.S. Census Bureau 2001
Patton
1,404
55
765
82
2,425
45
7
8
State College
3,449
289
1,986
28
6,167
14
57
34
Centre Region
7,068
605
6,002
386
13,262
381
143
69
Differences in housing stock and availability of the various heating fuel types may
contribute to the differences in types of household heating fuel between the municipalities
of the Centre Region. Natural gas, the most efficient fossil fuel for heating, is the primary
heating fuel for 31 percent of housing units in Ferguson Township and 29 percent of
housing units in Patton Township and State College Borough. Only 2 percent of housing
units in Harris Township and 15 percent in College Township have natural gas as the
primary heating fuel.
Households that rely on other types of fossil fuels for heat, such as fuel oil or
electricity (via indirect emissions from coal-fueled power plants), generate greater
amounts of GHG emissions per household (Figure 2-10). In 2006, the average Allegheny
Power residential customer with electric heat consumed nearly 18,000 kWh, while the
average customer with another primary heat source consumed less than 10,000 kWh
(Wahl 2007).
Harris Township and Halfmoon Township, with a large percentage of homes using
electricity and fuel oil for heat, generate over 15 MTCO2e of direct and indirect GHG
emissions per housing unit. Ferguson Township, in contrast, has many homes that use
natural gas as a heating fuel and generates 11 MTCO2e of direct and indirect GHG emissions
per housing unit.
18
Figure 2-10: Household heating fuel by number of housing units
Figure 2-11: Combined graph of emissions for electricity and on-site fuels per housing unit
19
2.04 Waste Management
The waste management sector includes indirect emissions generated from the
breakdown of solid and liquid waste. Solid waste includes trash from houses and
businesses in the Centre Region that municipalities and waste haulers deposit in landfills;
liquid waste includes sewage and other wastewater that flows to treatment plants or
domestic septic systems.
Solid waste releases methane due to anaerobic decomposition2. Methane in landfills
can escape to the atmosphere as a GHG, or it can be removed by flaring or recovered for
waste-to-energy systems. Waste collected in the Centre Region is sent to the Shade Landfill
in Somerset County, Pennsylvania. The Shade Landfill recovers methane for waste-toenergy purposes. The recovered methane is blended into the natural gas system for direct
use as an on-site fuel (PA DEP 2009).
Liquid waste includes municipal sewage and wastewater. Depending on the
treatment system, sewage treatment processes produce small amounts of methane and
nitrous oxide. Aerobic treatment systems that minimize anaerobic decomposition of
sewage sludge generate very small amounts of GHG emissions. Most of the wastewater
from the Centre Region flows to the University Area Joint Authority (UAJA) treatment plant,
which uses an aerobic system that produces very few GHGs. A portion of the wastewater
generated by State College Borough flows to the Penn State University treatment plant. The
Penn State plant treats wastewater using an anaerobic system, which generates larger
amounts of methane. This methane is collected and flared, resulting in emissions of carbon
dioxide. Domestic septic systems also produce small amounts of methane and nitrous oxide
emissions. We estimated GHG emissions from septic systems for Halfmoon Township,
which does not have municipal sewage service, as well as a small percentage of homes in
the remaining municipalities (excluding State College Borough) that use domestic septic
systems.
(a) Emissions sources
Indirect emissions in the waste management sector totaled 10,377 MTCO2e (Table
2-7). The majority of these emissions were due to the decomposition of solid waste, which
generated 8,466 MTCO2e, or 82 percent of emissions in the waste management sector.
Liquid waste contributed 1,911 MTCO2e, or 18 percent of emissions.
Table 2-7: Emissions within the waste management sector (MTCO2e)
College Ferguson Halfmoon Harris Patton State College
Solid waste
991
1,797
246
521
1,575
3,337
Liquid waste 142
396
219
123
259
773
Total
1,133
2,192
465
643
1,834
4,110
Centre Region
8,466
1,911
10,377
Waste incineration also produces GHG emissions, but no measurable quantities of waste in the Centre
Region were disposed of using this method.
2
20
Figure 2-12: Waste management emissions by waste type
Of all the Centre Region municipalities, State College Borough produced the largest
amount of emissions, 4,110 MTCO2e (40 percent) from both solid and liquid waste (Figure
2-11). Liquid waste emissions were relatively higher in State College Borough because
some of its municipal wastewater is treated at the Penn State University treatment plant,
which generates higher amounts of GHGs. Halfmoon and Harris Township, with the
smallest populations in the Centre Region, also produced the lowest total amount of
emissions from waste management.
Per capita waste management emissions were relatively similar across
municipalities (Figure 2-12). The Centre Region average was .12 MTCO2e. Halfmoon
Township had the highest per capita emissions, at .16 MTCO2e, while State College Borough
had the lowest per capita emissions at .10 MTCO2e.
Figure 2-13: Waste management emissions per capita in 2006
21
(b) Local characteristics
The Centre Region has a favorable combination of waste management processes
that result in very low GHG emissions from both solid and liquid waste. The aerobic
treatment process utilized by the UAJA for the majority of wastewater generated in the
Centre Region means that most liquid waste does not result in methane emissions. In
addition, the methane recovery waste-to-energy system at the Shade Landfill where solid
waste from the Centre Region is deposited prevents large quantities of methane from
escaping to the atmosphere and acting as a GHG.
22
2.05 Agriculture and Synthetic Chemicals
Certain agricultural practices result in GHG emissions. The agriculture and synthetic
chemicals sector includes emissions from fertilizer and lime applied to farm fields,
emissions from agricultural animals, and emissions from fertilizer applied to parks and golf
courses. The use of synthetic refrigerants, typically fluorinated gases, also emits GHGs.
Accurate data at the local scale are not available for fluorinated gases. Thus, as advised by
the EPA, they were not included in this inventory.
Synthetic fertilizers directly release nitrous oxide emissions through leaching and
runoff, and indirectly through volatilization. Lime application to agricultural soils indirectly
results in carbon dioxide emissions.
Livestock produce methane emissions during digestion (referred to as enteric
fermentation). Ruminant livestock such as cattle and sheep are the largest producers of
methane emissions. Management of manure from livestock also produces methane and
nitrous oxide emissions, depending on the type of manure management system. Livestock
included in this inventory were: cattle, poultry, horses, swine, sheep, and goats.
