Articles | Volume 13, issue 18
https://doi.org/10.5194/acp-13-9285-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-13-9285-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A plume-in-grid approach to characterize air quality impacts of aircraft emissions at the Hartsfield–Jackson Atlanta International Airport
J. Rissman
Energy Innovation: Policy and Technology LLC, 98 Battery St. Ste. 202, San Francisco, CA 94111, USA
S. Arunachalam
Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
Department of Environmental Science and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
J. J. West
Department of Environmental Science and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
T. BenDor
Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
F. S. Binkowski
Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
Related authors
No articles found.
Joshua Singleton, Hantao Wang, Jerry R. Ziemke, Marc L. Serre, and J. Jason West
EGUsphere, https://doi.org/10.5194/egusphere-2026-4798, https://doi.org/10.5194/egusphere-2026-4798, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Satellite ozone observations have been considered poor predictors of ozone at ground level. Here we evaluate the ability of one satellite product to estimate ground-level ozone globally over 18 years. The satellite product shows a modest correlation with ground-level ozone that does not vary strongly with year, season, world region, or ozone level. Using a linear regression, we translate the satellite product into a global monthly ground-level ozone dataset for use in future data fusion studies.
Hantao Wang, Marc L. Serre, Kazuyuki Miyazaki, Juan Cuesta, Jerry R. Ziemke, and J. Jason West
EGUsphere, https://doi.org/10.5194/egusphere-2026-2812, https://doi.org/10.5194/egusphere-2026-2812, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Ground-level ozone poses a significant health risk, yet ground monitors are sparse and satellites lack surface sensitivity. Here we develop a framework to infer surface ozone directly from satellite observations. By leveraging vertical profiles from balloons and aircraft and using chemical reanalysis vertical ratios, we significantly improved the accuracy of ozone estimates. Our 2005–2022 global dataset provides a valuable ground-level ozone background field for regions lacking ground networks.
Sebastian H. M. Hickman, Makoto M. Kelp, Paul T. Griffiths, Kelsey Doerksen, Kazuyuki Miyazaki, Elyse A. Pennington, Gerbrand Koren, Fernando Iglesias-Suarez, Martin G. Schultz, Kai-Lan Chang, Owen R. Cooper, Alex Archibald, Roberto Sommariva, David Carlson, Hantao Wang, J. Jason West, and Zhenze Liu
Geosci. Model Dev., 18, 8777–8800, https://doi.org/10.5194/gmd-18-8777-2025, https://doi.org/10.5194/gmd-18-8777-2025, 2025
Short summary
Short summary
Machine learning is being more widely used across environmental and climate science. This work reviews the use of machine learning in tropospheric ozone research, focusing on three main application areas in which significant progress has been made. Common challenges in using machine learning across the three areas are highlighted, and future directions for the field are indicated.
Hantao Wang, Kazuyuki Miyazaki, Haitong Zhe Sun, Zhen Qu, Xiang Liu, Antje Inness, Martin Schultz, Sabine Schröder, Marc Serre, and J. Jason West
Atmos. Chem. Phys., 25, 15969–15990, https://doi.org/10.5194/acp-25-15969-2025, https://doi.org/10.5194/acp-25-15969-2025, 2025
Short summary
Short summary
We compare six datasets of global ground-level ozone, developed using geostatistical, machine learning, or reanalysis methods. The datasets show important differences from one another in ozone magnitude, greater than 5 ppb, and trends, globally and regionally. Compared with measurements, performance varies among datasets, and most overestimate ozone, particularly at lower concentrations. These differences among datasets highlight uncertainties for applications to health and other impacts.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
Short summary
We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Shuping Zhang, Golam Sarwar, Jia Xing, Biwu Chu, Chaoyang Xue, Arunachalam Sarav, Dian Ding, Haotian Zheng, Yujing Mu, Fengkui Duan, Tao Ma, and Hong He
Atmos. Chem. Phys., 21, 15809–15826, https://doi.org/10.5194/acp-21-15809-2021, https://doi.org/10.5194/acp-21-15809-2021, 2021
Short summary
Short summary
Six heterogeneous HONO chemistry updates in CMAQ significantly improve HONO concentration. HONO production is primarily controlled by the heterogeneous reactions on ground and aerosol surfaces during haze. Additional HONO chemistry updates increase OH and production of secondary aerosols: sulfate, nitrate, and SOA.
Cited articles
Air New Zealand: Aircraft Statistics, available at: http://www.airnewzealand.co.nz/aircraft-statistics (last access: 22 June 2013), 2013.
