Characterization of municipal waste in Kampala, Uganda.

UNLABELLED: In Kampala, Uganda, about 28,000 tons of waste is collected and delivered to a landfill every month. Kampala Capital City Authority (KCCA) records show that this represents approximately 40% of the waste generated in the city. The remaining uncollected waste is normally dumped in unauthorized sites, causing health and environmental problems. However, the organic fraction of domestic waste can provide an opportunity to improve livelihoods and incomes through fertilizer and energy production. This study characterized the municipal waste generated in Kampala and delivered to Kiteezi landfill between July 2011 and June 2012, that is, covering the dry and wet months. On each sampling day, waste was randomly selected from five trucks, sorted and weighed into different physical fractions. Samples of the organic waste from each truck were analyzed for total solids, major nutrients, and energy content. During the wet months, the waste consisted of 88.5% organics, 3.8% soft plastics, 2.8% hard plastics, 2.2% paper, 0.9% glass, 0.7% textiles and leather 0.2% metals, and 1.0% others. During the dry months, the waste consisted of 94.8% organics, 2.4% soft plastics, 1.0% hard plastics, 0.7% papers, 0.3% glass, 0.3% textile and leather, 0.1% metals, and 0.3% others. The organic waste on average had a moisture content of 71.1% and contained 1.89% nitrogen, 0.27% phosphorus, and 1.95% potassium. The waste had an average gross energy content of 17.3 MJ/kg. It was concluded that the organic waste generated can be a suitable source of some plant nutrients that are useful especially in urban agriculture. IMPLICATIONS: The result of the waste characterization in Kampala was found to be significantly different from that obtained for other Sub-Saharan African (SSA) cities, showing that studies assuming average values for the waste fractions are likely to result in erroneous results. Furthermore, no reduction in organic fraction of the waste was noticed when compared with a study done two decades ago in spite of greatly improved economic status of Kampala city, a finding that is not in agreement with several other similar studies done for other SSA cities.

Quantification of multiple waterborne pathogens in drinking water, drainage channels, and surface water in Kampala, Uganda, during seasonal variation.

Longitudinal water quality monitoring is important for understanding seasonal variations in water quality, waterborne disease transmission, and future implications for climate change and public health. In this study, microfluidic quantitative polymerase chain reaction (MFQPCR) was used to quantify genes from pathogens commonly associated with human intestinal infections in water collected from protected springs, a public tap, drainage channels, and surface water in Kampala, Uganda, from November 2014 to May 2015. The differences in relative abundance of genes during the wet and dry seasons were also assessed. All water sources tested contained multiple genes from pathogenic microorganisms, with drainage channels and surface waters containing a higher abundance of genes as compared to protected spring and the public tap water. Genes detected represented the presence of enterohemorrhagic Escherichia coli, Shigella spp., Salmonella spp., Vibrio cholerae, and enterovirus. There was an increased presence of pathogenic genes in drainage channels during the wet season when compared to the dry season. In contrast, surface water and drinking water sources contained little seasonal variation in the quantity of microbes assayed. These results suggest that individual water source types respond uniquely to seasonal variability and that human interaction with contaminated drainage waters, rather than direct ingestion of contaminated water, may be a more important contributor to waterborne disease transmission. Furthermore, future work in monitoring seasonal variations in water quality should focus on understanding the baseline influences of any one particular water source given their unique complexities.