Model-driven experimental evaluation of struvite nucleation, growth and aggregation kinetics
Nutrient stewardship is emerging as an issue of global importance, which will drive the development of nutrient recovery in the near to medium future. This will impact wastewater treatment practices, environmental protection, sustainable agriculture and global food security. A modelling framework fo...
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Veröffentlicht in: | Water research (Oxford) 2014-06, Vol.56, p.122-132 |
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description | Nutrient stewardship is emerging as an issue of global importance, which will drive the development of nutrient recovery in the near to medium future. This will impact wastewater treatment practices, environmental protection, sustainable agriculture and global food security. A modelling framework for precipitation-based nutrient recovery systems has been developed, incorporating non-ideal solution thermodynamics, a dynamic mass balance and a dynamic population balance to track the development of the precipitating particles. The mechanisms of crystal nucleation and growth and, importantly, aggregation are considered. A novel approach to the population balance embeds the nucleation rate into the model, enabling direct regression of its kinetic parameters. The case study chosen for the modelling framework is that of struvite precipitation, given its wide interest and commercial promise as one possible nutrient recovery pathway. Power law kinetic parameters for nucleation, crystal growth and particle aggregation rates were regressed from an ensemble data set generated from 14 laboratory seeded batch experiments using synthetic solutions. These experiments were highly repeatable, giving confidence to the regressed parameter values. The model successfully describes the dynamic responses of solution pH, the evolving particle size distribution subject to nucleation, growth and aggregation effects and the aqueous magnesium concentration in the liquid phase. The proposed modelling framework could well be extended to other, more complex systems, leading to an improved understanding and commensurately greater confidence in the design, operation and optimisation of large-scale nutrient recovery processes from complex effluents.
[Display omitted]
•Process modelling framework for nutrient recovery through precipitation is presented.•Nucleation, crystal growth and aggregation processes drive a population balance.•Estimated parameters enable the model to describe experimental system.•Nucleation found to be the least significant mechanism.•The framework can be expanded to incorporate other solid phases and additional elements. |
doi_str_mv | 10.1016/j.watres.2014.03.002 |
format | Article |
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[Display omitted]
•Process modelling framework for nutrient recovery through precipitation is presented.•Nucleation, crystal growth and aggregation processes drive a population balance.•Estimated parameters enable the model to describe experimental system.•Nucleation found to be the least significant mechanism.•The framework can be expanded to incorporate other solid phases and additional elements.</description><identifier>ISSN: 0043-1354</identifier><identifier>EISSN: 1879-2448</identifier><identifier>DOI: 10.1016/j.watres.2014.03.002</identifier><identifier>PMID: 24662095</identifier><identifier>CODEN: WATRAG</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Agglomeration ; Applied sciences ; Dynamical systems ; Dynamics ; Exact sciences and technology ; General purification processes ; Kinetics ; Magnesium ; Magnesium Compounds - chemistry ; Mathematical models ; Models, Chemical ; Nucleation ; Nucleation, growth and aggregation ; Nutrient recovery ; Nutrients ; Parameter estimation ; Phosphates - chemistry ; Phosphorus - chemistry ; Pollution ; Population balance ; Process model ; Recovery ; Struvite ; Wastewaters ; Water Pollutants, Chemical - chemistry ; Water treatment and pollution</subject><ispartof>Water research (Oxford), 2014-06, Vol.56, p.122-132</ispartof><rights>2014 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2014 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c458t-46398000a32faa49e5a0f092c40210d1fc5190099fe63b2d5ac1404793d4c3a83</citedby><cites>FETCH-LOGICAL-c458t-46398000a32faa49e5a0f092c40210d1fc5190099fe63b2d5ac1404793d4c3a83</cites><orcidid>0000-0002-0964-1328</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.watres.2014.03.002$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28428280$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24662095$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Galbraith, S.C.