Airports Council International: ACI releases World Airport Traffic Report 2009, available at: http://www.aci.aero/Media/aci/file/Press Releases/2010/PR_WATR2009_050810_FINAL.pdf (last access: 4 January 2013), 2010.
Airports Council International: Annual Traffic Data (Movements) for years 2002 and 2005, available at: http://www.aci.aero/Data-Centre/Annual-Traffic-Data/Movements/ (last access: 16 February 2013), 2013.
Arunachalam, S., Baek, B. H., Holland, A., Adelman, Z., Binkowski, F. S., Hanna, A., Thrasher, T., and Soucacos, P.: An Improved Method to Represent Aviation Emissions in Air Quality Modeling Systems and their Impacts on Air Quality, in: Proceedings of the 13 Conference on Aviation, Range and Aerospace Meteorology, New Orleans, LA, January 2008, 135626, available at: https://ams.confex.com/ams/pdfpapers/135626.pdf (last access: 30 November 2012), 2008.
Arunachalam, S., Wang, B., Davis, N., Baek, B. H., and Levy, J. I.: Effect of Chemistry-Transport Model Scale and Resolution on Population Exposure to PM2.5 from Aircraft Emissions during Landing and Takeoff, Atmos. Environ., 45, 3294–3300, https://doi.org/10.1016/j.atmosenv.2011.03.029, 2011.
Aviation Environmental Design Tool: http://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/aedt/ (last access: 25 October 2010), 2010.
Baek, B. H., Arunachalam, S., Holland, A., Adelman, Z., Hanna, A., Thrasher, T., and Soucacos, P.: Development of an Interface for the Emissions Dispersion and Modeling System (EDMS) with the SMOKE Modeling System, in: Proceedings of the 16th Annual Emissions Inventory Conference, Emissions Inventories: Integration, Analyses and Communication, Raleigh, NC, May 2007, available at: http://www.epa.gov/ttn/chief/conference/ei16/session1/baek.pdf (last access: 30 November 2012), 2007.
Barrett, S. R. H., Britter, R. E., and Waitz, I. A.: Global mortality attributable to aircraft cruise emissions, Environ. Sci. Technol., 44, 7736–7742, 2010.
Byun, D. W. and Schere, K. L.: Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System, J. Appl. Mech. Rev., 59, 51–77, https://doi.org/10.1115/1.2128636, 2006.
Cimorelli, A., Perry, S., Venkatram, A., Weil, J., Paine, R., Wilson, R., Lee, R., Peters, W., and Brode, R.: AERMOD: A dispersion Model for Industrial Source Applications. Part I: General Model Formulation and Boundary Layer Characterization, J. Appl. Meteorol., 44, 682–693, https://doi.org/10.1175/JAM2227.1, 2005.
Eyers, C., Gilboy, M.: Revision of Calvert method for filling in missing smoke number data, QinetiQ, 2007.
FAA and EPA: Recommended Best Practice for Quantifying Speciated Organic Gas Emissions from Aircraft Equipped with Turbofan, Turbojet, and Turboprop Engines, http://www.faa.gov/regulations_policies/policy_guidance/envir_policy/media/FAA-EPA_RBP_Speciated OG_Aircraft_052709.pdf (last access: 28 February 2011), 2009.
Federal Aviation Administration: Emissions and Dispersion Modeling System (EDMS) policy for airport air quality analysis: Interim guidance to FAA Orders 1050.1D and 5050.4A, Federal Register, 63, 18068, available at: http://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/edms_model/media/EDMS Requirement for Airport Air Quality Analysis.pdf (last access: 30 November 2012), 1998.
Gery, M. W., Whitten, G. Z., Killus, J. P., and Dodge, M. C.: A photochemical kinetics mechanism for urban and regional scale computer modeling, J. Geophys. Res.-Atmos., 94, 12925–12956, https://doi.org/10.1029/JD094iD10p12925, 1989.
Gladstone, C., Glover, G., Massimini, P., Skiotsuki, C., and Simmons, B.: Analysis of Triple Arrivals to Hartsfield Atlanta International Airport, MITRE Technical Report, available at: http://www.caasd.org/library/tech_docs/2000/mtr00w0000023.pdf (last access: 6 March 2011), 2000.
Grell, G., Dudhia, J., and Stauffer, D.: A Description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5), NCAR Technical Note, available at: http://nldr.library.ucar.edu/repository/assets/technotes/asset-000-000-000-214.pdf (last access: 30 December 2011), 1994.
