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55 7.1 Introduction Case studies for this project featured four local airport sponsors. The interactions with the airports were accomplished through a series of airport-specific webinars and follow-up teleconferences. Airports had expressed concerns about the extent of staff resources that might be required to participate in the project, and the webinars provided a cost-effective way to interact with a more limited effort from airport staff than a series of site visits. The primary goal of these discussions was to introduce an illustrative case study for each air- port demonstrating the methodology described in the project handbook to help airports evaluate the potential impacts of climate change. The project team presented example scenarios of specific climate risks faced by each airport using the most recent and localized climate data. In the case studies, the risk and uncertainty faced by each airport was modeled using a Monte Carlo simulation implemented in an Excel spreadsheet. In the modelâs base case, the airport would do nothing and face the full risk of climate change in the future. In the scenario case, the airport would invest in a mitigation investment that would result in a reduction or elimination of the climate risk. It must be noted that the mitigation investments were chosen only for the purpose of dem- onstrating the analysis tools developed in this project. The airports were less interested in dis- cussing actual or potential projects and more interested in the climate data and methodology. As a result, neither the type of mitigation nor its feasibility was formally considered as potential capital improvements for the airports in question; they only served as examples for the benefitâ cost and financial feasibility analyses. However, it is important to point out that actual climate data projections were obtained for each airport. Thus, while the project mitigations are purely illustrative, the climate data shown in each case represent actual estimates of potential future climate outcomes. It is also important to emphasize that, in all cases, the climate projections used were those from RCP8.5 (recall Exhibit 3-1), which represents a high-emissions scenario for future climate change. Two of the case studies involved BCAs suitable for airport letter-of-intent (LOI) funding applications to the FAA; these studies were conducted for runway extensions designed to offset the impacts of high temperatures on commercial aircraft operations. Because the majority of benefits from runway extensions would be enjoyed by passengers and operators, it made sense to follow FAA guidance on appropriate benefitâcost methods, adjusted to account for climate risk as described in the following. FFA was applied for two cases involving increased exposure to flooding and storm surge. In these cases, airport infrastructure was catalogued for exposure, depending on the forecast C H A P T E R 7 Case Studies
56 Climate Resilience and BenefitâCost Analysis: A Handbook for Airports extreme water level. The higher the water level, the greater the number of infrastructure compo- nents that would be exposed. While operators and passengers could be affected by service inter- ruptions in the event that critical infrastructure was inundated, the FFA focused on whether the airport could justify investing in mitigations solely based on the expected costs avoided. 7.2 Case Study Overview It was desirable to have case studies of large, medium, and small hubs in order to assess whether there were variations in the levels of awareness of potential climate problems and how the airports were dealing with them. Originally the project team was planning to apply the latest climate data to Monte Carlo models for two of the case studies, with the other two being treated using only data from the ACROS model from ACRP Report 147 (Dewberry et al. 2015). However, it became apparent that the airports were interested in the Monte Carlo process, so Excel-based models using the latest climate data were developed for each case study. Agreement was reached with four airports: â¢ Large-hub airports (2) â Phoenix: Case study of the effects of higher temperatures on cancellations and payload/ range limitations potentially mitigated by a runway extension. The case study was based on cancellation experience in the summer of 2017 when regional jet flights were cancelled during the midday period because temperatures reached 118Â°F. â Boston: Case study of the exposure to storm surge due to sea level rise, potentially miti- gated through a variety of investments, including raising floor levels and building protec- tive infrastructure. â¢ Medium-hub airports (1) â New Orleans: Case study of the exposure to storm surge due to sea level rise. MSY is just 3.7 ft above sea level and has a perimeter dike to limit damage from storm surge. Although the airfield did not flood during hurricane Katrina, the facilities suffered extensive wind and water damage. The airport is also nearing completion of a new replacement terminal. Potential mitigations are similar to those considered in the Boston case study. â¢ Small-hub airports (1) â Little Rock: Case study of the effects of higher temperatures on cancellations and payload/ range limitations. LIT has an 8,200-ft runway, and payload range penalties for missions in excess of about 1,000 miles begin when temperatures exceed 100Â°F. A runway extension could potentially eliminate the problem. Information Request