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Economics of a Hydrogen Bus Transportation System: Case Study using an

After Tax Analysis (ATA) Model

Oscar Bonilla*, Donald N. Merino

School of Systems and Enterprises (SSE), Stevens Institute of Technology, Castle Point on Hudson, Hoboken NJ

07030-5991 USA. [email protected] of Systems and Enterprises (SSE), Stevens Institute of Technology, Castle Point on Hudson, Hoboken NJ

07030-5991 USA. [email protected].* Corresponding author. Tel.: 201-826-3703; Castle Point on Hudson, Hoboken - NJ 07030-5991 USA. Stevens

Institute of Technology. School of Systems and Enterprises (SSE). Babbio Building, 5th floor. E-mail address:[email protected]

Abstract

Because of global warming governments world-wide are taking actions to reduce Green HouseGases (GHGs) in transportation systems such as bus fleets. All involved aspire to make thesechanges in an economically efficient manner. This paper provides an after tax economic model

to help determine pricing (fares), the level of subsidies, the impact of carbon credits and financialleverage options.Most approaches to compare new technologies use before tax analyses like Societal Life CycleCosts (SLCC). Most industry analyses use an After Tax Analysis (ATA) approach. This paperdescribes and compares both techniques. To illustrate the proposed ATA transportation model acarbon free bus system fueled by Hydrogen is used with data extracted from published sources.Major conclusions are that a carbon credit (from Cap & Trade or carbon tax) provides someeconomic gain, but did not meet the economic criteria established. Borrowing funds (e.g. usingfinancial leverage) for the capital costs significantly increases the rate of return and could attractinvestors. However, increased borrowing increases the financial risk and this risk needs to bemoderated via risk mitigation strategies (default insurance, etc.). Other financing options need to

be explored.

Keywords: Societal Lifecycle Costs (SLCC), After Tax Analysis (ATA), Hydrogen BusEconomics.

1. Introduction

The transportation sector was chosen for this paper because it accounts for approximately14% of GHG emissions (Bernstein et al., 2007). Nearly 70% of the 21 million barrels of oil theUnited States consumes every day goes for transportation, with the bulk of that burned byindividual drivers, according to the National Commission on Energy Policy, a bipartisan research

group that advises Congress (Schwartz, 2008).Another reason to focus on the transportation sector is that there are large numbers of

existing and emerging technologies to choose from.The automotive industry is one of the largestin the world and includes major companies who have large financial resources. These resourcesallow automotive companies to conduct very large research and development efforts devoted tonew technologies. In addition, there is a large government sector providing bus and othertransportation needs for their citizens. Thus, there are many technologies to choose from andcapable industry and government organizations to implement these changes.

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2. Review of global warming Reduction of gas emissions

Global warming has been discussed for almost a decade with scientific and political opinionsvarying widely, particularly in the US. However, with the publications of the IntergovernmentalPanel on Climate Change (IPCC) Climate Change 2007: Synthesis Report (Bernstein et al.,

2007), a consensus has emerged in the United States that global warming is indeed a seriousproblem and that government and industry must find solutions.

Governments worldwide are developing legislation to combat global warming. Legislationproposed includes limiting Green House Gas (GHG) emissions and/or assessing some form ofcarbon tax. Governments have sponsored studies and demonstration projects to help decide themost economically attractive alternatives.

3. Review Societal Lifecycle Cost (SLCC) and After Tax Analysis (ATA) approaches

3.1. Choosing among alternatives using Societal Life Cycle Costs (SLCC)

An extensive literature search of transportation studies that reported on new technologieswhich reduced carbon emissions indicates that Societal Life Cycle Costs (SLCC) was used toevaluate and choose among competing alternatives. For example, Ogden and Williams usedSLCC to evaluate alternative fuels/engines (Ogden et al., 2004); Cockroft and Owen used SLCCto examine the economics of hydrogen fuel cell buses(Cockroft and Owen, 2007); Goedecke,Therdthianwong and Gheewala used SLCC to evaluate alternative vehicles in Thailand(Goedecke et al., 2007).In all of these cases the SLCC was a before tax analysis to select among competing technologies.No consideration was given to how the capital is financed or whether the capital meets the hurdlerate of return used by companies (e.g. a 10% minimum attractive rate of return or MARR).

The Societal Life Cycle Cost as defined by Ogden, Williams, et al. (2004) to assess the Life

Cycle Cost of cars with alternative fuels and engines is a before tax analysis approach and isdetermined by the following expression (Ogden et al., 2004):

LCC ($/vehicle) =+ vehicle first cost+ the present value of lifetime costs for:

(fuel + non-fuel operation and maintenance)+ full fuel cycle air-pollutant damages+ full fuel cycle GHG emission damages+ oil supply insecurity). (ref Ogden)

The Ph.D thesis written by Nicolas Ahouissoussi (1995) does not specifically mentionSocietal Lifecycle Cost, but he used a before tax analysis approach to compare and analyze thecost for biodiesel, compressed natural gas, methanol, and diesel fuels for transit bus systems,(Ahouissoussi, 1995).

