Montgomery County Greenhouse Gas Reduction Task Force Cou… · Greenhouse Gas Emissions in...

Reduction Analysis Technical Report 1 December 2007

Montgomery County Greenhouse Gas Reduction Task Force

Appendix B

Measuring Greenhouse Gas Emission Reductions in Montgomery County, Pennsylvania Reduction Analysis Technical Report

Introduction: In July of 2006, Sarah Knuth, then a graduate student at Penn State University, completed a greenhouse gas (GHG) emission inventory and draft action plan for Montgomery County for the period of time between 1990 and 2004.1 This greenhouse gas emission inventory was the first step toward developing a climate change action plan for the county, because it established baseline GHG emission levels and identified emission sources and sinks. The baseline levels not only provide known data through 2004, but can also be used to project what anticipated emissions levels will be in the future. Typically the projected baseline assumes that the county will generally continue to grow at similar rates and that the county will not take any action to reduce its GHG levels, as a result this baseline is often referred to as the “business as usual” trend line. The baseline can then be applied to explore trends, chose and implement reduction strategies, and track progress toward your emission reduction goals. Because the “business as usual” trend shows that the county’s GHG emissions will be increasing in the future, the next step for the county was to identify a set of recommendations to try to reduce future levels of greenhouse gases below predicted baseline levels. Not only did the county need to identify recommendations, but it was critical to quantify the potential GHG reductions that could result from implementing these various recommendations. The Montgomery County Commissioners formed the Greenhouse Gas Reduction Task Force in January 2007 to create a plan for the county. Following months of research, deliberation and public input, a Climate Change Action Plan was prepared by the Task Force, which identifies 105 reduction actions. To understand the potential impact of implementing these reduction actions, analysis was done to estimate the amount of GHG emissions that would result from the 40 actions anticipated not only to have the greatest impact but that also were generally the simplest to quantify. These estimated GHG emission reductions were then applied to the Montgomery County GHG emission baseline to calculate what the projected emission level would be after reduction actions were implemented in future years. Once a reasonable estimate of Montgomery County’s reduced emission levels was known, the Task Force was able to evaluate and choose a likely achievable GHG reduction target. The Task Force embraced the idea of a range of targets and chose reduction targets in 2012, 2017 and 2025 to

1 Knuth, Sarah (2006b). Greenhouse Gas Emissions in Montgomery County, Pennsylvania 1990-2004. Report compiled for the Montgomery County Planning Commission and Knuth, Sarah (2006c). A Global Warming Plan of Action for Montgomery County, Pennsylvania: Greenhouse Gas Emissions Reduction Strategies. Report compiled for the Montgomery County Planning Commission.


address short and long range planning concerns. Additionally, the targets set for each of these three years establish trends that would enable the county to achieve an 80% reduction of 1990 greenhouse gas emission levels by 2050, a reduction target that has been embraced by the scientific community necessary to significantly slow global warming effects.2

Baseline: A necessary first step in any greenhouse gas planning process is to complete a greenhouse gas inventory, so that a baseline (the measurement used as the basis for comparison) can be established. The Montgomery County Greenhouse Gas Inventory established that the county’s GHG emissions in 1990 were 9.5 million metric tons of carbon dioxide equivalents (MMCDE), which increased by 36% to 13.2 MMCDE by 2004.3 When setting targets and projected emissions reductions into the future, any annual GHG emissions rate can be chosen as the baseline year for comparison purposes. The baseline may be the most recent year for which there is data, typical when projecting emissions levels into the future, or may be the first year for which there is data (i.e. the oldest year), which is more typical when setting reduction targets. The inventory also revealed that the county’s GHG emissions rose consistently in every year since 1990 across nearly all identified GHG emissions sources.4 However, of the seven emission sources and sinks included in the county inventory (agriculture, forest, wastewater and sludge, municipal solid waste, on-site fuel, transportation and electricity), three GHG emissions sources were identified as predominant: electricity consumption, on-site fuel use and transportation.5 Following the completion of the county GHG emissions inventory, the Montgomery County Commissioners formed a Task Force in January 2007 to create a plan for reducing greenhouse gas emissions in the county. Following months of research, deliberation and public input, a Climate Change Action Plan was prepared by the Task Force, which identifies 105 reduction actions. To understand the potential impact of implementing these reduction actions, analysis was done to estimate the amount of GHG emissions that would come from the 40 actions anticipated not only to have the greatest impact but that also lent themselves as the simplest to quantify. Projections: From the established baseline, it is necessary to calculate three projected emissions trends. The first is the business as usual trend line, which is meant to project what emissions would be in a given year if no actions were taken to curb greenhouse gas emissions. The second projected emissions trend, referred to throughout this plan as the greenprint trend line, is meant to project what emissions would be in a given year if the greenhouse gas emissions reduction actions laid out in this plan were implemented. The final is the projected GHG emissions reduction trend line, which was calculated by estimating action by action the potential for GHG emissions reductions. Each of these three trends will be explained in detail to follow. Business As Usual Trend In order to project the business as usual GHG emissions trend, the average annual percent change in GHG emissions between 1990 and 2004 of 2.27% was applied as the business as

2 Union of Concerned Scientists, “How to Avoid Dangerous Climate Change: A Target for U.S. Emissions Reductions,” 2007. www.ucsusa.org/emissionstarget.html 3 Knuth, Sarah (2006b). Greenhouse Gas Emissions in Montgomery County, Pennsylvania 1990-2004. Report compiled for the Montgomery County Planning Commission. 4 Knuth, Sarah (2006b). 5 Knuth, Sarah (2006b).


usual annual growth rate between 2004 and 2050. (See Figure 4 for summary of data) In other words, the business as usual trend line is the rate at which emissions would increase or decrease (depending on whether the community is gaining or losing population) in the future if no other actions were taken. It is acknowledged that factors beyond the scope of this analysis may influence changes in green house gas emissions even if the county takes no action on the recommendations made by the Task Force.

Projected Emissions (Business As Usual) = Baseline Year Emissions *((1+ Projected Annual Rate of Change) ^ Number of Years from

Baseline)

Greenprint Trend Projecting the greenprint trend, or the GHG emissions after GHG reduction actions are implemented, is not quite as simple as calculating the business as usual projection, because calculating the greenprint greenhouse gas emissions trend requires that the Task Force know what reduction target Montgomery County should try to achieve and that calculations be completed to determine the reductions possible from implementing each individual GHG reduction action. In setting the GHG emissions reduction targets for Montgomery County, the Task Force wanted to be sure to set an attainable goal, while at the same time achieving enough GHG reduction to meet the minimums established in the scientific community necessary to curb the effects of climate change. At the outset, the Task Force sought to set three short terms targets in 2012, 2017 and 2025 that, if possible, could put the county on track to achieve an eighty percent reduction below 1990 emissions levels by 2050. However, before the Task Force was willing to finalize these short and long term targets, it was necessary to estimate the GHG emissions reduction potential of the actions in the plan to insure that the proposed short and long term targets were attainable. Potential GHG emissions reductions are calculated by taking estimated levels of reductions in GHG emissions producing actions (or increases in GHG reducing actions) and multiplying these actions by known GHG emissions coefficients. Generally activity data is derived from the extent of participation and level of participation in any measure.

GHG Emissions Reductions = Activity Data * GHG Emissions Coefficients The difference between calculating a GHG inventory and calculating GHG emissions reductions lies in the base statistical population used to determine the activity data. When calculating reductions, the base statistical population used to determine the activity data is an estimation of those it would be reasonable to assume could refrain from a GHG emissions producing activity (or engaging in a GHG emissions reducing activity), whereas in an inventory the base statistical population engaging in GHG emissions producing (or reducing) activity is known.

Projected Emissions (Greenprint) = (Baseline Year Emissions* Projected Percent Change * Number of Years From Baseline) –

(Projected GHG Emissions Reduction * Number of Years From Baseline) For comparison purposes, GHG emissions are typically expressed in a common metric. The metric used, throughout this report, will be carbon dioxide equivalent (CDE) expressed in metric tons, or as abbreviated MTCDE. The use of a common metric helps to standardize all of the various greenhouse gases, carbon dioxide, methane, nitrous oxide and fluorocarbons,


since some gases are more potent (i.e. have a higher global warming potential (GWP)) than others.6 Figure 1 lists the anthropogenic, or those resulting from human action, greenhouse gases and their respective global warming potentials. For example one ton of Methane gas has 21 times more effective in trapping heat in the atmosphere than one ton of carbon dioxide. Yet, even after taking the relative strengths of the different gases into account, carbon dioxide is the greenhouse gas emission from human activity that has the greatest impact on global warming. Figure 1: Anthropogenic Greenhouse Gases and their Global Warming Potentials7 Anthropogenic Greenhouse Gases Global Warming

Potentials Carbon dioxide (CO2) 1 Methane (CH4) 21 Nitrous oxide (N20) 410 Perfluorocarbons (CF4, C2F6) 6,500 / 9,200 Hydrofluorocarbons (HFC-24, etc) 11,700, etc. Sulfur Hexfluoride (SF6) 24,900 Emissions of gases other than carbon dioxide are translated into carbon dioxide equivalents, the international standard metric and the one used in this report, by applying their respective global warming potentials.8

MTCDE = Metric Tons of a Gas * Global Warming Potential of the Gas

Only anthropogenic GHGs, as listed in Figure 1, were considered in the county’s inventory and in this reduction analysis.9 Local level data, however, restricted final calculations to the three GHGs with the largest volumes: carbon dioxide (CO2), methane (CH4) and nitrous oxide (N20).10 Due to the diversity and specificity of the recommendations proposed by the GHG Task Force, no one reduction analysis methodology could be applied. However, where possible, the reduction analysis drew on the nationally-derived coefficients and standards of the Environmental Protection Agency (EPA) and the Energy Information Administration (EIA). For all other cases, appropriate coefficients were researched specific to the recommended actions and applied accordingly. Because the GHG reduction methodology is the compilation of many different sources and assumptions, the remainder of this report will serve as a technical guide to the methods used to calculate the reduction potential of each