Participants were asked to provide information on how their airport was organized to deal with climate change. There were two primary areas of interest: â¢ The first focus area was on the organizational process implemented at the airport to deal with climate change and potential adaptation strategies. The project team wanted to understand the people involved, both internally and externally. Particular attention was paid to the expertise of the individuals on the core team and whether specialists had been retained to deal with complicated issues related to climate change as well as economic and financial analysis under uncertainties. The research team also wanted to understand how the airport had engaged with the public on these matters and how airport operators made decisions on adaptation strategies. â¢ The second area of focus was on understanding how the airport was identifying its vulnerability to climate change risk and how it was determining what infrastructure might be critically affected in the future. The research team was interested in the data and tools being used by the
Case Studies 57 airport operators in making these determinations and, in particular, whether they were using the ACROS tool and the latest data available from the National Oceanic and Atmospheric Administration (NOAA) to assess climate risk. A brief summary of findings is shown in Exhibit 7-1; more details on the interactions with each airport are provided in Appendix H. In general, it was found that airports facing immediate climate-related impacts (PHX, BOS, and MSY) had taken steps to address the problems. The problems at LIT are likely to be faced further in the future and the airport is smaller, so it appropriately has fewer staff dedicated to these kinds of issues. Development of Workshop Materials For the case studies, the project team developed an Excel program employing the latest available climate data for each airport to conduct a VaR analysis. Based on the Excel model, a PHX BOS MSY LIT Senior climate change person Sustainability coordinator Climate mitigation and resiliency manager Cross functional Cross functional Reports to Cross-functional team* Assistant director â capital programs and environmental management Cross functional Director properties, planning, and development Climate risk evaluated in house or by consultants Primarily consultants Primarily consultants Primarily consultants Depends on airlines to evaluate payload penalties Airport access to climate data Via consultants Mass DOT partnership with Woods Hole Group, with Climate Ready Boston information as a supplement Via consultants Via consultants Investments in climate mitigation Cross-functional team* Capital programs and environmental affairs responsible for 5-year capital improvement program, subject to chief executive officer and board approval Extreme water events accounted for in the new North Terminal project None to date Existing operational mitigations Hold times when temps rise above thresholds; safety measures for on- ramp staff Arrangements to deploy flooding/storm surge/tidal surge countermeasures based on forecasts Yes for flooding None to date, but concerned about payload penalties effect on air service development to West Coast and New York Communications with public regarding climate change Just fact checking articles; otherwise airlines take the lead Participates in various community programs such as Climate Ready Boston and periodic public awareness events such as a drill on flood abatement deployment Extensive public discussion of new terminal, which is in the 100-year flood plain (per final supplemental environmental assessment of the project) Leaves this to the airlines *Operations, public safety and security (includes fire, police, first responders), facilities maintenance, design and construction services (for any changes to building specs, etc.), and risk management and financial management division. Exhibit 7-1. Summary of findings.
58 Climate Resilience and BenefitâCost Analysis: A Handbook for Airports PowerPoint presentation was prepared for the WebEx conference with each airport. The pre- sentations began with a common set of introductory slides and then moved on to the specific case study for the airport. Once the PowerPoint presentation was completed, the study team presented the Excel simulation model. Airport participants were encouraged to ask questions and comment on the materials throughout the WebEx conference. All the airports participated actively in the case study pro- cess. Follow-up calls and emails were placed to obtain missing information. Quantifying Risks and Uncertainty Two types of climate risks were analyzed in detail in the case studies, using the following information sources and operational assumptions: â¢ Very high temperature days (in excess of 100Â°F): Localized projections of 31 different climate models from RCP8.5 scenario15 for the four closest points to the subject airports (PHX and LIT); projections are from 2020 to 2090. Counts of high-temperature days in each year were randomly drawn from the available models. A set of predictions from 2020 to 2090 represent a single simulation, and a total of 5,000 simulations were conducted. â¢ Sea level rise and storm surge: NOAA historical extreme water level (EWL) and relative sea level (RSL) rise projections linked to RCP8.5 (MSY and BOS); projections are from 2020 to 2100. Outcomes for each year were based on a random draw from localized historical exceed- ance probability functions developed by NOAA