### COMMITTEE ON AVIATION ENVIRONMENTAL PROTECTION (CAEP)

NINTH MEETING

Montréal, 4 to 15 February 2013

Agenda Item 3: Review of technical proposals relating to aircraft noise.

COST

- BENEFIT ANALYSIS OF CAEP/9 NOISE STRINGENCY OPTIONS

(Presented by the United States)

SUMMARY This paper provides results from the U.S. cost benefit assessment of environmental impacts compared against economic costs for the CAEP/9 noise stringency options , with explicit consideration of interdependencies and uncertainties among impacts

. Given previous CAEP recognition of the need and importance of c onsidering the interdependencies of noise, fuel burn, a nd emissions , the U.S. conducted a cost benefit analysis to more fully assess potential interdependencies, and better inform decision making.

1. INTRODUCTION

1.1 This paper provides additional details from a U.S. cost

- benefit analysis that assessed the interd ependent impacts associated with the noise stringency options under consideration for CAEP/9. The analysis is in the appendix of this paper, and was used to inform the U.S. position on the noise stringency analysis (please see WP/34).

2. BACKGROUND

2.1 Interdepe ndencies

2.1.1 CAEP has increasingly recognized the importance and need to consider the interdependencies between noise, fuel burn and emissions and among individual emissions types. The current CAEP Work Programme acknowledges the need to take interdependencie s into account as part of task N.06.02 “to assess interdependency effects of noise stringency options with respect to CO 2 /fuel burn and NO X .” 1

1 CAEP

- SG.20123.IP.001 , page SD/5 .A2, Task N.06.02 CAEP/9

- IP/25 13/12/12 English onlyCAEP/9

- IP/25

- 2

-

2.1.2 Since 2004, the U.S. has routinely reported to CAEP regarding the development of a suite of tools, including the Aviation Environmental Portfolio Management Tool for Impacts (APMT

- Impacts), to facilitate thorough consideration of aviation's environmental e ffects . The tool suite has been designed and developed by the Federal Aviation Administration in collaboration with the National Aeronautics and Space Administration and Transport Canada. The main goal for developing these state

- of

- the

- art tools was to b e able to characterize and quantify the interdependencies among aviation

- related noise and emissions, impacts on health and welfare, and industry and consumer costs, under different policy, technology, operational, and market scenarios.

2.1.3 Following CAEP/7 agreement, the U.S. conducted a cost benefit analysis using APMT

Impacts to assess the interdependencies associated with the NO x stringency options under consideration at CAEP/8. Results of the U.S. analysis, and a comprehensive overview of the approach a nd methodologies used to conduct the analysis, were provided in CAEP/8 IP

- 30.

2.2 CAEP/9 Noise Stringency Analysis

2.2.1 C AEP/9 W o rk Prog ra mme directed WG1, WG3, MDG and FESG to conduct analyses of the potential noise stringency options under consideration for CAEP/9

. 2 The work conducted regarding the stringency options assessed , industry response, environmental benefits and cost effectiveness are documented in the MDG and FESG paper to CAEP/9. 3 The same data developed through the CAEP analysis process were used as inputs to the U.S. cost benefit analysis; specifically data from MDG’s AEDT fuel burn and emissions model, the MDG noise models, an d FESG’s APMT

- Economics model.

2.2.2 It is important to note the behaviour of MDG’s environmental results and the FESG costs as they feed the cost benefit analysis. The MDG noise results behaved as expected, showing increased noise benefits as the noise string ency levels increased. The MDG fuel burn and NO X results did not follow the noise data trend.

3. DISCUSSION

3.1 The U.S. conducted a cost benefit analysis to assess the interdependencies associated with the noise stringency options under consideration for CAEP/9 . The a nalysis took into consideration the environmental impacts of the stringency options, including assessing the health and welfare impacts; and, quantif

ied interdependencies in terms of physical and monetary impacts for a ircraft

- related noise

, fuel burn and emissions . The analysis followed a similar approach to that used for conducting a
cost

- benefit analysis of the stringency options for the CAEP/8 NO X Stringency Analysis.

3.2 As delineated in the appendix, the environmental benefits and economic co sts associated with the CAEP/9 noise stringency options were analyzed for the US domain from 2006 to 2036 with policy implementation in 2020. MDG noise, fuel burn and emissions data were used as inputs, along with FESG calculated recurring operating costs

. 4

3.3 All stringency options lead to a noise benefit ranging from 0.5% to 5% reduction in the cumulative number of people impacted by noise over the next 30 years.

2 Tasks N.06.01, N.06.02

, E.10, M.02, and F.02.
3 CAEP/9

- WP/8
4 Sensitivity tests incorporating FESG’s non

- recurring cost estimates did not change the cost benefit findings.CAEP/9

- IP/25

- 3

-

3.4 Stringency 1 (Chapter 4

- 3 EPNdB) is shown to be cost beneficial across all assumptions consi dered; however, the associated fuel burn emissions are within the resolution limits of the MDG models, indicating that environmental benefits are uncertain and not significant.

3.5 Stringency 2 (Chapter 4

- 5 EPNdB) is shown to be cost beneficial across all as sumptions considered; provides global reductions in noise, fuel burn and emissions; and, offers the largest reduction in direct operating costs relative to the no stringency case. Stringency 2 is the most cost beneficial option, irrespective of the combin ations of assumptions considered.

3.6 Stringency 3 (Chapter 4

- 7 EPNdB) has environmental benefits greater than Stringency 2; however, the recurring costs are greater than the monetized environmental benefits across most assumptions considered. Only under a v ery limited set of assumptions 5 (e.g., indicating a high level of impacts for noise, air quality and climate coupled with the highest values of statistical life) could Stringency 3 potentially become cost beneficial.

3.7 Stringency 4 (Chapter 4

- 9 EPNdB) inclu des an increase in fuel burn emissions because the fleet shifts to smaller, compliant aircraft that require increased operations to maintain seat demand

. Thus, while Stringency 4 has noise benefits, it also has air quality and climate dis

- benefits, and is not a sensible stringency consistent with CAEP principles.

3.8 Stringency 5 (Chapter 4

- 11 EPNdB) continues the dis

- benefit trend in air quality from Stringency 4 ; however

, the fleet shifts away from smaller aircraft, and demonstrates climate benefits. This

s tringency is even more inconsistent with CAEP principles.

— — — — — — — —

5 See Appendix Tables 4, 5, and 6 respectively for the range of noise, air quality and climate assumptions.APPENDIX

C OST

- B ENEFIT A NALYSIS OF CAEP/9 N OISE S TRINGENCY O PTIONS

1 I NTRODUCTION

................................ ................................ ................................ ........................... A

- 3 2 M ETHODS FOR ASSESSING TRADE

- OFFS AMONG ENVIRONME NTAL & ECONOMIC IMPACTS A

- 3 2.1 APMT

– Impacts

................................ ................................ ................................ ............. A

- 5 2.1.1 Noise Module

................................ ................................ ................................ ..... A

- 5 2.1.2 Air Quality Module

................................ ................................ ............................ A

- 6 2.1.3 Climate Module

................................ ................................ ................................ . A

- 6 3 C OMMUNICATION OF RESU LTS

................................ ................................ ................................ .. A

- 7 3.1 Decision

- Making Framework

– Lenses

................................ ................................ .......... A

- 7 3.2 Timescales

................................ ................................ ................................ ...................... A

- 8 4 N OISE S TRINGENCY P OLICY A NALYSIS

................................ ................................ .................... A

- 9 4.1 CAEP/9 Noise Stringency Options

................................ ................................ ................. A

- 9 4.1.1 FESG Fleet and Traffic Forecast

................................ ................................ ..... A

- 10 4.1.2 Emissions Modeling

................................ ................................ ........................ A

- 11 4.1.3 Cost of Stringency Options

................................ ................................ .............. A

- 11 4.2 APMT

- Impacts Modeling Assumptions

................................ ................................ ....... A

- 1 1 4.2.1 APMT

- Impacts

................................ ................................ ................................ A

- 12 4.3 AEDT Noise and Emissions Inputs

................................ ................................ .............. A

- 1 4 4.4 RESULTS

................................ ................................ ................................ ..................... A

- 19 4.4.1 APMT

- Impacts Physical Results

................................ ................................ ..... A

- 19 4.4.2 Cost

- Benefit Analysis

................................ ................................ ...................... A

- 23 4.4.2.1 Discount Rate Analysis

................................ ................................ ....... A

- 26 4.4.2.2 Lens Analysis

................................ ................................ ...................... A

- 29 4.4.2.3 Cost Sensitivity Analysis

................................ ................................ .... A

- 32 5 S UMMARY AND C ONCLUSIONS

................................ ................................ ................................ A

- 33 6 R EFERENCES

................................ ................................ ................................ ............................. A

- 3 4

L IST OF T ABLES

Table 1: APMT

- Impacts Effects Modeled

................................ ................................ ................................ A

- 5 Table 2: CAEP/9 Noise Stringency Options

................................ ................................ ........................... A

- 10 Table 3: Fleet Seat Class Designations

................................ ................................ ................................ ... A

- 10 Table 4: APMT

- Impacts Noise Assumptions for the CAEP/9 Noise Stringency Analysis

.................... A

- 13 Table 5: APMT

- Impacts Air Quality Assumptions for the CAEP/9 Noise Stringency Analysis

........... A

- 13 Table 6: APMT

- Impact s Climate Lens Assumptions for the CAEP/9 Noise Stringency Analysis

........ A

- 1 3 Table 7: APMT

- Impacts Policy

– Baseline Monetized Environmental Benefits

................................ ... A

- 2 6 Table 8: Noise Stringency Cost Benefit Summary, Midrange Lens, 3% Discount Rate

........................ A

- 2 6 CAEP/9

- I P/ 25 AppendixCAEP/9

- IP/ 25

Appendix A A

- 2

L IST OF F IGURES

Figure 1: Aviation Environmental Tool Suite Block Diagram

................................ ................................ . A

- 4 Figure 2: Timescales in Policy Analysis

................................ ................................ ................................ ... A

- 8 Figure 3: Noise Inputs: Baseline Noise Area Exposure

................................ ................................ .......... A

- 15 Figure 4: Noise Inputs: Area Exposure Stringency Cumulative Difference from Baseline

................... A

- 16 F igure 5: Air Quality Inputs; % Change in Fuel Burn Below 3000 feet

................................ ................. A

- 17 Figure 6: Air Quality Inputs; % Change in NO X emissions below 3000 ft.

