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An Examination of Greenhouse Gas Emissions Inventories: Analysis and Recommendations
- 1. + An Examination of State College Borough’s Transportation Greenhouse Gas Emissions Inventories: Analysis and Recommendations KELLI VOLKOMER BACHELOR OF SCIENCE IN ENERGY AND SUSTAINABILITY POLICY EME 466: ENERGY AND SUSTAINABILITY IN SOCIETY BRANDI ROBINSON, FACULTY COACH DR. VERA COLE, COURSE INSTRUCTOR FALL 2017
- 2. + Greenhouse Gases: Carbon Dioxide, CO2 Methane, CH4 Nitrous Oxide, N2O Fluorinated Gases Hydrofluorocarbons, HFCs Perfluorocarbons, PFCs Sulfur hexafluoride, SF6 Nitrogren trifluoride, NF3 Those gases that trap heat in our atmosphere resulting in a net warming of the planet (U.S. Environmental Protection Agency 2017)
- 3. + Emission Coefficients: The U.S. Energy Information Administration (2017), assigns values to activities that produce emissions MTCO2e: Metric Tons of Carbon Dioxide Equivalent VMT: Vehicle Miles Traveled Fuel Type Emission Coefficients CO2 CH4 N2O Gasoline 0.000393965 0.0000018125 0.00000840852 Diesel 0.001438754 0.00000157357 0.00000777665 Natural Gas 0.004264 0.000286 0.000048 (Hillmer-Pegram and Howe 2011, 37; Gallagher 2014, 23) MTCO2e = (VMT * CO2 coefficient) + (VMT * CH4 coefficient) + (VMT * N2O coefficient)
- 4. Have emissions for the transportation sector truly increased by 36.2% from 2006 to 2014?
- 5. + Previous State College Inventories Inventory Results Percentage of the Borough’s Total Emissions Total Transportation Emissions, MTCO2e Per Capita Transportation Emissions, MTCO2e per person 2006, Morath 37% 119,264 4.42 2006, Hillmer- Pegram & Howe 17% 39,950 1.0 2014, Gallagher 24% 54,502 1.29 Morath 2008, 14 & 24; Hillmer-Pegram and Howe 2011, 12, 27 & 32; Gallagher 2014, 2 & 21-22
- 6. 30% 28% 21% 12% 9% Sources of GHG Emissions 2015 Electricity Transportation Industry Commercial & Residential Agriculture (U.S. Environmental Protection Agency 2017) State College Transportation Emissions 2006 – 17% of all emissions 2014 – 24% of all emissions (Gallagher 2014, 21)
- 7. + Global Protocol for Community-Scale Greenhouse Gas Emission Inventories, GPC Produced by: “establishes credible emissions accounting and reporting practices that help cities develop an emissions baseline, set mitigation goals, create more targeted climate action plans and track progress over time, as well as strengthen opportunities for cities to partner with other levels of government and increase access to local and international climate financing (Fong, Doust, and Deng-Beck 2014, 7).”
