Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
1 The purpose of this handbook is to help airport practitioners assess the benefits, costs, and financial feasibility of infrastructure projects that are designed to improve resilience to the impacts of climate change and extreme weather events. The handbook presents up-to- date methods for conducting benefitâcost and financial feasibility analyses that explicitly recognize risks and uncertainties that are inherent in long-term climate projections and their potential effects on long-lived airport infrastructure. The methodology is also broadly applicable to any uncertain financial or economic matter being considered by airports. This summary presents some of the features of the analytical methods discussed at greater length later in the handbook. The methods and analyses presented here focus on two specific areas of climate change likely to affect airports: (1) the potential for extreme flooding events due to storm surge and sea level rise near coastal airports, and (2) the potential for rising temperatures that could require weight restrictions on aircraft takeoffs (or that may cause full flight delays) at airports with shorter runways in warm climates or at high elevations. While other aspects of climate change may also affect airportsâ including, for example, increasing likelihood of localized thunderstorms or air turbulence affecting takeoffs and landingsâthe methodologies presented in this handbook focus on these two specific areas because specific quantifiable projections are currently available for these climate measures. S.1 Suggested Two-Step Analytical Process Exhibit S-1 illustrates a suggested two-step process for dealing with climate change risk. Step 1 screens for potential problems using an existing software tool called Airport Climate Risk Operational Screening (ACROS), which was published as part of ACRP Report 147: Climate Change Adaptation Planning: Risk Assessment for Airports (Dewberry et al. 2015). This tool uses climate data published in 2013 to identify potential areas of concern. ACROS leads the user through a process for identifying when airport infrastructure might be vul- nerable to climate change (likely to be affected) and whether the infrastructure itself is critical to airport operations (loss of use would be costly to the airport and its users). The projected outcome from the worst-case ACROS data can reveal whether to proceed to Step 2. To illustrate how Step 1 might work, Exhibit S-2 shows a summary of ACROS climate projections for LaGuardia Airport (LGA). Baseline values for 2013 are shown, along with 25th/median/75th percentile projections for the years 2030 and 2060. Using these data, the airport could focus on the 75th percentile (worst-case) forecast to evaluate whether there are areas to investigate more thoroughly. In this case, sea level rise could expose the airport to flooding.1 S U M M A R Y Climate Resilience and BenefitâCost Analysis: A Handbook for Airports
Exhibit S-1. Suggested two-step method for evaluating airport climate risk. Source: ACROS from ACRP Report 147 (Dewberry et al. 2015). Exhibit S-2. ACROS climate screening for LGA.
Summary 3 Step 2 in the process is to evaluate the risk more systematically by recognizing the uncer- tainty inherent in climate projections and considering ways to potentially reduce the impacts through investments (or operational changes). Essentially, one wants to know whether it makes sense to address the uncertain climate risk by investing in or changing the airport infrastructure or by changing how the airport operates. S.2 Applying the Process An airport could evaluate investing in an enlarged stormwater system to account for increased frequency of storm surge, or it could apply for a Letter of Intent for an Airport Improvement Program (AIP) grant to support a runway extension to offset payload penal- ties suffered by carriers due to increased frequency of high-temperature days. An analyst working on the stormwater project would want to have estimates of the likelihood that stormwater would rise above the critical elevations of important airport infrastructure. The analyst working on the runway extension would want to know how many days per year temperatures would exceed critical levels that cause airlines to offload payload on long-haul flights. This handbook discusses how these estimates can be extracted from the multiple climate forecasts that are available. It provides greater geographic precision and richer prob- ability estimates than were available