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Disinfectant control in drinking water networks: Integrating advection–dispersion–reaction models and byproduct constraints
Effective disinfection is essential for maintaining water quality standards in distribution networks. Chlorination, as the most used technique, ensures safe water by maintaining sufficient chlorine residuals but also leads to the formation of disinfection byproducts (DBPs). These DBPs pose health ri...
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Published in: | Water research (Oxford) 2024-12, Vol.267, p.122441, Article 122441 |
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description | Effective disinfection is essential for maintaining water quality standards in distribution networks. Chlorination, as the most used technique, ensures safe water by maintaining sufficient chlorine residuals but also leads to the formation of disinfection byproducts (DBPs). These DBPs pose health risks, highlighting the need for chlorine injection control (CIC) by booster stations to balance safety and DBPs formation. Prior studies have followed various approaches to address this research problem. However, most of these studies overlook the changing flow conditions and their influence on the evolution of the chlorine and DBPs concentrations by integrating simplified transport-reaction models into CIC. In contrast, this paper proposes a novel CIC method that: (i) integrates multi-species dynamics, (ii) allows for a more accurate representation of the reaction dynamics of chlorine, other substances, and the resulting DBPs formation, and (iii) optimizes for the regulation of chlorine concentrations subject to EPA mandates thereby mitigating network-wide DBPs formation. The novelty of this study lies in its incorporation of time-dependent controllability analysis that captures the control coverage of each booster station. The effectiveness of the proposed CIC method is demonstrated through its application and validation via numerical case studies on different water networks with varying scales, initial conditions, and parameters.
•Disinfection byproduct (DBP) formation from chlorine injections poses health risks.•We develop spatiotemporal advection–dispersion–reaction model of (de)contaminants.•Near real-time chlorine injections are computed under varying network conditions.•Case studies reveal that optimized injections reduce DBP formation and health risks. |
doi_str_mv | 10.1016/j.watres.2024.122441 |
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•Disinfection byproduct (DBP) formation from chlorine injections poses health risks.•We develop spatiotemporal advection–dispersion–reaction model of (de)contaminants.•Near real-time chlorine injections are computed under varying network conditions.•Case studies reveal that optimized injections reduce DBP formation and health risks.</description><subject>Advection–dispersion–reaction</subject><subject>Booster stations injections</subject><subject>Chlorine</subject><subject>Disinfectants</subject><subject>Disinfection</subject><subject>Disinfection byproducts</subject><subject>Drinking Water</subject><subject>Models, Theoretical</subject><subject>Water Pollutants, Chemical</subject><subject>Water Purification - methods</subject><subject>Water quality control</subject><subject>Water Supply</subject><issn>0043-1354</issn><issn>1879-2448</issn><issn>1879-2448</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kM9OXCEUxkmjqVPbN2galm7uyAHuH1w0aew_ExM3uiYMnDGMd2AERuPKvoNv2Ccp47UuXR3O4fvOBz9CPgObA4PueDW_NyVhnnPG5Rw4lxLekRkMvWrqedgjM8akaEC08oB8yHnFGONcqPfkQCiuhJAwI4_fffZhibaYUKiNoaQ4Uh-oSz7c-HBNawomGrDcx3STT-hZKHidTNndGXdXnT6Gv3-enM8bTHlqEprnOV1Hh2OmJji6eNik6Lb2OSaXZHwo-SPZX5ox46eXekiufv64PP3dnF_8Ojv9dt5YPvSlgX7ROg4GWtm2wgk5dG6AJTjRd_XHHQgjW6s6NVhheqY4QKes4L0RiwGYEYfkaNpb33C7xVz02meL42gCxm3WAljXC86kqlI5SW2KOSdc6k3ya5MeNDC9Q69XekKvd-j1hL7avrwkbBdrdK-m_6yr4OskqEDwzmPS2XoMFp1PlaJ20b-d8A_cj5rk</recordid><startdate>20241201</startdate><enddate>20241201</enddate><creator>Elsherif, Salma M.</creator><creator>Taha, Ahmad F.</creator><creator>Abokifa, Ahmed A.</creator><general>Elsevier Ltd</general><scope>6I.