................................ ............ A

- 1 7 Figure 7: Climate Inputs; % Change in Full Flight Fuel Burn

................................ ................................ A

- 1 8 Figure 8: Climate Inputs; % Change in Full Flight NO X Emissions

................................ ....................... A

- 19 Figure 9: Percent Change in Cumulative People (in People

- Years) Impacted by Noise

........................ A

- 20 Figure 10: Baseline Air Quality Yearly Mortalities b y PM Species, Midrange Lens

............................ A

- 21 Figure 11: Noise Stringencies

- Baseline Air Quality Yearl y Mortality Incidences, Midrange Lens

.... A

- 21 Figure 12: Yearly Baseline Climate Physical Impacts, Midrange Lens

................................ ................. A

- 22 Figure 13: Noise Stringency Yearly Climate Physical Impacts, Midrange Lens

................................ .... A

- 2 2 Figure 14: Noise Stringencies

- % Change in APMT Physical Met rics, Midrange Lens

....................... A

- 2 3 Figure 15: Noise Stringency 2 (

- 5 EPNdB) minus Baseline Impacts and Costs

................................ .... A

- 2 4 Figure 16: Noise Stringency 3 (

- 7 EPNdB) minus Baseline Impacts and Costs

................................ ..... A

- 2 4 Figure 17: Noise Stringencies CBA

................................ ................................ ................................ ........ A

- 2 5 Figure 18: Noise Stringency 2

- B aseline Environmental Impacts Discount Rate Sensitivity

............... A

- 2 7 Figure 1 9 : Noise Stringency 3

- Baseline Environmental Impacts Discount Rate Sensitivity

............... A

- 2 7 Figure 20 : Noise Stringencies

- Baseline CBA for Aligned Discount Rates

................................ .......... A

- 2 8 Figure 21 : Noise Stringency Cost Benefit

- Non

- Aligned Discount Rates

................................ ............ A

- 29 Figure 22: Noise Stringency 2

- Baseline Environmental Impacts Lens Sensitivity

.............................. A

- 29 Figure 2 3 : Noise Stringency 3

- Baseline Environmental Impacts Lens Sensitivity

.............................. A

- 3 0 Figure 24 : Noise St

ringencies

- Baseline Net Cost

- Benefit Lens Sensitivity, 3% Discount Rate

.......... A

- 3 0 Figure 2 5 : Noise Stringency

- Baseline Cost Benefit Illustrative Lens, 3% Discount Rate

................... A

- 3 1 Figure 26: Cost Sensitivity to Combined Recurring and Non

- Recurring Costs

................................ ..... A

- 32A

- 3 CAEP/9

- IP/ 25 Appendix A

1. INTRODUCTION

The International Civil Aviation Organization (ICAO) Committee on Aviation Environmental Protection (CAEP) traditionally addressed aircraft noise and emissions impacts independently of each other. Though advances have been made in quantifying collateral environmental consequences, ICAO CAEP decisions have been based on cost

- effectiveness metrics that consider the cost to implement a proposed stringency against the benefit in the targeted environmental parameter. While interdependent fuel burn consequences are accounted for as part direct operating costs, any possible inconsistency between noise and NOx consequences can only be noted under the current ICAO CAEP cost

- effectiveness analysis process. Thus, the current process notes, but does not value environmental trade

- offs.

The seventh meeting of the ICAO

- CAEP, held in 2007, considered the necessity for comprehensive analyses that assess the trade

- offs among noise and emissions impacts and economic costs to better inform policymaking decisions [1]. As part of the CAEP/8 NO X Stringency analysis, a demonstration of the perspective provided by a more complete accounting of societal costs and benefits across different impact spheres was demonstrated using the Aviation environmental Portfolio Manage ment Tool for Impacts (APMT

- I) [2][3].

1.1 Paper Overview

The objective of this paper is to report on the direct assessment of environmental impacts compared against economic costs, with explicit consideration of interdependencies and uncertainties among impacts for the noise stringency options under consideration for the ninth meeting of the ICAO

- CAEP (CAEP/9) on 4 to 15 February 2013.

This cost benefit analysis used the Aviation Environmental Portfolio Management Tool for Impacts (APMT

- Impacts), which is a component of the aviation environmental tool suite. The tool suite has been designed and developed by the Federal Aviation Administration (FAA) in collaboration with the National Aeronautics and Space Administration (NASA) and Transport Canada (TCCA). The main goal for developing these tools is to be able to characterize and quantify the interdependencies among aviation

related noise and emissions, impacts on health and welfare, and industry and consumer costs, under different policy, technology, opera tional, and market scenarios. In addition to providing environmental and economic impact estimates, this work also quantifies uncertainties throughout the policy analysis process and explores the sensitivity of results to variability in model inputs and pa rameters.

2. METHODS FOR ASSESSIN G TRADEOFFS AMONG ENVIRONMENTAL AND EC ONOMIC IMPACTS

This Section provides an overview of the models and methods used for the U.S. cost

- benefit analysis of CAEP/9 noise stringency options. 1

Figure 1 is a functional schematic of the portions of the Aviation Environmental Tools Suite as applied to the subject analysis. The main functional components of the Tools Suite applied in this analysis are summarized below. 2 Other combinations of tools suite resources have included the Emissions Prediction

1 Additional information on the APMT

- I tools and methods is available on

- line at http://web.mit.edu/aeroastro/partner/apmt/
2 Additional information is available at http://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/CAEP/9

- IP/ 25

Appendix A A

- 4

and Policy Analysis (EPPA) tool for aviation and the Environmental Design Space (EDS); however, they were not used in this CAEP/9 analysis.

Figure 1: Aviation Environmental Tool Suite Block Diagram

The Aviation Environmental Tools Su ite development was preceded by an extensive survey of guidance documents on recommended practices for environmental policy analysis including [4][5][6][7][8][9][10][11][12][13] and which were reviewed by the Transportation Research Board of the US Nationa l Academies [14]. The current tools were built on the foundations laid out by the initial survey of economic guidance documents and they continue to evolve to incorporate new knowledge, as well as expand modeling capabilities.

For the CAEP/9 analysis repo rted in this paper, the Aviation environmental Portfolio Management Tool (APMT) for Impacts (APMT

- I), APMT for Economics (APMT

- E) and the Aviation Environmental Design Tool (AEDT) were employed.

 APMT

- E models airline and aviation market responses to envir onmental policy options.

 AEDT models aircraft performance in four

- dimensional space and time to produce fuel burn, emissions and noise.

 APMT

- I estimates the environmental impacts of aircraft operations through changes in health and welfare endpoints for climate, air quality and noise.

The modular arrangement of the tools is integrated to enable comprehensive cost

- benefit and cost

effectiveness analyses. As per conventional economics terminology, monetary flows in the aviation industry are defined as cos ts and environmental impacts (e.g. health impacts or noise exposure) as benefits. Both costs and benefits can be positive or negative. The remainder of this section includes an overview of the modeling methodology adopted in APMT

- I.A

- 5 CAEP/9

- IP/ 25 Appendix A

2.1 APMT

– Impacts

The APMT

- Impacts modules assess the physical and socio

- economic environmental impacts of aviation using noise and emissions inventories as the primary aviation inputs. Socio

- economic data and projections as well as health and welfare damage valuation schemes, des cribed in the following sections, form the basis of code algorithm inputs. Impacts and associated uncertainties are simulated using Monte Carlo methods with probabilistic distributions of key variables that have scientific, epistemic, and mono

structural u ncertainty. APMT

- I is sub

- divided into three different environmental modules: Noise, Air Quality, and Climate. Table 1 lists the effects modeled under each impact area and key corresponding metrics.

Table 1: APMT

- Impacts Effects Modeled
Impact Type Effects Modeled Primary Impact Metrics Physical Monetary Noise Area exposure to noise, population exposure to

noise, housing value and rental loss Number of people effected Net present value

Air Quality Primary and secondary particulate matter (PM) Incidences of mortality and morbidity Net present value

Climate CO 2

Non

- CO 2 : NO X - O 3 , NO X - CH 4 , contrails, aviation

- induced cloudiness, sulfates, soot, H 2 O Globally

- averaged surface temperature change Net present value

Policy evaluation with APMT

- I provide s information on the environmental benefits and economic costs resulting from the implementation of a policy relative to a baseline scenario. In conveying this information to decision

- makers, the uncertainties in the quantified impacts and the key assumpti ons about inputs and model parameters are provided with the results.