in the ACROS software, which was published in 2015. Because future threats are inherently uncertain, it is important to capture the envelope and likelihood of different outcomes. This can be accomplished by performing a so-called value-at-risk (VaR) analysis. The handbook demonstrates how to take advantage of the variations across different climate projections to capture the range of potential outcomes. For example, in one projection, there could be 3 days forecast to be in excess of 100°F in a future year, while in another projection there could be none. Investment decision making with this kind of uncertainty is best captured in a Monte Carlo framework, where many what-if simulations are considered that randomly sample from the various climate projec- tions to capture the variation in potential outcomes. This handbook shows how to assemble historic climate data and merge them with a range of climate change forecasts. It discusses how climate forecasts are based on historic data and how to sample the data based on assessments of how accurate the climate models have been historically. Accompanying this handbook are two Microsoft Excel files (one for extreme water rise causing potential flooding events, and the other for high temperatures that may affect weight restrictions on aircraft takeoffs; these Excel files may be found by searching for âACRP Research Report 199â at www.TRB.org) that help the user assemble and use the latest climate data to run Monte Carlo simulations and assess VaR results from risk-adjusted benefitâcost or financial feasibility models. The Excel files sample the climate data randomly over the life of the specified project. A large number of Monte Carlo simulations (5,000) are run, each one counting up the number of days with flood events (at different extreme water levels) or the number of days with payload penalties (at different high ambient tem- peratures) each year. S.3 Summarizing Outcomes from the Analysis Exhibit S-3 illustrates two ways of summarizing potential future climate outcomes based on the simulations. Exhibit S-3a shows forecast changes in water levels for Boston Logan Airport. Reading across any given row, notice that the probabilities of higher water levels increase over time as sea level rises. As shown in the bottom two rows, the median height of the flooding events and the height of the 100-year event (that which occurs with 1% annual
4 Climate Resilience and BenefitâCost Analysis: A Handbook for Airports Water Level Rise (ft) Historical 2025 2035 2045 2055 2065 2075 2085 2095 0-1 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1-2 3.88% 0.08% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 2-3 68.46% 45.28% 24.68% 8.84% 1.76% 0.40% 0.12% 0.04% 0.00% 3-4 24.16% 46.46% 60.06% 61.94% 48.16% 28.04% 15.24% 9.52% 4.38% 4-5 2.98% 7.24% 13.34% 24.90% 40.38% 50.00% 47.64% 37.10% 29.00% 5-6 0.40% 0.80% 1.76% 3.66% 8.58% 17.68% 27.32% 34.06% 34.94% 6-7 0.12% 0.12% 0.16% 0.52% 1.02% 3.34% 7.72% 13.76% 19.38% 7-8 0.00% 0.02% 0.00% 0.14% 0.10% 0.48% 1.48% 4.20% 8.66% 8-9 0.00% 0.00% 0.00% 0.00% 0.00% 0.04% 0.44% 1.00% 2.76% 9+ 0.00% 0.00% 0.00% 0.00% 0.00% 0.02% 0.04% 0.32% 0.88% TOTAL 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% Median (ft) 2.66 3.06 3.32 3.63 4.00 4.37 4.72 5.07 5.45 100-Yr Event (ft) 4.63 4.98 5.29 5.66 6.06 6.74 7.38 8.14 8.88 BOS Extreme Water Level Event Probabilities from 5,000 Simulations (RCP 8.5) S-3a. Water level events at Boston. S-3b. Count of 110°F days at Little Rock. Sim # 2021 2022 2023 2024 2025 ⦠2085 2086 2087 2088 2089 2090 1 0 0 0 0 0 ⦠2 2 0 4 9 11 2 0 2 0 0 2 ⦠12 12 1 3 19 12 3 0 0 0 0 2 ⦠1 33 1 10 7 0 4 0 2 0 0 0 ⦠1 1 9 6 1 15 5 0 0 0 1 2 ⦠7 2 0 0 0 2 6 0 0 4 0 2 ⦠0 2 34 0 1 11 7 0 0 0 0 0 ⦠2 6 4 9 2 17 8 0 2 0 0 0 ⦠22 2 20 0 0 58 9 0 0 0 0 0 ⦠2 32 4 8 9 0 10 0 0 0 0 0 ⦠9 2 4 34 13 10 11 0 0 0 0 0 ⦠25 1 0 3 3 1 12 0 0 0 0 0 ⦠17 31 20 0 5 0 13 0 0 4 0 0 ⦠10 19 0 0 2 6 14 0 0 0 0 0 ⦠3 1 9 3 0 12 15 0 0 0 0 0 ⦠0 1 42 9 3 57 16 0 2 0 0 0 ⦠22 2 1 23 20 0 17 0 0 0 0 0 ⦠6 2 27 1 2 1 18 0 0 1 0 0 ⦠9 2 0 1 31 25 19 0 0 0 0 0 ⦠10 79 0 35 1 10 20 0 0 0 0 0 ⦠0 6 44 1 9 11 ⦠⦠⦠⦠⦠⦠⦠⦠⦠⦠⦠⦠⦠5000 0 0 0 0 2 ⦠10 1 0 9 2 10 Exhibit S-3. Examples of ways to summarize climate risks. probability) both increase significantly over time. An analyst could use these results to deter- mine when airport infrastructure built to a specific standard would likely be exposed. For example, infrastructure designed to withstand water heights up to 5 ft would be exposed to approximately a 1.7% chance of flooding in the year 2035 according to these projections.2 If certain long-life infrastructure were being planned today, it would make sense to consider ways to offset these climate risks. Exhibit S-3b summarizes the results of projections of annual high heat days; this extract shows a count of days per year above 110°F for Little Rock Airport from 2021 to 2090. (Fore- casts for other temperatures could be created as well.) An analyst could treat these data as a probability distribution summarizing the chances of temperatures reaching at least this level each year into the future. If 110°F is a level that is important for certain long-haul operations
