{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/108213"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/108213","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Quantitative sustainable design of water and sanitation infrastructure in resource-rich and resource-limited contexts","abstract":"Quantitative sustainable design, a process of mechanistically linking design and operational decisions to sustainability indicators, can inform decision-making for water and sanitation infrastructure by enabling navigation of trade-offs across dimensions of sustainability (e.g., environmental, economic, human health). However, to be useful for decision-making, sustainable design tools must address context-specific objectives and constraints. This research addresses critical barriers for the practicality of two tools – life cycle assessment (LCA) and quantitative microbial risk assessment (QMRA) – in two different contexts. First in a resource-rich context, critical opportunities for advancing the use of LCA were identified including the integration of spatial considerations (e.g., spatialized characterization factors), water quantity (e.g., water quantity indicators), public health (e.g., integration with risk assessment), economic and social assessments (e.g., life cycle costing and social LCA), along with prioritization of continuous stakeholder engagement. In the second context of resource-limited communities, specifically an informal settlement in Uganda, this work leveraged uncertainty and sensitivity analyses to consider the implications of censored data management, identify major sources of uncertainty (e.g., pathogen concentrations, hand to mouth contact frequency), and incorporate risk perceptions to improve the utility of QMRA in these settings. Finally, to elucidate trade-offs among levels of data collection and implications for decision-making in resource-limited settings, two case studies of informal settlements were compared for five levels of data collection – (1) Demographic Health Survey data, (2) site-specific household surveys, (3) fecal indicator and pathogen detection, (4) QMRA using indicator to pathogen ratios, and (5) QMRA using pathogen data. In both settings, adapting quantitative sustainable design tools to address context-specific objectives and constraints can help make progress toward more sustainable water and sanitation infrastructure.","abstract_html":"Quantitative sustainable design, a process of mechanistically linking design and operational decisions to sustainability indicators, can inform decision-making for water and sanitation infrastructure by enabling navigation of trade-offs across dimensions of sustainability (e.g., environmental, economic, human health). However, to be useful for decision-making, sustainable design tools must address context-specific objectives and constraints. This research addresses critical barriers for the practicality of two tools – life cycle assessment (LCA) and quantitative microbial risk assessment (QMRA) – in two different contexts. First in a resource-rich context, critical opportunities for advancing the use of LCA were identified including the integration of spatial considerations (e.g., spatialized characterization factors), water quantity (e.g., water quantity indicators), public health (e.g., integration with risk assessment), economic and social assessments (e.g., life cycle costing and social LCA), along with prioritization of continuous stakeholder engagement. In the second context of resource-limited communities, specifically an informal settlement in Uganda, this work leveraged uncertainty and sensitivity analyses to consider the implications of censored data management, identify major sources of uncertainty (e.g., pathogen concentrations, hand to mouth contact frequency), and incorporate risk perceptions to improve the utility of QMRA in these settings. Finally, to elucidate trade-offs among levels of data collection and implications for decision-making in resource-limited settings, two case studies of informal settlements were compared for five levels of data collection – (1) Demographic Health Survey data, (2) site-specific household surveys, (3) fecal indicator and pathogen detection, (4) QMRA using indicator to pathogen ratios, and (5) QMRA using pathogen data. In both settings, adapting quantitative sustainable design tools to address context-specific objectives and constraints can help make progress toward more sustainable water and sanitation infrastructure.","abstract_has_math":false,"creators":["Byrne, Diana Marie"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Environ Engr in Civil Engr","degree_department":null,"school":null,"contributors":["Guest, Jeremy S","Winter-Nelson, Alex","Zerai, Assata","Smith, Rebecca L","Zilles, Julie"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-08-27T00:46:46Z","date_published":"2020-08-27T00:46:46Z","updated_at":"2026-07-22T22:24:48Z","subjects":["sustainable design"],"languages":["en"],"rights":["Copyright 2020 Diana Byrne"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/108213","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Guest, Jeremy S","Winter-Nelson, Alex","Zerai, Assata","Smith, Rebecca L","Zilles, Julie"]},{"key":"dc:creator","label":"Author","values":["Byrne, Diana