Hall, C., Mondoloni, S., and Thrasher, T.: Estimating the Impact of Reduced Thrust Takeoff on Annual NOx Emissions at Airports, CSSI, Inc., available at: http://www.cssiinc.com/public/technicalpapers/docs/13-Estimating the Impact of Reduced Thrust Takeoff on Annual NOx Emissions.pdf (last access: 16 February 2011), 2003.
Herndon, C., Jayne, J., Lobo, P., Onasch, T., Fleming, G., Hagen, D., Whitefield, P., and Miake-Lye, R.: Commercial Aircraft Engine Emissions Characterization of in-Use Aircraft at Hartsfield-Jackson Atlanta International Airport, Environ. Sci. Technol., 42, 1877–1883, available at: http://www.volpe.dot.gov/coi/ees/air/docs/2008-envi-sci-herndon.pdf, 2008.
Houyoux, M. R., Vukovich, J. M., Coats Jr., C. J., Wheeler, N. J. M., and Kasibhatla, P. S.: Emission inventory development and processing for the seasonal model for regional air quality (SMRAQ) project, J. Geophys. Res., 105, 9079–9090, 2000.
International Civil Aviation Organization (ICAO): International Standards and Recommended Practices – Environmental Protection Volume II, Second Edition, 1993.
International Civil Aviation Organization (ICAO): Emissions Databank Issue 17, http://www.caa.co.uk/default.aspx?catid=702 (last access: 28 February 2011), 2010.
Karamchandani, P., Seigneur, C., Vijayaraghavan, K., and Wu, S. Y.: Development and application of a state-of-the-science plume-in-grid model, J. Geophys. Res-Atmos., 107, 4403–4415, https://doi.org/10.1029/2002JD002123, 2002.
Karamchandani, P., Vijayaraghavan, K., Chen, S., Seigneur, C., and Edgerton, E.: Plume-in-grid modeling for particulate matter, Atmos. Environ., 40, 7280–7297, https://doi.org/10.1016/j.atmosenv.2006.06.033, 2006.
Karamchandani, P., Lohman, K., Seigneur, C.: Using a sub-grid scale modeling approach to simulate the transport and fate of toxic air pollutants, Environ. Fluid Mech., 9, 59–71, 2009.
Karamchandani, P., Vijayaraghavan, K., Chen, S., Balmori-Bronson, R., Knipping, E.: Development and application of a parallelized version of the advanced modeling system for transport, emissions, reactions and deposition of atmospheric matter (AMSTERDAM): 1. Model performance evaluation and impacts of plume-in-grid treatment, Atmos. Poll. Res., 1, 260–270, https://doi.org/10.5094/APR.2010.033, 2010.
Kinsey, J. S., Dong, Y., Williams, D. C., and Logan, R.: Physical Characterization of the fine particle emissions from commercial aircraft engines during the Aircraft Particle Emissions Experiment (APEX) 1-3, Atmos. Environ., 44, 2147–2156, https://doi.org/10.1016/j.atmosenv.2010.02.010, 2010.
Kraabøl, A., Flatøy, F., and Stordal, F.: Impact of NOx emissions from subsonic aircraft: Inclusion of plume processes in a three-dimensional model covering Europe, North America, and the North Atlantic, J. Geophys. Res.-Atmos., 105, 3573–3581, https://doi.org/10.1029/1999JD900931, 2000.
Kraabøl, A., Berntsen, T., Sundet, J., and Stordal, F.: Impacts of NOx emissions from subsonic aircraft in a global three-dimensional chemistry transport model including plume processes, J. Geophys. Res.-Atmos., 107, ACH 22-1–ACH 22-13, https://doi.org/10.1029/2001JD001019, 2002.
Lee, H., Olsen, S. C., Wuebbles, D. J., and Youn, D.: Impacts of aircraft emissions on the air quality near the ground, Atmos. Chem. Phys., 13, 5505–5522, https://doi.org/10.5194/acp-13-5505-2013, 2013.
Levy, J., Hsu, H., and Melly, S.: High Priority Compounds Associated with Aircraft Emissions: PARTNER 11 final report on subtask: Health Risk Prioritization of Aircraft Emissions Related Air Pollutants, Partnership for AiR Transportation Noise and Emissions Reduction, available at: http://web.mit.edu/aeroastro/partner/reports/proj11/p11compndsemiss.pdf (last access: 10 Apr 2011), 2008.