- 8. Five Principles for a “fair and true” report… 1. Relevance 2. Completeness 3. Consistency 4. Transparency 5. Accuracy (Fong, Doust, and Deng-Beck 2014, 25-26)
- 9. + Relevance Activities producing emissions will be “appropriately reflected” in the inventory. Must be considered “when selecting data sources, and determining and prioritizing data collection improvements.” (Fong, Doust, and Deng-Beck 2014, 25) Completeness Include all emissions for the locale Properly notate when discrepancies exist
- 10. + (Fong, Doust, and Deng-Beck 2014, 25 - 26) Consistency Same methods for calculations between inventories A reporting period of a consecutive 12 months Transparency Allows verification of findings Should be done so that any individual attempting to recreate the process would produce the same results
- 11. + Accuracy Ensures all data correctly reflects actual emissions Provides “assurance of the integrity of the reported information” (Fong, Doust, and Deng-Beck 2014, 26 - 30) Also… Consistent geographic boundary Reporting period of a consecutive 12 months Measure of all seven GHGs included under the Kyoto Protocol Specific sectors, sub-sectors, and sub-categories
- 12. + Scopes & City-Induced Frameworks Direct Emissions: “those that are generated from a source controlled by a person or organization (Hillmer-Pegram and Howe 2011, 9)” Scopes Framework: Scope 1– Consumed on-site Scope 2 – Indirect emissions; Electricity Scope 3 – All other indirect emissions City-Induced Framework: Only Scope 1 Emissions are included Allows aggregation without redundancy (Fong, Doust, and Deng-Beck 2014, 35)
- 13. Transportation Overview (Fong, Doust, and Deng-Beck 2014, 73)
- 14. Methodology recommendation: Use one of the four common methods 1. Fuel Sale Approach 2. Induced Activity 3. Geographic/Territorial 4. Resident Activity (Fong, Doust, and Deng-Beck 2014, 73)
- 15. Boundary types and scopes allocation (Fong, Doust, and Deng-Beck 2014, 78)
- 16. Methodology system boundaries (Fong, Doust, and Deng-Beck 2014, 77)
- 17. + Inconsistent Methodology Prevents Accurate Comparison
- 18. VMT: Vehicle Miles Traveled MTCO2e: Metric Tons of Carbon Dioxide Equivalent Past Inventories & Author’s Analysis MTCO2e = (VMT * CO2 coefficient) + (VMT * CH4 coefficient) + (VMT * N2O coefficient)
- 19. + Transit Analysis 2006 2014 Comparison Total VMT 1,246,439 1,648,803 402,364 ↑ State College VMT 316,064 449,812 133,748 ↑ State College Percentage Allocation 25.36% 27.28% 1.92% ↑ Number of Routes 22 27 5 ↑ Farepaying Passengers 806,500 1,380,823 574,323 (71.2%) ↑ Transit offsets private vehicle trips. Therefore, increased emissions from transit is not a bad thing. Centre Area Transportation Authority 2006, 15-16; Centre Area Transportation Authority 2014, 16-17
- 20. + Author’s Analysis • Geographic / Territorial Approach • GIS analysis performed with ArcGIS 10.5.1 • Pennsylvania Department of Transportation traffic count data from Pennsylvania Spatial Data Access
- 21. + Vehicle Miles Analysis 2006 State College Borough Non- Transit DVMT: 315,341 Multiply by proportion of traffic on state-monitored roads to estimated traffic on local roads in Centre County: 1.26134 Multiply by 365 for annual traffic count: 145,179,480 VMT 2014 State College Borough Non- Transit DVMT: 246,547 Multiply by proportion of traffic on state-monitored roads to estimated traffic on local roads in Centre County: 1.1265 Multiply by 365 for annual traffic count: 101,373,275 VMT
- 22. Transportation Category VMT Emission, MTCO2e Cars & Light Trucks (Gasoline) 139,865,911 56,532 Heavy Trucks (Diesel) 5,313,569 7,695 Transit (CNG) 316,064 1,453 Totals: 145,495,544 65,680
- 23. Transportation Category VMT Emission, MTCO2e Cars & Light Trucks (Gasoline) 98,352,551 39,753 Heavy Trucks (Diesel) 3,020,924 4,375 Transit (CNG) 449,812 2,068 Totals: 101,823,087 46,196