The Monte Carlo methods used to assess the policy impacts relative to the baseline can be used to account for the reduced uncertainties in outputs. When there are many modeling uncertain ties common to both the policy and the baseline scenario, the difference between two scenarios can be predicted with less uncertainty than when considering the baseline impacts in isolation. Therefore, in estimating policy impacts, a paired sampling approa ch is used where the same random draws for model parameters are applied to both the baseline and the policy scenarios. The only difference between the two scenarios is driven by the effect of the policy, such as a change in the emissions inventory. 3

2.1.1 Noise Module

A summary of the behavioral and physiological impacts of aircraft noise exposure is given in He et al. [18]. Monetary impacts of noise exposure are commonly attributed to costs from noise

- related health effects, loss of work productivity, and depre ciation of property values around airports [19]. The APMT

Noise Module can estimate US and global impacts of aviation noise in terms of both physical and monetary metrics by relating noise exposure and city

- wide income levels to an expected loss in housing value. Physical metrics in the Noise Module include estimates of population exposure to a given noise level, area exposure to noise around an airport, and the number of people highly annoyed due to aircraft noise. The Noise Module then estimates monetary damages from housing value depreciation around airports, which is used as an incomplete proxy for the complex set of health and welfare impacts associated with aircraft noise. The current method is described by He et al. [18]. The cost

- benefit analysis

3 Additional information regarding code assessments and sensitivities are explored in references [15][16][17]CAEP/9

- IP/ 25

Appendix A A

- 6

of CAEP/9 noise stringency options included in this report was limited to consideration of only U.S. airports.

2.1.2 Air Quality Module

The Air Quality Module within APMT

- Impacts estimates the health impacts of primary particulate matter (primarily soot) and seco ndary particulate matter (aerosols formed from SO X , NO X , and gaseous hydrocarbon emissions) emissions from aircraft for the landing

- takeoff cycle. Ozone

- related health impacts are not considered here as they are estimated to be immaterial relative to PM

- related impacts (less than ± 10%) by studies within the APMT

- I development effort (e.g., [21]), analysis conducted in support of the Energy P olicy Act of 2005 study [22] [23], and external studies such as the Clean Air for Europe Baseline Analysis [24]. APMT

- I quantifies PM

- related health impacts in terms of incidences of premature adult mortality, infant mortality, chronic bronchitis, respira tory and cardiovascular hospital admissions, emergency room visits for asthma and minor restricted activity days (MRADs) and their associated costs. Rojo [21], Masek [25], Ashok [26] and Brunelle

- Yeung [27] provide detailed information on the modeling meth odology for the APMT

- I Air Quality Module (the most complete description of the methodology is described in Brunelle

- Yeung, while Ashok provides minor updates that reflect the latest module).

Limitations of the APMT

- I Air Quality module used in this analys is include a restricted scope of geographic coverage and consideration of health impacts from only landing and takeoff emissions. Future analysis may consider addressing changes in the background atmospheric concentration over time that have an impact on a viation‘s contribution to environmental damages, and make aviation emissions more significant over time [26][28]. In addition, the contribution of cruise emissions to surface air quality impacts may be of future interest, as recent work shows that aircraft cruise emissions may cause degradation of air quality over a hemispheric scale [29] [30].

2.1.3 Climate Module

The APMT

- Impacts Climate Module estimates the societal impact of aviation CO2 and non

- CO2 emissions for both physical and monetary metrics. The APMT

- I Climate Module adopts the impulse response modeling approach based on the work by Hasselmann et al. [31], Sausen et al. [32], Fuglestvedt et al. [33], and Shine et al. [34]. Total anthropogenic societal emissions are taken from prescribed background scenarios. The climate module determines the climate system response by superimposing or convoluting the time s eries of yearly impulse response curves onto the background emissions. The aviation impacts are calculated by taking the difference of total emissions and total emissions not including aviation. The temporal resolution of the APMT

- I Climate Module is one y ear while the spatial resolution is at the global mean level. The effects modeled include long

- lived CO2, the intermediate

- lived impact of NO X on methane ( NO X - CH 4 ) and its associated primary mode interaction on ozone (NO X - O 3 long), and short

- lived effects including the direct impact of NO X on ozone ( NO X - O 3 short), the production of aviation induced cloudiness, sulfates, soot, and H 2 O. Long

- and intermediate

- lived radiative forcing impacts associated with yearly pulses of CO2 and NO X emissions decay accordin g to their e

- folding times or atmospheric lifetimes, while the RF from short

- lived effects including the warming NO X - O 3 short effect is assumed to last only during the year of emissions. A detailed description of the APMT

- I Climate Module can be found in [ 35][36][37][38], with the most up to date methodology provided by Wolfe [38].

Limitations of the APMT

- Impacts Climate Module include the use of a global spatial scale that does not capture regional variations in short

- lived aviation climate effects, the la ck of consideration of feedbacksA

- 7 CAEP/9

- IP/ 25 Appendix A

in the climate system that may enhance or mitigate the climate impacts associated with aviation emissions, and independent treatment of aviation effects that does not account for interactions among some of the different phy sical and chemical mechanisms. Further, climate impact estimation in APMT

- I (and the underlying MDG analyses) implicitly assumes that future operational changes involve no significant changes in flight routes.

3. COMMUNICATION OF RES ULTS

Given the complex na ture of APMT

- I with several inputs and model parameters that are influential in determining the results of any policy analysis, conveying all the critical policy

- relevant information in a clear, concise manner becomes a challenging task. An emphasis is pla ced on relaying three different kinds of information: quantified environmental and economic impacts, uncertainties in these impact estimates, and the inputs and model parameters that provided the results.

The assessment activities allow for a distillation of the large amounts of information accumulated through multiple Monte Carlo runs. For all components of APMT

- I, the assessment results indicate five or six inputs and model parameters to which the respective outputs are most sensitive. Based on this cond ensed information, a decision

- making framework was developed to enable an interactive application of APMT

I, where the user dictates the terms of analysis to be conducted depending on their preferences and perspectives. The selection of each of these influ ential parameters is described through a lens; Section 3.1 describes the lens concept in further detail.

A second issue of concern with the communication of results is the selection of a time

- frame over which the impacts of a proposed policy are evaluated. Given the different temporal characteristics of the various environmental impacts, not all the impacts from aviation activity are realized in an immediate time

- frame. CO2 impacts, for instance, tend to accrue over several centuries and that time

- span nee ds to be factored into the decision

- making process. Section 3.2 delves further into the selection of timescales for policy analysis.

3.1 Decision

- Making Framework

– Lenses

There are about five to six parameters for each APMT

- I module that are most influential in determining the magnitude of the estimated impacts and associated uncertainties. These influential parameters are derived from global sensitivity analyses, and the parameters and their associated values for this analysis are presented in Section 4.2.1. Impacts can be represented in physical or monetary terms, with the computation of monetary metrics introducing additional influential parameters relative to the important parameters for the evaluation of physical effects. Thousands of unique combinations of inputs and model parameters that may be of interest in assessing different policy options are possible.

In order to extract meaningful insights about the possible costs and benefits of a policy, it is therefore expedient for the analysis options to be s ynthesized into a set of pre

- defined combinations of inputs and assumptions. These combinations of inputs and model parameters can be thought of as describing a particular point of view or perspective, and are thus designated as lenses. Some example lenses include a lens with mid

- range environmental and economic impacts; one with worst

- case environmental impacts and mid

- range economic impacts; one focused on short or long

- term environmental impacts; or one that adopts a conservative perspective for one impa ct while keeping a mid

- range perspective on others. When chosen wisely and viewed as a whole, the lenses can be seen as representing the range of scientificCAEP/9

- IP/ 25

Appendix A A

- 8

perspectives of the relevant environmental impact domains. Section 4 demonstrates how the lens form ulation can be used to illustrate scientific perspectives across the uncertainty domain in the CAEP/9 Noise Stringency analysis.

3.2 Timescales

Defining timescales over which the policy analysis is conducted and over which the costs and benefits are accrued is an important issue in the communication of results. Selection of the analysis timescale can significantly alter the conclusions drawn about the efficacy of a proposed policy measure and therefore warrants a brief discussion here. There are two timescales embedded in a policy analysis. The first timescale is the policy influence time period, which is the duration over which a policy is assumed to significantly influence aviation activity. The second timescale is the time period over which the impacts of the different environmental effects attributed to the activity persist. As illustrated in Figure 2, in order to evaluate a proposed policy meas ure relative to a baseline scenario, aviation activity is modeled for the duration of the assumed policy influence time period (typically 20

- 30 years in ICAO

- CAEP practice).

Figure 2: Timescales in Policy Analysis

The time period over which the impacts o f the policy are felt on the environment is typically longer. For example, climate change impacts related to changes in aviation activity will persist for centuries. Thus, the environmental impacts are modeled for hundreds of years beyond the assumed polic y impact period. It is important to designate a time

- window across which the benefits are measured. The choice of time horizon can be influential in determining the expected benefit from a technological or operational change, especially when the emissions of shorter

- lived species (such as impacts from NO X ) are disproportionately impacted compared to CO2 [41].

