The air quality impact of aviation in future-year emissions scenarios

The rapid growth of aviation is critical to the world and US economy, and it faces several important challenges among which lie the environmental impacts of aviation on noise, climate and air quality. The first objective of this thesis addresses the requirements of section 753 of the US Energy Policy Act, and entails the quantification of present and future-year regional air quality impacts of US Landing and Take-Off (LTO) aviation emissions. In addition, this thesis characterizes the sensitivity of these impacts to variations in the projection of non-aviation anthropogenic emissions (referred to as background emissions). Finally, the implication of a future-year background emissions scenario on the current policy analysis tool, the response surface model (RSMv2), is discussed. Aviation emissions for 2006 are generated using the Aviation Environmental Design Tool (AEDT), while future-year aviation emissions are developed for 2020 and 2030 using the Federal Aviation Administration (FAA) Terminal Area Forecast (TAF) and the International Civil Aviation Organization (ICAO) Committee on Aviation Environmental Protection (CAEP/8) NOx Stringency scenario #6. Background emissions for the year 2005 and 2025 are generated from the US Environmental Protection Agency (EPA) National Emissions Inventory (NEI), and two additional sensitivity scenarios are derived from the emissions forecasts. Uncertainties in present and forecast aviation and background emissions are also characterized. The Community Multiscale Air Quality (CMAQ) model is evaluated to quantify its performance in predicting ambient PM2.5 and ozone concentrations, and it is used to estimate aviation air quality impacts of aviation. Future-year aviation particulate matter (PM2.5) concentrations are found to increase by a factor of 2 and 2.4 by 2020 and 2030, and are dominated by nitrate and ammonium PM. Aviation 8-hour daily maximum ozone is seen to grow by a factor of 1.9 and 2.2 by 2020 and 2030, with non-homogeneous spatial impacts. Aviation PM2.5 varies by ±25% with a ±50% variation of the forecast change in background emissions, while changes in ozone impacts are less symmetric at +34%/-21%. The RSMv2 is shown to under-predict future-year aviation nitrate and ammonium PM2.5. Finally, the implications of these results on the aviation industry and on aviation policy are discussed. Thesis Supervisor: Ian A. Waitz Title: Dean of Engineering, Jerome C. Hunsaker Professor of Aeronautics and Astronautics

[1]  Alexis Zubrow,et al.  Overview of the atmospheric model evaluation tool (AMET) v1.1 for evaluating meteorological and air quality models , 2011, Environ. Model. Softw..

[2]  Global simulation of tropospheric O3-NOx-hydrocarbon chemistry: 1. Model formulation , 1998 .

[3]  Stephen Kuhn,et al.  Cost-benefit analysis of ultra-low sulfur jet fuel , 2011 .

[4]  Elza Brunelle-Yeung,et al.  The impacts of aviation emissions on human health through changes in air quality and UV irradiance , 2009 .

[5]  Robin L. Dennis,et al.  A multi-resolution assessment of the Community Multiscale Air Quality (CMAQ) model v4.7 wet deposition estimates for 2002–2006 , 2010 .

[6]  D. Byun,et al.  Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System , 2006 .

[7]  R. Sokhi,et al.  Air Quality Modeling , 2008 .

[8]  Mark Z. Jacobson,et al.  Analysis of emission data from global commercial aviation: 2004 and 2006 , 2010 .

[9]  Daniel J. Jacob,et al.  Introduction to Atmospheric Chemistry , 1999 .

[10]  Yun Fat Lam,et al.  A novel downscaling technique for the linkage of global and regional air quality modeling , 2009 .

[11]  Reinhold Busen,et al.  Influence of fuel sulfur on the composition of aircraft exhaust plumes: The experiments SULFUR 1–7 , 2002 .

[12]  Y. Lam,et al.  Corrigendum to “ A novel downscaling technique for the linkage of global and regional air quality modeling ” published in Atmos . Chem . Phys . , 9 , 9169 – 9185 , 2009 , 2022 .

[13]  Paul E. Yelvington,et al.  Speciation and chemical evolution of nitrogen oxides in aircraft exhaust near airports. , 2008, Environmental science & technology.

[14]  Shaocai Yu,et al.  A performance evaluation of the 2004 release of Models-3 CMAQ , 2006 .

[15]  Anuja Mahashabde,et al.  Assessing environmental benefits and economic costs of aviation environmental policy measures , 2009 .

[16]  S. Chu PM2.5 episodes as observed in the speciation trends network , 2004 .

[17]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[18]  D. Byun,et al.  Chapter 12 METEOROLOGY-CHEMISTRY INTERFACE PROCESSOR ( MCIP ) FOR MODELS-3 COMMUNITY MULTISCALE AIR QUALITY ( CMAQ ) MODELING SYSTEM , 1999 .

[19]  Ian A. Waitz Assessment of the effects of operational procedures and derated thrust on American Airlines B777 emissions from London's Heathrow and Gatwick airports , 2006 .