</scope><scope>AAFTH</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><orcidid>https://orcid.org/0000-0002-2474-6670</orcidid><orcidid>https://orcid.org/0000-0002-1814-9431</orcidid></search><sort><creationdate>20241201</creationdate><title>Disinfectant control in drinking water networks: Integrating advection–dispersion–reaction models and byproduct constraints</title><author>Elsherif, Salma M. ; Taha, Ahmad F. ; Abokifa, Ahmed A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c287t-17b5d21a154553d3486d81f1d376187613a45c9698c3a70921169c327a3b810a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Advection–dispersion–reaction</topic><topic>Booster stations injections</topic><topic>Chlorine</topic><topic>Disinfectants</topic><topic>Disinfection</topic><topic>Disinfection byproducts</topic><topic>Drinking Water</topic><topic>Models, Theoretical</topic><topic>Water Pollutants, Chemical</topic><topic>Water Purification - methods</topic><topic>Water quality control</topic><topic>Water Supply</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Elsherif, Salma M.</creatorcontrib><creatorcontrib>Taha, Ahmad F.</creatorcontrib><creatorcontrib>Abokifa, Ahmed A.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</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><jtitle>Water research (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Elsherif, Salma M.</au><au>Taha, Ahmad F.</au><au>Abokifa, Ahmed A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Disinfectant control in drinking water networks: Integrating advection–dispersion–reaction models and byproduct constraints</atitle><jtitle>Water research (Oxford)</jtitle><addtitle>Water Res</addtitle><date>2024-12-01</date><risdate>2024</risdate><volume>267</volume><spage>122441</spage><pages>122441-</pages><artnum>122441</artnum><issn>0043-1354</issn><issn>1879-2448</issn><eissn>1879-2448</eissn><abstract>Effective disinfection is essential for maintaining water quality standards in distribution networks. Chlorination, as the most used technique, ensures safe water by maintaining sufficient chlorine residuals but also leads to the formation of disinfection byproducts (DBPs). These DBPs pose health risks, highlighting the need for chlorine injection control (CIC) by booster stations to balance safety and DBPs formation. Prior studies have followed various approaches to address this research problem. However, most of these studies overlook the changing flow conditions and their influence on the evolution of the chlorine and DBPs concentrations by integrating simplified transport-reaction models into CIC. In contrast, this paper proposes a novel CIC method that: (i) integrates multi-species dynamics, (ii) allows for a more accurate representation of the reaction dynamics of chlorine, other substances, and the resulting DBPs formation, and (iii) optimizes for the regulation of chlorine concentrations subject to EPA mandates thereby mitigating network-wide DBPs formation. The novelty of this study lies in its incorporation of time-dependent controllability analysis that captures the control coverage of each booster station. The effectiveness of the proposed CIC method is demonstrated through its application and validation via numerical case studies on different water networks with varying scales, initial conditions, and parameters.
•Disinfection byproduct (DBP) formation from chlorine injections poses health risks.•We develop spatiotemporal advection–dispersion–reaction model of (de)contaminants.•Near real-time chlorine injections are computed under varying network conditions.•Case studies reveal that optimized injections reduce DBP formation and health risks.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>39293341</pmid><doi>10.1016/j.watres.2024.122441</doi><orcidid>https://orcid.org/0000-0002-2474-6670</orcidid><orcidid>https://orcid.org/0000-0002-1814-9431</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Advection–dispersion–reaction Booster stations injections Chlorine Disinfectants Disinfection Disinfection byproducts Drinking Water Models, Theoretical Water Pollutants, Chemical Water Purification - methods Water quality control Water Supply |
title | Disinfectant control in drinking water networks: Integrating advection–dispersion–reaction models and byproduct constraints |
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