plus a random draw from localized sea level rise projections. The result was a single prediction of the height of an extreme water event each year.16 A set of predictions from 2020 through 2100 represent a single simulation, and a total of 5,000 simulations were conducted. In all cases, a climate event in any year could potentially trigger costs (to the airport, opera- tors, or passengers). In each of the 5,000 simulations, these costs were discounted and added up. Base Case The results of the simulations were used to consider the VaR to the airport if no mitigation were undertaken. â¢ In the case of flood risks at BOS and MSY, while it is common to base mitigation investments on the risk of a 100-year event (one with an annual probability of 1%), the VaR analysis provides more complete information by considering the entire range of potential outcomes on the expected loss to the airport and its users. The impact of a 100-year event is essentially embedded within the simulations and would be identified as the 50th (99th percentile out of 5,000) most costly loss generated from the simulations. â¢ In the case of PHX and LIT, the VaR analysis provides more complete information on the number of days each year where temperatures exceed critical levels; the data are presented in 2-degree increments. This would allow the airport to assess how often some aircraft types on scheduled missions would face payload penalties at, say, 110Â°F versus 114Â°F, and how often flights might have to be cancelled at very high temperatures (in excess of 118Â°F or 126Â°F). Scenario Case The same process was repeated for possible mitigation strategies. First, the effectiveness of the mitigation was defined: Would it eliminate the risk entirely by preventing flooding or averting cancellations and payload penalties due to high temperatures, or would it only be effective in some cases? Then the life-cycle costs of the mitigation were defined.
Case Studies 59 Applying the same climate risk profiles to the mitigation scenario generated 5,000 outcomes defined as net life-cycle costs (avoided risk minus the life-cycle costs of mitigation). These costs were then compared to the base case (without mitigation). By counting the instances where the net life-cycle costs of the mitigation were lower than the costs without mitigation, one could readily determine how often a mitigation project would pay off. The mitigation investments considered were fairly generic. The participating airports indicated a preference for focusing on the detailed modeling methodologies and providing comments, but they were not prepared to commit time or resources to the development or endorsement of specific mitigation investment possibilities. Therefore, the main focus of the presentations was on the methodology itself. The example mitigations were chosen only to facilitate the demonstration of the methodology and do not represent any plans of the participating airports. BenefitâCost Versus Financial Feasibility Analysis It is worth noting that the two high-temperature cases involved runway extensions and were presented as benefitâcost studies suitable for an FAA LOI application. This made sense in these cases because a large portion of the benefits were attributed to averted passenger delay costs. In the case of the two flood mitigation projects, the cases were presented as financial feasibility exercises because more of the costs of flooding would be incurred by the airport making repairs to damaged infrastructure. 7.3 Summary of Presentations and Lessons Learned A tabular summary of the presentations and sample analysis for each airport is shown in Exhibit 7-2. A summary of the lessons learned is presented in the following. â¢ Overall, the airport participants had no problem following the methodology for conducting the VaR analysis using the latest climate data. â¢ All airports appeared to be familiar with the potential threats from climate change. â¢ PHX and BOS had active programs in place that were evaluating climate risk. â¢ LIT depended on airline input on potential payload issues and was mostly concerned about the increased frequency of payload penalties affecting its attractiveness for longer-haul service to the East and West Coasts. â¢ MSY was in the middle of a new terminal project and indicated that the threat of sea level rise had been and would continue to be central to its planning. â¢ It was apparent that, in the case of sea level rise and flood threats, airports would benefit by linking flood maps with the probabilities that are produced in the VaR analysis. This would help engineers and decision makers visualize the threats to specific infrastructure. â¢ In the case of high-temperature days, PHX correctly noted that payload penalties in the form of weight restrictions could become an issue at much lower temperatures than the very high values that caused full flight cancellations in 2017. This was addressed directly in the Excel template for high temperatures. â¢ It became apparent during the case studies that, while ACROS is useful as a screening tool and as a way to classify infrastructure that is vulnerable and critical, the ACROS reports do not produce climate data (temperature or flood risk) that are precise enough to conduct benefitâcost or financial feasibility analyses. Different temperatures and levels of extreme water rise affect different operations and infrastructure. Having the full range or outcomes linked to probabilities allows the analyst to evaluate climate risks appropriately.
