Data for: Evaluation of conceptual model and predictors of faecal sludge dewatering performance in Senegal and Tanzania

Published: 26 Sep 2019 | Version 1 | DOI: 10.17632/w5y55vf3cn.1
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Description of this data

Data for Evaluation of conceptual model and predictors of faecal sludge dewatering performance in Senegal and Tanzania. Includes typically measured physical-chemical characteristics of faecal sludge samples (pH, EC, TS, TSS, VS, VSS) along with EPS concentration and fractionation and concentration of soluble cations. Also includes microbial community data for each sample, and questionnaire data collected at each sampling location. The full text of the questionnaire is included in the SI for this publication.

Experiment data files

This data is associated with the following publication:

Evaluation of conceptual model and predictors of faecal sludge dewatering performance in Senegal and Tanzania

Published in: Water Research

Latest version

  • Version 1

    2019-09-26

    Published: 2019-09-26

    DOI: 10.17632/w5y55vf3cn.1

    Cite this dataset

    Ward, Barbara; Traber, Jacqueline; Gueye, Amadou; Diop, Becaye; Morgenroth, Eberhard; Strande, Linda (2019), “Data for: Evaluation of conceptual model and predictors of faecal sludge dewatering performance in Senegal and Tanzania”, Mendeley Data, v1 http://dx.doi.org/10.17632/w5y55vf3cn.1

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Categories

Sanitation, Sludge Management, Municipal Wastewater, Sludge Dewatering

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?

This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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