- 24. + Comparison of Inventories Author’s Analysis Non-Transit VM T Transit VM T Total VM T Non-Transit Emissions, M TCO2e Transit Emissions, M TCO2e Total Emissions, M TCO2e 2006 145,179,480 316,064 145,495,544 64,227 1,453 65,680 2014 101,373,275 449,812 101,823,087 44,128 2,068 46,196 Comparison 30.2% ↓ 42.3% ↓ 30.0% ↓ 31.3% ↓ 42.3% ↓ 29.7% ↓ VMT: Vehicle Miles Traveled MTCO2e: Metric Tons of Carbon Dioxide Equivalent
- 25. + Highway Traffic Analysis Heavy truck traffic decreased in the Borough while increasing on Centre Region highways 2006 2014 Total Non- Transit Heavy Truck Percentage of Total Total Non- Transit Heavy Truck Percentage of Total State College Borough DVMT 315,341 11,542 3.66% 246,547 7,358 2.98% (0.68%↓ ) Centre Region Highway DVMT 390,861 44,157 11.30% 558,757 70,702 12.65% ( 1.35% ↑) Centre Region Non-HWY DVMT 962,519 48,517 5.04% 824,967 29,578 3.59% ( 1.45% ↓ ) Centre Region Total DVMT 1,353,380 92,674 6.85% 1,383,724 100,280 7.25% ( 0.4% ↑) 2006 2014 % change Total CR Traffic (mi.) 1,353,380 1,383,724 2.24% ↑ Total CR Hwy Traffic (mi.) 390,861 558,757 42.96% ↑
- 26. + 2006 Commuter Allocation Municipality College Ferguson Halfmoon Harris Patton State College Workers who use car, truck, or van to commute 3516 6211 1145 2014 5262 7169 Ratio of workers in each municipality who use car, truck or van to commute to total workers in the Centre Region who use car, truck, or van to commute 0.14 0.25 0.05 0.08 0.21 0.28 Centre Region Commuter Information. In 2006, total workers in the Centre Region who use car, truck, or van to commute: 25,317 people (United States Census Bureau 2000). Total Centre Region Car & Lt Truck VMT: 311,082,202 miles Multiplied by State College’s Allocation of Commuters (0.28): 87,101,017 miles 2006 VMT Assigned to State College: 86,996,501
- 27. + 2014 Commuter Allocation Municipality College Ferguson Halfmoon Harris Patton State College Workers who use car, truck, or van to commute 4248 ( 732↑) 7030 ( 819↑) 1433 ( 288↑) 2205 ( 191↑) 6893 ( 1631↑) 7223 ( 54↑) Ratio of workers in each municipality who use car, truck or van to commute to total workers in the Centre Region who use car, truck, or van to commute 0.15 ( 1%↑) 0.24 ( 1%↓) 0.05 ( - ) 0.08 ( - ) 0.24 ( 3%↑) 0.25 (3%↓) Centre Region Commuter Information. In 2014, total workers in the Centre Region who use car, truck, or van to commute: 29,032 people (United States Census Bureau, 2010-2014 American Community Survey 5-Year Estimates). Because 93% of workers within the Centre Region also work within the Centre Region, using this information was though to account “for the vast majority of local commutes (Hillmer-Pegram and Howe 2011, 36).”
- 28. Where do we go from here?
- 29. Recommendations: • Employ each of the GPC’s Five Principles in all future inventories • Utilize one of the “four common methods” recommended by the GPC, with preference on an Induced Activity followed by Geographic approach • Become a signatory of the Global Covenant of Mayors for Climate & Energy
- 30. + Compact of Mayors is now… Global Covenant of Mayors for Climate & Energy (C40 Blog June 22, 2016)
- 31. + ICLEI Membership Full software access including… • Forecasting tools • Planning tools • Monitoring • Peer Community • Technical Assistance ~$600 annual membership Become a Signatory of the Global Covenant of Mayors • Free access for ICLEI’s ClearPath Basic, its community-scale inventory tool • Provides consistency & streamlining • Allows comparison of results • Sends message to community and world that State College is serious about minimizing its impact on the climate. https://www.globalcovenantofmayors.org/
- 33. Questions?
Notes de l'éditeur
- Hi. My name is Kelli Volkomer. I will be graduating from Penn State on Saturday! with a degree in Energy and Sustainability Policy. For my senior capstone project I studied the State College Borough’s transportation sector greenhouse gas emissions.