60 Climate Resilience and BenefitâCost Analysis: A Handbook for Airports Sampling plan Random draw among models for each year of each simulation Random draw among models using interpolations based on RCP probabilities Random draw among models using interpolations based on RCP probabilities Random draw among models for each year of each simulation Monte Carlo simulations 5,000 5,000 5,000 5,000 Summary of climate risk Increase in median days above 118Â°F from near zero at time of this report to over 20 by the 2080s, with variances across simulations Median annual sea level rise event increases from 1.6 ft historically to 6.2 ft by 2095; wide variations in outcomes Median annual sea level rise event increases from 2.6 ft historically to 5.5 ft by 2095; wide variations in outcomes Increase in median days above 100Â°F with variances across simulations Type of analysis FAA benefitâcost study Financial analysis Financial analysis FAA benefitâcost study PHX MSY BOS LIT Date April 26, 2018 April 27, 2018 May 7, 2018 May 10, 2018 Format WebEx WebEx WebEx WebEx Climate risk Very high temperature days Extreme water level events due to sea level rise Extreme water level events due to sea level rise Very high temperature days Impacts investigated Increased exposure to full flight cancellations when temperatures exceed 118Â°F Increased exposure to extreme water events (flooding) due to sea level rise Increased exposure to extreme water events (flooding) due to sea level rise Increased exposure to passenger payload penalties when temperatures exceed 100Â°F Stage 1: ACROS screening Large increase in days where temperature exceeds 100Â°F (temp fixed in ACROS software) Flooding 365 days a year by 2030 No flooding through 2060 but an increase in BFE Large increase in days where temperature exceeds 100Â°F (temp fixed in ACROS software) Stage 2: Need for detailed modeling ACROS data not detailed enough to model critical temperatures for specific aircraft at PHX: 118Â°F and 126Â°F ACROS data do not differentiate among sea level rise events ACROS data do not cover the 100- year or 500-year event threat that BOS uses in planning ACROS not detailed enough to model payload restrictions that may occur at different temperatures for different aircraft Climate data used Localized projections of daily high temperatures for four points within 4 miles of PHX, 2020â2090 NOAA historic local extreme water return period data for Louisiana coast, plus six NOAA future coastal scenarios tied to circulation model probabilities, 2020â2100 NOAA historic local extreme water return period data for Boston coast, plus six NOAA future coastal scenarios tied to circulation model probabilities, 2020â2100 Localized projections of daily high temperatures for four points within 4 miles of LIT, 2020â2090 Circulation scenario RCP8.5 RCP8.5 RCP8.5 RCP8.5 Number of climate models 31 6 6 31 Exhibit 7-2. Summary of case study sample analysis.
Case Studies 61 Modeled impact of climate risk Using FAA critical values, evaluate cost of cancelled regional jet flights when temperatures reach 118Â°F and cancelled standard jet flights above 126Â°F Evaluate net benefit of reducing the impacts of extreme water events using generic cost values for differing water levels Evaluate net benefit of reducing the impacts of extreme water events using generic cost values for differing water levels Using FAA critical values, evaluate delay costs to passengers bumped from flights to current and potential new destinations due to payload restrictions Modeled mitigation Runway extension with discounted life- cycle cost of $30 million Flood mitigation project with discounted life- cycle cost of $20 million Flood mitigation project with discounted life- cycle cost of $20 million Runway extension with discounted life-cycle cost of $30 million Impact of mitigation Elimination of flight cancellations Eliminate flooding for extreme water events up to 5 ft and reduce impact of higher events 80% Eliminate flooding for extreme water events up to 5 ft and reduce impact of higher events 80% Elimination of payload restrictions for domestic flights Analysis results Project has negative expected NPV and pays off only 15% of the time; 3% chance of $35 million loss if not built, but project could pay off with a higher probability with delayed implementation 10â 20 years out. Project has positive expected NPV and pays off 70% of the time; 20% chance the airport would lose $40 million or more if the project were not built; results based on a 3% discount rate. Projects has positive expected NPV but pays off only 35% of the time; 10% chance the airport would lose $40 million or more if the project were not built; results based on 3% discount rate. Project has a negative expected NPV and pays off only 7% of the time. PHX MSY BOS LIT Exhibit 7-2. (Continued).