</creatorcontrib><creatorcontrib>Schneider, P.A.</creatorcontrib><creatorcontrib>Flood, A.E.</creatorcontrib><title>Model-driven experimental evaluation of struvite nucleation, growth and aggregation kinetics</title><title>Water research (Oxford)</title><addtitle>Water Res</addtitle><description>Nutrient stewardship is emerging as an issue of global importance, which will drive the development of nutrient recovery in the near to medium future. This will impact wastewater treatment practices, environmental protection, sustainable agriculture and global food security. A modelling framework for precipitation-based nutrient recovery systems has been developed, incorporating non-ideal solution thermodynamics, a dynamic mass balance and a dynamic population balance to track the development of the precipitating particles. The mechanisms of crystal nucleation and growth and, importantly, aggregation are considered. A novel approach to the population balance embeds the nucleation rate into the model, enabling direct regression of its kinetic parameters. The case study chosen for the modelling framework is that of struvite precipitation, given its wide interest and commercial promise as one possible nutrient recovery pathway. Power law kinetic parameters for nucleation, crystal growth and particle aggregation rates were regressed from an ensemble data set generated from 14 laboratory seeded batch experiments using synthetic solutions. These experiments were highly repeatable, giving confidence to the regressed parameter values. The model successfully describes the dynamic responses of solution pH, the evolving particle size distribution subject to nucleation, growth and aggregation effects and the aqueous magnesium concentration in the liquid phase. The proposed modelling framework could well be extended to other, more complex systems, leading to an improved understanding and commensurately greater confidence in the design, operation and optimisation of large-scale nutrient recovery processes from complex effluents.
[Display omitted]
•Process modelling framework for nutrient recovery through precipitation is presented.•Nucleation, crystal growth and aggregation processes drive a population balance.•Estimated parameters enable the model to describe experimental system.•Nucleation found to be the least significant mechanism.•The framework can be expanded to incorporate other solid phases and additional elements.</description><subject>Agglomeration</subject><subject>Applied sciences</subject><subject>Dynamical systems</subject><subject>Dynamics</subject><subject>Exact sciences and technology</subject><subject>General purification processes</subject><subject>Kinetics</subject><subject>Magnesium</subject><subject>Magnesium Compounds - chemistry</subject><subject>Mathematical models</subject><subject>Models, Chemical</subject><subject>Nucleation</subject><subject>Nucleation, growth and aggregation</subject><subject>Nutrient recovery</subject><subject>Nutrients</subject><subject>Parameter estimation</subject><subject>Phosphates - chemistry</subject><subject>Phosphorus - chemistry</subject><subject>Pollution</subject><subject>Population balance</subject><subject>Process model</subject><subject>Recovery</subject><subject>Struvite</subject><subject>Wastewaters</subject><subject>Water Pollutants, Chemical - chemistry</subject><subject>Water treatment and pollution</subject><issn>0043-1354</issn><issn>1879-2448</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqN0U2LFDEQBuAgiju7-g9E-iJ42G4rH92TXARZ_IIVL3oTQm1SPWbs6R6T9Kz-ezP2qDfZU6B4qlLUy9gTDg0H3r3YNreYI6VGAFcNyAZA3GMrrtemFkrp-2wFoGTNZavO2HlKWyhCSPOQnQnVdQJMu2JfPkyehtrHcKCxoh97imFHY8ahogMOM-YwjdXUVynH-RAyVePsBvpdvqw2cbrNXyscfYWbTaTNwr-FkXJw6RF70OOQ6PHpvWCf37z-dPWuvv749v3Vq-vaqVbnWnXS6LIcStEjKkMtQg9GOAWCg-e9a7kBMKanTt4I36LjCtTaSK-cRC0v2PNl7j5O32dK2e5CcjQMONI0J8vXaw2q08bcgR4dcLjD1LKVLpqLQtVCXZxSitTbfTkjxp-Wgz2mZbd2Scse07IgbcmitD09_TDf7Mj_bfoTTwHPTgCTw6GPOLqQ_jmthBYainu5OCpXPgSKNrlAoyMfIrls_RT-v8kvll60UQ</recordid><startdate>20140601</startdate><enddate>20140601</enddate><creator>Galbraith, S.C.</creator><creator>Schneider, P.A.</creator><creator>Flood, A.E.