- To ensure we’re all on the same page, greenhouse gases, as defined by the environmental protection agency, are those gases that trap heat in the atmosphere resulting in a net warming of the planet. They include carbon dioxide, methane, nitrous oxide, and the fluorinated gases.
- These gases are produced by many human activities including combustion of fossil fuels in the transportation sector. For the purpose of this analysis, I’ll generalize with the following assumption: car combust gasoline, heavy trucks combust diesel, and the CATA buses combust natural gas. Each of these fuels produces a distinct emissions footprint. We can use emissions coefficients for each gas to aggregate all greenhouse gases into the unit of Metric Tons of Carbon Dioxide Equivalent by multiplying the coefficient by the vehicle miles traveled by fuel type.
- So this brings me to the purpose of my presentation today. First in 2006 and then in 2014, the Borough conducted greenhouse gas emissions inventories across all emitting sectors in order to first understand, and then second to minimize its impact. Comparing the data between the two inventories allowed the Borough to see which emissions were increasing and which were decreasing. While many other sectors experienced declining emissions, the transportation sector appeared to have increased 36.2%. This is a considerable increase. Upon further review of the inventories, they found that the methods used to conduct the two were different, and due to these differences, comparing 2006 with 2014 was more like comparing apples to oranges than apples to apples. And that’s where I come in. The Borough requested a like comparison of the previous inventories, as well as a recommendation for how to perform inventories for the transportation sector moving forward.
- I’ve summarized the findings from each of the previous inventories here. This was my starting place for this project. As you can see the results are a bit of a rollercoaster. I’m not going to talk much about the first inventory you see here. This is the original 2006 inventory, but the 2011 update by Hillmer-Pegram and Howe improved upon methodology used and produces a much more accurate inventory. While I discuss Morath’s inventory in my full report, I’ll skip that discussion here. All discussion of 2006 refers to the 2011 update. So as you can see, emissions jumped from nearly 40 thousand metric tons in 2006 to 54 thousand metric tons in 2014. Although these figures show an increase of 36.2%, they really shouldn’t be compared.
- I performed research to better understand emissions in the transportation sector and best practices of producing an inventory for this sector. Nationally, the transportation sector is the second largest source of emissions. The same is true for the Borough. In 2006, transportation was the third largest emitting sector, while in 2014 it grew to the second largest emitting sector. Accurately modeling transportation sector emissions has an enormous impact on the Borough’s total emissions. So it’s important to get this right.
- No single prescription exists specifying how a city should conduct its GHG emissions inventory. Furthermore, several approaches may accurately capture the necessary information constituting a successful inventory. The World Resources Institute, C40 Cities Climate Leadership Group, and ICLEI – Local Governments for Sustainability together produced the Global Protocol for Community-Scale Greenhouse Gas Emissions Inventories, or the GPC. The GPC “establishes credible emissions accounting and reporting practices that help cities develop an emissions baseline, set mitigation goals, create more targeting climate action plans and track progress over time, as well as strengthen opportunities for cities to partner with other levels of government and increase access to local and international climate financing.” Following the GPC’s recommendation would strengthen the Borough’s inventory processes moving forward.
- The GPC provides Five Principles that, if followed, will lead to what it calls a, quote, fair and true inventory report. These five principles are: Relevance, Completeness, Consistency, Transparency, and Accuracy.
- Relevance means activities producing emissions will be appropriately reflected in the inventory. Relevancy must also be considered when selecting data sources, and determining and prioritizing data collection improvements. Improvements made in the 2011 update illustrate the use of this principle in Borough inventories. Utilizing Borough-specific data provides greater relevance to inventory results than state-level data with per capita scaling used formerly. Completeness requires inclusion of all emissions within a locale as well as notating when discrepancies exist. The GPC includes two separate categories for completeness: first inclusion of all seven GHGs covered under the Kyoto Protocol and second inclusion of all sub-sectors and sub-categories within the transportation sector. The Borough’s inventories include carbon dioxide, methane, and nitrous oxide and provide the reason for exclusion of other GHGs. This would meet the requirement for completeness. While including all sub-sectors is preferred, limited data availability in such sub-sectors as off-road or railways may make completeness difficult. In these cases, similarly explaining the exclusion would be required.