Levy, J. I., Woody, M., Baek, B. H., Shankar, U., and Arunachalam, S.: Current and Future Particulate Matter-related Mortality Risks from Aviation Emissions in the United States, Risk Anal., 32, 237–249, https://doi.org/10.1111/j.1539-6924.2011.01660.x, 2012.
Meilinger, S., Kärcher, B., and Peter, T.: Microphysics and heterogeneous chemistry in aircraft plumes – high sensitivity on local meteorology and atmospheric composition. Atmos. Chem. Phys., 5, 533–545, https://doi.org/10.5194/acp-5-533-2005, 2005.
Miracolo, M. A., Hennigan, C. J., Ranjan, M., Nguyen, N. T., Gordon, T. D., Lipsky, E. M., Presto, A. A., Donahue, N. M., and Robinson, A. L.: Secondary aerosol formation from photochemical aging of aircraft exhaust in a smog chamber, Atmos. Chem. Phys., 11, 4135–4147, https://doi.org/10.5194/acp-11-4135-2011, 2011.
Moss, M. and Segal, H.: Emissions and Dispersion Modeling System: Its Development and Application at Airports and Airbases, J. Air Waste Manage., 44, 787–790, https://doi.org/10.1080/1073161X.1994.10467281, 1994.
Naiman, A. D., Lele, S. K., Wilkerson, J. T., and Jacobson, M. Z.: Parameterization of subgrid plume dilution for use in large-scale atmospheric simulations, Atmos. Chem. Phys., 10, 2551–2560, https://doi.org/10.5194/acp-10-2551-2010, 2010.
Noel, G., Cointin, R., Allaire, D., Jacobson, S., and Willcox, K.: Assessment of the Aviation Environmental Design Tool, 8th USA/Europe Air Traffic Management Research and Development Seminar, Napa, CA, 29 June–9 July 2009, 84, available at: http://www.atmseminarus.org/seminarContent/seminar8/papers/p_084_EI.pdf (last access: 30 November 2012), 2009.
Pope, C., Burnett, R., Thun, M., Calle, E., Krewski, D., Ito, K., and Thurston, G.: Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution, JAMA-J. Am. Med. Assoc., 287, 1132–1141, https://doi.org/10.1001/jama.287.9.1132, 2002.
Ratliff, G., Sequeira, C., Waitz, I., Ohsfeldt, M., Thrasher, T., Graham, M., and Thompson, T.: Aircraft Impacts on Local and Regional Air Quality in the United States, Partnership for Air Transportation Noise and Emissions Reduction, available at: http://web.mit.edu/aeroastro/partner/reports/proj15/proj15finalreport.pdf (last access: 24 March 2011), 2009.
Rice, C.: Validation of Approach and Climbout Times-in-Mode for Aircraft Emissions Computation, 2003 Transportation Research Board Annual Meeting, Washington, DC, 12 Jan 2003, available at: http://www.ltrc.lsu.edu/TRB_82/TRB2003-001446.pdf (last access: 30 November 2012), 2003.
Santos, L. Sykes, R., Karamchandani, P., Seigneur, C., Lurmann, F., Arndt, R., and Kumar, N.: Second-order Closure Integrated Puff (SCIPUFF) model with gas and aqueous phase chemistry and aerosols, 11th Joint Conference on the Applications of Air Pollution Meteorology with the Air and Waste Management Association, Long Beach, CA, 9–14 January 2000, 10436, 2000.
Sarwar, G., Godowitch, J., Henderson, B., Fahey, K., Pouliot, G., Hutzell, W. T., Mathur, R., Kang, D., Goliff, W. S., and Stockwell, W. R.: A comparison of atmospheric composition using the Carbon Bond and Regional Atmospheric Chemistry Mechanisms, Atmos. Chem. Phys. Discuss., 13, 6923–6969, https://doi.org/10.5194/acpd-13-6923-2013, 2013.
Spicer, C. W., Holdren, M. W., Riggin, R. M., and Lyon, T. F.: Chemical composition and photochemical reactivity of exhaust from aircraft turbine engines, Ann. Geophys., 12, 944–955, https://doi.org/10.1007/s00585-994-0944-0, 1994.
Sykes, R. I. and Gabruk, R. S.: A Second-Order Closure Model for the Effect of Averaging Time on Turbulent Plume Dispersion, J. Appl. Meteorol., 36, 1038–1045, https://doi.org/10.1175/1520-0450(1997)036<1038:ASOCMF>2.0.CO;2, 1997.