(a) Emissions sources
Emissions within the agriculture and synthetic chemicals sector totaled 21,506
MTCO2e in 2006. Emissions from cattle were the largest contributor to this total, at 15,757
MTCO2e (73 percent). Agricultural fertilizer was the second-greatest source of emissions, at
2,548 MTCO2e (12 percent). Other agricultural animals (poultry, horses, swine, sheep, and
goats) contributed 1,702 MTCO2e (8 percent), and agricultural lime was the source of 1,291
MTCO2e (6 percent). Fertilizer applied to municipal parks and golf courses had a negligible
contribution at 208 MTCO2e (1 percent).
Table 2-8: Emissions within the agriculture and synthetic chemicals sector (MTCO2E)
College Ferguson
Halfmoon Harris Patton State College
Park and golf
33
3
0
55
57
59
course fertilizer
Ag. fertilizer
116
1,419
477
269
267
0
Ag. lime
59
719
242
136
135
0
Ag. animals: cattle 719
8,775
2,951
1,662 1,650
0
Ag. animals: other 78
948
319
179
178
0
Total
1,005
11,864
3,989
2,301 2,288
59
Centre Region
208
2,548
1,291
15,757
1,702
21,506
Figure 2-14: Agricultural and synthetic chemicals emission by source type.
Agriculture and synthetic chemicals emissions varied considerably between
municipalities. Ferguson Township was by for the largest source of emissions, emitting
11,864 MTCO2e or 55 percent of the total. Halfmoon Township was the second-largest
source of emissions at 3,989 MTCO2e (19 percent), followed by Patton, Harris, and College
Townships. State College Borough has no active agricultural lands, meaning its sole source
of emissions in this sector was park and golf course fertilizer, totaling 59 MTCO2e (.3
percent).
Figure 2-15: Agriculture and synthetic chemicals emissions per capita in 2006
(b) Local characteristics
Since the Centre Region is composed of both rural and urban land uses, agriculture
acreage varies between its component municipalities (Table 2-9). Accordingly, emissions in
24
the agriculture and synthetic chemicals sector vary by the acreage of fertilized and limed
land, as well as the populations of agricultural animals in each municipality.
Table 2-9: Local characteristics contributing to agriculture and synthetic chemicals emissions
Colleg Ferguso Halfmo
Patto
State
e
n
on
Harris
n
College
Park lawn acreage fertilized
13.0
10.5
6.5
2.0
5.0
49.5
Golf course acreage (estimate)
37.5
0.0
0.0
75.0
75.0
75.0
Agricultural Security Area (ASA)
acreage
1,304 15,918
5,353
3,014
2,993 0
Centre
Region
86.5
262.5
28,582.0
Beef cattle (head)
Milk cows (head)
Chickens: broilers (head)
Chickens: layers (head)
Chickens: pullets (head)
Turkeys (head)
Horses, mules, burros, and donkeys
(head)
Swine (head)
Sheep (head)
Goats (head)
48
152
25
79
8
5
581
1860
311
968
92
57
196
625
104
326
31
19
110
352
59
183
17
11
109
350
58
182
17
11
0
0
0
0
0
0
41
73
22
17
500
893
271
213
168
300
91
72
95
169
51
40
94
168
51
40
0
0
0
0
1,604
487
383
Nitrogen applied to parks & golf
courses (lbs)
7,881
691
0
13,181
13,69
0
27,69
4
338,0
59
14,150
49,594
294,534
966,683
3,595,391
11,800,348
27,69 294,53
27,694
4
4
338,0 3,595,3 338,05
Lime (lbs)
59
91
9
Sources: PA DA 2007a, 2007b, 2008, 2009; USDA 2009; CRPR 2009
Nitrogen applied to farm fields (lbs)
294,53
4
3,595,3
91
1,044
3,340
558
1,739
164
103
897
25
3. Total Greenhouse Gas Emissions
This section presents the overall results of the GHG emissions inventory for the
Centre Region and each municipality within the region. The results include statistics for
total emissions, the percentage of emissions generated by each sector, and per-capita
emissions within each municipality.
3.01 The Centre Region
Total emissions for the Centre Region for the year 2006 were 704,574 MTCO2e
(Table 3-1; Figure 3-1). In general, fossil fuel combustion for energy dominated GHG
emissions within the Centre Region. The large majority (59 percent) of these emissions
were the result of electricity consumption, which resulted in emissions of 412,539 MTCO2e.
Local transportation was the second-largest source of GHG emissions, at 146,473 MTCO2e
(21 percent), followed by the on-site fuels sector at 113,678 MTCO2e (16%). Agriculture
and synthetic chemicals (21,506 MTCO2e; 3 percent) and waste management (10,377; 1
percent) were minor contributors to total emissions.
Table 3-1: 2006 GHG emissions by sector in the Centre Region and municipalities (MTCO 2e)
Colleg Ferguso Halfmoo
State
e
n
n
Harris Patton College
19,88
37,686
7,365
10,56 31,021 39,950
Local transportation
8
2
45,75
87,887
16,158
35,68 82,183 144,872
Electricity
7
2
15,38
26,670
4,259
8,636 15,440 43,293
On-site fuels
0
Waste management
1,133
2,192
465
643
1,834
4,110
Agriculture & synthetic
1,005
11,864
3,989
2,301 2,288
59
chemicals
Total
83,16
166,301 32,236
57,82 132,76 232,284
2
6
5
Figure 3-1: Total Centre Region emissions by source sector in 2006
Centre Region
146,473
412,539
113,678
10,377
21,506
704,574
State College Borough, with the largest population in the Centre Region, had the
highest amount of total GHG emissions, followed by Ferguson Township, Patton Township,
College Township, Harris Township, and Halfmoon Township, respectively, (Figure 3-2)
although the distribution of emissions between source sectors varied widely between
municipalities.