- Perhaps the most important principle, consistency, provides the same methods for calculation between inventories. This allows for accurate comparison of different years’ inventories. Adherence to this principle may be the most applicable moving forward. The inconsistent treatment of pass-through traffic in 2006 and 2014 prevents an accurate comparison of results. It is essential that the Borough adopt one methodology for all future inventories. Transparency allows finding to be verified, and should be done so any individual attempting to recreate the process would produce the same results. One difficulty in completing this project has been the lack of details from prior inventories. When conducting future inventories, each step should be noted, including detailed sources for any information gathered. For example, in the 2006 inventory, allocation of the Centre Region’s total traffic count data to each municipality is based on commuter data from the U.S. Census Bureau. These data and methods for allocation were not included in the inventory report, preventing verification of results. Completed inventories need not only provide the results but also the specific methods and calculations used to achieve those results. Providing interim figures allows consideration of inventory methodology and increases transparency.
- The final principle, accuracy, ensures that all data correctly reflects the actual emissions produced by the city and provide assurance of the integrity of the reported information. Improvements to methodology between inventories improved the accuracy of the results. Using actual Borough data are used in calculating Borough emissions. Steps to continue improving and ensuring accuracy are important to conducting a “fair and true” report of Borough emissions While all five principles are important, consistency and transparency have prevented an accurate comparison of results from previous inventories from occurring. The GPC also requires a city uses a consistent geographic boundary for inventories, a reporting period of 12 consecutive months, and measures all seven of the GHGs included under the Kyoto Protocol. The GPC requires certain sectors, sub-sectors and sub-categories to be included in a complete inventory.
- Emissions from transportation are known as direct emissions. Hillmer-Pegram and Howe described direct emissions as quote “those that are generated from a source controlled by a person or organization.” end quote. This aligns with the GPCs Scopes framework. There are three scopes of emissions. Scope 1 emissions are direct emissions consumed on-site. The fuel in your car is combusting where you are using it. Scope 2 emissions are indirect emissions from electricity. Electricity emissions are produced at the power plant, but when you flip a switch and consume electricity, you are indirectly responsible for producing those emissions. As electric vehicles grow in popularity and pervasiveness, scope 2 will become a necessary consideration for the transportation sector. To this point, not enough data exists to factor it in. And finally Scope 3 includes all other indirect emissions. The GPC also utilizes a City-Induced Framework. In this way it can look at a city’s Scope 1 emissions and combine its emissions with other cities, regions, or states and know that the same emissions are not being double-counted.
- Here’s the breakdown I’ve just described for the transportation sector. You can see the different sub-sectors – on-road, railways, water transport, aviation, and off-road – and the three scopes. Sub categories are based on the fuel type used by each sub sectors.
- Considering methodology for the transportation sector, the GPC recommends one of four common methods: fuel sales approach, induced activity, geographic or territorial, or resident activity. It recommends using the Induced Activity method when possible as it provides results that are more suited to local policy making.
- Fuel Sales approach determines transportation emissions by calculating the total fuel sold within the boundary of the inventory and applies scaling to the data. The Geographic or Territorial method determines all traffic occurring within the boundary regardless of the origin or destination. The Resident Activity method calculates only those miles traveled by city residents. The limitation of this method is its exclusion of impacts made by “commuters, tourists, logistics providers, and other travelers. Again, the recommended approach is the Induced Activity allocation because it attempts to include all traffic induced by the city, including trips that begin, end, or are fully contained within the city. In one option, 50% of transboundary trips are allocated to the city for emissions purposes. For the second option, only departing trips made from the city are used, but the full trip is included. The portion within the boundaries would be scope 1 while the portion outside would be considered scope 3.