6 EPA (2005). Emission Facts: Metrics for Expressing Greenhouse Gas Emissions Carbon Equivalents and Carbon Dioxide Equivalents. EPA420-F-05-002. http://www.epa.gov/otaq/climate/420f05002.htm 7 EPA Emissions Inventory Improvement Program (1999). Estimating Greenhouse Gas Emissions. EIIP Documentation Series, Volume VIII. Washington, DC: Greenhouse Gas Committee, Emissions Inventory Improvement Program and US Environmental Protection Agency. 8 Note: The use of the CDE metric is a switch from the Montgomery County GHG Emission Inventory, which used carbon equivalents as a metric. Because the international standard is moving toward carbon dioxide equivalents and because inventories of adjacent cities and counties have used carbon dioxide equivalents, we felt it was important to use a metric that would permit easy comparison. 9 Knuth, Sarah (2006a). Measuring Greenhouse Gas Emissions in Montgomery County 1990-2004: Technical Report. Report compiled for Montgomery County Planning Commission. 10 Knuth, Sarah (2006a).


action. All sources are referenced and details are provided regarding what assumptions were built into the various coefficients applied in the reduction calculations. The seven sectors into which Knuth divided Montgomery County’s GHG sources and sinks in her inventory were further consolidated in this reduction analysis into just three categories: 1) energy, 2) transportation and land use, and 3) agriculture, forestry and waste. Each of the Task Force’s 105 reduction actions fits into one of these three categories. As a result, the reduction analysis was calculated action-by-action in each of the three sectors on a total of 40 actions, identified by the Task Force as quantifiable and most likely to have a significant impact on reducing GHG emissions in Montgomery County. Reduction Analysis by Sector Actions: The Basics The potential GHG emissions reductions for almost all of the 40 actions analyzed have both a County community and a County government component. The distinction between County community is necessary because the baseline emissions are different when considered on a countywide versus county government basis. Additionally, Montgomery County government can directly implement policies relating to its own facilities, fleet and operations whereas the county government can only serve as an educator and advisor to the countywide population. As a result, each of the forty following actions will have both an explanation of the County community and County government GHG emissions reduction calculation. Additionally, because it was not initially known what percent of the base statistical population would need to take each action, calculations were run assuming that ten, five and one percent of the base statistical population would engage in an emissions reduction activity using the follow equation.

Potential GHG Emissions Reduction from an Action = GHG Emissions Reduction per Unit * Percent of Base Statistical Population

Once enough information was uncovered regarding the current population of people taking actions and current trends in technology and regulation, assumptions were made to set reasonable percentage goals for each action. (See Potential GHG Emissions Reduction for more detailed information) For example, once it was determined that 3% of the current employee population in Montgomery County walks or bikes to work, it was assumed that this base population could increase by 3% in each of the three goal periods. This 3% increase in the number of people walking to work would yield a 9% cumulative increase by 2025, the final goal year, and reduce GHG emissions by just under 525 MTCDE during this time. The cumulative reductions for all 40 actions was added together for each goal year, 2012, 2017 and 2025, and compared to the reductions necessary to achieve the Greenprint goals. Furthermore, where it was appropriate, projected numbers from DVRPC’s most recent population and employment forecast were used to change the population baseline in the Montgomery County community calculations accordingly over time to reflect trends. Projected employment numbers for Montgomery County government do not exist and therefore could not be applied.


Energy 1. Purchase renewable energy in place of conventional energy, including

electrical and fossil fuel generated. Electrical Energy:

a.) County community In order to calculate the potential GHG emissions reduction that could result from a percentage of the Montgomery County community electric users switching to renewable energy, whether in the form of wind, hydropower, geothermal, photovoltaic or solar thermal energy, the total annual emissions from all of the residential, commercial and industrial kilowatt hours (kWh) consumed in 2004 in Montgomery County was pulled from the county GHG inventory, which relied on the EPA’s Emissions Inventory Improvement Program emissions coefficient to express CO2 emissions in MTCDE.11 This number was then divided by the projected 2004 population as established by the Delaware Valley Regional Planning Commission (DVRPC) to get MTCDE per capita.12 The MTCDE per capita number was applied to the forecasted populations from DVRPC for each of the target years to reflect the increases in GHG emissions reductions that could result from a larger population base engaging in reduction actions.

Annual CO2 Emissions Reduction = [(Annual Electricity Use * CO2 Emitted)/Unit Electricity Generated] * Percent Reduction

Because PECO provided the information that approximately one half of one percent of electrical energy in the county is already coming from renewable sources, 0.5% of the total kWh was subtracted from the County community usage number to get the base population who could be converted to renewable energy. In this case, a switch from conventional electric energy consumption to renewable energy consumption means a one hundred percent reduction in GHG emissions per converted kilowatt hour. So by simply applying a ten, five and one percent reduction in the emissions resulting from electric energy consumption, the GHG emissions reduction potential for conversion to renewable energy is determined.

b.) County government The Montgomery County government GHG emissions reduction potential from the purchase of renewable over electric energy was calculated in much the same way as the County community number. However, the County government annual kilowatt hour usage statistic was determined by contacting each department head and requesting their most recent annual kWh usage information for their facilities. At the time this calculation was conducted the County government currently was not purchasing any renewable energy.13 The Emissions Inventory Improvement Program methodology was applied to convert the total annual kWh usage number for the County government’s electricity consumption to MTCDE

11 Knuth, Sarah (2006b). 12 Delaware Valley Regional Planning Commission. “most recent Population and Employment Forecasts for Montgomery County.” July 2007. http://www2.montcopa.org/planning/cwp/fileserver,Path,PLANNING/pdf_files/PopulationForecastmost recent.pdf,assetguid,e094d769-cfc1-436f-85b0897b5001e4ec.pdf 13 Although as of September 2007, Montgomery County government facilities were completed powered by wind, a renewable energy source, the county government’s contract to be 100% wind will expire after a two year time period if not renewed. As a result, this calculation was not recalculated to reflect a 100% renewable energy source for electricity, as this may not be sustainable for the long term.


by multiplying the kWh usage number by the carbon content coefficient, converting from tons of carbon to tons of carbon dioxide and finally converting tons to metric tons.14 Fossil Fuel or On-Site Energy:

a.) County community In order to calculate the potential GHG emissions reduction that could result from a percentage of the Montgomery County community fossil fuel users (including natural gas, petroleum fuels and coal) for on-site energy switching to renewable energy, first the total annual emissions from all of the residential, commercial and industrial British Thermal Units (BTUs) consumed in 2004 in Montgomery County was obtained from the county GHG inventory, which relied on the EIIP emissions coefficient to express emissions in MTCDE.15 The emissions resulting from on-site fuel consumption was calculated by multiplying the energy source’s carbon content coefficient and its proportional oxidization to CO2 using the EIIP coefficients.16

Annual CO2 Emissions Reduction = Annual On-Site Fuel Use * C Content * Oxidation Fraction * Percent Reduction

This number then had to be converted from pounds to tons from tons to metric tons and then from metric tons of carbon equivalent (MTCE) to MTCDE to get the total MTCDE emitted from on-site fossil fuel use in Montgomery County. The base population was again adjusted using the Delaware Valley Regional Planning Commission’s most recent population and employment forecast for each of the target years to reflect the increases in GHG emissions reductions that could result from a larger base population engaging in reduction actions.17 Once again, a switch from fossil fuel on-site energy consumption to renewable energy consumption means a one hundred percent reduction in GHG emissions per converted British Thermal Unit. So by simply applying a ten, five and one percent reduction in the emissions resulting from fossil fuel on-site energy consumption, the GHG emissions reduction potential for conversion to renewable energy was determined.

b.) County government The Montgomery County government GHG emissions reduction potential resulting from the purchase of renewable energy in place of on-site fossil fuels was calculated in much the same way as the County community number. However, the County government annual BTU usage statistic was determined by contacting each department head and requesting their most recent annual BTU usage information for their facilities. At the time this calculation was conducted, the County government currently was not purchasing any renewable energy. The Emissions Inventory Improvement Program methodology was applied to convert the total annual BTU usage number for the County government’s on-site fossil fuel consumption to MTCDE by multiplied the energy source’s carbon content coefficient and its proportional oxidization to CO2 using the EIIP coefficients.18 Because a switch from fossil fuel on-site energy consumption to renewable energy consumption means a one hundred percent reduction in GHG emissions per converted British Thermal Unit, applying a ten, five and one percent reduction in the emissions resulting from fossil fuel on-site energy

14 EPA Emissions Inventory Improvement Program (1999). 15 Knuth, Sarah (2006b). 16 EPA Emissions Inventory Improvement Program (1999). 17 Delaware Valley Regional Planning Commission. “most recent Population and Employment Forecasts for Montgomery County.” July 2007. http://www2.montcopa.org/planning/cwp/fileserver,Path,PLANNING/pdf_files/PopulationForecastmost recent.pdf,assetguid,e094d769-cfc1-436f-85b0897b5001e4ec.pdf 18 EPA Emissions Inventory Improvement Program (1999).


consumption determines the GHG emissions reduction potential for conversion from on-site fossil fuel usage to renewable energy. 2. Reduce energy use in both new construction buildings and in existing

buildings through increased energy efficiency and conservation New Construction: Greenprint recommends that new construction buildings reduce energy consumption by roughly 35% when compared to conventionally built new construction. A 35% percent energy reduction is the same energy reduction rate typical in a Leadership in Energy and Environmental Design (LEED) certified new construction building.19 Although LEED certification was not required for new buildings in Greenprint, an average 38% energy reduction appeared achievable through various building measures similar to the energy reductions that comprise LEED standards.

a.) County community In order to calculate the greenhouse gas reductions that would result from a 38% decrease in the energy consumption of new construction buildings, the kWh/year and BTU/year consumed by all existing units in the residential, commercial and industrial sectors was taken from the Montgomery County GHG inventory. The next step was to calculate the number of existing residential, commercial and industrial units in the county through an analysis of the Montgomery County Board of Assessments Data land use code data.20 Once the number of existing units per sector was known, the average kWh/year and BTU/year was calculated per unit by sector, simply by dividing the kWh/year and BTU/year numbers by the number of existing units in each sector. The estimated kWh/year/unit and BTU/year/unit statistics were then multiplied by the average number of new units in each sector, which was calculated by taking the average of the new residential, commercial and industrial units between 2004 and 2006 as reported in the Montgomery County Residential and Nonresidential Construction Reports, determine the GHG emissions produced by all new constructed units in the county in a year. 21 Additionally, to account for the fact that there are new units added in each year during a goal period the emissions from new units in a year was multiplied by the number of years between goal periods (for instance 2008-2012 is 5 years). It was assumed that there was no renewable energy being purchased within the Montgomery County. The amount of greenhouse gas reductions resulting from ten, five and one percent of new construction buildings decreasing their energy consumption by 38% was calculated by multiplying the MTCDE created by all of the BTU/year and kWh/year consumed in new construction units by 38% and then multiplied again by the percentage of the units implementing the action (10%, 5% or 1%), since a reduction in a BTU or kWh is a one hundred percent reduction in GHG emissions per reduced unit.