Cockroft and Owen (2007) also use a Societal Life Cycle Cost approach to determine theeconomics of hydrogen fuel cell buses (Cockroft and Owen, 2007); again it is a before taxanalysis approach.



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3.2. Choosing among alternatives using After Tax Analysis (ATA)

The most prevalent industry approach to choose among competing alternatives is the AfterTax Analysis (ATA) (Lang and Merino, 1993). Figure 1 describes a typical ATA decisionprocess followed by a written description of each of the steps within the process.

Why is After Tax Analysis the standard methodology for industry? ATA is necessary

because the government is a partner in every capital decision. Depreciation rates, tax rates,investment tax credits and capital gains taxes greatly influence the attractiveness of capitalexpenditures.

In addition, ATA is used to determine the impact of borrowing on the projects profitability.Borrowing at after tax interest rates that are below the projects Internal Rate of Return (IRR)will increase the overall Rate of Return (RoR). Note that the opposite is true. These borrowingoptions are called Financial Leverage.

Companies first look at a projects RoR assumptions with full equity (100% of companyscash with 0% of loans) to determine if the investment should be included in the capitalexpenditure budget. Financial leverage is considered for some subset of projects. Those projectstend to be ones that are required by law and are mandatory and not optional or elective. Also

financial leverage is considered when there is a readily available pool of funds and/or leaseoptions.

1

3.2.1. ATA Process Flow Chart

Fig. 1. General decision model to determine economic feasibility.

1A lease could be considered the same as a loan in certain circumstances.



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3.2.2. Description of Typical ATA Decision Process

Figure 1 illustrates a typical decision process used to choose among competing alternatives.

Step 1 develops feasible alternatives that are mutually exclusive. In this case alternatives arevarious bus fleet sizes. In addition to alternatives, scenarios can be constructed which could

combine alternatives along with other factors such as potential breakdowns or disaster scenarios.Step 2 estimates the capital and operating costs. Appendix I explains the estimates for the

case under consideration.Step 3 is the most critical step because of the need to estimate the benefits. Benefits can be

savings in operating cost compared to a base case. This could be caused by a more fuel efficientdesign than the base case.

Step 4 is the economic analysis. The first part is to establish economic criteria like MinimumAttractive Rate of Return or MARR. The MARR reflects the opportunity cost for the investorscapital. Risk plays a role because some investments may be more risky than others.

The time horizon needs to be determined. The owners need to decide to use full equity orloans, or some sort of financial leverage (10 to 90% of loans generally, most companies conduct

the economic analysis using full equity and then, after choosing the most economical alternative,look at financing options. Because this is an after tax analysis an applicable tax rate needs to beestimated for the chosen time horizon.

The last criteria are the Figure of Merit (FoMs). Given that the ATA model is run on an excelspreadsheet it is relatively easy to report on more than one FoM. FoMs include the Net PresentValue (NPV) and the Equivalent Uniform Annual Cost or EUAC. EUAC is the Life Cycle Costs(LCC).

Step 5 involves evaluation of the intangibles and non-economic factors impacting thedecision. There are a number of multi-attribute tools which can be used. Analytical HierarchyProcess (AHP) and Utility Analysis are two common techniques.

Step 6 involves the decision process. Sensitivity analysis should be employed to determine

the most sensitive attributes impacting the decision. This helps to separate the vital few fromthe trivial many. It is an aid in decision making because it focuses the effort on the mostimportant variables. Next, a decision needs to be made whether an economic or non-economicanalysis is to be employed. If all the attributes can be monetized and converted into dollars thenthe standard ATA with a FoM such as NPV or EUAC can be used to either maximize benefits orminimize costs. However, if the downtime cannot be monetized then some form of non-economic analysis must be employed. There are at least three different process flows dependingupon the downtime values and costs. This will be discussed in the next section.

Step 7 involves the decision whether the analysis yields an alternative which meets theeconomic and/or not-economic criteria. If it does than a decision is made. If it does not, theprocess needs to be repeated starting with step number 1. This process needs to continue until a

mutually exclusive feasible solution is reached.Step 8 is the final decision. If all the economic and non-economic criteria are met then adecision can be made to accept the alternative under review.

3.3. Comparison of SLCC and ATA

Obviously the major difference between SLCC and ATA is the tax considerations. Anotherdifference is that the SLCC is normally used for various technologies applied across industry and



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the economy while ATA is generally employed on an individual company basis. Determining theeconomic benefits of financial leveraging is also a major difference. A case study will bepresented which highlights the use of ATA for a specific application. Table 1 shows the maindecision attributes for both of the approaches.

