Constraining NOx Emissions Using Spaceborne and Airborne Remotely Sensed NO2 Observations in the Southeast Texas

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dc.contributor.advisorChoi, Yunsoo
dc.contributor.committeeMemberRappenglueck, Bernhard
dc.contributor.committeeMemberJiang, Xun
dc.contributor.committeeMemberBowman, Kevin
dc.creatorSouri, Amirhossein 1989-
dc.date.accessioned2018-11-30T15:53:31Z
dc.date.available2018-11-30T15:53:31Z
dc.date.createdMay 2018
dc.date.issued2018-05
dc.date.submittedMay 2018
dc.date.updated2018-11-30T15:53:31Z
dc.description.abstractNitrogen oxides (NOx=NO+NO2) largely contribute to ozone formation which is a criterion air pollutant adversely affecting human health and crop yields. They are emitted by a range of anthropogenic and natural sources. The anthropogenic emissions are commonly estimated from the bottom-up inventories which are complicated by errors in underlying assumptions and county-level statistics. Therefore, the bottom-up NOx emissions could induce large biases and quickly become obsolete, which in turn introduce an obstacle for chemical transport models that heavily rely on this information. NO2 (a proxy for NOx) molecules have strong absorption in the ultra-violent wavelengths which facilitates their retrieval from several remote sensing sensors. We use tropospheric NO2 columns from Ozone Monitoring Instrument (OMI) to provide constraints on the bottom-up emissions using a Bayesian inversion in conjunction with the Community Multiscale Air Quality (CMAQ) model associated with Decoupled Direct Method (DDM) in Southeast Texas during DISCOVER-AQ campaign. Results suggest a reduction in area (44%), mobile (30%), and point sources (60%) in high NOx areas (ENOx> 0.2 mol/s). The top-down estimation largely mitigates the overprediction of the model in reproducing surface NO2 against monitoring sites. However, under-prediction of model NO2 in Houston on 09/25–09/26 potentially resulting from the unprecedented local NOx sources from the Houston Ship Channel (HSC) becomes more evident. To address this, we utilize, for the first time, the NO2 columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain NOx emissions in the Houston‐Galveston‐Brazoria area. To incorporate the observations into an analytical inversion, we convert the slant density columns to vertical columns using a radiative transfer model with i) NO2 profiles from a high‐resolution regional model (1×1 km2) constrained by P‐3B aircraft measurements, ii) the consideration of aerosol optical thickness impacts on radiance at NO2 absorption line, and iii) high‐resolution surface albedo constrained by ground‐based spectrometers. The modest high-quality observations from this airborne sensor enable us to quantify the unprecedented local emissions. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions.
dc.description.departmentEarth and Atmospheric Sciences, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/3441
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectInverse modeling
dc.subjectEmissions
dc.subjectRemote sensing
dc.titleConstraining NOx Emissions Using Spaceborne and Airborne Remotely Sensed NO2 Observations in the Southeast Texas
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2020-05-01
local.embargo.terms2020-05-01
thesis.degree.collegeCollege of Natural Sciences and Mathematics
thesis.degree.departmentEarth and Atmospheric Sciences, Department of
thesis.degree.disciplineAtmospheric Sciences
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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