- This is a breakdown of the different methods and how the traffic is allocated based on if it falls within or outside the Borough boundaries. Now we are ready to move on to my analysis…
- Both previous inventories used traffic count data provided by the Pennsylvania Department of Transportation. Where the methodologies diverge is related to pass-through traffic. In 2006, pass-through traffic was excluded, because the Borough cannot do much to influence this traffic through policy efforts. In 2014, this pass-through traffic was included in traffic counts for the Borough. Additionally, there was some manipulation of vehicle miles traveled based on U.S. Census commuter data for 2006 that was not performed in 2014, but the details on how this allocation was done was not included in the report. For this reason it is difficult to see what influence this may have had on the inventory’s results. The 2006 inventory would have more closely aligned with the GPC’s Induced Activity method. The use of commuter data is one indication of this method. In 2014, the methodology used best aligns with one of the other common methods known as the Geographic method. Geographic analysis produces the big picture of total miles incurred. Some traffic may be within the Borough’s influence while it has little control over others. Regardless of what methodology a city chooses to use, consecutive inventories must be produced using consistent methods. This is the only way inventories will produce comparable results.
- Considering the information I had at my disposal and the use of this methodology in 2014, I decided to use the geographic method for my comparison. That is why you will see that the traffic counts from my analysis align more closely with the 2014 figures than with the 2006. This does not mean that the 2006 figures are wrong. If I had been able to reproduce the 2006 methodology for both years, my figures would likely align more closely with 2006. I’d like to draw your attention to the three columns stating they are adjustments to 2014. While I was reviewing the past inventories, I discovered a possible error in the 2014 data. So in 2006, I was able to solve the formula for emissions produced by inputting the vehicle miles and the emissions coefficient for that category. For verification, the formula could also be solved using emissions produced and coefficients, solving for vehicle miles. Either method should produce the same output as produced by the given inventory. This is a form of checks and balances for the data. Transit miles were given in 2014 as 449,813 miles. Inputting this variable into the emissions formula results in total emissions of 2,068 MTCO2e. The same method was used in 2006 successfully, so it is not clear why the results for 2014 are different. I believe an error occurred. Therefore rather than a 36.2% increase, if you were to compare these inventories (which you still really should not) the increase drops to 28.9%. As you can see, following consistent geographic methodology to compare traffic counts for the Borough of State College, I found that emissions had actually decreased 29.7%. This is in distinct contrast to the increase in emissions illustrated by the prior results. But let me discuss this a little more so that you can understand how I reached this result.
- I will begin with transit miles as they are the most transparent. Transit miles came directly from CATA and could be verified their budgets for each of these years. Although Gallagher noted a threefold increase in transit emissions between inventories, I want to remind you – an increase in transit emissions is not necessarily a bad thing. Transit offsets private vehicle trips. So if there are more people taking the bus, you can be sure that fewer cars are on the road. Furthermore, the four routes assigned to Penn State have seen an overall decrease in miles traveled. CATA miles, excluding the 4 Penn State routes, have seen an increase of 51% from 2006 to 2014. However, with transit miles accounting for less than half a percentage of the total VMT in either year’s analysis, this increase also has very little impact on the overall transportation sector trend.
- Now moving on to the non-transit analysis. The method I used for this analysis is the same for 2006 and 2014 and specific details are provided in my report. I conducted my analysis using Pennsylvania Department of Transportation traffic count data from Pennsylvania Spatial Data Access and my manipulations were conducted with ArcGIS.