Marie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-08-27T00:46:46Z","2022-08-27T00:51:40Z","2019-12-20","2020-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Environ Engr in Civil Engr"]},{"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":["sustainable design"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Diana Byrne"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/108213"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Quantitative sustainable design, a process of mechanistically linking design and operational decisions to sustainability indicators, can inform decision-making for water and sanitation infrastructure by enabling navigation of trade-offs across dimensions of sustainability (e.g., environmental, economic, human health). However, to be useful for decision-making, sustainable design tools must address context-specific objectives and constraints. This research addresses critical barriers for the practicality of two tools – life cycle assessment (LCA) and quantitative microbial risk assessment (QMRA) – in two different contexts. First in a resource-rich context, critical opportunities for advancing the use of LCA were identified including the integration of spatial considerations (e.g., spatialized characterization factors), water quantity (e.g., water quantity indicators), public health (e.g., integration with risk assessment), economic and social assessments (e.g., life cycle costing and social LCA), along with prioritization of continuous stakeholder engagement. In the second context of resource-limited communities, specifically an informal settlement in Uganda, this work leveraged uncertainty and sensitivity analyses to consider the implications of censored data management, identify major sources of uncertainty (e.g., pathogen concentrations, hand to mouth contact frequency), and incorporate risk perceptions to improve the utility of QMRA in these settings. Finally, to elucidate trade-offs among levels of data collection and implications for decision-making in resource-limited settings, two case studies of informal settlements were compared for five levels of data collection – (1) Demographic Health Survey data, (2) site-specific household surveys, (3) fecal indicator and pathogen detection, (4) QMRA using indicator to pathogen ratios, and (5) QMRA using pathogen data. In both settings, adapting quantitative sustainable design tools to address context-specific objectives and constraints can help make progress toward more sustainable water and sanitation infrastructure.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01","The student, Diana Byrne, accepted the attached license on 2019-12-20 at 10:26.","The student, Diana Byrne, submitted this Dissertation for approval on 2019-12-20 at 10:39.","This Dissertation was approved for publication on 2019-12-20 at 11:15.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14835 on 2020-08-25 at 17:38:14","Made available in DSpace on 2020-08-27T00:46:46Z (GMT). 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However, to be useful for decision-making, sustainable design tools must address context-specific objectives and constraints. This research addresses critical barriers for the practicality of two tools – life cycle assessment (LCA) and quantitative microbial risk assessment (QMRA) – in two different contexts. First in a resource-rich context, critical opportunities for advancing the use of LCA were identified including the integration of spatial considerations (e.g., spatialized characterization factors), water quantity (e.g., water quantity indicators), public health (e.g., integration with risk assessment), economic and social assessments (e.g., life cycle costing and social LCA), along with prioritization of continuous stakeholder engagement. In the second context of resource-limited communities, specifically an informal settlement in Uganda, this work leveraged uncertainty and sensitivity analyses to consider the implications of censored data management, identify major sources of uncertainty (e.g., pathogen concentrations, hand to mouth contact frequency), and incorporate risk perceptions to improve the utility of QMRA in these settings. Finally, to elucidate trade-offs among levels of data collection and implications for decision-making in resource-limited settings, two case studies of informal settlements were compared for five levels of data collection – (1) Demographic Health Survey data, (2) site-specific household surveys, (3) fecal indicator and pathogen detection, (4) QMRA using indicator to pathogen ratios, and (5) QMRA using pathogen data. In both settings, adapting quantitative sustainable design tools to address context-specific objectives and constraints can help make progress toward more sustainable water and sanitation infrastructure.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-05-01","The student, Diana Byrne, accepted the attached license on 2019-12-20 at 10:26.","The student, Diana Byrne, submitted this Dissertation for approval on 2019-12-20 at 10:39.","This Dissertation was approved for publication on 2019-12-20 at 11:15.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14835 on 2020-08-25 at 17:38:14","Made available in DSpace on 2020-08-27T00:46:46Z (GMT). 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