Figure 3-2: Total 2006 GHG emissions within each Centre Region municipality
The activities of the typical resident of the Centre Region resulted in emissions of
8.2 MTCO2e in 2006. Per capita emissions varied between municipalities. Harris Township
had the highest per capita emissions (12.3 MTCO2e), followed by Halfmoon Township (10.9
MTCO2e), Patton Township (10.4 MTCO2e), Ferguson Township (10.3 MTCO2e), and College
Township (9.2). State College Borough had the lowest per capita emissions (5.8 MTCO2e)3.
These differences in per capita emissions mainly result from different levels of emissions within the
transportation, electricity, and on-site fuels sectors (described in the previous section).
3
27
Figure 3-3: Per capita emissions in 2006
28
3.02 Municipalities
This section presents charts of GHG emissions sources for each Centre Region
municipality. Total values can be found in Table 3-1, above.
(a) College Township
Figure 3-4
(b) Ferguson Township
Figure 3-5
(c) Halfmoon Township
Figure 3-6
(d) Harris Township
Figure 3-7
(e) Patton Township
Figure 3-8
30
(f) State College Borough
Figure 3-9
31
4. Emissions Over Time: Historical Estimates and Projections
4.01 Historical Estimates of GHG Emissions in 1990
Many GHG emissions inventories begin from a baseline year of 1990. This year is
used, for example, in the international agreement known as the Kyoto Protocol, which calls
for industrialized countries to reduce their emissions to an average of 5 percent below
1990 levels by 2012 (UNFCC 2009). To best understand the change in Centre Region GHG
emissions over time, we present estimates of past emissions for the year 1990. These
historical estimates utilize applicable data from the U.S. Census Bureau regarding the
demographics of the Centre Region for the year 1990. In addition, we use emissions
coefficients that account for changes in vehicle fuel efficiency and the fuel mix for electricity
generation between 1990 and 2006.
Table 4-1: Historical estimate of GHG emissions in 1990 (MTCO2e)
College
Ferguson Halfmoon Harris
Local transportation
16,036
23,593
3,994
10,181
Electricity
34,580
51,518
8,190
32,178
On-site fuels
11,461
15,416
2,129
7,680
Waste management
746
1,061
141
474
Agriculture &
1,329
20,523
7,980
2,575
synthetic chemicals
Total
64,150
112,111
22,434
53,088
Patton
26,177
64,928
12,028
1,243
2,908
State College
42,059
142,990
42,136
3,596
58
Centre Region
122,040
334,383
90,849
7,262
35,372
107,283
230,839
589,905
4.02 Future Projections of GHG Emissions in 2025
Climate change action planning is a process that occurs in short, medium, and longterm time scales. As such, it requires an understanding of how local conditions will change
over time. This section provides projections of how GHG emissions will change in the
Centre Region between 2006 and 2025. Using population estimates for each municipality
derived from the Centre County Metropolitan Planning Organization, this projection is a
rough estimate of future emissions. The 2025 scenario presented here assumes that all
emissions coefficients will remain the same between 2006 and 2025. It does not account
for possible changes in vehicle fuel efficiency, for example, or potential changes in
residential energy efficiency.
Table 4-2: Projection of GHG emissions in 2025 (MTCO2e)
College
Ferguson Halfmoon
Local transportation
22,013
48,441
10,513
Electricity
51,781
115,534
23,583
On-site fuels
17,407
35,063
6,221
Waste management
1,133
2,414
411
Agriculture &
896
9,026
2,731
synthetic chemicals
Total
93,231
210,478
43,458
Harris
14,471
49,993
12,105
748
1,680
Patton
39,470
106,941
20,093
2,076
1,789
State College
39,774
147,460
44,068
3,761
60
Centre Region
174,681
495,292
134,957
10,543
16,182
78,996
170,369
235,124
831,656
4.03 Comparing Past, Current, and Future Emissions
The Centre Region has experienced an increase in total GHG emissions of 16.3
percent between 1990 and 2006. Emissions could continue this rise and reach 15.3 percent
above 2006 levels by 2025, assuming the population of the Centre Region increases as
predicted (Figure 4-1).
The makeup of the GHG emissions profile for the Centre Region has shifted since
1990 and may continue to change. The electricity, local transportation, and on-site fuels
sectors have increased in total emissions as well as their percentage of overall emissions.
The agriculture and synthetic chemicals sector has decreased in its total emissions and its
percentage of overall emissions due to conversion of farmland to urban uses. The 2025
projection assumes that agriculture will continue its decline in total emissions, while onsite fuels, electricity, and local transportation emissions will continue to increase.
Figure 4-1: GHG emissions estimates for 1990, 2006, and 2025
33
5. Methodology
5.01 Population, housing, and businesses
(a) Data sources
We obtained demographic data from the U.S. Census Bureau. Detailed data from the
2000 Census were available for household heating fuels, transportation to work, and
housing unit counts (U.S. Census Bureau 2001). The U.S. Census Bureau’s 2008 Population
Estimates Program provided population estimates for the year 2006 for each municipality
(U.S. Census Bureau 2008). The Centre County Planning and Community Development
Office provided counts of residential building permits (Centre County Government:
Planning and Community Development Office 2006). Numbers of businesses were obtained
from the 2002 Economic Census for Ferguson Township, Patton Township, and State
College Borough (U.S. Census Bureau 2006a).
(b) Methods
Housing units in 2006, the baseline year, were calculated by adding the sum of
residential unit building permits within each municipality from 2000 to 2006 to the total
number of housing units in each municipality recorded in the 2000 Census. This method
accounts for unequal population growth and residential development across the Centre
Region. Numbers of businesses in College Township, Halfmoon Township, and Harris
Township were estimated by multiplying the average ratio of businesses to housing units
in Ferguson Township and Patton Township by the number of housing units in each
township.
5.02 Transportation
(a) Data sources
Emissions from the transportation sector relied on daily vehicle-miles-traveled
(DVMT) data from the Pennsylvania Department of Transportation (PennDOT). PennDOT
supplied GIS layers with attached data detailing on-road DVMT for each segment of statemonitored roadway in Pennsylvania (PennDOT 2007b). DVMT statistics are calculated
using traffic count data from the PennDOT Highway Performance Monitoring System
(HPMS). We also drew from PennDOT’s annual Highway Statistics Report, which provides
county-scale information on vehicle counts and road network classification (PennDOT
2007a). The Centre Area Transportation Authority (CATA) provided transit bus mileage
within each municipality (CATA 2006).