b.) County government Montgomery County government is not currently planning any major construction projects, but it was assumed that one new building might be built between now and 2025. Because

19 Personal communication with Jason Hartke, United States Green Building Council. 20 Montgomery County Board of Assessments. http://propertyrecords.montcopa.org/Main/home.aspx. Note: The industrial sector data included not only industrial land use codes but also those identified as utility. The commercial sector includes all other nonresidential codes, such as municipal, institution, etc. 21 Montgomery County Planning Commission. “Montgomery County Nonresidential Construction Report” (2004, 2005 and 2006) and “Montgomery County Residential Construction Report.” (2004, 2005 and 2006) http://planning.montcopa.org/planning/cwp/view,a,1462,q,41420,planningNav,%7C.asp


the County government’s buildings are mainly used as office space, it was assumed that this new building would be commercial in its use. The average kWh/year/unit and average BTU/year/unit were applied to one new commercial building to determine how many MTCDE could be saved if the new County government building were built to decrease its energy consumption by roughly 35% over a conventional commercial building. Existing Buildings: Greenprint recommends that existing buildings reduce energy consumption by 30% when compared to the average existing building. A 30% percent energy reduction is the same energy reduction rate typical in a Leadership in Energy and Environmental Design (LEED) certified existing building.22 Although the specific recommendation that existing buildings earn the LEED certification was excluded from Greenprint because of the cost associated with the certification, the Greenprint recommendation of a 30% energy reduction over conventionally operating existing buildings should produce the same results as if the homes were LEED certified.

a.) County community In order to calculate the greenhouse gas reductions that would result from a 30% decrease in the energy consumption of existing buildings, the kWh/year and BTU/year consumed by all existing units in the residential, commercial and industrial sectors was obtained from the Montgomery County GHG inventory. Additionally, to account for the fact that there are units built in the prior year that add to the number of existing units, the emissions from all of the previously new construction units that were not yet converted (90%) were added into the existing building emissions total, once the yearly existing building emissions total was multiplied by the appropriate number of years between goal periods (for instance 2008-2012 is 5 years) to reflect total emissions in a goal period. It was assumed that there was no renewable energy being purchased within the Montgomery County. The amount of greenhouse gas reductions resulting from ten, five and one percent of existing buildings decreasing their energy consumption by 30% was calculated by multiplying the MTCDE created by all of the BTU/year and kWh/year consumed in existing buildings by 30% and then again by the percentage of the units implementing the action (10%, 5% or 1%), since a reduction in a BTU or kWh is a one hundred percent reduction in GHG emissions per reduced unit.

b.) County government The potential greenhouse gas savings that could result from Montgomery County government existing buildings reducing their energy consumption by 30% was calculated by taking the number of existing Montgomery County government buildings (141) and multiplying by the average per unit kWh/year and BTU/year to get total energy consumption per year in County government existing buildings. The amount of greenhouse gas reductions resulting from ten, five and one percent of government existing buildings decreasing their energy consumption by 30% was calculated by multiplying the MTCDE created by all of the BTU/year and kWh/year consumed in government existing buildings by 30% and then again by the percentage of the units implementing the action (10%, 5% or 1%), since a reduction in a BTU or kWh is a one hundred percent reduction in GHG emissions per reduced unit. Transportation and Land Use

22 Personal communication with Jason Hartke, United States Green Building Council.


1. Reduce both the number of vehicles on the road as well as the vehicle miles traveled.

Telecommuting/Flex Time:

a.) County community First it was determined what percent of people travel to work via the various modes of transportation and applied these percentages to the number of employees, as estimated by the Delaware Valley Regional Planning Commission’s most recent population and employment forecast, in Montgomery County in the various goal years. Only those people who drive to work alone, carpool or take mass transit are included in this calculation, as these are the only modes emitting greenhouse gases. Once it was established how many people traveled by these modes to work, a reduction of ten, five and one percent of these commuters was applied, assuming that the ten, five or one percent of the population telecommuting or using flex time to stay home from work would do so one day a week and that they would each reduce greenhouse gases by the amount emitted from an average commute. An average commute was estimated to be 12 miles and 53 minutes in total for travel both to and from work.23 Additionally, because travel to work is done during rush hours, a congestion factor of 1.38 was applied to the distance traveled to account for the greenhouse gas emissions that occur when idling in traffic.24 Using the EPA statistic that a typical passenger car is driven 12,000 miles in a year and emits 1.5 MTCE while doing so, it was determined that typically 0.000125 MTCE are emitted per mile traveled.25 This emission coefficient was then applied to the total miles traveled per commuter and then multiplied by the reduction percentages to calculate the estimated greenhouse reductions that could come from telecommuting or flex time, before finally being converted to MTCDE.

CO2 Emissions Reduction = Forecasted Employment Population * Mode Percentages * Emissions from Average Commute *Days of Week * Congestion Coefficient * Percent Reduction

b.) County government

While the Montgomery County government greenhouse gas reduction potential applied the same formula to determine GHG savings possible from a telecommuting program, the base population used the current employee total and was not forecasted into the future. Mass Transit:

a.) County community In order to calculate the potential GHG reduction that could come from more people traveling to work via mass transit, the DVRPC’s most recent employment forecast estimates were again applied to the 2000 Census Journey to Work mode choice percentages to determine the number of people who drove alone to work and carpooled. Beyond the exclusion of the people already taking mass transit, the remainder of the mass transit calculations were the same as the telecommuting calculations for the Montgomery County community.

23 Clark, William and et al. Commuting Distance Sensitivity by Race and Socio-Economic Status. University of California, Los Angeles and University of New York, Albany. May 2002. and 2000 Census Journey to Work data. www.census.gov. 24 TTI (2007). 2007 Urban Mobility Report. Texas Transportation Institute. Texas A&M University. http://mobility.tamu.edu/ums/report/ 25 EPA (2005). Emission Facts: Greenhouse Gas Emissions from a Typical Passenger Vehicle. U.S. Environmental Protection Agency, Washington, DC. EPA420-F-05-004. http://www.epa.gov/otaq/climate/420f05004.htm


b.) County government

The Montgomery County government reduction was calculated in a slightly different way because of the information collected in a Montgomery County Planning Commission Transit Survey, completed in November 2006. This survey revealed that of the sixty five percent of Montgomery County government employees, whose addresses could be matched to a parcel, 709 employees live within three quarters of a mile of a bus stop or 3 miles from a train station. This means that on average approximately thirty nine percent of Montgomery County government employees could take mass transit to work. In other words, among the 3,100 full time county workers, roughly 1,210 people could take mass transit. Using the EPA statistic that a typical passenger car is driven 12,000 miles in a year and emits 1.5 MTCE while doing so, it was determined that typically 0.000125 MTCE are emitted per mile traveled.26 This emission coefficient was then applied to the total miles traveled per commuter and then multiplied by the reduction percentages to calculate the estimated greenhouse reductions that could come from telecommuting, before finally being converted to MTCDE. Walking:

a.) County community In order to determine the amount of greenhouse gas emissions that could be reduced if Montgomery County community members began to walk to work instead of using a mode of transportation that emits GHGs, the 2000 Census Journey to Work modes of transportation were applied to the DVRPC’s most recent employee forecast for the county to determine the number of people currently walking or biking to work (3%). Because walking and biking is reported in the Census Journey to Work information as one mode, an assumption was made that 75% of people who bike or walk to work are in fact walking. It was assumed that people would not walk a distance greater than a half of a mile for their daily commute, meaning their walk to and from work is no greater than a half of a mile. Additionally, it was assumed that people would only walk to work one day a week. Using the EPA statistic that a typical passenger car is driven 12,000 miles in a year and emits 1.5 MTCE while doing so, it was determined that typically 0.000125 MTCE are emitted per mile traveled.27 This emission coefficient was then applied to the total miles traveled per commuter and then multiplied by the reduction percentages to calculate the estimated greenhouse reductions that could come from increasing the population of people employed in Montgomery County to walk to work one day a week, before finally converting to MTCDE.

b.) County government The Montgomery County government reduction possible from an increase in the population of people living within a quarter of a mile from their office walking to work was calculated in the same way as the County community reductions were calculated. However, the number of people living within a quarter mile of their office was pulled from the Montgomery County Planning Commission 2006 Mass Transit Survey. Biking:

a.) County community

26 EPA (2005). Emission Facts: Greenhouse Gas Emissions from a Typical Passenger Vehicle. U.S. Environmental Protection Agency, Washington, DC. EPA420-F-05-004. http://www.epa.gov/otaq/climate/420f05004.htm 27 EPA (2005). Emission Facts: Greenhouse Gas Emissions from a Typical Passenger Vehicle. U.S. Environmental Protection Agency, Washington, DC. EPA420-F-05-004. http://www.epa.gov/otaq/climate/420f05004.htm


The reductions possible from increasing the number of people who bike to work was calculated in the same way as the reductions from walking were calculated in the community. The only difference is that instead of the base statistical population being 75% of 2000 Census reported 3% who currently bike/walk to work, the base population for biking was the remaining 25% of the base statistical population, calculated by applied 3% to the DVRPC’s most recent employment forecast for that target year. By multiplying by 3.67, the reductions for biking were converted from MTCE to MTCDE.

b.) County government The only difference for the County government biking calculations was the base population, which because we had not surveyed Montgomery County government employees to determine if they lived within 2.5 miles of their office, we had to estimate. It was estimated that double the amount of people who lived with a quarter of mile of their office lived with 2.5 miles. Working with this base population, calculations were the same. Carpooling:

a.) County community Carpooling greenhouse gas emissions reductions for the County community again were calculated with only a few minor differences from the way in which the other transportation calculations have been completed so far. The first difference is that the base population, while again applied 2000 Census Journey to Work mode choice percentages to DVRPC’s most recent employee forecast data, includes only the population of people who drove alone to work, as this is the only population of people that would result in a GHG reduction if they were to carpool. The only other difference in this calculation is that the congestion coefficient was not applied here, because the carpooling cars will still be on the road during rush hour, experiencing heavier volumes of traffic. With significant use of alternative transportation, some reduction in congestion is possible, though it is not assumed in this analysis.

