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Analysis of Drinking Water Quality a...

Ngasala, Tulakemelwa Mhamilawa.

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Analysis of Drinking Water Quality and Sanitation in a Peri-urban Area of Dar es Salaam, Tanzania.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analysis of Drinking Water Quality and Sanitation in a Peri-urban Area of Dar es Salaam, Tanzania./
Author:	Ngasala, Tulakemelwa Mhamilawa.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	224 p.
Notes:	Source: Dissertations Abstracts International, Volume: 81-06, Section: A.
Contained By:	Dissertations Abstracts International81-06A.
Subject:	Civil engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27665618
ISBN:	9781392787717

Analysis of Drinking Water Quality and Sanitation in a Peri-urban Area of Dar es Salaam, Tanzania.
Ngasala, Tulakemelwa Mhamilawa.

Analysis of Drinking Water Quality and Sanitation in a Peri-urban Area of Dar es Salaam, Tanzania. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 224 p.

Source: Dissertations Abstracts International, Volume: 81-06, Section: A.

Thesis (Ph.D.)--Michigan State University, 2019.

This item must not be sold to any third party vendors.

While the Sustainable Development Goal 6 called for universal access to water and sanitation by 2030, the challenge of achieving this goal seems daunting in the context of the bourgeoning peri- urban communities of the developing world. These areas are often in a regulatory grey area, receiving municipal water on an irregular basis and lacking sanitation and other basic services. And yet, SDG 6 recognizes that improving global health and wellbeing is critically linked to addressing this problem. A multi-method study of the peri-urban area of Dar es Salaam was conducted to determine the extent of the problem and to make recommendations for system-wide approaches to alleviate the risk of waterborne disease. Existing water sources in the area were identified. Water collection and storage practices were assessed at the household level to determine how water from relatively clean sources becomes contaminated. Escherichia coli (E. coli), nitrate, and total dissolved solid (TDS) were analyzed as indicators for the sewage contamination. Bivariate correlation and univariate regression analyses were used to identify the sources of contamination. The assessment focused on the relationship and association of water contamination with site-specific variables. The variable that had the highest negative impact to the water source was analyzed by using a groundwater flow and contaminant transport model as a tool to make recommendations for proper site-specific sanitation practices. Of the three water sources identified (city water, vendors, and domestic wells), water quality analysis showed that city water at the point of collection (POC) was deemed excellent, whereas it diminished at the point of use (POU) for all three water sources. Reasons for change in water quality at POU and POC were due to mixing of water from different water sources at homes during storage. Using a multinomial regression model, the main reason for mixing water was determined to be the dilution of the salty taste of well water (p < 0.05) and insufficient storage containers (p < 0.05). Of the three water sources identified, domestic wells were found to be the most contaminated. Further analysis on the domestic wells showed a significant contamination, where 80% of wells tested contained E. coli. Also, 58% and 81% of wells tested had concentrations of nitrate and TDS, respectively, that exceeded the WHO guidelines. Univariate regression analysis confirmed the association of contaminants with distance of a well from a sanitation system and well depth (p < 0.05). Groundwater transport modeling showed a strong correlation between the tracer and contaminants and the tracer and distance and helped identify the safe well setback distance that is specific to site conditions, soil type, and aquifer properties. Groundwater modeling was shown to be a good assessment tool for contamination within an aquifer system in urban overpopulated areas of developing countries. Our findings also indicate that the risk of exposure to waterborne disease comes from a combination of factors that involve multiple actors, from improved awareness and sanitation practices to improved regulatory oversight, supply practices, and sanitation technologies.

ISBN: 9781392787717Subjects--Topical Terms:

860360
Civil engineering.

Analysis of Drinking Water Quality and Sanitation in a Peri-urban Area of Dar es Salaam, Tanzania.
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245 1 0 $a Analysis of Drinking Water Quality and Sanitation in a Peri-urban Area of Dar es Salaam, Tanzania.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 224 p.
500 $a Source: Dissertations Abstracts International, Volume: 81-06, Section: A.
500 $a Advisor: Masten, Susan;Mantha, Phanikumar.
502 $a Thesis (Ph.D.)--Michigan State University, 2019.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a While the Sustainable Development Goal 6 called for universal access to water and sanitation by 2030, the challenge of achieving this goal seems daunting in the context of the bourgeoning peri- urban communities of the developing world. These areas are often in a regulatory grey area, receiving municipal water on an irregular basis and lacking sanitation and other basic services. And yet, SDG 6 recognizes that improving global health and wellbeing is critically linked to addressing this problem. A multi-method study of the peri-urban area of Dar es Salaam was conducted to determine the extent of the problem and to make recommendations for system-wide approaches to alleviate the risk of waterborne disease. Existing water sources in the area were identified. Water collection and storage practices were assessed at the household level to determine how water from relatively clean sources becomes contaminated. Escherichia coli (E. coli), nitrate, and total dissolved solid (TDS) were analyzed as indicators for the sewage contamination. Bivariate correlation and univariate regression analyses were used to identify the sources of contamination. The assessment focused on the relationship and association of water contamination with site-specific variables. The variable that had the highest negative impact to the water source was analyzed by using a groundwater flow and contaminant transport model as a tool to make recommendations for proper site-specific sanitation practices. Of the three water sources identified (city water, vendors, and domestic wells), water quality analysis showed that city water at the point of collection (POC) was deemed excellent, whereas it diminished at the point of use (POU) for all three water sources. Reasons for change in water quality at POU and POC were due to mixing of water from different water sources at homes during storage. Using a multinomial regression model, the main reason for mixing water was determined to be the dilution of the salty taste of well water (p < 0.05) and insufficient storage containers (p < 0.05). Of the three water sources identified, domestic wells were found to be the most contaminated. Further analysis on the domestic wells showed a significant contamination, where 80% of wells tested contained E. coli. Also, 58% and 81% of wells tested had concentrations of nitrate and TDS, respectively, that exceeded the WHO guidelines. Univariate regression analysis confirmed the association of contaminants with distance of a well from a sanitation system and well depth (p < 0.05). Groundwater transport modeling showed a strong correlation between the tracer and contaminants and the tracer and distance and helped identify the safe well setback distance that is specific to site conditions, soil type, and aquifer properties. Groundwater modeling was shown to be a good assessment tool for contamination within an aquifer system in urban overpopulated areas of developing countries. Our findings also indicate that the risk of exposure to waterborne disease comes from a combination of factors that involve multiple actors, from improved awareness and sanitation practices to improved regulatory oversight, supply practices, and sanitation technologies.
590 $a School code: 0128.
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