- While complete methods are given in my report, this slide shows a little of what I did. I took the total daily traffic counts for the State College Borough and multiplied them by the factor of state-monitored to local roads in the region. Multiplying this figure by 365 then produced the annual traffic count. In the same way, heavy truck traffic counts are also provided. Using this data you can find the percentage of truck traffic to total traffic and get the totals of passenger cars.
- Here is the map I created with the 2006 data of the Centre Region with the State College Borough in blue. The table shows the breakdown of vehicle miles for the three categories of traffic and resulting emissions for the Borough.
- Here’s the same for 2014.
- So now that we’ve looked at both inventories separately, we’ll look once again at my comparison. Analysis shows that while transit has seen a significant increase, the rest of the Borough’s traffic has decreased from 2006 to 2014. One significant difference in the Region’s transportation landscape between the two inventories was the completion of I-99. Although its location is entirely outside Borough boundaries, this major highway has a definite effect on Borough traffic. Considering heavy truck traffic is one way to analyze its effect.
- Overall heavy truck traffic as a percentage of total non-transit traffic in the Centre Region increased 0.4%, while in the State College Borough the percentage decreased 0.68%. It is possible that heavy trucks are utilizing Centre Region highways rather than alternate routes within Borough boundaries. As mentioned, Centre Region highway traffic counts were in some way allocated to the Centre Region municipalities in the 2014 inventory. Although this process was not discussed, inclusion of highway miles would skew actual trends in Borough traffic. While total Centre Region traffic saw an increase of just 2.24% from 2006 to 2014, Centre Region highway traffic increased by 42.96%. This indicates that traffic formerly using alternate routes through the Region is now utilizing highways within the Centre Region. The last part of this analysis I want to talk about is the commuter allocation from 2006 that I mentioned.
- In this approach, the total traffic for the Centre Region was multiplied by the ratio of workers in each municipality who used a car, truck, or van to commute to work to the total number of workers in the Centre Region who use a car, truck, or van to commute to work. However, neither inputs not outputs were provided in the original report. Hillmer-Pegram and Howe discussed using this allocation because 93% of workers within the Centre Region also work within the Centre Region. So using this information was thought to account “for the vast majority of local commutes. Considering this possibility, if the 2006 total Centre Region car and light truck miles as stated in the 2006 report, this 311 million miles is multiplied by the State College ratio of workers, 0.28, the resulting 87 million miles, supplies a much closer match to the 86 million miles assigned to the Borough in this inventory. Therefore, its possible that the traffic count for the borough in this inventory accounts only for commuter miles, although this is not stated within the report.
- I found the same U.S. Census Bureau data for 2014 as was used in the 2006 analysis. Although the commuters using cars, trucks, or vans increased for every municipality of the Centre Region, the proportions are a bit different. State College Borough experienced the least growth of just 54 more commuters. It dropped from 28% of commuters for the region to 25%. I was not able to recreate the two different inventories utilizing the methodology from 2006. The lack of transparency was extremely preventative. I was able to source the commuter data, but even figures like the total Centre Region traffic as provided in 2006 inventory is difficult to verify. My traffic counts are much different even though I truly feel that I used the same data sources used in these inventories. Perhaps with more time I would have been able to uncover this mystery. But given the actual commuter data trends for the Borough, I still feel this adds confidence to my findings that the emissions have decreased for the Borough.
- So we’ve discussed the previous inventories. We’ve talked about globally accepted methods and considerations for inventories. And we’ve even found that using consistent methodology, State College emissions have decreased. That takes care of the first part of my project, but I was still asked to provide a recommendation for moving forward.
- These are my recommendations. First the Borough should employ each of the GPC’s five principles in all future inventories – remember to focus on consistency and transparency as those have prevented accurate comparisons in the past. Second, utilize on the of the four common methods. If Induced Activity can be achieved, this would be best. Otherwise, the data and resources are available to produce an accurate inventory utilizing the geographic approach as I have done. And last, I believe the Borough would benefit from becoming a signatory of the Global Covenant of Mayors for Climate & Energy. These first two should be fairly clear at this point, so I’d just like to expand on this third bullet point a bit. Let me start by talking about what the Covenant is.
