{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/69969"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/69969","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Particle Class Balance for Apportioning Aerosol Mass","abstract":"Computer-controlled scanning electron microscopy (CCSEM) has been known as a powerful tool to characterize individual particles including various size parameters and major elemental composition in a short analysis time. To exploit CCSEM as a source apportionment receptor modeling technique, it is important to define the membership of each particle in a well defined particle class. Various clustering methods were examined to obtain possible members of homogeneous particle classes. An expert system was then used to build a universal classification rule based on examples of the homogeneous particle classes. The rule was extensively tested and completely confirmed. Ambient samples were classified by the universal classification rule. The mass fraction and its uncertainty for each homogeneous class in both source samples were calculated in order to be used as a source profile. Similarly, mass fractions and uncertainties were calculated for ambient samples. Based on this information, the concept of particle class balance (PCB) was developed as one of the receptor models. These methods were explored and tested, using data from a study in El Paso, Texas.","abstract_html":"Computer-controlled scanning electron microscopy (CCSEM) has been known as a powerful tool to characterize individual particles including various size parameters and major elemental composition in a short analysis time. To exploit CCSEM as a source apportionment receptor modeling technique, it is important to define the membership of each particle in a well defined particle class. Various clustering methods were examined to obtain possible members of homogeneous particle classes. An expert system was then used to build a universal classification rule based on examples of the homogeneous particle classes. The rule was extensively tested and completely confirmed. Ambient samples were classified by the universal classification rule. The mass fraction and its uncertainty for each homogeneous class in both source samples were calculated in order to be used as a source profile. Similarly, mass fractions and uncertainties were calculated for ambient samples. Based on this information, the concept of particle class balance (PCB) was developed as one of the receptor models. These methods were explored and tested, using data from a study in El Paso, Texas.","abstract_has_math":false,"creators":["Kim, Dong-Sool"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Environmental Engineering","degree_department":null,"school":null,"contributors":["Hopke, Philip K."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-12-15T20:36:28Z","date_published":"2014-12-15T20:36:28Z","updated_at":"2026-07-22T22:26:01Z","subjects":["Environmental Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(UMI)AAI8803087"],"render_values":[{"text":"(UMI)AAI8803087","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/69969","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hopke, Philip K."]},{"key":"dc:creator","label":"Author","values":["Kim, Dong-Sool"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-12-15T20:36:28Z","10000-01-01","1987"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Environmental Engineering"]},{"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":["Environmental Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/69969","(UMI)AAI8803087"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Computer-controlled scanning electron microscopy (CCSEM) has been known as a powerful tool to characterize individual particles including various size parameters and major elemental composition in a short analysis time. 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To exploit CCSEM as a source apportionment receptor modeling technique, it is important to define the membership of each particle in a well defined particle class. Various clustering methods were examined to obtain possible members of homogeneous particle classes. An expert system was then used to build a universal classification rule based on examples of the homogeneous particle classes. The rule was extensively tested and completely confirmed. Ambient samples were classified by the universal classification rule. The mass fraction and its uncertainty for each homogeneous class in both source samples were calculated in order to be used as a source profile. Similarly, mass fractions and uncertainties were calculated for ambient samples. Based on this information, the concept of particle class balance (PCB) was developed as one of the receptor models. 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