{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124431"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124431","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Parametric and structural uncertainties in modeling dry deposition of atmospheric aerosol particles","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","abstract_has_math":false,"creators":["D'Aquino, Zach"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Atmospheric Sciences","degree_department":null,"school":null,"contributors":["Riemer, Nicole","Dominguez, Francina","West, Matthew"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:25:00Z","subjects":["Atmospheric Aerosol","Aerosol Modeling","Parametric Uncertainty","Structural Uncertainty"],"languages":["en","eng"],"rights":["Copyright 2024 Zach D'Aquino"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124431","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Riemer, Nicole","Dominguez, Francina","West, Matthew"]},{"key":"dc:creator","label":"Author","values":["D'Aquino, Zach"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05","2024-05-02"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Atmospheric Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Atmospheric Aerosol","Aerosol Modeling","Parametric Uncertainty","Structural Uncertainty"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Zach D'Aquino"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124431"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","The student, Zach D'Aquino, accepted the attached license on 2024-04-29 at 11:41.","The student, Zach D'Aquino, submitted this Thesis for approval on 2024-04-29 at 11:53.","This Thesis was approved for publication on 2024-05-02 at 10:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20689 on 2024-09-16 at 00:37:21","Emissions of atmospheric aerosol particles---liquid, solid, or mixed-phase particles suspended in the air---and their precursor gases have increased markedly as a result of human activity relative to pre-industrial times. The aerosol indirect effect represents the single largest uncertainty in effective radiative forcing estimates. To begin shrinking this uncertainty, it is pivotal to first understand the individual sources of uncertainty associated with modeling the dynamics of an aerosol population. Since aerosol microphysical processes occur on scales much smaller than the size of larger-scale model grid cells and are strongly influenced by subgrid-scale variability, oftentimes a handful of simplified equations and fitted parameters are used to represent these processes. Parametric uncertainty refers to the uncertainty associated with the choice of model parameters. There are also many distinct mathematical representations used to characterize a simulated aerosol population, and structural uncertainty represents the uncertainty incurred from simply employing a particular mathematical projection. Previous modeling studies have found dry deposition, the size-dependent removal of particles without the assistance of precipitation, to be one of the largest sources of parametric uncertainty in estimates of global CCN concentrations within a single global aerosol model framework. In this thesis, the relative magnitudes of the structural and parametric uncertainties accompanying simulation of the dry deposition process are quantitatively compared through a series of methodical modeling experiments. These experiments involve the development of modal and sectional---frameworks commonly used to represent aerosol populations in global and regional models---box models equipped with two different dry deposition parameterizations. Uncertainties depend on the characteristics of the aerosol size distribution, and findings suggest that parametric uncertainty remains fairly consistent across model structures with the same initial size distribution parameters. The structural uncertainty is much more closely tied to the specifics of the size distribution with higher geometric standard deviations generally linked to larger structural uncertainties. It is also clear that the structural uncertainty is unequivocally determined by the choice in dry deposition paramterization, confirming that a deep understanding of the presentation of these two different sources of uncertainty is needed to make the most informed choices when modeling the dry deposition process."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Parametric and structural uncertainties in modeling dry deposition of atmospheric aerosol particles"]}]}],"canonical_facts":{"dc:contributor":["Riemer, Nicole","Dominguez, Francina","West, Matthew"],"dc:creator":["D'Aquino, Zach"],"dc:date":["2024-05","2024-05-02"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms","The student, Zach D'Aquino, accepted the attached license on 2024-04-29 at 11:41.","The student, Zach D'Aquino, submitted this Thesis for approval on 2024-04-29 at 11:53.","This Thesis was approved for publication on 2024-05-02 at 10:59.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20689 on 2024-09-16 at 00:37:21","Emissions of atmospheric aerosol particles---liquid, solid, or mixed-phase particles suspended in the air---and their precursor gases have increased markedly as a result of human activity relative to pre-industrial times. The aerosol indirect effect represents the single largest uncertainty in effective radiative forcing estimates. To begin shrinking this uncertainty, it is pivotal to first understand the individual sources of uncertainty associated with modeling the dynamics of an aerosol population. Since aerosol microphysical processes occur on scales much smaller than the size of larger-scale model grid cells and are strongly influenced by subgrid-scale variability, oftentimes a handful of simplified equations and fitted parameters are used to represent these processes. Parametric uncertainty refers to the uncertainty associated with the choice of model parameters. There are also many distinct mathematical representations used to characterize a simulated aerosol population, and structural uncertainty represents the uncertainty incurred from simply employing a particular mathematical projection. Previous modeling studies have found dry deposition, the size-dependent removal of particles without the assistance of precipitation, to be one of the largest sources of parametric uncertainty in estimates of global CCN concentrations within a single global aerosol model framework. In this thesis, the relative magnitudes of the structural and parametric uncertainties accompanying simulation of the dry deposition process are quantitatively compared through a series of methodical modeling experiments. These experiments involve the development of modal and sectional---frameworks commonly used to represent aerosol populations in global and regional models---box models equipped with two different dry deposition parameterizations. Uncertainties depend on the characteristics of the aerosol size distribution, and findings suggest that parametric uncertainty remains fairly consistent across model structures with the same initial size distribution parameters. The structural uncertainty is much more closely tied to the specifics of the size distribution with higher geometric standard deviations generally linked to larger structural uncertainties. It is also clear that the structural uncertainty is unequivocally determined by the choice in dry deposition paramterization, confirming that a deep understanding of the presentation of these two different sources of uncertainty is needed to make the most informed choices when modeling the dry deposition process."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124431"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Zach D'Aquino"],"dc:subject":["Atmospheric Aerosol","Aerosol Modeling","Parametric Uncertainty","Structural Uncertainty"],"dc:title":["Parametric and structural uncertainties in modeling dry deposition of atmospheric aerosol particles"],"dc:type":["text"],"thesis:degree_discipline":["Atmospheric Sciences"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:00Z"}