Table 1

Comparison of differences for SLCC and ATA

Decision Attribute SLCC ATA

Life Cycle Costs Yes (before tax) Yes (after tax)

Includes Tax Factorsa No Yes

Scope of Study By technologies By Project

a Includes Deprecation, Income Taxes Investment Tax Credits, etc.

4. After Tax Analysis (ATA) models

4.1. ATA Bus Transportation Model Reduce Carbon

Most bus systems are owned and operated by government units (states, localities, etc.) or byregional authorities. Generally these systems are subsidized by the taxpayer or via crosssubsidies in the case of regional authorities who own and operate more than one mode oftransportation. A study developed by a Canadian consultant firm (MARCON-DDM HIT, 2005)indicated that subsidies were about 1/3 of the operating costs (excluding capital). NYC Transit(MTA) indicated an overall operating subsidy of about 41% (MTA New York City Transit,2004) .

The recent increase in diesel fuel prices has caused many bus systems to increase fares. Thiswas necessary in spite of the increase in bus rider ship. Increased fares tend to correlate

negatively with increased rider ship over the long run. This problem coupled with mandates(enacted or proposed) to decrease Carbon Dioxide (CO2) emissions has caused a reexaminationof bus system economics and methods of ownership and financing.

One advantage of developing an ATA model is that it could be used to attract privateinvestment. Bus systems require large capital investments for buses, garages, etc. All of theproposals to reduce carbon emissions in transportation require large capital investments inresearch and development, vehicle manufacture and infrastructure. Finding a way to fund thecapital required involves some combination of bus revenue, subsidies, taxation, bonding and/orprivate capital investment.

Figure 2 outlines how an ATA model could be used by industry and government to makeeconomic decisions as to investment in free carbon alternatives such as the hydrogen bus fleet.

This model could determine the:

Level of revenues/fares required to meet predetermined economic criteria (steps 1 3). Level of subsidy required to offset operating expenses (steps 1 3). Impact of carbon credits on revenue/fares (step 2). Impact of financial leverage on revenue/fares/subsidies (step 3). Most sensitive attributes impacting the after tax economics.



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The model has three phases as shown in Figure 2. The first step provides the base caseeconomics of the bus system. The second step evaluates the impact of carbon credits and thethird step the impact of financial leverage. In all three cases the owner/operator needs to judgethe level of revenue/fares and subsidies required to meet the economic criteria they established.

There is precedent for using ATA for public entities to raise capital and/or operating funds.Private ownership of transit cars and sell-lease back of public utilities (water systems, buildings,

etc.) are some examples.

Fig. 2. Low carbon transportation model.



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4.2. Process to Use the Low Carbon Transportation Model

Step 1: The purpose of this step is to establish a base case economics. In this case a lowcarbon hydrogen bus system was chosen. To conduct the ATA assumptions and estimates needto be provided. Refer to Appendix I for assumptions. The Life Cycle Cost (LCC) or EquivalentUniform Annual Cost (EUAC) is calculated with and without revenues. Revenues include all

fares and subsidies.Do these revenues meet the economic criteria (MARR) established for this system?If they do then the owner/operator has the right level of fares and subsidies. If they do not thenother sources of revenue and/or financing should be investigated (Steps 2 & 3).

Step 2: The purpose of this step is to determine the economic value of a carbon credits.Do these revenues with carbon credits meet the economic criteria (MARR) established for thissystem? If they do then the owner/operator has the right level of fares and subsidies.If they do not then other sources of revenue and/or financing should be investigated (Step 3).

Step 3: The purpose of this step is to determine the economic value of financing a portion ofthe capital required for this bus system.Do the revenues with financing meet the economic criteria (MARR) established for this system?

If they do then the owner/operator has the right level of fares and subsidies.If they do not then other sources of revenues/subsidies should be investigated (Step 1).

Feedback Loops: Note that this model is iterative. That is, if Step 1 is not ok go to Step 2. IfStep 2 is not ok go to Step 3. If Steps 2 and 3 are not ok go back to step 1. Also Steps 2 and 3 canbe done sequentially or individually.

5. Case Study: Hydrogen Busses

5.1. Carbon Free Case Study Hydrogen Buses Overview

To illustrate how ATA results influence bus system economics in a carbon free case a hydrogen

bus fleet was selected. Figure 3 below presents the various technologies considered to obtain alow /free carbon footprint for this application.

Note:Bolded Technologies could all be involved in a H2 Bus Fleet.

Fig. 3. A low carbon footprint model for the transportation sector.

Note that there are numerous technologies involved in providing low or free carbonfootprints for a bus system. Obviously, the owner/operator would want to examine the



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economics of all the combinations before choosing the most economic alternative. That set ofstudies was beyond the scope of this paper.

This paper concentrates on a Hydrogen fueled bus fleet example to illustrate how the ATAmodel works and could be used to provide economic direction to the bus owner/operator.

