Literature DB >> 20888682

A decision model for selecting sustainable drinking water supply and greywater reuse systems for developing communities with a case study in Cimahi, Indonesia.

Justin J Henriques1, Garrick E Louis.   

Abstract

Capacity Factor Analysis is a decision support system for selection of appropriate technologies for municipal sanitation services in developing communities. Developing communities are those that lack the capability to provide adequate access to one or more essential services, such as water and sanitation, to their residents. This research developed two elements of Capacity Factor Analysis: a capacity factor based classification for technologies using requirements analysis, and a matching policy for choosing technology options. First, requirements analysis is used to develop a ranking for drinking water supply and greywater reuse technologies. Second, using the Capacity Factor Analysis approach, a matching policy is developed to guide decision makers in selecting the appropriate drinking water supply or greywater reuse technology option for their community. Finally, a scenario-based informal hypothesis test is developed to assist in qualitative model validation through case study. Capacity Factor Analysis is then applied in Cimahi Indonesia as a form of validation. The completed Capacity Factor Analysis model will allow developing communities to select drinking water supply and greywater reuse systems that are safe, affordable, able to be built and managed by the community using local resources, and are amenable to expansion as the community's management capacity increases.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 20888682     DOI: 10.1016/j.jenvman.2010.09.016

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  1 in total

1.  Assessment of municipal infrastructure development and its critical influencing factors in urban China: A FA and STIRPAT approach.

Authors:  Yu Li; Ji Zheng; Fei Li; Xueting Jin; Chen Xu
Journal:  PLoS One       Date:  2017-08-07       Impact factor: 3.240

  1 in total

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