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QH</scope><scope>7ST</scope><scope>7U6</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>L.G</scope><scope>SOI</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><orcidid>https://orcid.org/0000-0002-0964-1328</orcidid></search><sort><creationdate>20140601</creationdate><title>Model-driven experimental evaluation of struvite nucleation, growth and aggregation kinetics</title><author>Galbraith, S.C. ; Schneider, P.A. ; Flood, A.E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c458t-46398000a32faa49e5a0f092c40210d1fc5190099fe63b2d5ac1404793d4c3a83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Agglomeration</topic><topic>Applied sciences</topic><topic>Dynamical systems</topic><topic>Dynamics</topic><topic>Exact sciences and technology</topic><topic>General purification processes</topic><topic>Kinetics</topic><topic>Magnesium</topic><topic>Magnesium Compounds - chemistry</topic><topic>Mathematical models</topic><topic>Models, Chemical</topic><topic>Nucleation</topic><topic>Nucleation, growth and aggregation</topic><topic>Nutrient recovery</topic><topic>Nutrients</topic><topic>Parameter estimation</topic><topic>Phosphates - chemistry</topic><topic>Phosphorus - chemistry</topic><topic>Pollution</topic><topic>Population balance</topic><topic>Process model</topic><topic>Recovery</topic><topic>Struvite</topic><topic>Wastewaters</topic><topic>Water Pollutants, Chemical - chemistry</topic><topic>Water treatment and pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Galbraith, S.C.</creatorcontrib><creatorcontrib>Schneider, P.A.</creatorcontrib><creatorcontrib>Flood, A.E.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Water research (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Galbraith, S.C.</au><au>Schneider, P.A.</au><au>Flood, A.E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Model-driven experimental evaluation of struvite nucleation, growth and aggregation kinetics</atitle><jtitle>Water research (Oxford)</jtitle><addtitle>Water Res</addtitle><date>2014-06-01</date><risdate>2014</risdate><volume>56</volume><spage>122</spage><epage>132</epage><pages>122-132</pages><issn>0043-1354</issn><eissn>1879-2448</eissn><coden>WATRAG</coden><abstract>Nutrient stewardship is emerging as an issue of global importance, which will drive the development of nutrient recovery in the near to medium future. This will impact wastewater treatment practices, environmental protection, sustainable agriculture and global food security. A modelling framework for precipitation-based nutrient recovery systems has been developed, incorporating non-ideal solution thermodynamics, a dynamic mass balance and a dynamic population balance to track the development of the precipitating particles. The mechanisms of crystal nucleation and growth and, importantly, aggregation are considered. A novel approach to the population balance embeds the nucleation rate into the model, enabling direct regression of its kinetic parameters. The case study chosen for the modelling framework is that of struvite precipitation, given its wide interest and commercial promise as one possible nutrient recovery pathway. Power law kinetic parameters for nucleation, crystal growth and particle aggregation rates were regressed from an ensemble data set generated from 14 laboratory seeded batch experiments using synthetic solutions. These experiments were highly repeatable, giving confidence to the regressed parameter values. The model successfully describes the dynamic responses of solution pH, the evolving particle size distribution subject to nucleation, growth and aggregation effects and the aqueous magnesium concentration in the liquid phase. The proposed modelling framework could well be extended to other, more complex systems, leading to an improved understanding and commensurately greater confidence in the design, operation and optimisation of large-scale nutrient recovery processes from complex effluents.
[Display omitted]
•Process modelling framework for nutrient recovery through precipitation is presented.•Nucleation, crystal growth and aggregation processes drive a population balance.•Estimated parameters enable the model to describe experimental system.•Nucleation found to be the least significant mechanism.•The framework can be expanded to incorporate other solid phases and additional elements.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>24662095</pmid><doi>10.1016/j.watres.2014.03.002</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-0964-1328</orcidid></addata></record> |
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subjects | Agglomeration Applied sciences Dynamical systems Dynamics Exact sciences and technology General purification processes Kinetics Magnesium Magnesium Compounds - chemistry Mathematical models Models, Chemical Nucleation Nucleation, growth and aggregation Nutrient recovery Nutrients Parameter estimation Phosphates - chemistry Phosphorus - chemistry Pollution Population balance Process model Recovery Struvite Wastewaters Water Pollutants, Chemical - chemistry Water treatment and pollution |
title | Model-driven experimental evaluation of struvite nucleation, growth and aggregation kinetics |
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