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galvis

Water treatment

of bacterial predators

of bacterial predators present in the sand bed and thus reduce their capacity to remove harmful microorganisms (Lloyd, 1974 and 1996). This important potential reduction in biological performance is, however, rarely cited in the technical literature despite the fact it may have a very negative effect on the quality of the treated water. The literature seems to particularly focus instead on the difficulties of treating water sources with small particles of colloidal nature or the impact of high concentrations of particulate matter on the duration of filter runs. Table 2.5 Treatment efficiencies of slow sand filters (Galvis et al, 1992a; Fox et al, 1994; Lambert and Graham, 1995) Water quality parameter Performance or removal capacity Enteric bacteria 90 to 99.9% Enteric viruses 99 to 99.99% Comments Reduced by low temperatures; increased hydraulic rates; coarse and shallow sand beds; and decreased contaminant level References Cleasby et al, 1984; Schellart, 1988; Smet and Visscher, 1989 At 20 o C: 5 logs at 0.2 mh -1 and 3 logs at 0.4 mh -1 Poynter and Slade, 1977; At 6 o C: 3 logs at 0.2 mh -1 and 1 log at 0.4 mh -1 Wheeler et al, 1988 99 to High removal efficiencies, even directly after Bellamy et al, 1985; Logsdon, Giardia cysts 99.99% cleaning (removal of the filter skin) 1987 Crypstosporidium >99.9% Crypstosporidium Oocytes. Pilot scale studies Timms et al, 1995 Cercaria 100% Virtually complete removal Ellis, 1985 The level of turbidity and the nature and Slezak and Sims, 1984; Smet Turbidity < 1 NTU distribution of particles affect treatment capacity and Visscher, 1989 Pesticides 0 to 100% Affected by the rate of biodegradation Lambert and Graham, 1995 DOC 5 to 40% UV-absorbance (254 nm) 5 to 35 % Mean around 16%. Removal appears to be site specific and varies with raw water and O&M Lambert and Graham, 1995 A Slight, but not significant difference in treating upland and lowland water sources. Mean 16-18% Lambert and Graham, 1995 True Colour 25 to 40% Colour associated with organic material and humic acids. 30% being the average Ellis, 1985; Smet and Visscher, 1989 UV-absorbance (400 nm) 15 to 80% Colour ( 0 Hazen). Mean 34%, but upland water sources 42% and lowland water sources 26% Lambert and Graham, 1995 TOC; COD < 15 - 25% Total organic carbon; Chemical Oxygen demand Haarhoff and Cleasby, 1991 AOC 14 to 40% Assimilable organic carbon. Mean about 26%. Lambert and Graham, 1995 BDOC 46 to 75% Biodegradable dissolved org. carbon. Mean 60% Lambert and Graham, 1995 Iron, manganese 30 to 90% Fe levels > 1 mgl -1 reduce the filter runs Ellis, 1985; Di Bernardo, 1993 To prevent high effluent turbidities, frequent blockage of the filter bed (filter runs shorter than one month) or an environment that is unfavourable for microbiological activity, upper limits are indicated for the influent turbidity. These vary however between

Although accepted as indirect indicator of the presence of particulate matter because of its ease of application, this parameter however, does not always properly reflect the load of solids that the filter receives, particularly if the particles are of organic nature such as algae. In addition, very few recommendations exist about the maximum charge of suspended solids (SS) an SSF can accept. However Wegelin (1986) suggests a charge below 5 mgl -1 but without evidence related to the impact of this level of SS on SSF units. Iron and manganese. Bacteria that contribute to the oxidation of iron and manganese are present in the filter bed. Small quantities of iron deposits improve the removal capacity for organic components (Collins et al., 1985). Nevertheless, high concentrations of iron (above 1 mgl -1 ) may contribute significantly to the clogging of the SSF unit (Spencer and Collins, 1991). Algae may grow in the rivers, lakes, storage reservoirs, or even in the supernatant of the SSF. The presence of algae in moderate quantities is usually beneficial for the functioning of the SSF units. Most algae are retained by the SSF, but under certain conditions occasional and significant algae growth or algae blooms may develop. This massive growth may cause a quick reduction of the permeability of the filtering bed, greatly reducing the filter run. Algae may also play an important role in the production of high concentrations of soluble and biodegradable organics in the water, which may create smell and taste problems, and contribute to microbial growth in the distribution system. Furthermore, as a result of the photosynthesis, algae may affect the buffer capacity of the water and increase the pH to levels of 10 or 11, which may in turn, result in the precipitation of magnesium and calcium hydroxides in the sand bed (Ives, 1957). This can contribute to the obstruction of the filter bed, increase the effective diameter of the sand, and reduce the efficiency of the process. Controlling the algae is difficult, but the possible methods are based on reducing the nutrient contents in the raw water, or creating a storage system or a supernatant environment in which algae can be controlled by the exclusion of light. Different levels have been established for the concentration of algae (table 2.5). It has to be remembered that algae can be present in the raw water source or grow in the filters of the supernatant water if conditions in terms of nutrients and solar radiation are favourable. Only in the last case will covering the filters be effective, as this will reduce the algal growth. Before deciding to cover the SSF, it needs to be checked if standard operation and maintenance procedures are not enough to manage moderate quantities of algae by occasional harvesting. Organic colour and organic carbon. The limitation of SSF to sufficiently remove organic colour and organic carbon of raw waters is normally reported. In fact, some studies report no removal at all and others (Fox et al, 1984, and Haberer et al, 1984; quoted by Haarhoff and Cleasby, 1991) present TOC and COD removal in the range of 15 to 19%. However, other studies (Joshi et al, 1982; quoted by Haarhoff and Cleasby, 1991) report COD removals in the range of 50 to 68%. "The discrepancy [in these removal efficiencies] lies in the diverse composition in organic compounds which are grouped together under surrogate parameters such as COD or TOC" (Haarhoff and Cleasby, 1991). To support this observation the results of research in Germany (Haberer et al, 1984), having removal efficiencies for six classes of 35