Mechanistic representation of soil nitrogen emissions in atmospheric modeling

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dc.contributor.advisorCohan, Daniel Sen_US
dc.creatorRasool, Quazi Ziauren_US
dc.date.accessioned2019-05-17T16:05:39Zen_US
dc.date.available2019-08-01T05:01:08Zen_US
dc.date.created2018-08en_US
dc.date.issued2018-08-02en_US
dc.date.submittedAugust 2018en_US
dc.date.updated2019-05-17T16:05:40Zen_US
dc.description.abstractSoils are a major and long overlooked source of reactive nitrogen emissions below our feet. These emissions include species like nitric oxide (NO), nitrous acid (HONO), nitrous oxide (N2O), and ammonia (NH3). Their prevalence in the summer ozone season (growing season) may become increasingly important as fertilizer use grows and fossil fuel combustion sources of nitrogen decline. Most air quality models, including the Community Multiscale Air Quality (CMAQ) model, use outdated parametric emissions schemes that neglect HONO and tend to underpredict soil NO and misrepresent its variability in time and space. This work introduces a mechanistic, process-oriented representation of soil emissions of N species (NO, HONO, N2O, and NH3) in a regional air quality model. The mechanistic scheme accounts for biogeochemical processes for soil N transformations such as mineralization, volatilization, nitrification, and denitrification. The rates of these processes are influenced by soil parameters, meteorology, land use, and mineral nitrogen availability. We account for spatial heterogeneity in soil conditions and biome types by using a global dataset for soil carbon and nitrogen across terrestrial ecosystems to estimate daily mineral N availability in non-agricultural soils, which was not accounted in earlier parametrizations for soil NO. Our mechanistic scheme also uses daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model. A soil map with sub-grid biome definitions was used to represent conditions over the continental United States. CMAQ modeling for May and July 2011 shows that the mechanistic scheme improves model performance for simulating Ozone Monitoring Instrument (OMI) satellite-observed NO2 columns for regions where soils are the dominant source of NO emissions. We also assess how the new scheme affects model performance for NOx (NO+NO2), nitrate (NO3) fine particulate matter, and ozone observed by various ground-based monitoring networks. Soil NO emissions in the new mechanistic scheme tend to fall between the magnitudes of the previous parametric schemes and display much more spatial heterogeneity. The enhanced representation of soil biogeochemical processes introduced here could enable future studies to explore how agricultural practices and climate change impact soil emissions and air quality.en_US
dc.embargo.terms2019-08-01en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationRasool, Quazi Ziaur. "Mechanistic representation of soil nitrogen emissions in atmospheric modeling." (2018) Diss., Rice University. <a href="https://hdl.handle.net/1911/105837">https://hdl.handle.net/1911/105837</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/105837en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectSoil nitrogenen_US
dc.subjectair qualityen_US
dc.subjectNitrogen cyclingen_US
dc.subjectatmospheric modelingen_US
dc.subjectsoil nitrogen emissionsen_US
dc.subjectHONOen_US
dc.subjectsoil NOen_US
dc.subjectParametric soil NO schemesen_US
dc.subjectMechanistic soil N schemeen_US
dc.subjectEPICen_US
dc.subjectCMAQen_US
dc.subjectDAYCENTen_US
dc.titleMechanistic representation of soil nitrogen emissions in atmospheric modelingen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentCivil and Environmental Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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