b.) County government The county government reductions from carpooling were calculated by applying the number of Montgomery County government employees and applying the percentage of people driving alone to work (80.5%) from the 2000 census. An average commute was estimated to be 12 miles and 53 minutes in total for travel both to and from work.28 In this calculation the congestion coefficient was not applied, because carpooling vehicles will still be on the road during rush hour experiencing heavier volumes of traffic. Using the EPA statistic that a typical passenger car is driven 12,000 miles in a year and emits 1.5 MTCE while doing so, it was determined that typically 0.000125 MTCE are emitted per mile traveled.29 This emission coefficient was then applied to the total miles traveled per carpooler and then multiplied by the reduction percentages to calculate the estimated greenhouse reductions that could come from carpooling, before finally being converted to MTCDE. Mixed Use and Transit-Oriented Developments:

28 Clark, William and et al. Commuting Distance Sensitivity by Race and Socio-Economic Status. University of California, Los Angeles and University of New York, Albany. May 2002. and 2000 Census Journey to Work data. www.census.gov. 29 EPA (2005). Emission Facts: Greenhouse Gas Emissions from a Typical Passenger Vehicle. U.S. Environmental Protection Agency, Washington, DC. EPA420-F-05-004. http://www.epa.gov/otaq/climate/420f05004.htm


Although the impacts of land use on greenhouse gas emissions are somewhat difficult to quantify, vehicle miles traveled were used as a proxy to gain a sense of how much greenhouse gas emissions could be reduced if mixed use or transit-oriented developments were built instead of conventional auto-oriented developments.

a.) County community To start, the average annual number of approved developments with 10 or more units in Montgomery County between 2000 and 2006 from the Montgomery County Planning Commission’s database was calculated.30 During this time period, 41 developments met the minimum units’ criteria and averaged 63 units per development. The average number of units, 63, was then multiplied by the assumed average number of cars per household of 2 (estimated based on the statistic that the average household size in Montgomery County is 2.54 people). The average number of cars associated with new units in the county on an annual basis was then multiplied by the EPA statistic that the average passenger vehicle travels 12,000 miles in a year to determine how many vehicle miles traveled are related to new development. Transit-oriented and mixed use developments, according to a factsheet from the Surface Transportation Policy Partnership Action Network, typically reduce vehicles miles traveled by twenty to forty percent. For this calculation, a 30% reduction was applied to the vehicle miles traveled related to 10%, 5% and 1% of the new developments during each goal period. The greenhouse gas emissions decreased by the lowered vehicle miles traveled, calculated again using the EPA statistic that 12,000 miles equates to 1.5 MTCE, was then adjusted for the impact of congestion and finally converted to MTCDE.

b.) County government The County government does not build housing developments and thus this calculation does not apply. 2. Improve the efficiency and cleanliness of all vehicle emissions through hybrid

or biofuel technologies. Conversion of Vehicle to Hybrid Car at time of Vehicle Replacement:

a.) County community In order to estimate the greenhouse gas emissions reduction potential from converting a certain percentage of vehicles to hybrids at the time of replacement, the number of gasoline powered vehicles in Montgomery County needed to be established. The number of gasoline and diesel powered vehicles by vehicle type in 2007 was applied as reported in the Energy Information Administration’s (EIA) Annual Energy Outlook.31 The next step was to determine how many vehicle replacement transactions typically occur annually. While the EIA provides forecasts of the number of new vehicle purchases through 2030, which is an average annual increase of about 1%, the information reported by CNW Marketing Research’s Automotive News that the number of used vehicle purchases in a year is 2.6 times the number of new vehicle purchases was necessary to determine the total number of vehicle transactions in a year.

30 Residential developments with less than 10 units were excluded from consideration due to the limitations of small developments supporting mixed or transit-oriented design. 31 EIA (2008). 2008 Annual Energy Outlook Transportation (Early Release). Energy Information Admistration. U.S. Department of Energy, Washington, DC. DOE/EIA-0383(2008). http://www.eia.doe.gov/oiaf/aeo/index.html


Once it had been established how many gasoline powered vehicle transactions occur in a year (which was then multiplied by the appropriate number of years to get a goal period transaction total), it was necessary to calculate and apply the hybrid vehicle greenhouse gas reduction to those vehicles that would be converted. To determine the difference in GHG emissions from a conventional vehicle to a hybrid gasoline powered vehicle the average annual emissions from nine hybrid vehicles available as of 2006 was determined to be 0.81 MTCE, as reported by the U.S. Department of Energy’s Alternative Fuels and Advanced Vehicles Data Center, compared to the emissions from a conventional vehicle of 1.5 MTCE. The GHG emissions reduction that would result from 10%, 5% and 1% of the gasoline powered vehicle transactions that take place in a goal year converting at the time of the transaction to a hybrid was then determined by applying this difference in emissions, before converting MTCE to MTCDE by multiplying by 3.67.

b.) County government The GHG emissions reductions that could come from the County government fleet vehicles being converted at the time of replacement to hybrid vehicles was calculated by taking the number of new vehicles purchased by the County government in a typical year, which is about six vehicles, from a personal communication with Rich Flood, who is in charge of the county motor pool. If six vehicles were purchased each year between 2008 and 2025, the end year of the reduction measurements, a total of 102 new vehicles could be converted to hybrid. As was previously established, a hybrid vehicle emits only 0.81 MTCE per year while a conventional vehicle emits 1.5 MTCE per year. The reductions were calculated from 10%, 5% and 1% of the new vehicles purchases by the County government being converted to hybrid vehicles and the reductions were then converted from MTCE to MTCDE. Biofuels: The Energy Policy Act of 1992 defines the following seven fuel sources as alternative fuels that have or are now commercially available for use in vehicles: biodiesel, electricity, ethanol, hydrogen, methanol, natural gas and propane. Using the Alternative Fuel Station Locator from the Department of Energy’s Alternative Fuels and Advanced Vehicles Data Center, there are currently only biodiesel and ethanol available for public purchase for vehicles within and adjacent to Montgomery County. Therefore, these are the only two alternative fuels for which an estimated GHG reduction potential was calculated. Fuel blends, such as E10 (10% ethanol/90% gasoline), B5 (5% biodiesel/95% diesel), and B2 (2% biodiesel/98% diesel), are another popular alternative fuel option, which consist of two types of fuels most commonly one alternative and one conventional, although some are blends of two alternative fuels. Low-level biodiesel and ethanol fuel blends, like those described above, are the most widely available on the market currently, as they do not typically require any physical upgrades to the vehicle and do not compromise fuel economy.32 Currently, blends of up to 10% ethanol, which is made from renewable agricultural resources like corn, and gasoline (E10), the fuel found at most US pumps today, are approved for use in all gasoline vehicles.33 Ethanol blends over 10% however require vehicles to be flexible fuel capable, or a vehicle that has special controls and materials to accommodate higher levels of ethanol. Flexible fuel, or flex fuel, vehicles are sold as the

32 EPA (2006). E85 and Flex Fuel Vehicles. US Environmental Protection Agency, Washington D.C. EPA 420-F-06-047. http://www.epa.gov/smartway/growandgo/documents/factsheet-e85.htm 33 DOE (2005). Clean Cities Fact Sheet: Low-Level Ethanol Fuel Blends. National Renewable Energy Laboratory. U.S. Department of Energy. DOE/GO-102005-2028. April 2005.


standard model by many automakers today, although station locations offering ethanol blends of over 10% are still limited. Biodiesel, a registered alternative fuel with the U.S. Environmental Protection Agency made from agricultural resources like vegetable oils, is legal for use in both on and off road diesel vehicles at any blend level.34 Additionally, most diesel vehicles can run on biodiesel of any blend level without the need for special equipment. However, the fact that biodiesel and ethanol are the only alternative fuels examined in this reduction analysis in no way implies that they should be pursued exclusively to reduce greenhouse gas emissions from vehicles or that they do not have further improvements that could enhance their overall performance. To the contrary, it is the hope that advances continue in fuel efficiency and GHG emissions reductions in all of the above identified alternative fuels, and any others identified in the future.

Biodiesel (B20): According to the Alternative Fuel Station Locator provided by the Department of Energy, there are currently two biodiesel, including B20, B2-B5, and B99-B100, stations within 25 miles of the Norristown zip code that are open to the public. Although it is common for many stations to have only one diesel storage tank and therefore not to have yet converted to offering a biodiesel blended fuel, PA DEP notes that most station tanks in PA were last replaced in the late 1980’s and will need replacement in the next five years. It is likely that at this time gas stations will convert their diesel storage tank(s) to offer a biodiesel, particularly in light of the recently passed Energy Independence and Security Act of 2007’s mandatory Renewable Fuel Standard.35 However, to be sure that our reduction estimates tended toward the conservative side, the reduction analysis for biodiesel was done assuming a conversion to a blend of 20% biodiesel and 80% gasoline, B20 as opposed to a higher blend level.36

a.) County community To calculate the potential GHG emissions reduction from the County community switching a portion of the diesel vehicles to use B20 fuel began with calculating the number of diesel vehicles in the county (which includes light duty vehicles, buses and freight trucks) by applying the national percentages from the Energy Information Administration to the county’s vehicle total to get diesel vehicles by vehicle type.37 The EIA also provided the typical annual mileage by vehicle type (light duty vehicle- 12,000 miles, buses- 40,000 and freight trucks- 82,000 miles). A standard mile per gallon of 25 was then applied to 0.011 MTCDE emitted per gallon of distillate fuel. This conversion factor of 0.011 MTCDE per gallon of distillate fuel was calculated by converting 22.384 lbs of CO2 per gallon (the amount of GHG emissions resulting from distillate fuel as reported by the Energy Information Administration to MTCE by multiplying lbs by .00045 to convert it to metric tons of carbon dioxide emitted, 0.011 MTCDE per gallon. According to the 1998 study by the