5.2. Carbon Free Case Study Hydrogen Buses Cost / Benefit Analysis

Published studies were used to generate the data for the case. Since no study was availablewhich contained all the data for an ATA analysis a number of studies were used. Table 2 showsthe list of study cases used to collect data.

Studies used as a basis for the ATA

1. Transforming the future: moving toward fuel cell-powered fleets in Canadian urbantransit systems by the consultant group MARCON-DDM HIT (MARCON-DDM HIT,2005).

2. Summary of Electrolytic Hydrogen Production by Johanna Ivy (Ivy, 2004).3. CU, RTD and the cost of a Hydrogen bus fleet by Erik Phillips (Phillips, 2006).

Table 2Sources for case study data

Source ElectricalRates

H2 Prod.Cap/Oper.

H2 Stor.Cap/Oper.

BusCap/Oper.

BusFares

1 Xa O O X Nd

2 O Zc O O N

3 O O Z O N

a X = Source used as is.b Z = Source used but modified.c O = Source not used.d N = Source not provided. Total revenues were not included but some information on subsidies was included.

The overall objective was to develop a reasonable set of estimates within a + or 10% rangethat could be used in an ATA. The purpose of the case study is to demonstrate how ATAanalysis could be used to help make economic decisions such as the level of revenue/subsidies,the impact of carbon credits and financial leverage opportunities.

Obviously, with so many sources with different dates, different currencies and otherdifferences it was a formidable task to construct a reasonable set of numbers. Fortunately thereare a number of different studies which could be consulted to establish a range and verify the

numbers used. The estimates were also reviewed by industry experts to determine whether or notthey were reasonable. Appendix I provides a summary of the estimates used.

For this case the revenue was estimated to be the same as the operating expenses in Step 1.This figure was also used to calculate the impact of financing leveraging. The operating cost permile for the case was close to published studies adjusting for the time frame (2015 versus 2007),the cost of fuel and other variables. Thus, verified the revenue assumption.



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5.3. Step 1 - After Tax Analysis Results

The first step is to establish a base case for the bus system economics. An initial set ofestimates and assumptions was entered into the ATA model in order to determine the totalannual cost of the alternative without revenues. See Appendix I.

Next, the revenue/fares and subsidies were added. Revenue/subsidies are usually calculated

via models developed by the transportation agency. Establishing the Cost of Capital (CoC) /Minimum Attractive Rate of Return is critical to this analysis. Every entity whether it be publicnon-profit or private for-profit has a cost of capital. Interest rates for government borrowing havevaried from 5% to 12%, usually with tax exempt privileges. The United States Office ofManagement and Budget established an MARR of 10% (Lang and Merino, 1993). For theprivate sector, MARR vary between 12 15% depending upon a number of factors. Thedetermination of MARRs is a complex topic and beyond the scope of this paper. A conservative10% CoC/MARR was used for this case.

The life of this case/project was determined to be 18 years according to the Canadian study(MARCON-DDM HIT, 2005), due to the average useful life for a conventional diesel bus andthe assumption that the hydrogen buses will have the same usability. The results are presented in

Table 6.As noted previously, revenue/fare/subsidy level where chosen assuming that the revenues

/fares/subsidies equaled the operating expenses. In other words, no profit at all. This assumptionwas based on the observation that most public transportation systems are subsidized by thegovernment and/or by a cross subsidy of other modes of transportation. The equivalent numberof passengers per year was estimated in order to verify the revenue/fare assumptions. For thiscase the fare price was calculated at $2/passenger and the number of passengers per bus per hourwas calculated to be 8 in an 18 hours per day basis. This was close to the study results andverified these assumptions.

Did the Internal Rate of Return (IRR) and other FoMs meet the 10% MARR? In this case itdid not see Table 6. This means that the revenues/fares, subsidies and capital involved do not

meet the economic criteria established.Given that the revenue/fare/subsidies are not sufficient what can the transportation

owner/operator do? Obviously one answer is to raise fares and to receive increased subsidies.Given the current economic conditions neither option is attractive.

Another option would be to try and obtain some form of carbon credit (step 2) and/or somelevel of loans to offset the capital (step 3) Note Step 1 has to be done every time a change onrevenue / subsidy estimates occur.

If the criteria were met it means that the revenue/subsidy levels meet the economic criteria.However, Step 2 and/or 3 can still be undertaken as a means of decreasing the fares/subsidies.

5.4. Step 2 Economic Impact of Carbon Credits

The purpose of Step 2 is to determine the economic value of a carbon credit. Carbon creditscan exist in addition to the base case revenues/subsidies or substitute for them, depending uponthe magnitude of the credit and the economic criteria chosen.

Determining the carbon credit is complex and somewhat uncertain as laws are passed (e.g.Cap and Trade). The Chicago Climate Exchange (CCX) operates the main carbon tradingplatform in the United States and the European Carbon Exchange. Carbon credits are traded inthe form of Carbon Finance Instruments (CFI) units (Davis and Hale, 2007).