- First, I just want to start by saying if you’ve looked at my poster, I mention this as the Compact of Mayors. The Compact of Mayors and the Covenant of Mayors merged into the Global Covenant of Mayors for Climate & Energy approximately 6 months after the Paris climate change conference in June 2016. Together they produce the largest coalition of cities committed to fight climate change. There are now more partners with greater resources and reach. The requirements remain unchanged. The Global Covenant of Mayors for Climate & Energy, according to their website is quote an international alliance of cities and local governments with a shared long-term vision of promoting and supporting voluntary action to combat climate change and move to a low emission, resilient society. End quote. There are now over 7400 cities and local governments from 6 continents and 121 countries involved with this initiative, and I believe State College should be included.
- The Global Covenant closely aligns with the Borough's commitment to tackle climate issues. As a signatory the Borough would have free access to ICLEI’s ClearPath software, which would help the Borough produce future emissions inventories. This software would provide consistency and ease to the inventory process. Also, using a standard approach allows results to not only be compared to other years’ inventories, but also with other cities. In this way you can find out how your efforts are stacking up against others. Finally, the Covenant differs from other initiatives in that it requires action. The Borough is given three years to navigate through the phases of Commitment, Inventory, Target, and Plan to finally become compliant. These phases align with goals the Borough already plans to achieve. However, by signing the Covenant, you are sending a powerful message to the community and the entire world that State College is serious about minimizing its impact on the climate. Let me go back to the first perk I mentioned – free access to ClearPath. ICLEI has developed this software tool for managing local climate mitigation efforts. ICLEI was one of the organizations responsible for forming the GPC so you can be assured that this tool will help to produce an inventory that adheres to all the recommendations of the GPC. ICLEI provides its community-scale inventory tool for free to any signatory of the Global Covenant of Mayors for Climate & Energy. However, full ICLEI membership does have its advantages. Membership includes full software access including government operations inventory, forecasting, planning, and monitoring tools, as well as access to a peer community and technical assistance. These tools would allow the Borough to see the effects of specific policy efforts. In this way resources can be allocated efficiently. And remember, these tools are for completing the full inventory – so they affect all emitting sectors, not only the transportation sector. I had the opportunity to speak with Eli Yewdall, Senior Program Officer for ICLEI USA. He said that for a city the size of State College annual membership would be approximately $600.
- Over the course of this project, I provided research about techniques of performing an inventory with globally accepted methods. In doing so I learned about ICLEI and the GPC. I discussed the value of incorporating the five principles – relevance, completeness, consistency, transparency, and accuracy – into an inventory to produce a “fair and true” emissions report. These five principles used together with one of the four common methods will produce a quality inventory. ICLEI’s ClearPath software would make the process of inventorying even easier for the Borough. Joining the Global Covenant of Mayors for Climate & Energy provides the software at no cost, while continuing to promote the Borough’s commitment to climate action. I discussed the methodology followed in each of the Borough’s inventories and the difficulty comparing their results due to inconsistencies and a lack of transparency. In an effort to provide the Borough with a true indication of emission from 2006 to 2014 in the transportation sector, I performed my own analysis, using the geographic approach. While prior results showed emissions growing by more than 36% in the transportation sector, my analysis showed emissions decreasing nearly 30%. I believe the GPC’s Induced Activity method should be the first choice of methodology used in future inventories. However, if this approach is either not preferred nor possible, I suggest the Borough follows the same approach used in my analysis – geographic allocation. Annual inventory updates would provide the Borough with timely feedback of emissions trends. By following either method in coordination with the GPC’s five principles, the Borough will produce a quality inventory illustrative of its true emissions.
- Thank you so much for providing me this opportunity to discuss this project with you this morning. If there are any questions, I would be happy to answer them at this time.