34 EPA (2006). Biodiesel. US Environmental Protection Agency, Washington D.C. EPA 420-F-06-044. http://www.epa.gov/smartway/growandgo/documents/factsheet-biodiesel.htm 35 The White House (2007). Fact Sheet: Energy Independence and Security Act of 2007. Office of the Press Secretary. December 19, 2007 Press Release. http://www.whitehouse.gov/news/releases/2007/12/print/2007/1219-1.html 36 According to the EPA’s SmartWay Grow & Go program, B20 will reduce GHG emissions by at least 10% where B100 reduces GHG emissions by more than 50%. 37 EIA (2008). 2008 Annual Energy Outlook Transportation (Early Release). Energy Information Admistration. U.S. Department of Energy, Washington, DC. DOE/EIA-0383(2008). http://www.eia.doe.gov/oiaf/aeo/index.html


Department of Agriculture and the Department of Energy, biodiesel fuels typically reduce GHG emissions by roughly 15%.38 This reduction coefficient was then applied to 10%, 5% and 1% of the diesel vehicle population in the county, assuming they would consume biodiesel, to estimate the GHG emissions reduction.

b.) County government The reduction calculation for the County government switching to biodiesel fuel assumed that as in the US 2% of light duty and commercial vehicles are diesel.39 As reported by the county’s vehicle fleet manager, the county fleet of over 300 vehicles consumes about 100,000 gallons of fuel per. The total number of gallons of fuel consumed by diesel vehicles in the county fleet was estimated. The conversion factor, 0.011 MTCDE per gallon of distillate fuel, was then multiplied by the number of gallons. This conversion factor was calculated in the same way as it was for the County community vehicles. Again relying on the statistic from the 1998 study by the Department of Agriculture and the Department of Energy that biodiesel fuels typically reduce GHG emissions by roughly 15%, this reduction coefficient was then applied to 10%, 5% and 1% of the diesel vehicle population in the County government fleet, assuming they would consume biodiesel, to estimate the GHG emissions reduction.40

Ethanol (E85): According to the Alternative Fuel Station Locator provided by the Department of Energy, there is currently only station that has E85 ethanol within 25 miles of the Norristown zip code that is open to the public. Currently, E85 can only be used in flex vehicles. Additionally it is not currently sold at all gas stations. Again, according to PA DEP, most gas station tanks were last replaced in the late 80's and will need replacement again in the next 5 years, at which time it is likely for gas stations to begin storing at least one tank of E85. Currently, there is only one station planned for E85 in the county in Jeffersonville, although the Energy Independence and Security Act of 2007’s mandatory Renewable Fuel Standard will likely result in a growing number of stations.41 There may be some additional cost for older cars (particularly those over 20 years old) to convert to be ethanol capable. Fuel for county vehicles is currently dispensed at county fueling sites located in Norristown, Eagleville, and other county facilities. The number of tanks at these locations is limited and would need to be expanded to accommodate additional fuel types. This reduction analysis was calculated assuming that the ethanol would be produced using starch (or corn), which EPA’s SmartWay Grow & Go program states can reduce emissions up to 70% .42 (NOTE: If cellulosic ethanol, which is ethanol produced from the cellulose in agricultural wastes like wood wastes and corn stalks, becomes more available because of developing research, the GHG reduction potential of ethanol as a biofuel becomes much

38 DOA and DOE (1998). An Overview of Biodiesel and Petroleum Diesel Life Cycles. US Department of Agriculture and US Department of Energy. May 1998. http://www.biodiesel.com/PDF/Biodiesel%20Life%20Cycle.pdf 39 This assumption implies that the county fleet does not include any freight trucks or buses, vehicle types have much higher percentages of diesel vehicles. 40 DOA and DOE (1998). An Overview of Biodiesel and Petroleum Diesel Life Cycles. US Department of Agriculture and US Department of Energy. May 1998. http://www.biodiesel.com/PDF/Biodiesel%20Life%20Cycle.pdf 41 The White House (2007). Fact Sheet: Energy Independence and Security Act of 2007. Office of the Press Secretary. December 19, 2007 Press Release. http://www.whitehouse.gov/news/releases/2007/12/print/2007/1219-1.html 42 EPA (2006). E85 and Flex Fuel Vehicles. US Environmental Protection Agency, Washington D.C. EPA 420-F-06-047. http://www.epa.gov/smartway/growandgo/documents/factsheet-e85.htm


greater.) However, in trying to produce a cautious estimate of the reduction potential of E85, the reduction coefficient applied in this calculation was 55%, the lower end of the range of GHG emissions reductions presented in the 1998 study by the Department of Agriculture and the Department of Energy.

a.) County community The potential GHG emissions reduction from the County community switching a portion of the gasoline vehicles to use E85 fuel began with a calculation of the number of gasoline vehicles in the county (which includes light duty vehicles, commercial light duty vehicles, buses and freight trucks) by applying the national percentages from the Energy Information Administration to the county’s vehicle total to get diesel vehicles by vehicle type.43 The EIA also provided the typical annual mileage by vehicle type (light duty and commercial vehicles- 12,000 miles, buses- 40,000 miles and freight trucks- 82,000 miles). A standard mile per gallon of 25 was then applied to 0.011 MTCDE emitted per gallon of distillate fuel. This conversion factor of 0.011 MTCDE per gallon of distillate fuel was calculated by converting 22.384 lbs of CO2 per gallon (the amount of GHG emissions resulting from distillate fuel as reported by the Energy Information Administration to MTCE by multiplying lbs by .00045 to convert it to metric tons of carbon dioxide emitted, 0.011 MTCDE per gallon. According to the 1998 study by the Department of Agriculture and the Department of Energy, E85 fuels typically reduce GHG emissions by roughly 55%.44 This reduction coefficient was then applied to 10%, 5% and 1% of the gasoline vehicle population in the county, assuming they would consume E85 fuel over gasoline, to estimate the GHG emissions reduction.

b.) County government The reduction calculation for the County government switching to E85 fuel assumed that as in the US 98% of light duty and commercial vehicles run on gasoline.45 As reported by the county’s vehicle fleet manager, , county fleet consumes about 100,000 gallons of fuel per year. The total number of gallons of fuel consumed by diesel vehicles in the county fleet was then estimated to which the conversion factor that there is 0.011 MTCDE per gallon of distillate fuel was applied. This conversion factor was calculated in the same way as it was for the County community vehicles. Again relying on the statistic from the 1998 study by the Department of Agriculture and the Department of Energy that E85 fuel typically reduces GHG emissions by roughly 55%, this reduction coefficient was then applied to 10%, 5% and 1% of the gasoline vehicle population in the County government fleet, assuming they would consume E85, to estimate the GHG emissions reduction.46

Agriculture, Forestry and Waste Management

1. Promote sustainable agriculture.

43 EIA (2008). 2008 Annual Energy Outlook Transportation (Early Release). Energy Information Admistration. U.S. Department of Energy, Washington, DC. DOE/EIA-0383(2008). http://www.eia.doe.gov/oiaf/aeo/index.html 44 DOA and DOE (1998). An Overview of Biodiesel and Petroleum Diesel Life Cycles. US Department of Agriculture and US Department of Energy. May 1998. http://www.biodiesel.com/PDF/Biodiesel%20Life%20Cycle.pdf 45 This assumption implies that the county fleet does not include any freight trucks or buses, vehicle types have much higher percentages of diesel vehicles. 46 DOA and DOE (1998). An Overview of Biodiesel and Petroleum Diesel Life Cycles. US Department of Agriculture and US Department of Energy. May 1998. http://www.biodiesel.com/PDF/Biodiesel%20Life%20Cycle.pdf


Local Food: County community To determine the greenhouse gas savings that could result from using locally grown food supplies (within 100 miles), it was necessary to first calculate the pounds of food consumed per person in Montgomery County. The 2004 food consumption data, reported by the U.S. Department of Agriculture’s National Agricultural Statistics Service (NASS), was used to determine that the average American consumes 1,982 pounds of food per year.47 The national pounds per capita statistic was then applied to the population of Montgomery County, as projected by the DVRPC population and employment forecast, resulting in the total pounds of food consumed in the county per year. According to the U.S. Department of Transportation, the cargo weight limit for freight trucks is 50,000 pounds, although the gross vehicle weight maximum is 80,000 pounds.48 Using the typical pounds of food consumed and the maximum cargo weight limit for a freight truck to calculate the number of truck loads needed to supply Montgomery County with food for a year, the number of truck loads was then multiplied by the average miles traveled, 1,300 miles, for food in the US.49 A mile traveled by an item of food is now frequently referred to as a food mile. A food mile is “the distance food travels from where it is grown or raised to where it is ultimately purchased by the consumer.”50 The Energy Information Administration rated a freight truck with a fuel efficiency of roughly 5.5 mpg, which was used to determine the total gallons of fuel consumed per year to provide Montgomery County’s residents with food. The Energy Information Administration also provides that a gallon of distillate fuel emits 0.011 MTCDE per gallon. This multiplier was applied to the number of gallons consumed annually to provide Montgomery County with food to determine the total greenhouse gas emissions relating to food transport. From this, the greenhouse gas emissions that would be reduced if 10%, 5% and 1% of the pounds of food consumed in Montgomery County were obtained from local sources (for purposes of this report local was defined as food traveling no more than 100 miles) was determined.

a.) County government When calculating the potential GHG reductions that could come from purchasing local food at the Montgomery County government level, much of the steps were the same. The same pounds consumed per capita food statistic was applied to the number of Montgomery County government full time employees (3,100) to determine the pounds per year consumed by employees. It was then assumed that Montgomery County government employees ate one third of their food at work, meaning that most people eat only one of their three main meals a day while at the office. The pounds of food consumed by employees was then divided by 50,000 pounds to determine the number of truck loads needed to deliver this food. The number of trucks was then multiplied by 1,300 miles, the

