Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/17465
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dc.contributor.authorSinha, Deborsheeen_US
dc.contributor.authorJain, Mayur Shirishen_US
dc.date.accessioned2025-12-17T13:28:58Z-
dc.date.available2025-12-17T13:28:58Z-
dc.date.issued2025-
dc.identifier.citationSinha, Deborshee, Uma Bhartiya, and Mayur Shirish Jain. 2025. “Integrating Field-Based Wastewater Characterization and Multivariate Analysis for Nature-Based Rural Sanitation Planning.” Environment, Development and Sustainability. doi:10.1007/s10668-025-07068-5.en_US
dc.identifier.issn1387-585X-
dc.identifier.otherEID(2-s2.0-105024104792)-
dc.identifier.urihttps://dx.doi.org/10.1007/s10668-025-07068-5-
dc.identifier.urihttps://dspace.iiti.ac.in:8080/jspui/handle/123456789/17465-
dc.description.abstractWastewater management in rural areas remains a critical challenge for environmental sustainability and public health in developing countries. Traditional centralized wastewater treatment plants struggle in rural and peri-urban settings due to their high energy demands, cost, limited flexibility towards heterogeneous domestic effluents, and complex operations. Conversely, Nature-based Solutions (NbS) are low-cost, low-energy, and can be managed by the community, making them a better fit for decentralized rural sanitation. Initial characterization provides important information on physical, chemical, and biological parameters of wastewater, enabling informed decisions on proper treatment planning. This research highlights the need for systematic preliminary characterization through proximate and ultimate analysis of household wastewater as a diagnostic step toward planning appropriate Nature-based treatment facilities. Field-based sampling was conducted in seven socio-environmental clusters at Simrol, Madhya Pradesh, covering mixed wastewater discharges. Twenty-one physicochemical and heavy metal parameters were analyzed using APHA methods. Results revealed high organic pollution, with COD ranging from 720 to 2880 mg/L and BOD from 356 to 633 mg/L, alongside elevated ionic loads (Na⁺: 64–166 mg/Len_US
dc.description.abstractCl⁻: 69–489 mg/L). Multivariate statistical techniques, including Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Pearson correlation, were conducted to identify key clusters of contaminants and illustrate relationships. It also presents possible NbS options for the treatment of domestic wastewater. This framework demonstrates that systematic initial characterization coupled with multivariate analysis can inform decentralized NbS planning, mitigate technology failure, and facilitate safe reuse, promoting sustainable rural sanitation. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.en_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media B.V.en_US
dc.sourceEnvironment, Development and Sustainabilityen_US
dc.subjectDecentralized systemsen_US
dc.subjectDomestic wastewateren_US
dc.subjectInitial characterizationen_US
dc.subjectMultivariate statistical analysisen_US
dc.subjectNature-based solutionsen_US
dc.subjectSustainable sanitation planningen_US
dc.titleIntegrating Field-Based wastewater characterization and multivariate analysis for nature-based rural sanitation planningen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Civil Engineering

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