{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Joint Application of Concentration and Isotope Ratios to Investigate the Global Atmospheric Carbon Monoxide Budget: An Inverse Modeling Approach","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/1951/55574"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"Since carbon monoxide is one of the major sinks of hydroxyl radicals, it has been used as a proxy of hydroxyl radicals, which largely control the oxidizing capacity of the atmosphere. Thus, CO-related chemistry directly or indirectly affects the abundance of other atmospheric trace gases including methane, halocarbons and tropospheric ozone. Carbon monoxide has also been shown its usefulness as a tracer of transport of pollution and fire emissions and as an additional constraint for CO<sub>2</sub> fluxes. Variations in the global CO cycle are closely related to the change of total source strengths.  Previously, to estimate the global CO budget, most inverse modeling techniques have been applied to concentration of CO only and showed large discrepancies in each source estimate.  Since CO from certain sources may have a specific isotopic signature, the different isotopic species of CO provides additional information to constrain the sources.  Thus, coupling the concentration and isotope fraction information can provide a better constraint on CO source strengths and lead to a more realistic global CO budget estimation.In this thesis, MOZART-4, a 3-D global chemical transport model, was used to simulate the global CO concentration and its oxygen minor isotopologue, C<super>18</super>O.  Also, a tracer version (a tagged CO version) of MOZART-4 was developed to analyze contributions of each CO source, emission region and isotopologue efficiently. To validate model performance, CO concentrations and isotopic signatures measured from the Max Plank Institute for Chemistry, National Institute of Water and Atmospheric Research and Stony Brook University were compared to the modeled results over a nine year period. The model reproduced the observations fairly well and the averaged model-observation difference was 10.5ppbv for concentration and 3 per mil for d<super>18</super>O. Also, d<super>18</super>O of biomass burning source was estimated through the Keeling plot method and sensitivity test of d<super>18</super>O of biomass burning. Both methods suggest the d<super>18</super>O signature from biomass burning is higher than 20 per mil which is significantly enriched compared to previous estimates.Bayesian inversion techniques are used to calculate the most probable global CO budget based on observations and source strength.  In the inversion analysis, oxygen isotope information is jointly applied with concentration information. The joint inversion results provide not only more accurate and precise inversion results in comparison with [CO]-only inversion. Also, various methods combining the concentration and isotopic ratios were tested to maximize the benefit of including isotope information. The joint inversion of [CO] and d<super>18</super>O estimated total global CO production at 2951Tg CO/yr, 3084Tg CO/yr and 2583Tg CO/yr in 1997, 1998 and 2004 respectively. The updated CO budget improved modeled concentration and oxygen isotope ratio and since the improvement was more clearly shown in oxygen isotope ratio, this implied that more accurate a posteriori sources are estimated.Inversion analysis was performed with multi-year NOAA GMD [CO] to examine the interannual change of non-methane hydrocarbons oxidation source of CO which is directly affected by climate variation, such as El Ni\u00a4o/Southern Oscillation (ENSO) events. A close correlation between the NMHC oxidation source and ENSO events and the Earth surface temperature change was found. The interannual variation of NMHC oxidation source was \u00f152% from the mean and during a strong ENSO event in 1997 and 1998, global NMHC-derived CO increased by 74\u00f113%."},{"label":"dcterms.available","value":"2012-05-15T18:05:39Z"},{"label":"dcterms.contributor","value":"Daniel Knopf"},{"label":"dcterms.creator","value":"Park, Key Hong"},{"label":"dcterms.dateAccepted","value":"2015-04-24T14:52:55Z"},{"label":"dcterms.dateSubmitted","value":"2015-04-24T14:52:55Z"},{"label":"dcterms.description","value":"Department of Marine and Atmospheric Science"},{"label":"dcterms.format","value":"Monograph"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/72627"},{"label":"dcterms.issued","value":"2010-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2015-04-24T14:52:55Z (GMT). No. of bitstreams: 3\nPark_grad.sunysb_0771E_10378.pdf.jpg: 1894 bytes, checksum: a6009c46e6ec8251b348085684cba80d (MD5)\nPark_grad.sunysb_0771E_10378.pdf.txt: 203284 bytes, checksum: 2acc16e3ca3712f1f95c7179873e3d6f (MD5)\nPark_grad.sunysb_0771E_10378.pdf: 9035725 bytes, checksum: 75b49069b20bbe75038ed6cced956ef8 (MD5)\n  Previous issue date:    1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"Atmospheric Chemistry --  Atmospheric Sciences"},{"label":"dcterms.title","value":"Joint Application of Concentration and Isotope Ratios to Investigate the Global Atmospheric Carbon Monoxide Budget: An Inverse Modeling Approach"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/14%2F92%2F80%2F149280779549270672339030098738665958211/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/14%2F92%2F80%2F149280779549270672339030098738665958211","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}