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dc.contributor.authorSullivan, John T.
dc.contributor.authorBerkoff, Timothy
dc.contributor.authorGronoff, Guillaume
dc.contributor.authorKnepp, Travis
dc.contributor.authorPippin, Margaret
dc.contributor.authorAllen, Danette
dc.contributor.authorTwigg, Laurence
dc.contributor.authorSwap, Robert
dc.contributor.authorTzortziou, Maria
dc.contributor.authorThompson, Anne M.
dc.contributor.authorStauffer, Ryan M.
dc.contributor.authorWolfe, Glenn
dc.contributor.authorFlynn, James
dc.contributor.authorPusede, Sally E.
dc.contributor.authorJudd, Laura M.
dc.contributor.authorMoore, William
dc.contributor.authorBaker, Barry D.
dc.contributor.authorAl-Saadi, Jay
dc.contributor.authorMcGee, Thomas J.
dcterms.creatorhttps://orcid.org/0000-0001-6586-4043en_US
dc.date.accessioned2021-10-13T18:18:09Z
dc.date.available2021-10-13T18:18:09Z
dc.date.issued2019-02-01
dc.description.abstractCoastal regions have historically represented a significant challenge for air quality investigations because of water–land boundary transition characteristics and a paucity of measurements available over water. Prior studies have identified the formation of high levels of ozone over water bodies, such as the Chesapeake Bay, that can potentially recirculate back over land to significantly impact populated areas. Earth-observing satellites and forecast models face challenges in capturing the coastal transition zone where small-scale meteorological dynamics are complex and large changes in pollutants can occur on very short spatial and temporal scales. An observation strategy is presented to synchronously measure pollutants “over land” and “over water” to provide a more complete picture of chemical gradients across coastal boundaries for both the needs of state and local environmental management and new remote sensing platforms. Intensive vertical profile information from ozone lidar systems and ozonesondes, obtained at two main sites, one over land and the other over water, are complemented by remote sensing and in situ observations of air quality from ground-based, airborne (both personned and unpersonned), and shipborne platforms. These observations, coupled with reliable chemical transport simulations, such as the National Oceanic and Atmospheric Administration (NOAA) National Air Quality Forecast Capability (NAQFC), are expected to lead to a more fully characterized and complete land–water interaction observing system that can be used to assess future geostationary air quality instruments, such as the National Aeronautics and Space Administration (NASA) Tropospheric Emissions: Monitoring of Pollution (TEMPO), and current low-Earth-orbiting satellites, such as the European Space Agency’s Sentinel-5 Precursor (S5-P) with its Tropospheric Monitoring Instrument (TROPOMI).en_US
dc.description.sponsorshipThis work was supported by the 2017 NASA Science Innovation Fund. The authors gratefully acknowledge support provided by the NASA Tropospheric Composition Program, the TEMPO Student Collaboration Project (supported by NASA Earth System Science Pathfinder Program), the NASA GSFC Pandora Project, the NASA AERONet Project, and the pilots/captains and crew of the LaRC B200, WFF C-23 Sherpa, and R/V SERC. Thanks for the continued support and guidance from the Tropospheric Ozone Lidar Network (TOLNet). Gracious support was also provided from the EPA’s Air, Climate, and Energy Research Program. Additional support was provided by NASA Grant NNX15AB84G. Ceilometer equipment and support were also provided by Ricardo Sakai, Ruben Delgado, and Belay Demoz. Near-real-time processing of the Pandora data was provided by Alexander Cede, Martin Tiefengraber, Moritz Mueller, Axel Kreuter, and Christian Posch. The OWLETS team would also like to thank the NOAA Environmental Modeling Center (EMC) and the NOAA Air Resources Laboratory (ARL) for guidance and support of operational forecasting, with a special thanks to Jeff McQueen and Pius Lee. We would like to extend our gratitude toward Alexander Dimov, Peter Pantina, and Nader Abuhassan for their commitment to ground site installation. The authors also acknowledge the support of Dr. Vickie Connors and the VCU Rice Center staff. Additional measurements and data processing for the C-23 Sherpa were provided by Donald Blake, Barbara Barletta, Thomas F. Hanisco, Jason St. Clair, Reem Hannun, Jessica Munyan, Natasha Dacic, Melissa Yang, and Michael Shook. Thanks to Daniel Salkovitz, Kristen Stumpf, John Brandt, and Charles Turner for air quality forecasting and air quality monitoring assistance from the Virginia Department of Environmental Quality. Thanks to continued support from Dan Summers and the Virginia Living Museum (VLM), especially for coordinating access and installment of a monitor at the VLM during and beyond the study period. Special thanks to an exceptional group of student interns: Lance Nino, Betsy Farris, Lindsey Rodio, Jeremy Schroeder, Pablo Sanchez, Emily Gargulinski, Marlia Harnden, Desorae Davis, Angela Atwater, Owen Parker, Julio Roman, Joseph Robinson, Lena Shalaby, Ian Fenn, Sahil Banyopadhyay, Amanda Engel, Faran Haider, Weston Millar, Fayzan Saleem, Hakeen Bisyir, Nyle Rodgers, Vicky Baker, Sunglee Choi, Nash Kocur, Brett Poche, and Nabil Nowak. Thanks to Ed Adcock, Zak Johns, Mark Motter, Jim Neilan, and Matt Vaughan of the NASA LaRC UAV team. This work could also not have been completed without the thoughtful accommodations of Edward Spencer and all of the management and employees with the Chesapeake Bay Bridge and Tunnel District. Unless otherwise noted, all data from the OWLETS campaign and those used in this manuscript have been uploaded to an archive web interface (www-air.larc.nasa .gov/missions/owlets). Additional field reports, flight forecasts, presentations, and other information to facilitate use of OWLETS data by the research community at large. NAQFC archive and verification plots are available through the NOAA Environmental Modeling Center (EMC) (at www.emc.ncep.noaa.gov/mmb/aq/cmaq/web /html/max.html) and have real-time official dissemination via NOAA Air Resources Laboratory (ARL) (at http:// airquality.weather.gov/).en_US
dc.description.urihttps://journals.ametsoc.org/view/journals/bams/100/2/bams-d-18-0025.1.xmlen_US
dc.format.extent16 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2ubyr-rm9m
dc.identifier.citationSullivan, John T. et al.; The Ozone Water–Land Environmental Transition Study: An Innovative Strategy for Understanding Chesapeake Bay Pollution Events; Bulletin of the American Meteorological Society, 100, 2, pages 291-306, 1 February, 2019; https://doi.org/10.1175/BAMS-D-18-0025.1en_US
dc.identifier.urihttps://doi.org/10.1175/BAMS-D-18-0025.1
dc.identifier.urihttp://hdl.handle.net/11603/23088
dc.language.isoen_USen_US
dc.publisherAmerican Meteorological Societyen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleThe Ozone Water–Land Environmental Transition Study: An Innovative Strategy for Understanding Chesapeake Bay Pollution Eventsen_US
dc.typeTexten_US


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This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
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