(b) Methods
Specific DVMT data for car and heavy truck travel were not available at the
municipality scale from PennDOT. DVMT data for were available for individual road
segments within the Centre Region. Thus, we used the following method to calculate
municipality DVMT based on PennDOT HPMS data. The 2006 DVMT shapefile (PennDOT
2007b) was imported into ArcGIS 9.2, along with a shapefile of the boundaries of the six
Centre Region municipalities. Road segments were selected if the centroid of the road
segment intersected with one of the municipalities. Tables of DVMT data for the road
segments within each municipality were then exported from ArcGIS. Calculating the sum of
34
road segment DVMT returned the total DVMT for state-monitored road segments within
the Centre Region. To account for travel on non-state-monitored road segments, which
include primarily local roads, the total DVMT for each county was multiplied by 1.26134,
the proportion of traffic on state-monitored roads to estimated traffic on local roads in
Centre County (PennDOT 2007a).
The goal of this analysis was to calculate emissions generated by residents of the
Centre Region. As such, we attempted to exclude daily traffic generated by car and truck
trips neither originating nor terminating within the Centre Region. We assumed that most
of these trips utilized the Interstate 99 corridor (still under construction in 2006) and the
US 322 corridor. For the purposes of this analysis, we excluded segments within these
corridors from our analysis.
To obtain estimates of DVMT within each municipality, total DVMT within the
Centre Region was multiplied by the ratio of workers in each municipality who used a car,
truck, or van to commute to work to the total number of workers in the Centre Region who
used a car, truck, or van to commute to work (U.S. Census Bureau 2001, adjusted to 2006
values). This value was used to account for differences in trip mode choice between
municipalities. Since 93 percent of workers living in the Centre Region are employed in the
Centre Region, this method accounts for the vast majority of local commutes. It does not
account for travel that occurs beyond the boundaries of the Centre Region (see Appendix
for estimates of emissions generated by long-distance travel).
To obtain total annual VMT for each municipality, DVMT was multiplied by 365.
Table 5-1: Annual vehicle miles traveled (VMT) in 2006
Cars and light
trucks
Heavy trucks
Transit vehicles
Source: PennDOT
College
41,875,73
5
1,596,005
141,528
Ferguson
80,383,89
4
3,063,662
165,252
Halfmoon
16,033,50
0
611,083
0
Harris
22,758,22
4
867,382
23,447
Patton
66,228,30
4
2,524,152
129,952
State
College
83,802,544
Centre
Region
311,082,202
3,193,957
316,064
11,856,240
776,242
CATA operates a fleet of natural-gas powered transit buses within and beyond the
Centre Region. Revenue miles within each municipality are recorded in the CATA annual
budget (CATA 2006).
To estimate GHG emissions from transportation, VMT for cars and heavy trucks
within each municipality was multiplied by emissions coefficients representing carbon
dioxide, methane, and nitrous oxide emitted per vehicle-mile (EIIP 2003; CACP 2009). For
the purposes of this analysis, all car emissions were assumed to be caused by gasoline
combustion, and all heavy truck emissions were assumed to be caused by diesel
combustion. Transit bus VMT were multiplied by emissions coefficients for natural gas
buses (Steuer 2004).
Formula
35
MTCO2E = (vehicle-miles * CO2 coefficient) + (vehicle-miles * CH4 coefficient) + (vehicle-miles * N2O
coefficient)
Table 5-2: Emissions coefficients for the local transportation sector
CO2
CH4
N2O
Motor vehicles VMT 0.000393965 1.8125 x 10-6
8.40852 x 10-6
-6
Heavy trucks VMT
0.001438754 1.57357 x 10
7.77665 x 10-6
Transit vehicles VMT 0.004264
0.000286
0.000048
Source: EIIP 2003; CACP 2009
5.03 Electricity
(a) Data sources
This inventory relies on electricity consumption data supplied by Allegheny Power
(Kearney 2006, Morath 2008). Allegheny Power’s subsidiary, West Penn Power Company,
is the sole electricity utility in the Centre Region. At the date of this inventory, Allegheny
Power was unable to provide data for 2006, our baseline year. We thus rely on 18 months
of data from March 2004 to August 2005, annualized over 12 months, as a proxy for 2006
data (see Morath 2008 for a detailed description of this process). We also utilize state- and
county-scale data recorded in Allegheny Power’s annual reports to the Pennsylvania Public
Utility Commission (Wahl 2007). Allegheny Power’s annual reports over the period from
2002 to 2008 show that household electricity consumption in 2004 and 2005 was not
significantly different from the 2002-2008 average.
Data supplied by Allegheny Power are comprised of monthly electricity usage, in
kilowatt-hours (kWh), aggregated by ZIP code and electricity rate code. Rate codes span
five types of end-user: 1) residential, 2) small commercial, 3) large commercial and
industrial, 4) large industrial, and 5) street and area lighting.
Electricity supplied by Allegheny Power to the Centre Region is obtained from PJM
Interconnection, a regional transmission organization that distributes wholesale electricity
across much of the Middle Atlantic U.S. This inventory uses the fuel mix reported by PJM for
the year 2006 as the basis for calculating emissions from electricity (PJM Environmental
Information Services 2007). The 2006 fuel mix was: 57.47% coal, 5.14% natural gas, 31%
oil, 34.98% nuclear, and 2.10 % renewable sources.
(b) Methods
Electricity consumption data were reported by ZIP code, which do not conform to
municipal boundaries. Two types of per-unit scaling were used to estimate electricity usage
within municipal boundaries based on the available ZIP code data, one for residential usage
and another for commercial and small industrial usage.
For residential usage, per-housing-unit electricity consumption was calculated for
each ZIP code in the Centre Region by dividing annual residential consumption within each
ZIP code by the number of housing units in each ZIP code. We multiplied the number of
housing units in each municipality by the per-housing-unit usage amount for that
municipality’s representative ZIP code. Each municipality’s representative ZIP code was
that which covered the largest area within municipal boundaries. For example, ZIP code
36
16801 was the representative ZIP code for College Township and State College Borough,
since it represents the largest total area within each municipality.