47 Donahoe, Julie. Food Consumption and Population. U.S. Department of Agriculture. National Agricultural Statistics Service- PA Office. Pennsylvania Agricultural Statistics 2005-2006. http://www.nass.usda.gov/Statistics_by_State/Pennsylvania/Publications/Annual_Statistical_Bulletin/2005_2006/foodcons.pdf 48 DOT. Commercial Vehicle Size and Weight Program. Freight Management and Operations. Federal Highway Administration. U.S. Department of Transportation. FHWA-OP-03-099. May 2003. http://www.ops.fhwa.dot.gov/freight/sw/overview/index.htm. 49 Priog, Richard and Andrew Benjamin. “Checking the food odometer: Comparing food miles for local versus conventional produce sales to Iowa Institutions.” Leopold Center for Sustainable Agriculture. July 2003. http://www.leopold.iastate.edu/pubs/staff/files/food_travel072103.pdf 50 Priog, Richard. “Food Miles: A Simple Metaphor to Contrast Local and Global Food Systems.” Hunger and Environmental Nutrition Summer 2004 Newsletter. Dietetic Practice Group of the American Dietetic Association. http://www.leopold.iastate.edu/pubs/staff/files/local_foods_HEN0604.pdf


average miles traveled for food in the U.S. The mileage was then divided by a fuel efficiency of 5.5 miles per gallon to determine the number of gallons of fuel consumed in food transport annually. Finally, the number of gallons was multiplied by 0.011 MTCDE to determine the total greenhouse gas emissions relating to food transport. From this, the greenhouse gas emissions that would be reduced if 10%, 5% and 1% of the pounds of food consumed by Montgomery County government employees were obtained from local sources (for purposes of this report local was defined as food traveling no more than 100 miles) was determined. No Till Farmland:

a.) County community After communicating with the Montgomery County Cooperative Extension office to determine the number of total farmed acres in the county as well as the number of these acres currently using no till practices, where the soil is left undisturbed from harvest to planting to save not only time, money and greenhouse gas emissions but also to prevent soil erosion. The acreage of farmland in the county not already implementing no till practices was first multiplied by the conversion factor that 1.58 MTCE is sequestered per acre of land under no till practices to determine the greenhouse gas reductions that could come from converting 10%, 5% and 1% of this cultivated farmland to no till farmland. Because no till practices reduce greenhouse gas emissions not only through the ability of the untilled land to sequester carbon but also because of the reduction in fuel needed when the standard cultivating machinery is not operated, there was a need to also calculate fuel savings. The Montgomery County Cooperative Extension estimates that tilled farmland requires about 5.3 gallons of fuel per acre, while no till farmland only consumes 1.4 gallons of fuel per acre (a savings of 3.9 gallons per acre on converted land). Taking the gallons saved by converting an acre of tilled farmland to no till and multiplying it by the MTCE in a gallon of fuel, it is possible to determine the MTCE reduced per acre of converted land. This number is then multiplied by the converted acres of land to calculate the greenhouse gas savings that would result of decreases in fuel consumption as related to no till practices, before this fuel savings is added to the sequestration savings already determined. Finally, both the fuel and sequestration GHG emissions reductions are converted to MTCDE.

b.) County government Montgomery County government owned farmland was included in the overall County community calculation above. Farmland Preservation: As with no till practices, there are multiple ways in which preserving farmland helps to reduce greenhouse gas emissions. First, the crops on the farmland sequester carbon dioxide as they grow. The clearing of these crops for development also causes a concentrated one time release of this previously stored carbon dioxide into the atmosphere. As a result, in order to fully estimate the greenhouse gas emissions reductions that result from farmland preservation, both sequestration and prevention of the release of stored GHG emissions needed to be calculated and added together. Additionally, it is felt that with permanently preserved farmland, a farmer is more likely to manage the property more carefully as a long term investment and install various conservation measures.

a.) County community To start, the total acres of farmland, as reported in the Montgomery County Comprehensive Land Use Plan, was pulled. As was reported in the NY Times, there is approximately a quarter of a ton of carbon sequestered on a piece of agricultural land (including the average


of the sequestered amounts from farmland and rangelands).51 Applying this GHG conversion factor, calculated the greenhouse gas reductions that would be associated with preserving an additional 10%, 5% and 1% of the existing preserved agricultural acreage were then calculated. The associated GHG reductions that would come from preserving the same additional 10%, 5% and 1% of farmland as it relates to the prevention of the release of stored carbon was calculated by applying the difference, 2 MTCE, between the 35 MTCE emitted into the atmosphere when forestland is converted for development and the 33 MTCE emitted to the atmosphere when forestland is converted to pasture or farmland.52 Then, the GHG reductions possible through fuel reductions and carbon storage were added together to determine the total GHG potential reductions resulting from farmland preservation, before both are converted to MTCDE.

b.) County government The County government farmland is included in the County community calculation, and thus is not recalculated here.

2. Increase vegetation, especially trees.

Tree Canopy: a.) County community

The calculation of the greenhouse gas emissions that would be reduced through an increased tree canopy began by determining the percent of wooded or forested land in the county from the Montgomery County Comprehensive Plan. An additional 10%, 5% and 1% in acreage was applied to calculate potential GHG savings, using the conversion factor that 1.2 metric tons of carbon per acre per year is stored by a growing forest and multiplying it by 18 years to calculate reductions through 2025.

b.) County government The Montgomery County government calculation was completed the same way as the County community, although there was an assumption that the County government, based on current tree planting program rates, could plant just under 1,000 acres by 2025. No Mow Practices:

a.) County community Beyond planting trees, another way to increase the vegetative cover in the county is to reduce or eliminate the need to mow certain lands, thereby allowing them to naturalize either as meadows or growing forests. Because it was too difficult to determine how much of the lawn acreage in privately owned hands (i.e. the Montgomery County community) could functionally be taken out of mowed space or would be, due to the varying aesthetic preferences of land owners, this calculation was not completed.

b.) County government However, having a much better sense of the Montgomery County government owned parks and heritage land that was currently being mowed, an estimate was completed for greenhouse reductions as a result of naturalizing some of these areas. Parks and Heritage

51 Robbins, Jim. “Sale of Carbon Credits Helping Land-Rich, But Cash Poor Tribes.” The New York Times Online. May 8, 2007. http://www.nytimes.com/2007/05/08/science/earth/08carb.html?ex=1336276800&en=c7f2935cfb4bfd76&ei=5124&partner=digg&exprod=digg 52 Chaisson, Joe. “Biofuels and Climate.” Clean Air Task force. September 25, 2007. http://www.ccap.org/domestic/documents/CATF%20Biofuels.pdf


Services estimated that roughly 300 of the nearly 6,000 acres of County owned parkland is regularly mowed. As the result of internal study, fifty percent, or 150 acres, of this land could be naturalized. Richard Birdsey of the USDA Forest Service anticipated a 4.5 MTCDE per naturalized acre per year in GHG emissions reductions.53 Open Space Preservation: As with farmland preservation, there are multiple ways in which preserving open space helps to reduce greenhouse gas emissions. First, the vegetation and forest on the open space sequesters carbon dioxide as it grows. Additionally, the clearing of this vegetation for development causes a concentrated one time release of this previously stored carbon dioxide into the atmosphere. Because open space is usually largely forested, the resulting release of clearing these parcels is dramatically higher than the 2 MTCE per acre for farmland clearings at 35 MTCE per acre.54 As a result, in order to fully estimate the greenhouse gas emissions reductions from open space preservation, both sequestration and prevention of the release of stored GHG emissions needed to be calculated and added together.

a.) County community To start, the total acres of open space, as reported in the Montgomery County Comprehensive Land Use Plan, was pulled. Using the EPA statistic that 1.2 MTCE per acre of growing forest is sequestered, the greenhouse gas reductions that would be associated with preserving an additional 10%, 5% and 1% of the existing preserved open space acreage were then calculated.55 The associated GHG reductions that would come from preserving the same additional 10%, 5% and 1% of open space as it relates to the prevention of the release of stored carbon was calculated by applying the 35 MTCE emitted into the atmosphere when forestland is converted for development.56 Then, the GHG reductions possible through fuel reductions and carbon storage were added together to determine the total GHG potential reductions resulting from open space preservation, before both are converted to MTCDE.

b.) County government The open space that is preserved through the Montgomery County government’s Green Fields/Green Towns program is the open space being referenced in the County community calculation and thus is not recalculated here.

3. Decrease the emissions resulting from the waste sector by advocating waste reduction and recycling.

Recycling: Trash:

a.) County community

53 Smith, James E.; Heath, Linda S.; Skog, Kenneth E.; Birdsey, Richard A. 2006. Methods for calculating forest ecosystem and harvested carbon with standard estimates for forest types of the United States Gen. Tech. Rep. NE-343. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. http://www.fs.fed.us/ne/newtown_square/publications/technical_reports/pdfs/2006/ne_gtr343.pdf 54 Chaisson, Joe. “Biofuels and Climate.” Clean Air Task force. September 25, 2007. http://www.ccap.org/domestic/documents/CATF%20Biofuels.pdf 55 EPA. “Calculations and References for Equivalency Calculator.” Clean Air. U.S. Department of Environmental Protection. http://www.epa.gov/cleanenergy/energy-resources/refs.html. 56 Chaisson, Joe. “Biofuels and Climate.” Clean Air Task force. September 25, 2007. http://www.ccap.org/domestic/documents/CATF%20Biofuels.pdf


In order to assess the potential GHG reductions that could result from increasing the amount of trash that is recycled instead of sent to a landfill, it was necessary to first determine the amount of trash that the Montgomery County community disposes of in a year. A conversation with Art Feltes, Montgomery County’s Recycling Coordinator, revealed that Montgomery County currently produces about 875,000 tons of trash in a year of which roughly 30% is recycled. This means that approximately 620,000 tons of trash are managed at the Montgomery County waste to energy incinerator or at several landfills each year. The current population of the county was divided by the tons produced by the county to determine the tons per person. The tons of trash per person statistic was then applied to the population of Montgomery County, as projected by the DVRPC’s most recent population and employment forecast, resulting in tons of trash projections for 2012, 2017 and 2025. The EPA conversion factor that one ton of waste, which is recycled instead of sent to a landfill, creates a 0.81 MTCE reduction was applied to the tons of trash in the county discarded which could instead be recycled to determine the GHG reductions possible from 10%, 5% and 1% of the landfilled waste being recycled.57 MTCE were then converted to MTCDE by multiplying by 3.67.

b.) County government The Montgomery County government trash statistics were provided by the Public Property department and Santangelo Brothers in yards per week. Next, yards were converted to pounds by applying the estimate that a yard of paper and cardboard, likely the largest components of County government trash, weighs seventy pounds. Pounds per week were then converted to tons per year to establish that Montgomery County government produces approximately 720 tons of trash of which about 145 tons are currently diverted to recycling. This leaves 577 tons of trash that could still be diverted from the landfill. Again, the EPA conversion factor that one ton of waste which is recycled instead of landfilled creates a 0.81 MTCE reduction was applied to determine the GHG reductions possible from 10%, 5% and 1% of the government landfilled waste being recycled.58 MTCE were then converted to MTCDE by multiplying by 3.67. Construction and Demolition Waste: But municipal waste is not the only type of discarded material that needs to be considered when trying to reduce GHG emissions. Construction and demolition (C&D) activities, that are happening frequently throughout the growing county, produce large amounts of waste, which is often bulky, heavy material collected and managed by specialty waste companies. C&D waste can include concrete, wood, asphalt, gypsum, metals, bricks, glass, plastics, salvaged building components (like plumbing fixtures, doors, windows) as well as trees, dirt and rocks from site clearing.59 Recycling C&D materials can not only reduce GHG emissions, but save landfill space, prevent the need for the production of new materials, create jobs and reduce overall project expenses.