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Credits, such us carbon credits, are estimated based on the market price per metric ton ofcarbon (metric tC). The process to calculate the carbon credits is depicted in five steps as follow(Davis and Hale, 2007):

Step 1: CO2 emissions from personal vehicle travel to substitute for transit travel.Step 2: CO2 emissions from transit travel.

Step 3: CO2 emissions savings from transit travel instead of personal vehicle travel.Step 4: CO2 emissions savings from fuel savings due to transit caused congestionreduction.Step 5: Total CO2 emissions savings from transit in 2005.

In this case the hydrogen buses are carbon free which means that all the CO2 generated bythe base case can be counted as carbon credits benefits. The credit carbon price is established bythe international capital market and therefore is subject to volatility.

The carbon credit value used for this study is $41/tC (metric tonne of Carbon). This value isthe current market price at which the credits are traded by the time this paper was written(Mouawad, 2008). The carbon credits estimates are presented in table 3.

Table 3Carbon credit estimation

Parameters Amount Units

External Carbon Credit 41 $/ metric tC

CO2 emissions (base case diesel bus) 22,449metric tonne ofCO2/Yr

CO2 emissions (H2 Bus) 0metric tonne ofCO2/Yr

Total Carbon credit 30,000,000 $/Year

Some standard assumptions on the distance driven per year and the fuel efficiency per buswere made in order to calculate the total amount of CO2 generated by the base case. The averagedriven mileage per bus was 60,000 Km/Yr and the bus fuel efficiency was 0.558 Liters of dieselper kilometer according to the Canadian study (MARCON-DDM HIT, 2005).

The estimated carbon credit for this alternative is around $30M. This value was calculated byextrapolating information from the Bus Rapid Transit (BRT) system in Bogot , Colombia(Transmilenio), which sells a total of $100 to $300 million worth of carbon credits for a 500 to600 diesel bus fleet (Rosenthal, 2009).

Did the Internal Rate of Return (IRR) and other FoMs meet the 10% MARR? In this case itdid not see Table 6. This means that the revenues/fares, subsidies and capital involved do not

meet the economic criteria established. The NPV and EUAC are still negative and the IRR is stilllower than the MARR.

Given that the carbon credit combined with the revenue/fare/subsidies are not sufficient whatcan the transportation owner/operator do? Obviously one answer is to try and increase theamount of carbon credits. Strategies may involve obsolescing older buses as was done in Bogot,Colombia. Another would be to decrease auto usage by alternating via banning traffic on certaindays (e.g. Bogot - Colombia, New York City U.S.A, San Paulo - Brazil, etc).



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Another option would be to try and obtain a level of loans to offset the capital (step 3) NoteStep 1 has to be completed every time a change of revenue / subsidy estimates are made.

If the criteria were met it means that the revenue/subsidy levels plus the carbon credits meet theeconomic criteria. However, Step 3 can still be undertaken as a means of decreasing thefares/subsidies.

5.5. Step 3 Economic Impact of Financing Options

The purpose of Step 3 is to determine the economic value of financing a portion of the capitalrequired for this bus system.Given that the carbon credit did not add sufficient revenue, the transportation model (Figure 2 Step 2) suggests examining finance alternatives. Different debt-equity ratios were evaluated todetermine whether or not the alternative will be economically feasible.

The U.S. Department of Transportations Federal Transit Administration (FTA) can fund upto 80% of the capital cost of transit buses (U.S. Federal Transit Administration, 2003). For thisreason the model was conducted using different debt-equity ratios from 10% up to 80% debt.

Those values were entered in the model and a new outcome was calculated. The revenue for thisassessment had the carbon credit included.

For an 80% debt ratio the NPV and EUAC become positive and the IRR is much higher thanthe MARR, reaching a value of 19.65%. The results indicate that the economic criteria have beenmet and the decision to proceed with the alternative can be made. The results are presented inTable 6.

Five cases were considered as indicated in Table 6. The first two cases (no loan and 10%loan) would apply to any alternative. The third and forth case (60% and 80% loan) are supportedby the Department of Transportations Federal Transit Administration (FTA) because they canfund up to 80% of the capital cost of transit buses (U.S. Federal Transit Administration, 2003).The fifth case (90% loan) would require some extra level of loan guarantee.

Table 4Low carbon transportation model Financial leverage

Loan (%) Equity (%) Revenue = Oper. Exp. + Carbon credits

NPV (k$) IRR (%/yr) EUAC (k$)

Base case 0 100 -35,937 8.08 -4,382

10 90 -26,029 8.47 -3,174

60 40 23,512 12.86 2,867

80 20 43,328 19.65 5,283

90 10 53,236 31.65 6,491

As indicated in Table 4, the FoMs increase significantly as the amount of loans increase.Since financial leverage (using loans instead of equity) is commonly used to finance large publictransportation projects, it has the effect of improving the projects rate of return. This is causedby substituting relatively cheaper loan dollars for more expense equity dollars.

