Plantas de Tratamiento de Aguas Residuales

The current versions of the hydraulic models have some issues that need to be considered in future versions and are discussed in more detail below. Despite these issues, the hydraulic models presented here can serve as important tools for filter manufacturers to improve their design, and/or for filter users to derive maximum benefit. The models presented here are, to the best of our knowledge, the first mathematical models capable of predicting how water level, instantaneous filtrate flow rate, and cumulative water production vary over time during use of a ceramic water filter. Future work will be aimed at accounting for the key factors, discussed below, that have not yet been incorporated into the model.

5.5.1 Spatial Variability of Filter Properties

The filter thickness d is treated as spatially uniform, even though our measurements indicated the thickness of the filter bottom may be as much as 50% different from the thickness of the side walls. Similarly, the hydraulic conductivity K is treated as spatially uniform; e.g. for the frustum, the hydraulic conductivity of the bottom is assumed equal to that of the sides. However, previous experiments demonstrated the hydraulic conductivity varied along the wall of paraboloid filters (Miller 2010) and similar conclusions have been observed for frustum filters (Lantagne et al. 2010). Future versions of the hydraulic models could be modified to account for spatial variations in wall thickness and/or hydraulic conductivity. Spatial heterogeneity is a factor in many applications of porous media, and sometimes necessitates progression from analytical models to numerical models. In the case of ceramic filters, analytical models may be able to effectively account for such heterogeneity. Unlike the soil matrix in groundwater science, porous ceramic is a manufactured material, and therefore the properties can more easily

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be controlled. Significant efforts are being made to improve manufacturing processes and reduce material heterogeneity (Raynor 2009). Furthermore, the good agreement between experimental data and the current versions of the models shows that using a single “effective” thickness and conductivity does not prevent the models from accurately describing filter hydraulics.

5.5.2 Estimating Hydraulic Conductivity

The current versions of the models require the hydraulic conductivity, K, to be treated as an adjustable or “fitting” parameter. Ideally, the models would use a priori estimates of K to eliminate the need for data fitting. However, it is likely very difficult to a priori estimate K, because filter construction is likely to vary greatly from one factory to another, and perhaps even between individual filters from a single factory. Unless more stringent quality control measures are implemented, it may be unavoidable that K must be estimated individually for each filter whose performance is of interest. What is desirable, then, is a simple and rapid test that can accurately estimate K, preferably in a time frame shorter than the 28 hr. required for the falling- head tests reported here. For instance, it may be that a constant-head permeability test, in which the filters are kept full during testing, would be able to yield an accurate but more rapid estimate of K. This hypothesis will be tested in a future study.

5.5.3 Effect of Turbidity and Filter Clogging Over Time

It would generally be expected that more turbid water would filter more slowly than less turbid water, because the higher particulate loading would more rapidly clog some of the filter pores. Also, as the turbidity leads to filter clogging, it would be expected that the hydraulic performance of the filter would decline over time (van Halem et al. 2007; van Halem et al.

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2009). The current versions of the hydraulic models do not account for the effect of turbidity on hydraulic performance, nor for the change in hydraulic performance over time.

Several previous studies have investigated how turbidity and other water-quality parameters affect filter hydraulics and filter clogging over time (Ragusa et al. 1994; Pavelic et al. 2007; Siefert and Engesgaard 2012). These studies quantify the rates and effects of clogging due to both physical factors (i.e. decrease in filter porosity as particles accumulate in filter pore spaces) and biological factors (i.e. growth of biofilms or biological colonies that alter filter hydraulics). However, to the best of our knowledge, most or all previous work pertains to granular-media filters or membrane filters, and there has not yet been an investigation into the effects of turbidity on the hydraulics of CWFs. Phenomenological filtration models, as reviewed elsewhere (Crittenden et al. 2005; Iritani et al. 2007) may be applicable to CWFs. However, for CWFs, the situation may be more complicated because the presence of colloidal silver on the inside surface or in the CWF microstructure affects microbial growth (Lantagne et al. 2010; Bielefeldt et al. 2010; Brown and Sobsey 2010; Kallman et al. 2011, Mwabi et al. 2012) and because the leaching of silver nanoparticles over time may also affect filter hydraulics. Therefore, a quantitative description of how turbidity affects filter hydraulics is left for future work.

It is worth noting that, in the field, source waters with high levels of turbidity (i.e. > 30 NTU) are recommended to be pre-treated. Established sedimentation and filtration methods for pre-treatment include the three-pot treatment system or locally produced cloth and paper filters (Mihelcic et al. 2009). Therefore, it is not likely that CWFs would be used to treat highly turbid waters without pre-treatment. In addition, CWF manufacturers have methods for “cleaning” the filter that are provided to a user in training when filters are sold or distributed.

148 5.5.4 Other Filter Configurations

This chapter has focused on only two filter geometries, both of which are based on the same general filter configuration (see Figure 5-1), and were used in the field research component in the Dominican Republic (see Chapter 4). Other ceramic filter configurations that are not manufactured from clay, such as the “candle” filter, are widely used in some locations (Chaudhuri et al. 1994; Clasen and Menon 2007). The candle filters are typically made from a synthetic ceramic, which, as noted elsewhere, requires high-purity raw materials and an industrial manufacturing process, often resulting in a more expensive filter (Oyanedel-Craver and Smith 2008). Therefore, this chapter considered only the filter configurations that are typically made locally with locally available materials, like the ones manufactured in the Dominican Republic and studied in Chapter 4. However, the same general approach applied here is applicable to candle filters, and perhaps to other filter configurations as well (e.g. the “tulip” filter). These extensions are left for future research.

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6 CONCLUSION

Significant progress has been made with regard to the Millennium Development Goal Target 7c, to halve the population without sustainable access to safe drinking water and basic sanitation by 2015. The goal for drinking water, achieving 88% coverage to an improved source, has been reached ahead of the 2015 deadline; however there is evidence that the sustainability of a significant proportion of the water supply infrastructure in developing countries is questionable (Sara and Katz 1996; Harvey and Reed 2006; IRC 2009). In addition, progress reducing the population without access to basic sanitation, currently at 37% without coverage, is well behind the 2015 target of 25%. Lack of access to an improved water source or basic sanitation and hygiene services and/or declining levels of service from existing water, sanitation, and hygiene (WASH) infrastructure can lead to negative impacts on health. Furthermore, disaggregating the WASH monitoring data it is clear that there are inequities with regard to coverage and how improvements in WASH services have been experienced by different demographics (e.g. poor, rural inhabitants, disabled, other marginalized groups). It is therefore important to ensure the appropriate management of water WASH infrastructure.

Understanding the current global status of WASH, this research focuses on the water sector. The objective of this research is to identify the critical factors affecting the management of water supply and treatment at the community or household level, with an emphasis on rural and peri-urban areas in the developing world. Chapter 1 provided background information on

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the status of water and sanitation coverage worldwide and also an overview of the different management models that are used in the provision of water supply services.