a.) County community In order to assess the potential GHG reductions that could result from increasing the amount of C&D waste that is recycled instead of landfilled, it was necessary to first determine the amount of C&D waste that the Montgomery County community disposes of in

57 EPA. “Calculations and References for Equivalency Calculator.” Clean Air. U.S. Department of Environmental Protection. http://www.epa.gov/cleanenergy/energy-resources/refs.html. 58 EPA. “Calculations and References for Equivalency Calculator.” Clean Air. U.S. Department of Environmental Protection. http://www.epa.gov/cleanenergy/energy-resources/refs.html. 59 EPA. “Construction and Demolition Materials.” U.S. Department of Environmental Protection. http://www.epa.gov/epaoswer/non-hw/debris-new/index.htm


a year. A conversation with Art Feltes, Montgomery County’s Recycling Coordinator, revealed that Montgomery County currently produces about 250,000 tons of C&D waste in a year of which little is recycled. The current population of the county was divided by the tons of C&D waste produced by the county to determine the tons per person. The tons of C&D trash per person statistic was then applied to the population of Montgomery County, as projected by the most recent DVRPC Population and Employment Forecast, resulting in tons of C&D trash projections for 2012, 2017 and 2025. Again, the EPA conversion factor that one ton of waste which is recycled instead of landfilled creates a 0.81 MTCE reduction was applied to determine the GHG reductions possible from 10%, 5% and 1% of the landfilled C&D waste being recycled.60 MTCE were then converted to MTCDE by multiplying by 3.67.

b.) County government Although the Montgomery County government has participated in some smaller construction or demolition projects in more recent years and may do so again before 2025, there was a lack of quantifiable information on how much C&D trash may have resulted from these projects. As a result, no calculation was done to estimate the GHG emissions reductions that might come from the County government recycling C&D waste. However, the Montgomery County government is aware that a savings is possible and will consider this on all of its future projects. Biosolids: Biosolids, or the nutrient-rich organic material that results from the treatment of sewage, can be safely recycled as fertilizers when federal regulations are met.61 When land applied as a fertilizer, biosolids act to sequester greenhouse gases by making the carbon available for plant uptake. However, most biosolids in the county are instead disposed of by burning them in an incinerator or landfilling them, both of which result in added GHG emissions.

a.) County community In order to assess the potential GHG reductions that could result from land application of biosolids, it was necessary to first determine the amount of biosolids that are produced by the Montgomery County community in a year. A conversation with Diane Garvey, Garvey Resources Inc., revealed that Montgomery County currently produces about 2,600 dry tons in a year. The current population of the county was divided by the tons of biosolids produced by the county to determine the tons per person. The tons of biosolids per person statistic was then applied to the population of Montgomery County, as projected by the DVRPC’s most recent population and employment forecast, resulting in tons of biosolids projections for 2012, 2017 and 2025. Garvey ran two biosolids land application scenarios in which net GHG emissions were calculated after biosolids were transported by truck and applied using machinery (both emissions producing activities were accounted for in the balance) on 100 acres of land, which in one case was vegetated by hybrid poplars and in the other was grasses and legumes. The results in both cases was a net sequestration of greenhouse gases, where the hybrid poplars saw 1.02 tons of CO2 sequestered per ton of biosolid applied and the grasses and legumes saw 1.70 tons of CO2 sequestered per ton of biosolid. The average of these two results, 1.36 tons of CO2 per ton of biosolid land applied, was then used to calculate the amount of greenhouse gases that could be sequestered if 10%, 5% and 1% of

60 EPA. “Calculations and References for Equivalency Calculator.” Clean Air. U.S. Department of Environmental Protection. http://www.epa.gov/cleanenergy/energy-resources/refs.html. 61 EPA. “A Plain English Guide to EPA Part 503 Biosolids Rule.” Biosolids. U.S. Department of Environmental Protection. http://www.epa.gov/owm/mtb/biosolids/503pe/index.htm


the biosolids produced in Montgomery County were land applied as fertilizer instead of incinerated or landfilled.62 In addition to the GHG reductions from the sequestration that occurs when biosolids are land applied, there is an additional GHG reduction that comes from the prevention of the additional GHG emitted in the disposal process when done through incineration and landfilling. If chosen as the disposal method, incineration and landfilling of biosolids would emit additional greenhouse gases, making it necessary to also estimate the amount of emissions that come from each of these disposal methods to adequately capture the true savings of land applying biosolids. Incineration- ??? Landfill- ???

b.) County government The County government does not operate any wastewater treatment plants or process or dispose of sewage sludge or biosolids. As a result, no calculation was completed. Source Reduction: Another way to reduce waste is to reduce the amount of it that is created in the first place by cutting down on packaging, producing more reusable items and less disposable ones, as well as using materials that are biodegradable or can be one hundred percent recycled and reused.

a.) County community In order to assess the potential GHG reductions that could result from reduction of waste at the source, the calculation began with the tons of trash currently produced in Montgomery County, 875,000 tons. However, because there are quite significant differences in the amount of greenhouse gases that results from various materials, as listed in the EPA Source Reduction chart, it was necessary to break down the annual tons of trash in Montgomery County by material.63 The MTCE reduced per ton of each material reduced was then applied to the tons of that material in the Montgomery County waste stream. Additionally, the current population of the county was divided by the tons of waste produced by the county to determine the tons per person. The tons of waste per person statistic was then applied to the population of Montgomery County, as projected by the DVRPC’s most recent population and employment forecast, resulting in tons of waste projections for 2012, 2017 and 2025. 10%, 5% and 1% of the total MTCE that could be saved in the county was then taken to get an estimate of the GHG emissions reduction possible through source reduction of waste. MTCE were then converted to MTCDE by multiplying by 3.67.

b.) County government In order to assess the potential GHG reductions that could result from reduction of waste at the source for Montgomery County government, it was again necessary to break down the

62 EPA. “Calculations and References for Equivalency Calculator.” Clean Air. U.S. Department of Environmental Protection. http://www.epa.gov/cleanenergy/energy-resources/refs.html. 63 EPA (2006). Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions and Sinks. 3rd Edition. U. S. Environmental Protection Agency, Washington DC. http://epa.gov/climatechange/wycd/waste/downloads/fullreport.pdf


annual tons of trash produced by Montgomery County government by material.64 The MTCE reduced per ton of each material reduced was then applied to the tons of that material in the Montgomery County government waste stream. 10%, 5% and 1% of the total MTCE that could be saved by the Montgomery County government was then taken to get an estimate of the GHG emissions reduction possible through source reduction of waste. MTCE were then converted to MTCDE by multiplying by 3.67. Potential GHG Emissions Reduction Once the initial calculations of GHG emissions reductions (using 10%, 5% and 1% of the base statistical population) were complete, the technical subcommittee of the greenhouse gas reduction Task Force met to review the various GHG emissions reduction levels by action. The technical subcommittee reviewed each action individually to make a determination as to what percentages of the base statistical population could reasonably be expected to take a particular action in the given time periods between the target years. The Task Force considered a broad spectrum of factors beyond the GHG emissions reduction potential in determining what percent of the base statistical population they thought could take a particular action, including but not limited to cost of action, availability of necessary infrastructure, existing trends as well as the impact of existing and proposed local, state or federal regulation. Once the percent of the base statistical population was determined, it was then applied, in lieu of the 10%, 5% and 1% that were initially used, in the below formula to calculate the final estimated potential GHG emissions reduction for each action.

Potential GHG Emissions Reduction from an Action = GHG Emissions Reduction per Unit * Percent of Base Statistical Population (or Other

Appropriate Number of Units) Participating

The various percentages, and the corresponding number of units and MTCDE reductions, are summarized for each of the target years in Figure 2 for the County community and in Figure 3 for the County government. The sum of the final estimated potential GHG emissions reductions from each action was then compared against the greenprint trend to determine the likelihood of Montgomery County achieving its GHG reduction targets, which will be discussed next in more detail.

64 EPA (2006). Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions and Sinks. 3rd Edition. U. S. Environmental Protection Agency, Washington DC. http://epa.gov/climatechange/wycd/waste/downloads/fullreport.pdf


Figure 2: Montgomery County community GHG Emissions Reduction Targets


Figure 3: Montgomery County government GHG Emissions Reduction Targets

Comparing Trends and Reductions to Set Goals As was mentioned earlier, the Task Force embraced the idea of a range of targets. They chose reduction targets in 2012, 2017 and 2025 to address both short and long term planning concerns. The targets set for each of the three target years were chosen in such a way that would put the county on track to achieve an eighty percent reduction from its 1990 greenhouse gas emission level by 2050, as shown in the Greenprint trend line in Figure 4. The eighty percent below 1990 levels reduction target is one that has been embraced by the scientific community as the target necessary to significantly slow the effects of global warming.65

Because the Task Force wanted to set short term goals that put the county on target to reach the eighty percent below 1990 target by 2050, 1.9 MMTCDE was set as the Montgomery County target for 2050 and used to calculate the amount of reductions needed between the end of 2007 and 2012, 2017 and 2025. This target is expressed in Figures 4

65 Union of Concerned Scientists, “How to Avoid Dangerous Climate Change: A Target for U.S. Emissions Reductions,” 2007. www.ucsusa.org/emissionstarget.html


and 5 below as the Greenprint trend. Recall that an average growth rate of 2.27% in GHG emissions was applied to our baseline emissions number from 2004 to determine the anticipated emissions level in 2007 of 13.9 MMTCDE, as displayed in Figures 3 and 4 by the business as usual trend. 13.9 MMTCDE minus 1.9 MMTCDE determines that Montgomery County needs to reduce its emissions in the 43 year time period between the start of 2008 and 2050 by 12 MMTCDE, if it is to achieve emissions that are 80% below 1990 levels.