Sykes, R. I., Parker, S. F., Henn, D. S., Cerasoli, C. P., and Santos, L. P.: PC-SCIPUFF Version 1.1PD.1 Technical Documentation. ARAP Report No. 718. Titan Corporation, Titan Research & Technology Division, ARAP Group, P.O. Box 2229, Princeton, NJ, USA, 08543-2229, 1998.
Timko, M., Onasch, T., Northway, M., Jayne, J., Canagaratna, M., Herndon, S., Wood, E., and Miake-Lye, R.: Gas Turbine Engine Emissions – Part II: Chemical Properties of Particulate Matter, J. Eng. Gas Turb. Power, 132, 061505–061519, https://doi.org/10.1115/1.4000132, 2010.
Tsai, F., Sun, W., and Chen, J.: A Composite Modeling Study of Civil Aircraft Impacts on Ozone and Sulfate over the Taiwan Area, J. Terr. Atmos. Ocean. Sci., 12, 109–135, available at: http://carl.as.ntu.edu.tw/chinese/jpchen/018.pdf, 2001.
Vijayaraghavan, K., Karamchandani, P., Seigneur, C., Balmori, R., and Chen, S.: Plume-in-grid modeling of atmospheric mercury, J. Geophys. Res-Atmos., 113, D24305, https://doi.org/10.1029/2008JD010580, 2008.
Wayson, R., Fleming, G., and Iovinelli, R.: Methodology to Estimate Particulate Matter Emissions from Certified Commercial Aircraft Engines, J. Air Waste Manage., 59, 91–100, https://doi.org/10.3155/1047-3289.59.1.91, 2009.
Wayson, R. L., Fleming, G. G., and Kim, B.: Status report on proposed methodology to characterize jet/gas turbine engine particulate matter emissions, Federal Aviation Administration, 2003.
Whitt, D., Jacobson, M. Z., Wilkerson, J. T., Naiman, A. D., and Lele, S. K.: Vertical mixing of commercial aviation emissions from cruise altitude to the surface, J. Geophys. Res-Atmos., 116, D14109, https://doi.org/10.1029/2010JD015532, 2011.
Wilkerson, J. T., Jacobson, M. Z., Malwitz, A., Balasubramanian, S., Wayson, R., Fleming, G., Naiman, A. D., and Lele, S. K.: Analysis of Emission Data from Global Commercial Aviation: 2004 and 2006, Amos. Chem. Phys., 10, 6391–6408, https://doi.org/10.5194/acp-10-6391-2010, 2010.
Wong, H., Yelvington, P., Timko, M., Onasch, T., and Miake-Lye, R.: Microphysical Modeling of Ground-Level Aircraft-Emitted Aerosol Formation: Roles of Sulfur-Containing Species, J. Propul. Power, 24, 590–602, https://doi.org/10.2514/1.32293, 2008.
Wood, E., Herndon, S., Timko, M., Yelvington, P., and Miake-Lye, R.: Speciation and chemical evolution of nitrogen oxides in aircraft exhaust near airports, Environ. Sci. Technol., 43, 1884–1891, https://doi.org/10.1021/es072050a, 2008.
Woody, M. and Arunachalam, S.: Secondary Organic Aerosol Produced from Aircraft Emissions at the Atlanta Airport: An Advanced Diagnostic Investigation Using Process Analysis, Atmos. Environ., 76, 101–109, https://doi.org/10.1016/j.atmosenv.2013.06.007, 2013.
Woody, M., Baek, B. H., Adelman, Z., Omary, M., Lam, Y. F., West, J., and Arunachalam, S.: An Assessment of Aviation Contribution to Current and Future Fine Particulate Matter in the United States, Atmos. Environ., 45, 3424–3433, https://doi.org/10.1016/j.atmosenv.2011.03.041, 2011.
Unal A., Hu Y., Chang M. E., Odman M. T., and Russell A. G.: Airport related emissions and impacts on air quality: Application to the Atlanta International Airport, Atmos. Environ., 39, 5787-5798, https://doi.org/10.1016/j.atmosenv.2005.05.051, 2005.
US EPA: 2002 National Emissions Inventory Data and Documentation, http://www.epa.gov/ttn/chief/net/2002inventory.html (last access: 1 November 2010), 2013a.
US EPA: SPECIATE Version 4.3, http://www.epa.gov/ttn/chief/software/speciate/index.html (last access: 10 March 2011), 2013b.
Altmetrics
Final-revised paper
Preprint