Distinctions between the timescales become important when one wishes to aggregate economic costs and environmental benefits resulting from a proposed policy measure relative to a baseline scenario. The time period over which the costs and benefits are accrued may change the balance between costs and benefits making a policy seem more or less desirable, especially when one considers different discount r ates that weight the value of long and short term benefits and costs differently. For the policy analysis presented inA

- 9 CAEP/9

- IP/ 25 Appendix A

Section 6 costs and benefits aggregated over the full environmental impacts time period are compared, which extends well beyond the polic y influence period. The policy influence time period is typically chosen to be 30 years which is consistent with the ICAO

- CAEP forecasting and analysis practice for assessing policy measures, and approximately the same as the time

- scale for the development , adoption, and significant use of new technology in the fleet.

4. NOISE STRINGENCY POL ICY ANALYSIS

On an international level, aircraft certification noise limits have been the primary tool to reduce the impact of aviation noise. In 1971, ICAO published Anne x 16: Environmental Protection, Volume I: International Noise Standards, which has subsequently been updated to reflect newer aircraft technologies. International aircraft noise limits were last set in 2001 as part of the CAEP/5 cycle. As part of CAEP/7, a formal review of noise certification limits was initiated to be presented at CAEP/8. Subsequently, proposed stringency options were developed for consideration at CAEP/9. A first round of noise stringency analysis was conducted and presented to CAEP/9 SG 2 in September 2011, which highlighted a number of areas of concern and led to Steering Group agreement for additional work. To accomplish the work, members agreed to establish a Noise Stringency Ad Hoc Group (NoSAHG) with representation from WG1, WG3, MDG and FESG. The work of that group led to consensus refinements to the assumptions that formed the basis of the second round of noise stringency modeling [42].

4.1 CAEP/9 Noise Stringency Options

At the Steering Group in June 2009, a future work item on a new n oise Standard for subsonic jet and heavy propeller

- driven airplanes was discussed. Working Group 1 (WG1) suggested the following more precise wording: ―Review and analyze certification noise levels for subsonic jet and heavy propeller

driven airplanes and , based on the analysis, develop stringency scenarios for impact analysis considering open rotor technology.

It was stressed that an analysis be undertaken that would enable CAEP/9 to decide whether a more stringent noise standard is technically feasible, economically reasonable and environmentally beneficial. WG1 was tasked under Task N.06.01 to review and analyze certification noise levels for subsonic jet and heavy propeller

- driven airplanes and to develop a range of stringency options up to 10

- 12 dB cum ulative margin relative to Chapter 4 standards. A first round of noise stringency analysis was conducted and presented to CAEP/9 SG2 in September 2011. This work led to significant refinements of assumptions for the fleet evolution process, and a second ro und of analysis was performed.

Based on this, WG1 recommended a range of noise stringency options for consideration by CAEP/9, which were approved at the first meeting of the CAEP Steering Group in November 2010. The five noise stringency scenarios under consideration are:

- 3,

- 5,

- 7,

- 9 and

- 11 cumulative EPNdB reduction relative to Chapter 4 noise limits. Each scenario, as well as a baseline Business

- As

- Usual scenario, was analyzed until 2036, with a single stringency implementation year of 2020 [43].CAEP/9

- IP/ 25

Appendix A A

- 10

Table 2 : CAEP/9 Noise Stringenc y Options

Scenario Name Stringency Baseline Chapter 4 Noise Limits Stringency 1 (S01)

- 3 EPNdB Stringency 2 (S02)

- 5 EPNdB Stringency 3 (S03)

- 7 EPNdB Stringency 4 (S04)

- 9 EPNdB Stringency 5 (S05)

- 11 EPNdB

Since their inception, the ICAO Annex 16 noise limits have incorporated  ̳flat portions‘, such that below maximum take

- off weights (MTOW) of between 20.2 and 48.1 tonnes and above weights of 280 or 400 tonnes the noise constraint limit is constant. The basic shape of these limits have remained con stant over the two stringency increases since they were established by the ICAO Committee on Aircraft Noise (CAN) and reported in their fifth meeting in 1976. WG1 formed a Flat Portion ad

- hoc group to study the current relevance of low MTOW stringency nois e limits. While this significant effort resulted in two proposals, no proposal for consideration achieved consensus within WG1. Thus, no change to the shape of low MTOW stringency noise limits is considered here [44].

4.1.1 FESG Fleet and Traffic Forecast

The Growth and Replacement (G&R) database was populated with information from WG1/WG3 (including linking noise and emissions data) and FESG (seat configuration); and, then formed the basis of available aircraft used for developing the future fleets. MDG de veloped a noise stringency options spreadsheet, as a subset to the G&R, which identified the aircraft/engine combinations that were consistent with each of the five stringency scenarios analysed. This spreadsheet also took into account a 1 dB supplemental condition. For this noise stringency assessment, the G&R database contained a number of project aircraft. Project aircraft are defined as aircraft models that have been designed and tested sufficiently to provide noise and emissions estimates but have not yet entered production (e.g. A350). Project aircraft were modelled using operation characteristics from the most representative in

- production aircraft in the G&R database as baseline estimates and then adjusting these estimates based on expert input from W G1 and WG3 [44]. Aircraft were split into ―Fleet Seat Class‖ assignments, designated by aircraft seat capacity, and fleet replacements were modelled as being consistent across seat classes. Seat class designations are shown in Table 3.

Table 3: Fleet Seat Class Designations

Seat Class Designation SC1 SC2 SC3 SC4 SC5 SC6 SC7 SC8 SC9 SC19

Seat Range 20

– 50 51

– 100 101

– 150 151

– 210 211

– 300 301

– 400 401

– 500 501

– 600 601

– 650 < 20

In accordance with FESG analysis recommendations, the following forecast assumptions were used: (1) CAEP/8 central (traffic and fleet) forecast for passenger services; (2) the CAEP/8 low

- growth scenario forecast for cargo services (i.e. freighter traffic and fleet); and (3) the CAEP/8 business jet forecast for aircraft with less than 20 seats [45][46]. Specific attention was given to conserving projected seat demand provided by the FESG CAEP/8 forecasts. This assumption required adjusting the number of ope rations flown when quieter aircraft replaced non

- compliant aircraft with a different capacity. Per consensus reached through the NoSAHG, the former equal market share approach was replaced with an APMT

-A

- 11 CAEP/9

- IP/ 25 Appendix A

Economics computed market

- driven cost

- based modeling a pproach. Model sensitivity to this assumption was explored in APMT

- Economics. With FESG and MDG agreement, this revised market share approach was modified for Commonwealth of Independent States CIS aircraft, those aircraft built by the Russian Federation o r the Ukraine, operating in certain countries, as had been done for the equal market share approach [47]. Furthermore, market share assumptions were shown to poorly represent expected trends in business jet projections. Thus, SC19 was stratified into four different groups based on weight

- class.

4.1.2 Emissions Modeling

Modeled emissions are divided into terminal area emissions for air quality and greenhouse gas or full mission greenhouse gas emissions for climate change. AEDT provides both AQ and full mission emissions [49] [50]. AEDT models aircraft emissions including carbon dioxide (CO2), water (H2O), sulfur oxides (SO2), nitrogen oxides ( NO X ), non

- volatile particulate matter (PMNV), total fuel organics (PMFO), and total sulfur organics (PMSO) for LTO segments below 3000 ft. In addition, it provides NO X , CO2, H2O, and SO X emi ssions for all flight segments. AQ emissions are modeled using ICAO times

- in

- mode for the taxi, takeoff, climb

- out, and approach flight segments below 3000 feet. Full

- flight emissions and aircraft noise data are provided on a global basis, however due to c urrent modeling limitations in the air quality domain, only US results are utilized in the Cost

- Benefit analysis. Details on the modeling methodology are provided in the AEDT Technical Manual [50].

4.1.3 Cost of Stringency Options

Recurring costs are calculated by APMT

- Economics and broken into three functional cost categories: fuel costs, capital costs, and other direct operating costs.

All stringency options have been tested for an assumed implementation year of 2020 using the c ore set of assumption values draw ing from those used by FESG [39], specifically:

 fuel prices of $3 per U.S. gallon from 2020 to 2036

 Range of Aviation Noise Design Effects Study (ANDES) Fuel Use Impacts. Two variants are noted in the response curves defined by CAEP Working Group 1 and the high fuel impact case has been used in the tests presented in this report.

 No pass through of increased costs relative to the Baseline, to fares in the Stringency cases and hence no demand and seat demand changes between Baseline and Stringency cases.

 Mar ket

- driven (relative cost) market shares between aircraft types.

Non

- recurring costs are included in a cost sensitivity analysis in Section 4.4.2.3

.

4.2 APMT

- Impacts Modeling Assumptions

The APMT

- I noise stringency analysis presented is limited to US

- related impacts in order to align with the geographic scope of the APMT

- I air quality model and to ensure that the economic costs and environmental benefits are compared in a consistent manner. There are several key sources of uncertainty involved in conducting an analysis of the CAEP/9 Noise Stringency options.

a. Uncertainties from APMT

- Impacts model inputs. Aleatoric uncertainty from natural variability and cycles in the airline industry will constrain the accuracy of future aviation growth scenarios.CAEP/9

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Appendix A A

- 12

Epistemic and aleatoric uncertainty from emissions and operational impacts of technology response both exist and can impact how different stringency options relate to expected environmental benefits. Finally, monostrucutural from how emissions and noise pr ojections are mapped to APMT

- Inputs can have an impact on final societal costs. While many of these uncertainties can be explored through the modeling process, the effectiveness of this exploration is limited by data availability from the CAEP analysis.

b. Un certainties from APMT

- Impacts model outputs. Environmental impacts models must contend with scientific, economic, and modeling uncertainty across the entire operations

- impact pathway. These uncertainties for each of the APMT

- Impacts modules are discussed i n detail in [27][16][37][15]. The APMT

- Impacts Air Quality and the APMT

- Impacts Climate modules, which include simplified representations of more complex computationally

- intensive models, are both limited by the structural appropriateness of the underlying complex model and the simplification technique.

c. System

- level sensitivity and uncertainty. Together the models that produce the inputs to the APMT Cost

- Benefit Analysis and those models that produce the outputs form a complex system. Interactions across th e system can propagate uncertainties. System

- level assessment is an on

going subject of research [51].

