{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105004"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105004","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Particle-resolved aerosol modeling on the regional scale – insights into importance of capturing aerosol mixing state","abstract":"Aerosol particles in the atmosphere are complex mixtures of different chemical species, and their compositions are constantly evolving as coagulation and multiphase processes act on the particle population. The particles interact with the climate system directly by scattering and absorbing solar radiation, and indirectly by forming clouds. These macroscale climate effects depend on the size and composition of individual particles. Simulating the evolution of aerosols and predicting their impacts remains a challenge due to the multiscale nature of the system. Various methods exist for representing aerosols in models, which range in complexity and computational cost — from very simple and computationally efficient, suitable for simulation on the regional and global scale, to highly-detailed and computational expensive, suitable for box model simulations on the process level. With the development of the particle-resolved model PartMC-MOSAIC, it became possible to simulate the aerosol mixing state in great detail. However, previous applications of PartMC-MOSAIC have lacked spatial resolution, which only a three-dimensional chemical transport model can provide. To address this shortcoming, the goal of this thesis was to create a particle-resolved aerosol modeling framework that is also spatially resolved, the first of its kind. Several modeling advances were required to attain this goal. At the core was the development of efficient algorithms for particle transport in three dimensions and particle removal at the surface by dry deposition. Additionally, we have contributed a framework for developing particle-resolved, source-oriented aerosol emissions. This framework is flexible and can make use of a variety of user-defined emission data sets. We applied the newly developed model system to simulate an episode during the Carbonaceous Aerosol and Radiative Effects Study (CARES) campaign in California in June 2010. The interactions of atmospheric transport and spatially distributed emissions led to a rapid aging of aerosols in urban areas resulting in internally mixed populations in those areas. Errors in cloud condensation nuclei concentrations when assuming internally mixed aerosols were quantified using a composition-averaging technique to replicate a sectional aerosol representation, which is common in many state-of-the-art chemical transport models. These errors amount up to 100% for more externally mixed populations, and can remain up to 50% for region that are internally mixed. This dissertation research created a new framework model for high-detail aerosol simulations on the regional scale and a benchmark capability for the community to quantify errors in predicted aerosol impacts due to simplified aerosol representations.","abstract_html":"Aerosol particles in the atmosphere are complex mixtures of different chemical species, and their compositions are constantly evolving as coagulation and multiphase processes act on the particle population. The particles interact with the climate system directly by scattering and absorbing solar radiation, and indirectly by forming clouds. These macroscale climate effects depend on the size and composition of individual particles. Simulating the evolution of aerosols and predicting their impacts remains a challenge due to the multiscale nature of the system. Various methods exist for representing aerosols in models, which range in complexity and computational cost — from very simple and computationally efficient, suitable for simulation on the regional and global scale, to highly-detailed and computational expensive, suitable for box model simulations on the process level. With the development of the particle-resolved model PartMC-MOSAIC, it became possible to simulate the aerosol mixing state in great detail. However, previous applications of PartMC-MOSAIC have lacked spatial resolution, which only a three-dimensional chemical transport model can provide. To address this shortcoming, the goal of this thesis was to create a particle-resolved aerosol modeling framework that is also spatially resolved, the first of its kind. Several modeling advances were required to attain this goal. At the core was the development of efficient algorithms for particle transport in three dimensions and particle removal at the surface by dry deposition. Additionally, we have contributed a framework for developing particle-resolved, source-oriented aerosol emissions. This framework is flexible and can make use of a variety of user-defined emission data sets. We applied the newly developed model system to simulate an episode during the Carbonaceous Aerosol and Radiative Effects Study (CARES) campaign in California in June 2010. The interactions of atmospheric transport and spatially distributed emissions led to a rapid aging of aerosols in urban areas resulting in internally mixed populations in those areas. Errors in cloud condensation nuclei concentrations when assuming internally mixed aerosols were quantified using a composition-averaging technique to replicate a sectional aerosol representation, which is common in many state-of-the-art chemical transport models. These errors amount up to 100% for more externally mixed populations, and can remain up to 50% for region that are internally mixed. This dissertation research created a new framework model for high-detail aerosol simulations on the regional scale and a benchmark capability for the community to quantify errors in predicted aerosol impacts due to simplified aerosol representations.","abstract_has_math":false,"creators":["Curtis, Jeffrey Henry"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Atmospheric Sciences","degree_department":null,"school":null,"contributors":["Riemer, Nicole","West, Matthew","Nesbitt, Stephen W.","Sriver, Ryan L."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T20:35:50Z","date_published":"2019-08-23T20:35:50Z","updated_at":"2026-07-22T22:24:44Z","subjects":["Aerosols","Mixing state","Particle-resolved modeling","Aerosol modeling"],"languages":["en"],"rights":["Copyright 2019 Jeffrey Henry Curtis"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105004","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Riemer, Nicole","West, Matthew","Nesbitt, Stephen W.","Sriver, Ryan L."]},{"key":"dc:creator","label":"Author","values":["Curtis, Jeffrey Henry"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-08-23T20:35:50Z","2021-08-24T09:15:20Z","2019-04-11","2019-05"]},{"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":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Aerosols","Mixing state","Particle-resolved modeling","Aerosol modeling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Jeffrey Henry Curtis"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105004"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Aerosol particles in the atmosphere are complex mixtures of different chemical species, and their compositions are constantly evolving as coagulation and multiphase processes act on the particle population. 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To address this shortcoming, the goal of this thesis was to create a particle-resolved aerosol modeling framework that is also spatially resolved, the first of its kind. Several modeling advances were required to attain this goal. At the core was the development of efficient algorithms for particle transport in three dimensions and particle removal at the surface by dry deposition. Additionally, we have contributed a framework for developing particle-resolved, source-oriented aerosol emissions. This framework is flexible and can make use of a variety of user-defined emission data sets. We applied the newly developed model system to simulate an episode during the Carbonaceous Aerosol and Radiative Effects Study (CARES) campaign in California in June 2010. The interactions of atmospheric transport and spatially distributed emissions led to a rapid aging of aerosols in urban areas resulting in internally mixed populations in those areas. Errors in cloud condensation nuclei concentrations when assuming internally mixed aerosols were quantified using a composition-averaging technique to replicate a sectional aerosol representation, which is common in many state-of-the-art chemical transport models. These errors amount up to 100% for more externally mixed populations, and can remain up to 50% for region that are internally mixed. 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To address this shortcoming, the goal of this thesis was to create a particle-resolved aerosol modeling framework that is also spatially resolved, the first of its kind. Several modeling advances were required to attain this goal. At the core was the development of efficient algorithms for particle transport in three dimensions and particle removal at the surface by dry deposition. Additionally, we have contributed a framework for developing particle-resolved, source-oriented aerosol emissions. This framework is flexible and can make use of a variety of user-defined emission data sets. We applied the newly developed model system to simulate an episode during the Carbonaceous Aerosol and Radiative Effects Study (CARES) campaign in California in June 2010. The interactions of atmospheric transport and spatially distributed emissions led to a rapid aging of aerosols in urban areas resulting in internally mixed populations in those areas. Errors in cloud condensation nuclei concentrations when assuming internally mixed aerosols were quantified using a composition-averaging technique to replicate a sectional aerosol representation, which is common in many state-of-the-art chemical transport models. These errors amount up to 100% for more externally mixed populations, and can remain up to 50% for region that are internally mixed. 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