Summary 5 at the airport, it might be worth considering whether a runway extension would make sense to mitigate the implied weight restrictions. The impacts of the events will vary. The costs of a water rise of 2 ft might threaten some infrastructure, while a 4-ft flood would affect more of the airport. Similarly, only a small number of long-haul flights might be affected when temperatures reach 110°F, while more flights would be affected at higher temperatures. The methods described in this handbook are designed to account for the probabilities of different events. The effectiveness and life-cycle costs of each mitigation project are also an input in the investment model of the Excel files. For example, a runway extension of 500 ft might reduce all of the payload penalties at 110°F but only half of them at 115°F. The Excel models can be used to quickly assess the impacts of different stormwater adaptations or runway extension lengths based on the probable future need for them; they also provide useful information on the distribution of different but uncertain climate results so that the airport and its users can assess the financial risks they are willing to incur. To illustrate how this all comes together, Exhibit S-4 summarizes the results of a flood mitigation project evaluation. The blue line in the chart is the range of probable outcomes without mitigation, and the red line is with mitigation. Each line represents 5,000 possible outcomes for the airportânet costs to the airport expressed in net present values. The box Exhibit S-4. Risk-adjusted evaluation of a climate project.
6 Climate Resilience and BenefitâCost Analysis: A Handbook for Airports in the upper left reports the average net present value and benefitâcost ratio for the project. In this example, conventional decision making would suggest that the project is justified and should be pursued (absent capital constraints) since the ratio is greater than one. The graphic on the right represents the results of the VaR analysis and is informative because one can assess the probabilities of the different possible outcomes. For example, it shows that 70% of the time the project would pay off if it were built today, which means that 30% of the time it would not. If the airport does nothing, there is a 20% chance it could lose $40 million or more over the analysis period (expressed in todayâs dollars). Over the course of the life of the project, an unmitigated 100-year storm would cost the airport over $80 million. (This is the value of the blue line at 1% probability.) This handbook also describes how to apply the methodology to options such as delaying a project. These findings could be relevant for both financial management and enterprise risk management. To be clear, the results presented in the VaR analysis do not necessarily make the decision on whether to invest in a mitigation project any easier, but the results do provide a full range of potential outcomes and possibilities for management to consider. The decision makers must essentially decide how much risk they are willing to accept. S.4 Related Topics In addition to the analytical methods themselves, this handbook discusses other inputs and factors that should be considered when undertaking such analyses of how to respond to climate change challenges. It provides information on classifying relevant airport assets and infrastructure, assessing how vulnerable these assets may be, and identifying feasible responses (including those not involving infrastructure) and financial constraints. Finally, this handbook includes some discussion of topics that, while not directly related to the methodology, may be relevant considerations for airport analysts. These include direct environmental strategies, how to handle hard-to-quantify impacts, and identifying broader economic impacts beyond the strictly defined project benefits and costs typically used for benefitâcost analysis.