As described in Section 3.1, the lens concept allows analysts and decision

- makers to view the impacts of
a cost

- benefit analysis across a range of persp ectives where there exists significant uncertainty. The following sections describe the lenses selected for conducting a cost

- benefit analysis of the proposed noise stringencies using the APMT model. The only parameter not grouped in the lens assumptions w as the discount rate. This was done so that the full range of discount rates could be applied to each result regardless of the lens selected for analysis. Further, while the probabilistic parameters modeled in the APMT

- Impacts modules reflect the range of scientific, economic, and modeling uncertainty, choice of discount rate can be seen as a choice of policy

- maker preference.

4.2.1 APMT

- Impacts

Table 4, Table 5, and Table 6 show the lens assumptions for the APMT

- I Noise, Air Quality, and Climate Modules respect ively. APMT

- I noise and air quality impacts are modeled over the 30

- year period from 2006 to 2036. APMT

- I climate impacts are modeled over an approximately full time horizon lasting for 800 years following the 30

- year aviation activity period to capture i mpacts from long

- lived effects such as CO2. Impacts are expressed in both physical and monetary metrics. Further, discounting effectively reduces the period of significant climate monetary impacts to a few hundred years for low and moderate discount rates (2%

- 5%) and to a few decades at high discount rates (7%

- 9%). For all lenses, zero population growth and income growth were assumed, in accordance with the CAEP practices for policy analysis.A

- 13 CAEP/9

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Table 4: APMT

- Impacts Noise Assumptions for the CAEP/9 Noise S tringency Analysis

Noise Assumptions Low Lens Midrange Lens High Lens
Income Coefficient 0.0013 Mean = 0.0143 SD = 0.0079 0.0272 Income Interaction Term 0.0154 Mean = 0.0170 SD = 0.0094 0.0154 Income Intercept

- 30.3440 Mean =

- 37.5292 SD = 207.8134

- 30.0440 Background noise level 55 dB Triangular distribution (mode = 52.5, range = 50

- 55) dB 50 dB Income growth rate 0 0 0 Significance level 65 dB 52.5 dB 52.5 dB Contour uncertainty

- 2 dB Triangular distribution (mode = 0, range =

- 2

– 2) dB 2 dB Population growth rate No growth No Growth No Growth

Table 5: APMT

- Impacts Air Quality Assumptions for the CAEP/9 Noise Stringency Analysis

Air Quality Assumptions Low Lens Mid Lens High Lens Population Growth No growth No growth No growth Emissions Indices a. Fuel burn b. SOx (FSC) c. NOx d. Non

- Volatile PM a. 0.92 b. 0.0066 (5 th percentile) c. 0.83 d. 0.52 a. Uniform [0.92 1.12]

b. Weibull [mean = 0.0627, std = 1.2683] c. Uniform [0.83 1.23] d. Uniform [0.52 2/06] a. 1.12 b. 0.154 (95 th percentile) c. 1.23 d. 2.06 Adult Premature Mortality CRF (% per μg/m 3 PM 2.5 0.6 Triangular distribution (mode = 1, range = 0.6

– 1.7) 1.7

Value of a Statistical Life (VSL) $6.3 Million $6.3 Million $6.3 Million Background Emissions NEI 2001 NEI 2001 NEI 1001 Post

- Processing SMAT SMAT SMAT

Table 6: APMT

- Impacts Climate Lens Assumptions for the CAEP/9 Noise Stringency Analysis

Climate Assumptions Low Lens Midrange Lens High Lens Climate sensitivity 2K Triangular (2, 3, 4.5) K 4.5K NO X related effects Stevenson et al. (2004) Discrete Uniform distribution: Wild,

Stevenson, Hoor (2009) Wild et al. (2001)

Short

- lived effects radiative forcing [AIC, sulfates, soot, H 2 O, contrails] [11

- 29.3 0.56, 0.39, 5.4] mW/m 2 Triangular:

[(11, 33, 87), (

- 29.3,

- 4.8, 0.79), (0.56, 3.4, 20.7), (0.39, 2.8, 20.3), (5.4, 11.8, 25.6)] mW/m 2 [87,

- 0.79, 20.7, 20.3, 25.6] mW/m 2

Background Scenario SRES A2 SRES B2 SRES A1B Damage Coefficient 5 th percentile of DICE DICE 2007 Normal Distribution 95 th percentile of DICE Mixed layer heat capacity 2.52*10 8 J/(K*m 2 ) Triangular: [2.53, 4.41, 6.31] *10 8 J/(K*m 2 ) 6.31*10 8 J/(K*m 2 )

Deep ocean heat capacity 2.52*10 10 J/(K*m 2 ) Triangular: [6.39, 1.26, 25.2]*10 9 J/(K*m 2 ) 6.3*10 9 J/(K*m 2 )

Mixing Depth 500 m Triangular: [500, 1000 , 2000] m 2000 m

APMT

- Impacts models aim to represent the current state of scientific and modeling consensus. However, the models have some assumptions that may be considered conservative. An additional illustrative lens was include d to capture known under

- representations in the current modeling assumptions. For this illustrative lens, the midrange lens parameterizations formed the basis against which first orderCAEP/9

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Appendix A A

- 14

approximation factors were applied to capture underrepresentation from conservative assumptions. This work updates the simplified additional lens explored in the CAEP/8 NO X Stringency analysis [2].

The additional illustrative lens is meant to address the following three areas of importance in air quality for this analysis: th e impact of cruise emissions, the impact of changing background concentrations over time, and the impact of modeling scale and resolution.

As noted previously, the current APMT

- I Air Quality methodology accounts for only the effects LTO emissions up to 30 00 ft. While this is consistent with other aviation air quality modeling tools and impact studies, there is growing evidence that aircraft cruise emissions contribute significantly to air quality impacts [29] [30].

In addition, while emissions from the av iation sector are expected to grow over time, emissions that impact air quality from other sectors are not expected to follow the same trend. Woody et al. [28] estimate the impact of aviation emissions against projections of changing future background scen arios taken from the IPCC and with reference to domestic air quality control and mitigation strategies. Studies by Ashok [26] also indicate that the APMT

- I Air Quality methodology currently under

- represents impacts.

Finally, the choice of model and resolution can have an impact on estimates of societal damage from aviation

- attributable particulate matter. The APMT

- I Air Quality module models air quality impacts on a 36km x 36km grid with a domain that covers the continental United States. This resolu tion may not capture the severity of air quality impacts at locations very near to the airport, where particulate matter concentrations are higher. Findings by Barrett et al [29] and Lee [52] infer that impacts from LTO emissions as quantified by APMT

- I ma y be underestimated.

For these reasons, the additional illustrative lens applies a linear multiplier on Baseline and Policy physical impacts that starts at 1 for the baseline year (2006) and grows to 1.6 in (2036). A factor of 1.1 is used on Policy

- Basel ine LTO monetized environmental benefits to account for near

- airport impacts not accounted for due to model resolution. Finally, a multiplier of 1.7 is used on Policy

- Baseline LTO monetized environmental benefits to account for US cruise emissions on globa l mortalities for Stringencies 1 through 4, consistent with results from Koo [30]. For Stringency 5, the expected impact of full flight emissions is of the opposite sign of the expected impact from the LTO emissions. To account for this, a correction fact or (CF) scaling the ratio of global mortalities to global fuel burn from Koo [30] is used according to the equation:

where LTO represents US LTO fuel burn and LTO_bar represents US total fuel burn less LTO fuel burn.

4.3 AEDT Noise and Emissions Inputs

AEDT noise inputs for this analysis are area impacted by noise contours around 99 US airports expressed in terms of the average day

- night noise level from 55dB to 75+ dB. These US airports are a part of 185 AEDT Shell

- 1 airports worldwide that account for 91% of total global noise exposure (102 of the Shell

- 1A

- 15 CAEP/9

- IP/ 25 Appendix A

airports are located in North America). Figure 3 shows the change in total area exposure to aircraft noise across the range of noise impact levels from 2006

- 2036 for the unconstrained baseline case.

Figure 3: Noise Inputs: Baseline Noise Area Exposure

Projections in 2026 and 2036 of area exposure to noise for the unconstrained baseline case remain roughly consistent with previous estimates provided by AEDT [37][16]. However, modeling of the area
exp osure to noise in the datum year is significantly different from previous estimates, with total US exposure being increased by 21%. This change leads to an unexpected and unexplained trend of improved areal exposure to noise until 2026 even absent policy m easures. With expanding operations, area exposure is expected to grow from 2026 through 2036.