For commercial and small industrial electricity usage, the number of customers in
the Centre Region was downscaled from the total number of Allegheny Power commercial
and small industrial customers in Pennsylvania using the following method: the ratio of
commercial and small industrial customers to residential customers in Pennsylvania was
multiplied by the number of residential customers in the Centre Region. The number of
residential customers in the Centre Region was assumed to equal the number of housing
units, adjusted to 2006. The estimated number of commercial and small industrial
customers in the Centre Region was divided among each municipality by multiplying the
ratio of businesses in each municipality to all businesses in the Centre Region by the
average electricity usage of Allegheny Power’s commercial and small industrial customers.
The only ZIP code to record large industrial usage was 16803. ZIP code 16803 spans
Ferguson Township, Halfmoon Township, Patton Township, and State College Borough. In
this case, large industrial usage was assigned to Ferguson Township, which has the largest
area of industrial and light industrial zoning within ZIP code 16803.
Electricity usage from street and area lighting, when not reported directly by the
municipality, was calculated in the same manner as residential usage.
To estimate GHG emissions from electricity usage, a total emissions coefficient for
each GHG was calculated by multiplying the percentage of coal, natural gas, and oil,
respectively, by their percentage of the PJM Interconnection fuel mix and their respective
carbon dioxide, methane, and nitrous oxide emissions. Emissions coefficients were
obtained from Steuer (2004). Total emissions coefficients for each GHG were then
multiplied by the electricity usage (kWh) across each municipality.
Formula
MTCO2E = (% coal * CO2 coefficient) + (% natural gas * CO2 coefficient) + (% oil * CO2 coefficient) + (% coal
* CH4 coefficient) + (% natural gas * CH4 coefficient) + (% oil * CH4 coefficient) + (% coal * N2O coefficient) + (%
natural gas * N2O coefficient) + (% oil * N2O coefficient)
Table 5-3: Emissions coefficients for the electricity sector
CO2
CH4
N2O
Coal (tons)
0.001
0.00000018 0.00000091
Natural gas (MCF) 0.000476 0.0000002
0.0000026
Fuel oil (barrels)
0.000847 0.00000017 0.0000011
Other
0
0
0
Source: Steuer 2004
5.04 On-site fuels
(a) Data sources
The on-site fuels sector comprises fossil fuels burned on-location, primarily for
residential and commercial heating. Fuel categories recorded by the U.S. Census Bureau
include utility gas, bottled, tank and liquefied petroleum gas, fuel oil and kerosene, and coal
37
or coke. For residential emissions, this inventory relies on the number of housing units
listing each primary heating fuel within each municipality, as recorded by the 2000 Census
(U.S. Census Bureau 2001). Counts have been adjusted to estimated 2006 values as detailed
above.
Columbia Gas of Pennsylvania, Inc. is the sole provider of natural gas (utility gas) in
the Centre Region. For natural gas usage, we use state- and county-scale data recorded in
Columbia Gas’ 2006 annual report to the Pennsylvania Public Utility Commission (Kriner
2007). Columbia Gas also provided detailed gas transmission volumes for the State College
market from 2006 to 2009 (Leppo 2009). These data record daily delivery volumes at each
of the three delivery points (TCO, Eastern States and TETCO) that supply the State College
market. Columbia Gas was unable to provide detailed consumption data at the municipality
scale due to technical limitations.
The U.S. Energy Information Administration (EIA) records natural gas usage and
number of customers in the residential, commercial, and industrial sectors at the state
scale (EIA 2009a, 2009b). The EIA also records total consumption of liquefied petroleum
gas, fuel oil, kerosene, and coal at the state scale (EIA 2008).
(b) Methods
On-site fuels usage was calculated for two sectors: 1) residential, and 2) commercial
and industrial. Natural gas usage was determined by first calculating the average usage per
residential, commercial, or industrial customer in Columbia Gas’ Pennsylvania service area.
Second, for residential consumption average usage was multiplied by the number of
housing units listing utility gas as their primary heating fuel in the 2000 Census, adjusted to
2006 values. To determine commercial and industrial consumption, average 2006
Columbia Gas commercial and industrial consumption was multiplied by the number of
businesses in each municipality and the ratio of residential natural gas to other fuels in
each municipality.
For the remaining on-site fuels (fuel oil, kerosene, etc; bottled, tank, or LP gas; and
coal or coke), average 2006 Pennsylvania residential consumption was multiplied by the
number of housing units listing each fuel type as a primary heating fuel in each
municipality. For the commercial and industrial sector, average 2006 Pennsylvania
consumption was multiplied by the number of businesses in each municipality. This
number was then multiplied by the ratio of each primary heating fuel in the residential
sector to all other heating fuels to account for variation in fuel types across municipalities.
The above calculations generated estimates for residential and combined
commercial and industrial consumption of each on-site heating fuel using the following
units: natural gas— thousand cubic feet (MCF); bottled, tank, or LP gas—barrels; fuel oil,
kerosene, etc.—barrels; coal or coke—tons.
To estimate GHG emissions from on-site fuels, usage volumes were multiplied by an
emissions coefficient representing carbon dioxide, methane, and nitrous oxide emissions
per unit of consumption (Steuer 2004).
Formula
38
MTCO2E = (fuel usage * CO2 coefficient) + (fuel usage * CH4 coefficient) + (fuel usage * N2O coefficient)
Table 5-4: Emissions coefficients for the on-site fuels sector
CO2
CH4
N2O
Natural gas (MCF)
0.0545 0.000023 0.000302
Bottled, tank, or LP gas (barrels) 0.2499 0.000095 0.00548
Fuel oil, kerosene, etc. (barrels) 0.4224 0.000089 0.000584
Coal or coke (tons)
2.29
0.0004
0.00201
Source: Steuer 2004
5.05 Waste management
(a) Data sources
Data on solid waste generated in 2006 were obtained for the Centre Region
municipalities, excluding State College Borough and Halfmoon Township, which contract
with Veolia Environmental Services for residential waste pickup (COG 2009). Solid waste
generated in State College, as well as waste from businesses and multi-unit residences, was
obtained separately from the Centre County Solid Waste Authority (CCSWA 2009).