However, increasing the percentage of loans increases the financial risk of default. If theproject is not successful (technology does not work, demand for service declines, etc.), the



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financial losses could be substantial and the probability of default increases. There are a numberof strategies to offset this risk including purchasing insurance to guarantee the loan. While this isexpensive, the additional economic return from the investment is more than adequate to coverinsurance costs.Figure 4 illustrates how increasing the loan percentage increases the projects rate of return(IRR).

Fig. 4. Financial leverage results

The results are as expected. When after tax loan monies are substituted into a project (loans)at lower rates (7% before tax and 4.6% after tax compared to 8.08% after tax t he project earns)

the IRR increases. The greater the loan amount the greater the increase in IRR

2

. This is anexample of financial leveraging.Did the Internal Rate of Return (IRR) and other FoMs meet the 10% MARR? In this case it didsee Table 6. This means that the revenues/fares, subsidies, capital involved and carbon creditstogether with loans meet the economic criteria established.

How difficult would it be to secure private investments? That would depend upon anadequate rate of return (e.g. 10% IRR) and moderate levels of risk. Given that bus systems are amature industry and that almost all systems are dedicated (e.g. no direct competition) it is likelythat loans to fund the capital from 60 to 90% could be available. If the government unit providessome guarantees this would be helpful. The promise of reducing Green House Gases (GHGs)will also aids in the fund raising effort.

Any financial leverage option should include a thorough risk assessment. This should includethe financial as well as the operating risks. As noted above there are risk mitigating strategiesthat should be evaluated along with the loans (e.g. insurance policies to protect against default,etc).

2 The opposite is also true. That is, substituting loans at higher after tax rate into a project with lower ROR willlower the IRR.



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Another benefit for financial leverage is that fares and/or subsidies could be reduced. Forinstance Table 5 illustrates the impact of financial leverage on the operating revenue. Reducingthe IRR to a 12% DCF RoR could result in a reduction of 28.4% in operating revenue. This is asubstantial reduction which could be used to reduce fares and/or subsidies and make the H2 busalternative in this paper economically attractive.

Table 5Financial Leveraging Scenarios Impact on Revenues

Equity (%) Loan (%) IRR (%) OperatingRevenue (%)

Difference (%)

100 0 8.08 100.0 0

10 90 12.00 71.6 -28.4

5.6. Step 1 - 3 Summary of Economics

The table 6 below summarizes the major FoMs for the three steps in the model.

Table 6After Tax Analysis model results.

Parameters Units WithoutRevenue

Revenue =Oper. Exp.

Revenue = Oper. Exp.+ carbon credits

80% Debtratio

ATA Step >> 1 2 3

Internal Rate of Return % 0 -5.40 8.08 19.65

Net Present Value k$ -360,219 -214,343 -35,937 43,328

5.7. Sensitivity Analysis

Sensitivity analysis is employed to determine the most sensitive attributes impacting thedecision. This helps in separating the vital few from the trivial many. This is an aid indecision making because it focuses the effort on the most important variables. Table 7 shows thesensitivity analysis results while Figure 5 is a spider plot of the sensitivity data.



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Table 7Sensitivity analysis results

Attribute Used in the ATA Model Spread Hydrogen Bus Fleet

Sen. Ratioa Rankb

Total capital cost +/- 20% 6.00 1

MARR Cost of Capital - 20% 5.24 2Carbon Credit +/- 20% 4.96 3

MARR Cost of Capital + 20% 4.21 4

Revenue only / Operating Costs +/- 20% 4.06 5

a The ratio provided by the change in parameter with respect to its initial value (Base case).b Rank is given by considering the most sensitive variable as number 1 and the less sensitive as number 5.

Fig. 5. Spider plots for sensitivity analysis results.

Total Capital Costs and the Cost of Capital (Minimum Attractive Rate of Return MARR)and Carbon credits are the most sensitive economic factors in this case. The spider plot (SeeFigure 5) graphically illustrates the sensitivity analysis. Operating costs/revenue were somewhatless sensitive.

The total capital cost and the Cost of Capital (CoC)/(MARR) have the steepest slopes

although in opposite directions. That is, for a given change of the parameter (capital orMARR/CoC) there is a relatively large change in the Figure of Merit (NPV or IRR or EUAC).The implication of this is that the economic feasibility of this case is highly dependent upon thecapital cost and CoC which is a function of the technology and how it is financed. This is truenot only for this case but for almost all new technologies used to reduce GHGs. Technologicalchange requires large expenditures in research and development which is reflected in the capitalcost.