Figure 4 shows decline in area exposure for the range of stringency options relative to the baseline case summed over the 30 years of the scenario. While the shor t term decrease in exposure followed by a long term increase trend is seen across all 5 stringencies, Stringency 4 and Stringency 5 (a

- 9 EPNdB and

- 11 EPNdB reduction from Chapter 4 limits respectively) both have a total area exposure to noise reduction i n 2036 relative to 2006. While percentage decrease in cumulative area exposure is greater for increasing noise contour level, absolute reductions in area exposure are largest at the 55 dB DNL level and range from 273 mi2 reduction for Stringency 1 to 2711 mi2 reduction for Stringency 5. For this analysis, AEDT also provided estimates of population impacted by noise at each airport at each noise level using US Census population estimates at the Census Block Group level and 200m x 200m resolution.CAEP/9

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Appendix A A

- 16

Figure 4: Noise Inputs: Area Exposure Stringency Cumulative Difference from Baseline

AEDT inputs to the APMT

- Impacts Air Quality Module include fuel burn, emissions of NO X , SO X and

non

- volatile PM below 3000 feet for the landing and takeoff flight segments. Some sp ecies, such as SO X emissions scale directly with fuel burn with an assumed emissions index (EI) of 1.2 g/kg

- fuel based on a fuel sulfur content of 600ppm. While the relationship between SO X emissions to fuel burn is well understood, there remains some unce rtainty about the exact EI ratio with the AEDT default EI of 1.16, AEDT guidance for use recommendations of 1.1762 [53], and upper

- bound estimates of 1.2. Here, the upper bound of this limit was conservatively used as the median EI to capture all potential impacts from SO X emissions, and uncertainty is capture by a probabilistic multiplier in the APMT

- Impacts Air Quality model. This assumption is consistent with the AEDT guidance for use recommendations. Here, 100% conversion of fuel sulfur to SO2 is conser vatively assumed with no emissions as SVI. This assumption leads to an approximately 1% increase in total damages over the typical AEDT guidance for use recommendation. Figure 5 and Figure 6 show the percent change in fuel burn and NO X across the different noise stringencies relative to the unconstrained baseline.

Figure 5 shows the relationship between the noise stringency options and LTO fuel burn. Stringencies 1

- 3 all have moderate fuel burn improvements across the lifetime of the policy. However, Strin gency 4 shows a significant increase in LTO fuel burn while Stringency 5 shows a moderate increase in fuel burn. From Stringency 3 to Stringency 4, the number of compliant aircraft in higher fleet seat classes 4 and 6 become significantly reduced with the limited number of compliant aircraft having lower seat capacities. Therefore, to maintain FESG seat demands, operations must be increased at these seat classes by upwards of 7%. While Stringency 5 is also impacted by this increase in operations, at

- 11 EPN dB, a fuel inefficient aircraft in seat class 5 also becomes noncompliant. This is the reason for the moderate fuel burn benefit relative to Stringency 4, although it still leads to an increase over the unconstrained case. The resolution limit in distingui shing among policies by AEDT has been estimated to be less than 0.05% of fuel burn [54]. Only Stringency 1 falls within the estimated AEDT resolution limits throughout the lifetime of the policy. No stringency falls outside of the terminal area fuel burn u ncertainty estimation.A

- 17 CAEP/9

- IP/ 25 Appendix A

Figure 5: Air Quality Inputs; % Change in Fuel Burn Below 3000 feet

Figure 6 shows that all stringency options lead to a reduction in LTO NO X emissions relative to the baseline. While the increased fuel burn effect at Stringency 4 occurs due to the expected increase in number of operations, the impact is not significant enough to offset engine technology improvements in NO X reductions. Stringen cy 5 has the greatest reduction in expected LTO NO X emissions followed by Stringency 3.

Figure 6: Air Quality Inputs; % Change in NO X emissions below 3000 ft.

Inputs for the APMT

- Impacts Climate Module include fuel burn, CO2, and NO X emissions. CO2 emiss ions scale directly with fuel burn with an EI of 3155g/kg

- fuel and are not presented here. Figure 7 and Figure 8 show the percent changes in full flight fuel burn and NO X emissions across the range of noise stringencies relative to the baseline. AEDT resul ts for full flight emissions are provided for NorthCAEP/9

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Appendix A A

- 18

America, and US emissions have been scaled from these results assuming that US operations account for 93% of North American operations. These data also exhibit an expected resolution of limit 0.05% for di stinguishing changes between policy and baseline cases. This resolution limit is considered by applying an uncertainty multiplier to the input inventories in the APMT

- Impacts module.

Figure 7 shows that Stringency 1 has an expected fuel burn detriment for full mission flights in 2026, but it provides a minor benefit by 2036. However, Stringency 1 is always within the AEDT data resolution limits. Stringencies 2 and 3 show increasing fuel burn benefit with increasing Stringency, while Stringency 4 once again displays the increased fuel burn effect from increased operations described in the Air Quality input data. The benefit from seat class 5 engine efficiency in Stringency 5 results in Stringency 5 overcoming the effect seen in Stringency 4 to result in a fue l burn benefit relative to the baseline. Stringency 3 remains the most beneficial to fuel burn reduction across the lifetime of the policy. Figure 8 indicates that full flight NO X reductions follow the same trend as LTO NO X emissions; however, the effect i n Stringency 4 produces a net negative impact in full

- flight NO X emissions.

Figure 7: Climate Inputs; % Change in Full Flight Fuel BurnA

- 19 CAEP/9

- IP/ 25 Appendix A

Figure 8: Climate Inputs; % Change in Full Flight NO X Emissions

For reference, the social cost of carbon values (calculated for the CO2 impacts only) for the low, mid, and high lenses, when averaged over the 30

- year policy period, were $13/tC, $61/tC, and $511/tC, respectively. These are consistent with the range of SCCs estimated by EPA and suggested by the Interag ency Working Group on Social Cost of Carbon [55][56].

4.4 Results

The goal of the policy analysis presented in this Section is to examine the environmental benefits and economic costs of the range of noise stringency options relative to the baseline no stringe ncy case. The analysis is conducted using Monte Carlo methods and the results represent the mean of several thousand Monte Carlo runs unless otherwise specified.

4.4.1 APMT

- Impacts Physical Results

The baseline results provided in this Section are for the mid

- ra nge lens model parameters. Physical impacts of noise in terms of number of people exposed to noise levels of 55dB DNL and higher are presented first.

Figure 9 shows the impact of different stringency options using a physical metrics: net cumulative people impacted by noise measured in person

- years. Cumulative metrics like those shown in Figure 9 are useful in that the earlier the change from the baseline occurs, the larger the final metric. Figure 9 shows a nonlinear trend in percent change of area impacted by noise as stringency level increases. Furthermore, while increasing stringency leads to increasing benefits at the 55 DNL level, higher stringency reductions have disproportionately large benefits at higher noise levels.CAEP/9

- IP/ 25

Appendix A A

- 20

Figure 9: Percent Change in Cu mulative People (in People

- Years) Impacted by Noise

Baseline air quality impacts expressed in terms of yearly incidences of premature mortality attributed to exposure to aircraft particulate matter emissions are shown in Figure 10 and Figure 11. Figure 10 shows premature mortality due to separate emissions species for the baseline case; incidences of premature mortality attributed to particulate matter constitute more than 95% of the total monetized air quality health impacts. These impacts are due to aircr aft emissions below 3000 feet and do not account for impacts of cruise PM emissions. Impacts are apportioned to the different aircraft emissions species contributing to changes in ambient particulate matter concentrations. Nitrates dominate the total impac ts with smaller contributions from sulfates, elemental carbon, particle bound water, and organics. Figure 11 shows the impact of stringency choice on expected aviation PM attributable mortalities throughout the modeled policy time horizon. Stringency 2 and Stringency 3 are shown to both be beneficial with respect to air quality physical impacts. Despite reductions to LTO NO X , both Stringency 4 and Stringency 5 produce significant air quality dis

- benefits.A

- 21 CAEP/9

- IP/ 25 Appendix A

Figure 10: Baseline Air Quality Yearly Mortalitie s by PM Species, Midrange Lens

Figure 11: Noise Stringencies

- Baseline Air Quality Yearly Mortality Incidences, Midrange Lens

Figure 12 presents baseline climate impacts in terms of changes in globally

- averaged surface temperature. For the first 30 year s, the time horizon over which the policy is modeled, the physical impacts are dominated by short

- lived species, particularly aviation

- induced cloudiness such as cirrus clouds and contrails. Longer

- lived aviation

- related climate impacts such as the warming CO2 effect and the cooling effects of NO X - CH 4 and NO X - O 3 - long continue well beyond year 2036, the last year for which aviation emissions are modeled. CO2 impacts are dominant by 2040 and contribute to over 98% of total impacts (warming and cooling) by 2075. Short

- lived effects including NO X - O 3 short, aviation

- induced cloudiness (AIC), sulfates, soot, and H2O decay to negligible impacts within 20 years after the 30

- year scenario. For noise and air quality impacts, the duration over which the selected pol icy influences the fleet mix (2006

-CAEP/9

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Appendix A A

- 22

2036 in this case) coincides with the time period over which the impacts persist. However, as seen in Figure 12, climate impacts persist for several centuries past the last of the scenario.

Figure 12: Yearly Baseline Climate Physical Impacts, Midrange Lens

Figure 13 shows the expected climate physical impacts for the different stringencies studied. The solid lines represent mean expected global temperature change and the shaded regions represent the 10th and 90th perce ntile ranges of results. The physical impacts follow the trends expected from the fuel burn input patterns with Stringencies 2, 3, and 5 showing climate benefits during the second quarter of the century and Stringency 4 showing a climate dis

- benefit during the same time. Stringency 1 shows little change in physical impacts from climate change reflecting its similar emissions profile to the baseline, while Stringency 3 shows the most significant benefit.