The majority of liquid waste in the Centre Region is treated by the University Area
Joint Authority (UAJA). A smaller amount of waste from the State College Borough is
treated by the Penn State University treatment plant. Data on wastewater flows were
obtained from both UAJA and State College (UAJA 2000, 2007; State College 2009).
Halfmoon Township relies exclusively on local septic systems for wastewater treatment.
Thus, specific data were not available and were estimated as described below. Data on the
number of housing units with septic systems were obtained from the 1990 Census, which
had the most recent data available (U.S. Census Bureau 1991). The 2000 Census did not
include question items on household sewer systems.
(b) Methods
Neither the Centre County Solid Waste Authority nor the Centre Region COG
maintain data on solid waste tonnage at the municipality level. Accordingly, aggregate data
for the Centre Region municipalities (excluding State College) were used. Total solid waste
tonnage for the year 2006 was allocated to each municipality by the number of housing
units in each municipality. Solid waste tonnage for Halfmoon Township was estimated by
multiplying the average annual amount of waste collected per housing unit in the Centre
Region by the number of housing units in Halfmoon Township. State College Borough
operates its own solid waste collection service for which specific tonnage amounts were
available. Waste collected in the Centre Region is sent to the Shade Landfill in Shade
Township, Pennsylvania. The breakdown of solid waste in landfills results in methane
emissions. The Shade Landfill recovers methane, which is blended into the natural gas
system for direct use as an on-site fuel (PA DEP 2009). The total solid waste tonnage for
each municipality was multiplied by a methane emissions coefficient that takes into
account the methane recovery process at the Shade Landfill.
As with solid waste, specific data on liquid waste were not available at the
municipality level for municipalities other than State College Borough. UAJA provided data
39
on total and average wastewater flows for the year 2006, and State College Borough
provided data on wastewater flows to UAJA and the Penn State treatment plant. To
calculate wastewater amounts for the Centre Region municipalities (excluding State College
Borough and Halfmoon Township), we subtracted wastewater from State College Borough
from the UAJA annual total and allocated the remainder of the total annual flow based on
the number of housing units in each municipality. To accurately estimate emissions from
wastewater, it is necessary to calculate the amount of organic material, reported as
biochemical oxygen demand (BOD) in wastewater (EIIP 2003). To calculate the amount of
BOD in total 2006 wastewater flows, the average BOD loading at the UAJA treatment plant
was multiplied by the number of gallons of wastewater flow for each municipality. The
average BOD loading at the Penn State treatment plant was used for the portion of State
College Borough’s wastewater that is diverted to the Penn State plant. The UAJA treatment
plant utilizes an aerobic wastewater treatment system that neutralizes potential methane
emissions from wastewater BOD. Thus, wastewater flows to the UAJA plant did not
generate methane emissions. The Penn State plant, however, uses an anaerobic process
that does generate methane emissions, although this methane is collected and flared. The
amount of BOD (in tons) was multiplied by an emissions coefficient for wastewater flows to
the Penn State plant. Both anaerobic and aerobic systems generate a small percentage of
nitrous oxide emissions. The total amount of wastewater flows (in gallons) for each
municipality were multiplied by an emissions coefficient to estimate nitrous oxide
emissions.
To estimate wastewater and BOD amounts for Halfmoon Township, which relies
exclusively on domestic septic systems, we multiplied the average annual amount of
wastewater and BOD per housing unit in the Centre Region by the number of housing units
in Halfmoon Township. Wastewater and BOD amounts were then multiplied by emissions
coefficients for methane and nitrous oxide emissions from septic systems (CACP 2009). We
also accounted for housing units in the remaining municipalities that were not connected
to the UAJA wastewater systems and instead utilize domestic septic systems. We estimated
the number of housing units with septic systems in the remaining municipalities using
Census data.
Formula
MTCO2E = (waste type * CO2 coefficient) + (waste type * CH4 coefficient) + (waste type * N2O coefficient)
Table 5-5: Emissions coefficients for the waste management sector
CO2 CH4
N2O
Solid waste (tons)
0
0.117
0
Wastewater BOD, aerobic (tons)
0
0
0
Wastewater BOD, anaerobic (tons) 0
0.48
0
Wastewater (gallons)
0
0
5.05 x 10-7
Septic wastewater (gallons)
0
0.00000483 5.05 x 10-7
Source: EIIP 2003, Steuer 2004, CACP 2009
40
5.06 Agriculture and synthetic chemicals
(a) Data sources
The agriculture and synthetic chemicals sector includes emissions from the
application of fertilizer and lime to farm fields and lawns. It also includes emissions from
agricultural animals. Data on the amount of agricultural land within each township were
obtained from the Pennsylvania Department of Agriculture; these data are based on the
acreage of Agricultural Security Areas in each township (PA DA 2009). Total amounts of
fertilizer used in Centre County, and total amounts of lime used in Pennsylvania, were also
obtained from the DA (PA DA 2007b, 2007a, 2008). Data on amounts of fertilizer used on
park lawns were obtained from Centre Region Parks and Recreation (CRPR 2009).
Fertilizer used on golf courses was estimated from previous personal communications with
golf course grounds managers (Morath 2008).
Data on numbers and types of agricultural animals in Centre County were obtained
from the U.S. Department of Agriculture 2007 Census of Agriculture (USDA 2009).
(b) Methods
To estimate amounts of agricultural fertilizer, farmland acreage in each township
was multiplied by the average amount of nitrogen (in tons) applied per acre in Centre
County. To estimate agricultural lime use, farmland acreage in each township was
multiplied by the average amount of lime (in tons) applied to farmland in Pennsylvania.
Precise amounts were available for fertilizer use in the Centre Region park lawns within
each municipality. The average amount of nitrogen fertilizer used per acre on golf courses
was multiplied by the number of golf course acres within each municipality. Nitrogen
fertilizer amounts were multiplied by a nitrous oxide emissions coefficient, and lime
amounts were multiplied by a carbon dioxide emissions coefficient.