What this case shows is that if the owner operators used their own equity/capital theeconomic returns do not meet the criteria established. However, with loans (financial leverage)



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the economic feasibility became acceptable. Again this is not a surprising result. Virtually allnew technologies require financing to succeed. Why?, because new technologies require largeamounts of research and development, which makes the price for this technology expensive.Hydrogen busses are just one of many examples. Equity financing is too expensive while debtfinancing is more affordable.

6. Conclusions

The ATA Transportation model was useful in determining the level of revenues/fares andsubsidies for the hydrogen bus example in this paper.This case illustrates that the carbon credit (from Cap & Trade or carbon tax), while economicalattractive, did not meet the assumed MARR/CoC in this study. Ways to increase the carboncredit and/or the revenues/fares and subsidies were needed to meet the relatively conservative10% MARR/CoC.

This study indicated that obtaining loans (financial leverage) was financially very attractivedepending upon the level of debt to equity ratio used (See Figure 4). Financial leverage couldhelp in reducing revenues/fares, subsidies and even accepting lower carbon credits, The use of

financial leveraging could provide an opportunity for private investors to make a reasonablereturn on their investment and at the same time provide the capital investment required for newbuses, Hydrogen infrastructure, garages and parking.

This study reinforces other economic studies completed by the authors (Bonilla et al., 2009)and others as to the importance of financing in adopting new technologies. While this study is aspecific micro-economic example it has macro-economic implications. Adapting newtechnologies to reduce GHGs has major economic impacts on electricity generation,weatherization, insurance and other areas. While some of these impacts may be captured in theCarbon Tax and/or Cap and Trade benefits, many impacts will not be captured.

A question arises as to how this specific case could be used in general. Given that the datacame from published sources and was verified by cross checking these various studies and by

expert opinion, this would suggest that the ATA model has general applicability.Another verification of this model is the conclusions it generated. As noted previously it is

not surprising that financial leverage would help make this case economically attractive. Whilethis is generally known there are not many specific case studies in the literature that validate thisconclusion. In fact, most of the new technology comparisons use the Societal Life Cycle Cost(SLCC). The SLCC approach which is a before tax analysis methodology does not show theimpact of financial leverage.

7. Future Research

A specific example needs to be developed that provides the data for a more specific bus case.

This should include local conditions which are an important aspect of this problem. Prevailingfare structure, levels of subsidies, capital costs for buses, Hydrogen production, diesel costs,GHG Cap and Trade subsidies, and other key factor (e.g. cost of electricity for Hydrogenproduction) need to be identified. The ATA transportation model in this paper should be used inthis case. This would help validate this approach with specific data from other sources. Thetransportation model could be extended to include the impact of traffic regulations like banningcars on certain days.



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There should be a thorough risk assessment made for any case under consideration. Thisshould include both the financial as well as the operating risks. Risk mitigating strategies shouldbe evaluated along with the loans (e.g. insurance policies to protect against default, etc).

Another area for research is to focus on how Green Banks and other financing schemeswould impact the adoption of new technologies such as Hydrogen busses. Included is theimpact of even lower cost loans (less than 7%) and higher leverage (above 80%). These options

would require even greater risk mitigations.

Appendix I Summary of Estimates / Assumptions

Basis: 250 Bus Fleet; 2015US$; 18 yr. project life;

Table 8Summary of estimates

Cost Element Amount (k$) Sourcesa

Depreciable Capital - Buses 250,250 1

Depreciable Capital H2 Production and Storage 15,518 2,3

Depreciable Capital - Garage and Parking 6,229 1Non Depreciable Land for 1, 2, 3 above 14.06 2

Working Capital for 1, 2, 3 above 5,496 1,2,3

Operating Costs Electricity for H2 6,561 2,3

Operating and fixed Costs for H2 excluding electricity 1,611 2

Operating and fixed Costs for Busses 24,601 1

Operating and fixed Costs for Garage and Parking 202 1

a See table 1 for references

Table 9Summary of assumptions

Assumptions Units Value

Tax Rate Operating %/year 40

Tax Rate - Capital %/year 20

Loan Rate %/year 7

Inflation Rate %/year 3

Minimum Attractive Rate of Return (MARR) Cost of Capital %/year 10

Salvage Rate: Equipment yr. 18 %r 20

Salvage Rate: Land and Building yr. 18 % 100



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References

Ahouissoussi, N.B., 1995. A comparative cost analysis for biodiesel, compressed natural gas,methanol, and diesel fuels for transit bus systems. University of Georgia, Athens,Georgia.

Bernstein, L., et al., 2007. Climate Change 2007: Synthesis Report. Summary for policy makers.

Intergovernmental Panel on Climate Change (IPCC), Valencia, Spain, p. 22.

Bonilla, O., et al., 2009. Commercializing A New Technology: Using After Tax Analysis (ATA)to Assess a Wave Energy Farm System. Renewable Energy, under review.

Cockroft, C.J., Owen, A.D., 2007. The Economics of Hydrogen Fuel Cell Buses. EconomicRecord 83, 359.