Figure 13: Noise Stringency Yearly Climate Physical Impacts, Midrange LensA

- 23 CAEP/9

- IP/ 25 Appendix A

Results presented in this section indicate that growth in operations will lead to increasing environmental impacts in the future in the absence of new environmental policies. Absent increased stringency, physical noise impacts follow an unexpected trend, however it remains unclear whether the first 20 years of this trend reflect expectations or are a result of datum modeling assumptions. It can also be seen that different stringency levels lead to different environmental impacts. Impl ementation of the noise stringency leads to significant decreases in areas impacted by noise commensurate with the level of the stringency increase. On a percentage basis, these benefits increase nonlinearly with increasing noise level. This nonlinearity i s important as it suggests that showing only area or populations impacted by noise levels from 55

- 65 dB DNL, a practice common in CAEP [42], may under

- represent environmental benefits. Stringency 4 results in both an air quality and a climate dis

- benefit f rom an increase in flight operations of Seat Classes 4 and 6. Stringency 5 incurs an air quality dis

- benefit, primarily from the same increase in operations seen in Stringency 4, but has a resulting climate benefit from a switch to more efficient aircraft in Seat Class 5. The next section presents an aggregated cost

- benefit analysis comparing the monetized environmental benefits and the economic costs of the stringency options relative to the baseline case using monetization methods described in Section 2.

4.4.2 Cost

- Benefit Analysis

The results in this section present a comparison of costs and benefits across the environmental and economic domains. Results are presented here using the midrange lenses as described in Section 4.2.1 and monetary impacts are calculat ed using a 3% discount rate unless otherwise noted. Figure 14 shows the impacts of the five stringency levels on physical metrics across all environmental domains. Noise impacts are measured cumulative people impacted at the 55dB level and higher, air qual ity is measured in total mortalities, and climate is measured in integrated temperature change out to a 100 year time horizon. The physical metrics show that all policies have a larger impact on noise impacts than other environmental effects, and that thes e impacts increase disproportionately with increasing stringency. Lower stringency levels have small but significant emissions co

- benefits from an increased proportion of efficient aircraft in the fleet. While the noise benefits from Stringency 3 to String ency 4 more than double, there is a reverse in the emissions trend for both air quality and climate.

Figure 14: Noise Stringencies

- % Change in APMT Physical Metrics, Midrange LensCAEP/9

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Appendix A A

- 24

However, it is important to examine impacts on a monetized scale as the societal cost of an impact can be highly non

- linear and because environmental impacts have different baseline expected costs. Example of monetized environmental impacts along with industry impacts is shown in Figure 15 and Figure 16. The results in Figure 15 represent the difference between Stringency 2 and the baseline business

- as

- usual case while Figure 16 represents the difference between Stringency 3. The net impact for monetized results is calculated by summing the three environmental impacts: noise, a ir quality, and climate, and the FESG economic impacts (where 27% of the total recurring costs was estimated to be the US operations costs based on previous analyses conducted with APMT

- Economics). For these examples, only the midrange lens with 3% discoun t rate of both the environmental and recurring industry costs of one

- stringency is presented. The uncertainties in the environmental impacts are estimated through Monte Carlo methods. (Details on the treatment of uncertainties in the different APMT modules were presented in Section 5.) While all these impacts and associated uncertainties have common assumptions and are not entirely independent of each other, for a first order estimate it is assumed that they are statistically independent effects. All of the mean impacts are summed to get the net impact and all their variances are summed to get the variance. The height of the bars indicates the mean value and the error bars represent the 10th and 90th percentile values. Note that Figure 16 presents policy min us baseline results and therefore a positive change is considered detrimental while a negative change is beneficial.

Figure 15: Noise Stringency 2 (

- 5 EPNdB) minus Baseline Impacts and Costs (mid lens, 27% recurring costs, 3% costs discount rate, 3% environmental discount rate)

Figure 16: Noise Stringency 3 (

- 7 EPNdB) minus Baseline Impacts and Costs (mid lens, 27% recurring costs, 3% costs discount rate, 3% environmental discount rate)A

- 25 CAEP/9

- IP/ 25 Appendix A

The costs and benefits are summed for each of the proposed stri ngencies to demonstrate how total impacts and net costs are impacted by stringency level. First, results for environmental benefits at the midrange lens are presented with costs and benefits both monetized under a 3% discount rate, as shown in Figure17. Se ction 4.4.2.1 considers the impact of discount rate on net cost benefit while Section 4.4.2.2 explores net impacts across different environmental lenses.

Figure 17: Noise Stringencies CBA (mid lens, 27% recurring costs, 3% costs discount rate, 3% environ mental discount rate)

Figure 17 shows that moderate stringency increases (Stringencies 1 and 2) have a net benefit under the 3% discount rate for the midrange lens. Stringency 3 has a moderate net cost while Stringency 4 and Stringency 5 are dominated by r ecurring costs. Table 7 shows the environmental benefits for each environmental impact as well as the total monetized environmental impact by stringency for a midrange lens at 3% discount rate. Table 8 shows the environmental impacts and recurring costs le ading to the net cost or benefit of the stringency.

Table 7 indicates a total environmental benefit for all stringencies. Despite having a much smaller percent change in physical metrics relative to noise, climate impacts have the largest monetized benefit for Stringencies 2 and 3 due to the nonlinear relationship between temperature change and societal costs. The fuel burn increase effect from increased operations in Stringency 4 leads to a small air quality dis

- benefit and a moderate climate dis

- benefit, which are both offset by the noise benefit. Stringency 5, with dominating noise benefits, has the largest total environmental impact with a mean benefit of $1.3 Billion USD (in 2006 dollars) followed by Stringency 3.CAEP/9

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Appendix A A

- 26

Table 7: APMT

- Impacts Policy

– Baseli ne Monetized Environmental Benefits

APMT

- I Assumptions Stringency Noise (2006 US $Billion) Air Quality

(2006 US $Billion) Climate

(2006 US $Billion) Total Impact

(2006 US $Billion)

mean 10

- 90% mean 10

- 90% mean 10

- 90% mean 10

- 90%

Midrange Lens

3% Discount Rate S01

- 0.11 - 0.14

- 0.08 0.00 - 0.01

0.00 0.00 - 0.01

0.00 - 0.12 - 0.15

- 0.08

S02

- 0.19 - 0.25

- 0.14 - 0.05 - 0.07

- 0.02 - 0.34 - 0.57

- 0.14 - 0.58 - 0.90

- 0.30

S03

- 0.33 - 0.42

- 0.23 - 0.07 - 0.11

- 0.03 - 0.44 - 0.73

- 0.19 - 0.83 - 1.26

- 0.45

S04

- 0.79 - 1.02

- 0.56 0.06 0.01

0.13 0.27 0.12

0.45 - 0.46 - 0.89

0.02

S05

- 1.21 - 1.56

- 0.88 0.18 0.05

0.36 - 0.30 - 0.50

- 0.13 - 1.33 - 2.00

- 0.64

Table 8: Noise Stringency Cost Benefit Summary, Midrange Lens, 3% Discount Rate

APMT

- I Assumptions Stringency Total Impact (2006 US $Billion) Recurring Cost (2006 US $Billion) Net Cost Benefit (2006 US $Billion)

mean 10

- 90% mean mean 10

- 90%

Midrange Lens

3% Discount Rate S01

- 0.12 - 0.15

- 0.08 - 0.27

- 0.39 - 0.42

- 0.35

S02

- 0.58 - 0.90

- 0.30 - 1.89

- 2.47 - 2.79

- 2.19

S03

- 0.83 - 1.26

- 0.45 2.70 1.87 1.44 2.25

S04

- 0.46 - 0.89 0.02 8.64 8.18 7.75 8.66

S05

- 1.33 - 2.00

- 0.64 14.04 12.7 12.0 13.4

4.4.2.1 Discount Rate Analysis

The discount rate is the method by which future damages are monetized in comparison to current year costs. The discount rate accounts for the fact that individuals have a positive time preference, explained because people expect to be wealthier in the future, people are impatient, or from a combination of these two factors. Proponents of constant discoun ting of environmental costs cite the partial Pareto improvement criterion: if aggregate welfare is higher under one policy, then a compensation mechanism can be implemented to transfer benefits between parties [57]. Opponents of market discount rates cite intergenerational inequity due to the long lifetimes of environmental damages, high cost or infeasibility of benefit transfer, and the inability to account for irreversible events such as species extinction [58].