To estimate numbers of agricultural animals in each municipality, the ratio of
agricultural land in each municipality to all agricultural land in Centre County was
multiplied by the total number of each type of animal in Centre County. Animals included
were: beef cattle, milk cows, poultry (broilers, layers and pullets, and turkeys), horses,
swine, sheep, and goats. Numbers of each animal type were multiplied by applicable
methane and nitrous oxide emissions coefficients.
Table 5-6: Emissions coefficients for the agriculture and synthetic chemicals sector
CO2
CH4
N2O
Nitrogen fertilizer (lbs)
0
0
0.004198
Agricultural lime (lbs)
0.0002 0
0
Beef cattle (head)
0
1.44
0.617
Milk cows (head)
0
2.91
1.165
Poultry, broilers (head)
0
0.000019 0.0029
Poultry, layers & pullets (head) 0
0.00046
0.005
Poultry, turkeys (head)
0
0.00009
0.0086
Horses (head)
0
0.49
0.741
Swine (head)
0
0.15
0.0367
Sheep (head)
0
0.19
0.138
Goats (head)
0
0.19
0.138
Source: Steuer 2004
41
42
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46
Appendix A: Emissions from Long-Distance Travel
Residents of the Centre Region generate emissions from transportation not only
within the region, but also on their travels beyond the region. Long-distance travel, while
not typically included in local GHG emissions inventories, represents a substantial portion
of emissions generated by the residents of a local area. In accordance with the end-use
approach presented in this inventory, this section presents estimates of emissions
generated by the long-distance travel of Centre Region residents.
Long distance travel is defined by the Bureau of Transportation Statistics (BTS) as
roundtrip travel of distances at least 50 miles away (BTS 2004). The majority of long
distance trip person-miles in the U.S. are made for personal purposes (61 percent).
Business travel makes up 21 percent of long-distance person-miles. Long-distance modes
denominated by the BTS included personal-use vehicle, airplane, bus, train, and ship, boat
or ferry. Personal-use vehicles account for 56 percent of long-distance person-miles in the
U.S., followed by airplanes with 41 percent.
The methodology used to calculate long-distance travel emissions considers the
complete length of all long-distance trips made by Centre Region residents. For example,
the method would include the total trip of a resident who departs on a flight from
University Park Airport, connects in Philadelphia for a flight to Los Angeles, and flies from
Los Angeles to Beijing. Since the trip is made by a Centre Region resident, the portion of
emissions attributed to one passenger on these flights would be assigned to the Centre
Region. The precise methodology and data used to calculate long-distance travel emissions
are detailed below.
Long-distance travel emissions are not included in the main body of this report for
two reasons: 1) specific data on the long-distance travel behavior of Centre Region were
not available at precise spatial scales, and 2) emissions from long-distance travel are not
typically included in local GHG inventories. These emissions nevertheless represent sector
that local decision makers could target for emissions reductions.
Total Emissions Including Long-Distance Travel
Long-distance travel makes up 18 percent of total emissions in the Centre Region
(Figure A-1). When long-distance travel is included, total GHG emissions rise to 856,170
MTCO2e (Table A-1). Long-distance travel accounts for 1.77 MTCO2e per person.
Table A-0-1: Greenhouse gas emissions, including estimated emissions from long-distance travel (MTCO2e)
Colleg Ferguso Halfmoo
State
Centre
e
n
n
Harris Patton
College
Region
19,888 37,686
7,365
10,56 31,021 39,950
146,473
Local transportation
2
45,757 87,887
16,158
35,68 82,183 144,872
412,539
Electricity
2
On-site fuels
15,380 26,670
4,259
8,636 15,440 43,293
113,678
Waste management
1,133
2,192
465
643
1,834
4,110
10,377
Agriculture & synthetic
1,005
11,864
3,989
2,301 2,288
59
21,506
chemicals
Long-distance travel
Total
18,135
83,162
31,263
166,301
6,451
32,236
9,832
57,82
6
23,799
132,76
5
62,116
232,284
151,596
856,170
Figure A-0-1: 2006 Centre Region emissions, including the long-distance travel sector.
Components of the Long-Distance Travel Sector
Emissions from long-distance travel are roughly split between air travel and
passenger vehicle travel (Table A-2; Figure A-2). Air travel accounts for 77,781 MTCO2e (51
percent) of emissions, while passenger vehicle travel contributes 72,220 MTCO2e (48
percent). Bus and rail travel account for a very small portion of all emissions, generating
1,596 MTCO2e of GHG emissions (1 percent).
Air travel is the largest source of GHG emissions even though fewer passenger-miles
take place on airplanes than on passenger vehicles. Only 35 percent of all passenger-miles
traveled by Centre Region residents are on airplanes; 63 percent of passenger-miles take
place in passenger vehicles, but air travel is the largest source of GHG emissions. Air travel
is a major contributor of GHG emissions nationally (EPA 2009). Airplanes use relatively
more fuel than other travel modes to transport people and cargo similar distances. In
addition, most airplane emissions occur at high altitudes and can magnify global warming
more than emissions that are generated at ground level.
Table A-0-2: Emissions within the long-distance travel sector (MTCO2e)
College Ferguson Halfmoon Harris Patton
9,785
16,579
3,586
5,392 12,365
Air travel
201
340
74
111
254
Bus & rail travel
14,344
2,792
4,329 l11,180
Passenger vehicle travel 8,149
18,135 31,263
6,451
9,832 23,799
Total
State College
30,074
617
31,425
62,116
Centre Region
77,781
1,596
72,220
151,596
48
Figure A-0-2: Long distance travel emissions by travel mode and municipality
Table A-3: Long distance travel passenger miles by mode.