[20]  R. Dickinson,et al.  Couplings between changes in the climate system and biogeochemistry , 2007 .

[21]  Marc E.J. Stettler,et al.  Air quality and public health impacts of UK airports. Part I: Emissions , 2011 .

[22]  Gregg G Fleming,et al.  Methodology to Estimate Particulate Matter Emissions from Certified Commercial Aircraft Engines , 2009, Journal of the Air & Waste Management Association.

[23]  Robin L. Dennis,et al.  Observable indicators of the sensitivity of PM2.5 nitrate to emission reductions—Part I: Derivation of the adjusted gas ratio and applicability at regulatory-relevant time scales , 2008 .

[24]  W. Malm,et al.  The relative importance of soluble aerosols to spatial and seasonal trends of impaired visibility in the United States , 1994 .

[25]  M. Chin,et al.  Natural and transboundary pollution influences on sulfate‐nitrate‐ammonium aerosols in the United States: Implications for policy , 2004 .

[26]  METHODS FOR ASSESSMENT OF UNCERTAINTY AND SENSITIVITY IN INVENTORIES , 2005 .

[27]  John-Paul Clarke,et al.  Development, Design, and Flight Test Evaluation of a Continuous Descent Approach Procedure for Nighttime Operation at Louisville International Airport , 2006 .

[28]  H. Christopher Frey Quantification of Uncertainty in Emission Factors and Inventories , 2007 .

[29]  N. Frank,et al.  Retained Nitrate, Hydrated Sulfates, and Carbonaceous Mass in Federal Reference Method Fine Particulate Matter for Six Eastern U.S. Cities , 2006, Journal of the Air & Waste Management Association.

[30]  Abdiel Alexander Santos Galindo,et al.  Next Generation Air Transportation System (NextGen) , 2011 .

[31]  H. Christopher Frey,et al.  Development of hourly probabilistic utility NOx emission inventories using time series techniques: Part II—multivariate approach , 2003 .

[32]  D. Jacob,et al.  Global modeling of tropospheric chemistry with assimilated meteorology : Model description and evaluation , 2001 .

[33]  G. Grell,et al.  A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5) , 1994 .

[34]  Shahab Hasan,et al.  JPDO Case Study of NextGen High Density Operations , 2009 .

[35]  Tudor Maşek,et al.  A response surface model of the air quality impacts of aviation , 2008 .

[36]  김성문,et al.  [해외 대학 연구센터 소개] Rutgers, The State University of New Jersey , 2012 .

[37]  Steven R H Barrett,et al.  Global mortality attributable to aircraft cruise emissions. , 2010, Environmental science & technology.

[38]  Changlie Wey,et al.  Nitrogen Oxide (NO/NO2/HONO) Emissions Measurements in Aircraft Exhausts , 2007 .

[39]  Using Historical Information to Improve Emission Projections ( or How to Avoid Being Doomed to Repeat History ) , 2007 .

[40]  Philip J. Wolfe,et al.  Assessing the environmental impacts of aircraft noise and emissions , 2011 .

[41]  J. Seinfeld,et al.  Atmospheric Chemistry and Physics: From Air Pollution to Climate Change , 1997 .

[42]  Mina Jun,et al.  Microphysical modeling of ultrane hydrocarbon-containing aerosols in aircraft emissions , 2011 .

[43]  S. Baughcum,et al.  Scheduled civil aircraft emission inventories for 1992: Database development and analysis , 1996 .

[44]  H Christopher Frey,et al.  Probabilistic analysis of during cycle-based highway vehicle emission factors. , 2002, Environmental science & technology.

[45]  Saravanan Arunachalam,et al.  An assessment of Aviation’s contribution to current and future fine particulate matter in the United States , 2011 .

[46]  신응배,et al.  Air Quality Modeling 소개 , 1982 .

[47]  A. James 2010 , 2011, Philo of Alexandria: an Annotated Bibliography 2007-2016.

[48]  Hsin Min Wong,et al.  Near-Term Feasibility of Alternative Jet Fuels , 2009 .

[49]  Jeffrey Young,et al.  Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 , 2009 .

[50]  S. Isukapalli UNCERTAINTY ANALYSIS OF TRANSPORT-TRANSFORMATION MODELS , 1999 .

[51]  G. Whitten,et al.  The carbon-bond mechanism: a condensed kinetic mechanism for photochemical smog. , 1980, Environmental science & technology.

[52]  Loretta J. Mickley,et al.  Impacts of future climate change and effects of biogenic emissions on surface ozone and particulate matter concentrations in US , 2011 .

[53]  Changlie Wey,et al.  Aircraft Particle Emissions eXperiment (APEX) , 2006 .

[54]  Andrew Malwitz,et al.  System for Assessing Aviation's Global Emissions (SAGE), Version 1.5-Technical Manual , 2005 .

[55]  E. N. Lawrence Clean Air Act , 1971, Nature.