The costs and benefits for a range of discount rates are explored, in keeping with US and international best practice. Figure 18 and Figure 19 illustrate the effect of the discount rate across the environmental impacts for two sample stringencies analyzed for a midrange lens. Climate, which has the longest

- lived impacts, is most affected by discount rate with monetized impacts decreasing below those of noise at discount rates of 5% and higher. For Stringency 2, total mean environmental benefits range from $ 900 million USD(2006) to $100 million USD (2006) while for Stringency 3 environmental benefits range from $1.2 billion USD (2006) at 2% to just under $200 million USD (2006) at 9%.A

- 27 CAEP/9

- IP/ 25 Appendix A

Figure 18: Noise Stringency 2

- Baseline Environmental Impacts Discount R ate Sensitivity

Figure 19: Noise Stringency 3

- Baseline Environmental Impacts Discount Rate Sensitivity

First, the cost and benefit trends across a range of discount rates are examined where recurring costs and environmental benefits are computed with a ligned discounting assumptions. FESG costs were computed at 3%, 7% and 9% discount rates. Figure 20 shows that choice of discount rate does not impact the relative ranking of stringency options, and that Stringencies 1 and 2 remain cost beneficial at all t hree discount rates, while Stringencies 3, 4, and 5 all have net societal costs. However, choice of discount rate can have a large impact on the net cost as seen in the nearly 7 billion USD difference in net costs between a 3% and 7% discount rate on Strin gency 5.CAEP/9

- IP/ 25

Appendix A A

- 28

Figure 20: Noise Stringencies

- Baseline CBA for Aligned Discount Rates

Because of the long lifetime and potential irreversibility of environmental impacts, decisions in the present have the possibility of affecting future generations with no op portunity for benefit transfer. Thus, it has been argued that non

- environmental costs should be discounted with a social discount rate that aligns more closely with a market or private investment rate of return, while environmental costs should be discount ed with a lower discount rate [59]. In the United States, the OMB recommends discount rates of between 2.5% and 7% for regulatory analysis but allows for the use of a lower discount rate for intergenerational impacts [5]. In past ICAO

- CAEP analyses of cost s of environmental stringencies, discount rates of 9% and 13% have been used to discount future recurring costs [60], while environmental benefits have been estimated using discount rates of 2

- 5% [2]. The cost

- benefit analysis of proposed stringencies is e xamined where the environmental benefits are discounted under the 2%, 3%, and 5% discount rates, while costs are discounted under a 9% discount rate. Results are shown in Figure 21. With costs computed at a 9% discount rate, Stringency 3 becomes cost benef icial at 2% and 3% discount rates on environmental benefits. Stringency 4 and Stringency 5 maintain a net societal dis

- benefit for all discount rates.A

- 29 CAEP/9

- IP/ 25 Appendix A

Figure 21: Noise Stringency Cost Benefit

- Non

- Aligned Discount Rates

(recurring costs at 9% discount r ate, midrange lens)

4.4.2.2 Lens Analysis

The sensitivity analysis presented here focuses on variability in results depending on selection of inputs and model parameters explored using the lenses described in Section 4.2.1. The sensitivity to lenses is shown for t wo sample stringencies (Stringency 2 and Stringency 3) minus baseline at a 3% discount rate in Figure 22 and Figure 23. Monetized benefits from climate change are highly sensitive to lens assumptions. This sensitivity is explained by the asymmetric distrib ution on climate sensitivity and the squared relationship between temperature change and damages. Thus, while a midrange of scientific and economic expectation indicates moderate climate benefits from Stringency 3, there is a possibility that those benefit s could be significantly greater.

Figure 22: Noise Stringency 2

– Baseline Environmental Impacts Lens Sensitivity 3% Discount RateCAEP/9

- IP/ 25

Appendix A A

- 30

Figure 23: Noise Stringency 3

- Baseline Environmental Impacts Lens Sensitivity 3% Discount Rate

Figure 24 shows the sensitivity of cost

- benefit results to lens assumptions. Stringency 2 remains the most cost beneficial policy under all lenses with net benefits ranging from about $1 billion 2006 USD to about $7.5 billion USD. Stringency 3 is dominated by costs in the low and mid lenses, but becomes significantly cost beneficial under the high lens. Stringencies 4 and 5 maintain a net detriment across all lenses, but their relative order changes under the high lens where large climate benefits make Stringency 5 less detrim ental than Stringency 4.

Figure 24: Noise Stringencies

- Baseline Net Cost

- Benefit Lens Sensitivity, 3% Discount Rate

Because APMT

- I contains several conservative assumptions, as described in Section 4.2.1, an additional illustrative lens is used to exam ine the sensitivity of the results to those assumptions. Specifically, this lens considers the impact of modeling resolution, cruise emissions, and changing background on air quality and the impact of modeling domain on noise damages. Other conservative as sumptions, such as changes in population over the policy lifetime or the effect of noise and emissions on non

- market impacts such as public space enjoyment and visibility are not examined in this lens.A

- 31 CAEP/9

- IP/ 25 Appendix A

Figure 25 shows the sensitivity of the cost benefit an alysis to first order approximations to account for these conservative assumptions. As shown in the figure, the cost benefit results are not sensitive to these assumptions. For example, for Stringency 3 at a 3% discount rate the illustrative lens has an a ir quality benefit that is 2.9 times greater than that of the midrange lens. However, air quality accounts for less than 10% of total environmental impacts and less than 3% of the recurring costs. While accounting for these conservative assumptions may hav e compounding effects under high lens or lower discount rates, this sensitivity analysis shows that the net cost benefit result for CAEP/9 Noise Stringency is more sensitive to choice of discount rate or choice of traditional environmental lens than it is to conservative modeling assumptions.

Figure 25: Noise Stringency

- Baseline Cost Benefit Illustrative Lens, 3% Discount RateCAEP/9

- IP/ 25

Appendix A A

- 32

4.4.2.3 Cost Sensitivity Analysi s

The cost benefit analyses in Sections 4.4.2.1 and 4.4.2.3 consider only the recurring economic costs. This section examines a sensitivity test for combined recurring and non

- recurring (N

- R) costs on the net cost

benefit analysis. The scope of N

- R costs considered by FESG included various combinations of N

- R aircraft owner/operator costs and N

- R manufacturer costs with low and high estimates. This sensitivity study was conducted d ue to uncertainty associated with cost estimates. For this sensitivity study the mid

range environmental assumptions were used with 50%, 75%, and 100% of t otal costs to test how sensitive the cost

- benefit results are to cost assumptions. The results are shown in Figure 26. The analysis indicates that Stringency 4 and Stringency 5 are the most sensitive to cost assumptions, and that those stringencies have a strong net dis

- benefit for any consideration of costs. For all cost assumptions considered, Stringency 2 is the most cost

- beneficial stringency for midrange lens at 3% discount rate. Stringency 1 remains cost

- beneficial across the cost assumptions consider ed here, but benefits are small and emissions are within the estimated data resolution. Stringency 3 has a net cost for all cost sensitivity assumptions.

Figure 2 6 : Cost Sensitivity to Combined Recurring and Non

- Recurring Costs

Sections 4.4.2.1, 4.4.2.2, and 4.4.2.3 are designed to show the sensitivity of the results to various assumptions. As such, not all modeling assumption s , scientific uncertainty consideration s , and policy

maker preference combinations are explicitly shown in this paper

.A

- 33 CAEP/9

- IP/ 25 Appendix A

5. SUMMARY AN D CONCLUSIONS

This paper reports on the inclusion of environmental impact assessment and quantification of modeling uncertainties to enable a more comprehensive evaluation of CAEP/9 noise stringency options. The APMT

- Impacts modules were employed to conduc t the cost benefit analysis (CBA). This section offers a brief summary of the justification and methodology, concluding thoughts based on the work presented in this paper.

While modeling uncertainties grow as one proceeds down the impact pathway, decision

- making uncertainty decreases as one gains a better understanding of the ultimate impacts of the policy on a human health and welfare scale. This work used a CBA to inform the CAEP/9 decision

- making practices regarding aircraft noise stringency.

An applic ation of the lens framework was provided through the cost

- benefit analysis of the proposed CAEP/9 Noise stringencies. Several different lenses reflecting economic, scientific, and modeling uncertainties were presented. The environmental benefits and econo mic costs associated with the CAEP/9 noise stringency options were analyzed for the US domain from 2006 to 2036 with policy implementation in 2020. Operating costs were taken as economic costs and were calculated by APMT

- E. All stringency options lead to a noise benefit ranging from 0.5% to 5% improvement in the cumulative number of people impacted by noise over the next 30 years.

Stringency 1 (Chapter 4

- 3 EPNdB) is shown to be cost beneficial across all assumptions considered; however, the associated fue l burn emissions are within the resolution limits of the MDG models, indicating that environmental benefits are uncertain and not significant.

Stringency 2 (Chapter 4

- 5 EPNdB) is shown to be cost beneficial across all assumptions considered; provides glo bal reductions in noise, fuel burn and emissions; and, offers the largest reduction in direct operating costs relative to the no stringency case. Stringency 2 is the most cost beneficial option, irrespective of the combinations of assumptions considered.

Stringency 3 (Chapter 4

- 7 EPNdB) has environmental benefits greater than Stringency 2; however, the recurring costs are greater than the monetized environmental benefits across most assumptions considered. Only under a very limited set of assumptions 4 ( e.g., indicating a high level of impacts for noise, air quality and climate coupled with the highest values of statistical life) could Stringency 3 potentially become cost beneficial.

Stringency 4 (Chapter 4

- 9 EPNdB) includes an increase in fuel burn emis sions because the fleet shifts to smaller, compliant aircraft that require increased operations to maintain seat demand. Thus, while Stringency 4 has noise benefits, it also has air quality and climate dis

- benefits and is not consistent with the CAEP principles of environmental effectiveness, economic reasonableness, and consideration of interdependencies

. Stringency 5 (Chapter 4

- 11 EPNdB) continues the dis

- benefit trend in air quality from Stringency 4; however, the fleet shifts away from smaller ai rcraft, and demonstrates climate benefits. This stringency is even more inconsistent with CAE P principles.

4 See Tables 4, 5, and 6 respectively for the range of noise, air quality and climate assumptions

.CAEP/9

- IP/ 25

Appendix A A

- 34

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