Halfmoo
College
Ferguson n
12,601,8
21,351,7
4,618,2
17
25
54
Air passenger-miles
850,365
1,440,80
311,638
Bus & rail passenger4
miles
20,162,6
35,488,3
6,907,5
Passenger vehicle
47
76
67
miles
Harris
6,943,79
1
468,564
10,711,6
37
Patton
15,925,1
18
1,074,62
0
27,660,4
40
State
College
38,732,773
2,613,669
77,749,106
Centre
Region
100,173,47
9
6,759,660
178,679,77
3
49
Methodology for Estimating Long-Distance Travel Emissions
(a) Data sources
Specific data on the long-distance travel behavior of Centre Region residents were
not available. Thus, calculating emissions from long-distance travel required the use of
broad-scale data on average U.S. residents’ travel behavior. The Bureau of Transportation
Statistics (BTS) collects data on U.S. residents’ travel behavior in the National Household
Travel Survey (NHTS). We used NHTS data on long distance travel mode choice and total
passenger-miles, allocated by income category (BTS 2004, 2009), and assigned to
municipalities based on population and income statistics from the U.S. Census Bureau
adjusted to estimated 2006 values (U.S. Census Bureau 2001).
(b) Methods
Long-distance travel is composed of trips that are more than 50 miles from home to
destination (BTS 2006). Estimating emissions from long-distance travel by Centre Region
residents required the calculation of passenger-miles-traveled statistics for each mode of
long-distance travel. Travel modes included in the NHTS and represented in this report are:
air, bus, train, and personal vehicle4.
Estimates of long-distance travel within each municipality were calculated using the
following method: 1) Per-capita U.S. passenger-miles on for long-distance personal vehicle
travel were calculated for four per-capita income categories (less than $25,000, between
$25,000 and $49,000, between $50,000 and $74,000, and $75,000 and above) based on
NHTS statistics (BTS 2004). 2) Per-capita passenger vehicle miles were multiplied by
population falling into each of the four income categories within each township to
determine total long-distance passenger vehicle miles for each township. 3) Per capita mile
traveled, excluding passenger vehicles, were calculated by subtracting passenger vehicle
miles from total passenger miles in each income category. 4) Per capita non-vehicle
passenger miles were multiplied by the population of each township within the four
income categories to determine total non-vehicle passenger miles within each township. 5)
Passenger miles for the air, bus, and rail modes were estimated by multiplying total nonvehicle miles by the proportion of person-miles each mode accounted for out of all personmiles, excluding personal vehicles.
Passenger-miles for each mode of travel were multiplied by emissions coefficients
for carbon dioxide, methane, and nitrous oxide to obtain total emissions (CACP 2009).
Table A-0-4: Emissions coefficients for the long-distance travel sector
CO2
CH4
N2O
Air passenger-miles
0.000773570 1.75199 x 10-7 2.71422 x 10-9
Rail passenger-miles
0.000188657 7.75595 x 10-8 9.60129 x 10-9
Bus passenger miles
0.000251748 3.28732 x 10-7 2.00829 x 10-9
Passenger vehicle passenger-miles 0.000393965 1.18125 x 10-6 8.40852 x 10-6
Source: CACP 2009
“Other” modes sampled by the NHTS, including ships and ferries, represent less than 0.5% of all trips and
were not included in the inventory due to the lack of ship or ferry trips originating in the Centre Region.
4
50
Appendix B: Example Scenario—A Possible Option for Climate Change
Action
This section presents an example scenario for specific climate change mitigation
actions in the Centre Region. This example is not meant to be prescriptive nor
comprehensive. It is presented here in order to illustrate how local actions can effectively
respond to climate change.
Scenario: Wind Energy Credits for Households
As this report found, consumption of electricity was the single largest source of GHG
emissions in the Centre Region. The majority of electricity that is consumed in the Centre
Region is generated through fossil fuel combustion, mostly in coal-fired power plants. This
scenario presents a possible way to eliminate household emissions from fossil-fuel
combustion to generate electricity: wind energy credits.
In this scenario, we envision the purchase of wind energy credits to offset the fossilfuel electricity consumption of all households in the Centre Region by the year 2025.
Allegheny Power currently offers Renewable Energy Certificates supplied by Community
Energy, Inc. (CEI 2009). These certificates, available to residential and commercial
customers, pay for additional electricity from wind power to be transmitted over the
regional electric grid. In 2009, the charge for Renewable Energy Certificates available to
Allegheny Power customers is $2.50 per 100 kilowatt-hour (kWh) block, or 2.5 cents per
kWh.
In 2025, this report estimates that 323,274,518 kWh of electricity will be generated
by fossil fuels and consumed by households in the Centre Region5 (Table B-1). This
electricity demand will create 309,589 MTCO2e of GHG emissions, equaling over 3 MTCO2e
for every resident of the Centre Region. At the 2009 price for Renewable Energy
Certificates, the cost to offset all residential electricity emissions from fossil fuel would be
$8,081,863, or $214.40 per household per year6. On a monthly basis, the average household
would spend $17.87 to offset their electricity emissions from fossil fuel.
The purchase of wind energy credits to offset fossil fuel GHG emissions from
residential electricity consumption would substantially reduce the GHG emissions of the
Centre Region. An offset of all residential fossil fuel electricity would prevent 309,589
MTCO2e from being emitted and contributing to climate change. This number is equivalent
to removing a municipality with the 2006 emissions of State College Borough and College
Township. It is 37 percent lower than projected 2025 emissions, 26 percent below 2006
emissions, and 11 percent below 1990 emissions (Figure B-1).
This scenario assumes the fuel mix for electricity transmitted over the PJM Interconnection remains at 2006
levels. This likely a conservative overestimate: the number also assumes a similar level of residential energy
efficiency to that in 2006, with a slight increase in per-household electricity use.
5
The price for Renewable Energy Certificates would likely drop by 2025 as new wind farms are brought
online.
6
51
Table B-0-1:
Residential electricity generated by fossil fuels, annual
Number of housing units in the Centre Region
Average fossil electricity use per housing unit
2006
2025
2006
2025
2006
2025
Renewable Energy Certificates (100% wind)
Annual cost to offset 2025 total residential fossil electricity
Annual cost per housing unit
Monthly cost per housing unit
GHG emissions reduced
2025
266,869,064 kWh
323,274,518 kWh
31,853
37,695
8,378 kWh
8,576 kWh
$0.025 / kWh
$8,081,863
$214.40
$17.87
309,589 MTCO2e
37.2% below total 2025 emissions
25.9% below total 2006 emissions
11.5% below total 1990 emissions
Figure B-0-1: Potential GHG emissions reduction from the purchase of wind energy credits.
52