Davis, T., Hale, M., 2007. Public Transportations Contribution to U.S. Greenhouse GasReduction. Science Applications International Corporation (SAIC), McLean, Virginia p.43.

Goedecke, M., et al., 2007. Life cycle cost analysis of alternative vehicles and fuels in Thailand.Energy Policy 35, 3236-3246.

Ivy, J., 2004. Summary of Electrolytic Hydrogen Production. Milestone Completion Report. U.S.Department of Energy. National Renewable Energy Laboratory, Golden, Colorado, p. 27.

Lang, H.J., Merino, D.N., 1993. The selection process for capital projects, illustrated ed. JohnWiley and Sons, New York.

MARCON-DDM HIT, 2005. Transforming the future: Moving towards fuel cell powered fleetsin canadian urban transit systems. Natural Resources Canada, Montreal, Canada, p. 116.

Mouawad, J., 2008. Industries allied to cap carbon differ on the details The New York Times,Business 2.

MTA New York City Transit, 2004. Financial Report. MTA New York City Transit (NYCT),

New York, p. 1.Ogden, J.M., et al., 2004. Societal lifecycle costs of cars with alternative fuels/engines. Energy

Policy 32, 7-27.Phillips, E., 2006. CU, RTD and the cost of a Hydrogen Bus Fleet. University of Colorado at

Boulder, Boulder, Colorado, p. 25.

Rosenthal, E., 2009. Buses May Aid Climate Battle in Poor Cities The New York Times,Americas 1.

Schwartz, N.D., 2008. American Energy Policy, Asleep at the Spigot The New York Times,Business 4.

U.S. Federal Transit Administration, 2003. Bus Rapid Transit Offers Communities a Flexible

Mass Transit Option. United States General Accounting Office, p. 19.

http://www.bvsde.paho.org/bvsacd/cd68/synthesum.pdfhttp://www.apta.com/research/info/online/climate_change.cfmhttp://www.calstart.org/programs/FuelCell/Hydrogen_Bus_Source_Issue_1_August_2005.pdfhttp://www.calstart.org/programs/FuelCell/Hydrogen_Bus_Source_Issue_1_August_2005.pdfhttp://www.colorado.edu/physics/phys3070/phys3070_sp06/rtd.pdfhttp://www.colorado.edu/physics/phys3070/phys3070_sp06/rtd.pdfhttp://www.calstart.org/programs/FuelCell/Hydrogen_Bus_Source_Issue_1_August_2005.pdfhttp://www.calstart.org/programs/FuelCell/Hydrogen_Bus_Source_Issue_1_August_2005.pdfhttp://www.apta.com/research/info/online/climate_change.cfmhttp://www.bvsde.paho.org/bvsacd/cd68/synthesum.pdf


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Bus Trans ATA V10 authors version docx 18 of 18 1/23/2011

Author Biography

Oscar Bonilla, Ph.D StudentOscar Bonilla is PhD student of Engineering Management at Stevens Institute of Technology.He obtained his bachelor degree in Automation Engineering from La Salle University in Colombia as well as hismasters degree in Industrial Process Automation from Los Andes University. As a six sigma certified professionalwho has years of professional experience within the industry in different areas such as project management,

maintenance and support and six sigma projects, as well as serving as researching and teaching assistant currently atStevens Institute of Technology.

Donald N. Merino, Ph.D., P.E.Alexander Crombie Humphreys Professor of Economics of Engineering

Donald N. Merino is a tenured full professor and the Alexander Crombie Humphreys Chaired Professor ofEconomics of Engineering at Stevens Institute of Technology. He teaches Engineering Economy, DecisionAnalysis, Total Quality Management, and Strategic Planning. He is Founder Emeritus of the undergraduateBachelor of Engineering in Engineering Management (BEEM) and the Executive Master in TechnologyManagement (EMTM) Program at Stevens.He won the Morton Distinguished Teaching Award for full professors at Stevens. John Wiley published his book,The Selection Process for Capital Projects. Dr. Merino received two Centennial certificates from the ASEE inEngineering Economics and Engineering Management. He is past Chair of the Engineering Management Division

and Engineering Economy Division of ASEE. Dr. Merino was awarded the ASEM and ASEE Bernard SarchetAward. He is an ASEM and ASEE Fellow and past president of ASEM.Dr. Merino has 25 years of industrial experience in positions of increasing managerial / executive responsibilities.He worked 10 years for Mobil and 10 years for Celanese. His initial assignment at Celanese was Director ofHydrocarbon Planning where he was responsible for forecasting energy prices.Since joining academe 24 years ago, he has published 42 refereed journal articles and conference papers and over50 research reports.

Address:

c/o School of Systems and EnterpriseStevens Institute of Technology, Hoboken, New Jersey, 07030Work telephone: 201-216-5504; E-mail: dmerino@ stevens.edu

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