Baseline Year GHG Emissions – Final Year GHG Emissions Target = Total Emissions Reduction Needed

12 MMTCDE of reductions, when divided evenly, amounts to an annual reduction of approximately 280,000 MTCDE. Once the reduction per year number is known, calculating the emissions reduction goals for each target year is simply a matter of multiplying the per year reductions by the number of years within a target period.

Emissions Reductions Needed Per Year * Number of Years in Target Period = Emissions Reductions Needed by Target Year

For example, because there are five years to implement GHG emissions reducing actions from 2008 to 2012, the 280,000 MTCDE per year reductions would be multiplied by five to determine the emissions reductions target for 2012, assuming the actions were implemented immediately at the start of the target period in 2008. However, in this analysis, the assumption was built into the calculations that the recommended base statistical population for any target period would not be participating until after two years had pasted, i.e. at the start of the third year (2010) of a five year target period (2008-2012), so as not to inflate the projected GHG emissions reductions. Because it was assumed that the base statistical populations converting to a GHG reducing action would not be converted right away but rather take time to be implemented, the GHG emissions reductions possible during each target period were applied two years after the start of that target period rather than for the full duration of the target period. For example, the five percent of employees in Montgomery County that were recommended to telecommute one day a week by 2012 would not start to do so on the first day of 2008, but instead it would take time to establish a telecommuting program and to build enough momentum behind the program to achieve participation at the five percent rate. It was assumed that after two years the telecommuting program would be established enough to have reached its full participation rate. Thus, the reductions from this action were applied in 2010 (and again accordingly in 2015 and 2020) as seen below in Figure 3 in the column listing projected GHG emissions reductions. Figure 4: Montgomery County GHG Emissions Trends Comparison (MTCDE)

Year Business As

Usual Greenprint Projected Reduced GHG

Emissions 1990 9,601,488 9,601,488 9,601,488 1991 9,216,940 9,216,940 9,216,940 1992 9,784,515 9,784,515 9,784,515 1993 10,218,657 10,218,657 10,218,657 1994 10,409,667 10,409,667 10,409,667 1995 10,850,701 10,850,701 10,850,701 1996 10,949,572 10,949,572 10,949,572 1997 10,844,713 10,844,713 10,844,713 1998 10,652,227 10,652,227 10,652,227 1999 10,815,279 10,815,279 10,815,279


2000 10,981,777 10,981,777 10,981,777 2001 11,530,332 11,530,332 11,530,332 2002 12,147,453 12,147,453 12,147,453 2003 13,003,813 13,003,813 13,003,813 2004 13,064,070 13,064,070 13,064,070 2005 13,360,624 13,360,624 13,360,624 2006 13,663,910 13,663,910 13,663,910 2007 13,974,081 13,974,081 13,974,081 2008 14,291,293 13,693,761 14,291,293 2009 14,615,705 13,413,440 14,615,705 2010 14,947,482 13,133,120 12,817,282* 2011 15,286,790 12,852,799 13,108,234 2012 15,633,800 12,572,478 13,405,7912013 15,988,687 12,292,158 13,710,102 2014 16,351,630 12,011,837 14,021,322 2015 16,722,812 11,731,517 11,630,606* 2016 17,102,420 11,451,196 11,894,620 2017 17,490,645 11,170,876 12,164,6282018 17,887,683 10,890,555 12,440,765 2019 18,293,733 10,610,234 12,723,171 2020 18,709,001 10,329,914 9,292,987* 2021 19,133,695 10,049,593 9,503,938 2022 19,568,030 9,769,273 9,719,677 2023 20,012,224 9,488,952 9,940,314 2024 20,466,502 9,208,632 10,165,959 2025 20,931,091 8,928,311 10,396,7262026 21,406,227 8,647,991 2027 21,892,148 8,367,670 2028 22,389,100 8,087,349 2029 22,897,333 7,807,029 2030 23,417,102 7,526,708 2031 23,948,670 7,246,388 2032 24,492,305 6,966,067 2033 25,048,281 6,685,747 2034 25,616,877 6,405,426 2035 26,198,380 6,125,105 2036 26,793,083 5,844,785 2037 27,401,286 5,564,464 2038 28,023,295 5,284,144 2039 28,659,424 5,003,823 2040 29,309,993 4,723,503 2041 29,975,330 4,443,182 2042 30,655,770 4,162,862 2043 31,351,655 3,882,541 2044 32,063,338 3,602,220 2045 32,791,176 3,321,900 2046 33,535,536 3,041,579 2047 34,296,792 2,761,259 2048 35,075,329 2,480,938 2049 35,871,539 2,200,618 2050 36,685,823 1,920,297 *The GHG emissions reductions possible during each target period were applied two years from the start of that period, because it was assumed that the base statistical populations converting to a GHG reducing action would not be converted right away but rather take time to become established. For example, the five percent of people that were assumed to be capable of telecommuting one day a week by 2012 would not start to do so on the first day of 2008, but instead it would take time to establish a telecommuting program and to build enough momentum behind the program to achieve participation at the five percent rate. So as not to inflate the projected GHG emissions reductions, the assumption was built in to the calculations that the recommended base statistical population for any target period would not be participating until at two years had pasted, i.e. at the start of the third year (2010) of a five year target period (2008-2012)

Once the projected emissions reductions were calculated, a comparison of the business as usual trend, the Greenprint (or target) trend and the projected emissions levels after reductions was possible. Figure 4 depicts the relationship of the three trend lines to one another. . True GHG emissions levels will vary annually, increasing in some years and


Greenhouse Gas Emissions Trends Comparison

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

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2016

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2022

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Year

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of C

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Business As Usual Greenprint Projected Reduced GHG Emissions

decreasing in others due to a variety of factors. However, despite potential shifts in the actual emissions levels in the years between the target years, the trends are reflective of the overall emissions trends needed to reach the final target set by the Task Force of 80% below the1990 emissions level. Figure 5 shows three scenarios, compared from the present on. The two trends or scenarios depicted in solid blue and red lines illustrate county emissions levels assuming business as usual (red) and the county’s greenprint emissions goal for 2025 (blue). The yellow dashed line attempts to illustrate how close the 40 actions quantified in the reduction analysis, if successfully implemented, can bring the county to achieving its greenprint goal. Figure 5: Montgomery County GHG Emissions Trends Comparison (MTCDE) As Figure 6 summarizes, after quantifying the impact of implementing the top 40 GHG reducing actions of the 105 recommended in the plan, the county is ultimately able to come within about 1.3 MMTCDE of its ambitious 2025 GHG emissions reduction goal. Figure 6: Projected GHG Emissions Levels compared to Greenprint Target

Although this greenhouse gas

reduction analysis does not demonstrate that the county will be able to offset all of the emissions it would need to reach the 2025 goal of emissions at no more than 8.9 MMTCDE, there are several reasons why the 2025 goal should still be viewed as attainable. First, the greenhouse gas emissions reductions that will come from the implementation of the remaining 60+ actions that were not quantified still need to be considered. Although the remaining 60+ actions are not likely to have reductions as high as those that were quantified and are more abstract and difficult to quantify, there will still be additional emissions reductions that come from implementing these actions to offset some of the

Target Years Greenprint

Projected GHG Reduced

Emissions Difference2012 12,572,478 13,449,929 -877,450

2017 11,170,876 12,299,773-

1,128,898

2025 8,928,311 10,254,149-

1,325,837


county’s GHG reduction deficit. Another difficult impact to quantify is the reductions that will come as secondary impacts of implementing the reductions in this plan. Take for example, the fact that as the county increases its tree canopy, many buildings will have the added energy efficiencies that result from shade in terms of heating and cooling costs. Secondary impacts such as these were not quantified or included in the reduction analysis conducted and thus offer the county yet another way to earn additional reductions. Likewise, there are advances, whether in technology or regulation that might raise the amount of reductions possible above what was estimated in this analysis, as a result of improved efficiencies and/or increasing the base statistical population of people, cars, buildings involved in a greenhouse gas reducing action. Also, the invisible hand of the market place may influence greater greenhouse gas emissions reductions. It is likely that new economic opportunities may arise from interest in green lifestyles which may spur quicker changes than are projected in this analysis. Finally, because there will need for monitoring and evaluation done throughout the implementation of these actions, the county has room to adjust (both up and down) the percentages of the population that need to engage in the various actions to keep them on track to meet their 2025 ambitious yet achievable target. The county’s work, as mentioned, will need to extend beyond merely creating the greenhouse gas reductions outlined in this plan to quantify additional baselines and validate reductions, as detailed in a recently published manual from the Nicholas Institute for Environmental Policy Solutions.66 Effective measurement of GHG reductions resulting from an action requires monitoring and quantification of baseline emissions before a project begins. Once an action is implemented, it is just as critical to assess the actual realized reductions and to evaluate the realized reductions against the reductions needed to meet set targets. Reduction verifications should serve as audits of the reduction strategy and determine the extent of its success. If reductions are not sufficient, modifications and adjustments need to be made in order to ensure that targets are met. It should also be noted that because this analysis looked only at GHG emissions reductions, or mitigation, it did not estimate the extent to which Montgomery County will need to adapt to the climate changes that will result from greenhouse gases already emitted. However, climate mitigation strategies cannot be considered independently of the need for climate adaptations. Anticipating the need for adaptations to climate change depends on the ability to anticipate how quickly and to what extent the climate will change in the county. As a result, any plans regarding adaptation depend directly on how successfully the county is able to implement the greenhouse gas mitigation/reduction strategies outlined in this plan.

Montgomery County stands at a turning point. Failure to implement appropriate greenhouse gas reduction strategies could endanger the health, safety and welfare of future generations and could result in the need for expensive reactive measures to adapt to changes in the climate. Alternatively, the mitigation strategy laid out in Greenprint: A Climate Change Action Plan for Montgomery County provides the county with a unique opportunity to carve out its place in the emerging low-carbon economy, by pioneering greenhouse gas emissions reducing policies that ensure the future continues the Montgomery County’s tradition of providing a high quality of life to its employees and residents.

66 Willey, Zach and Bill Chameides, Eds. (2007). Harnessing Farms and Forests in the Low-Carbon Economy: How to Create, Measure, and Verify Greenhouse Gas Offsets. The Nicholas Institute for Environmental Policy Solutions. Duke University Press. Durham & London. 2007. http://www.nicholas.duke.edu/institute/ghgoffsetsguide/ghgexerpts.pdf

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