Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/17465
Title: Integrating Field-Based wastewater characterization and multivariate analysis for nature-based rural sanitation planning
Authors: Sinha, Deborshee
Jain, Mayur Shirish
Keywords: Decentralized systems;Domestic wastewater;Initial characterization;Multivariate statistical analysis;Nature-based solutions;Sustainable sanitation planning
Issue Date: 2025
Publisher: Springer Science and Business Media B.V.
Citation: Sinha, 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.
Abstract: Wastewater 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/L
Cl⁻: 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.
URI: https://dx.doi.org/10.1007/s10668-025-07068-5
https://dspace.iiti.ac.in:8080/jspui/handle/123456789/17465
ISSN: 1387-585X
Type of Material: Journal Article
Appears in Collections:Department of Civil Engineering

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