Browsing by Author "Raude, James M."

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  • Publication
    Publication
    Enhancement of anaerobic digestion by co-digesting food waste and water hyacinth in improving treatment of organic waste and bio-methane recovery
    (Elsevier Ltd, 2022-09-01) Oduor, William W.; Wandera, Simon M.; Murunga, Sylvia I.; Raude, James M.
    In Kenya, 57% of the municipal solid waste generated is Food waste (FW) which has high organic content. However, the treatment and bioconversion of FW to biogas have always been challenging due to its rapid biodegradation, resulting from rapid hydrolysis and accumulation of volatile fatty acids and lowering pH in the bioreactor. In this study, the anaerobic digestibility of FW as a mono substrate was compared to co-digestion of FW with water hyacinth (WH) for improved biogas production and organic matter removal efficiency in a laboratory batch reactor. Different mix proportions of FW and WH were co-digested under mesophilic conditions (37 °C) at a dilution of 6% (w/v) Total Solids (TS) content. The TS of the substrates (Food waste and Water Hyacinth) were pre-processed to have a concentration of TS at 6% (60 g/L) to operate a wet AD which requires the substrate to be less than 15% TS. The proportions of WH: FW (v/v) were 100:0, 85:15, 70:30, 55:45, 30:70, 15:85, and 0:100. In the batch rectors the anaerobic co-digestion was conducted with Substrate to Inoculum (S/I) ratio of 1:1. FW is generally considered to have high volatile solids which hydrolyze rapidly lowering pH arising from excess production of Hydrogen which in presence of CO2 and acetogenic bacteria leads to more production of acetate, formate and other long chain fatty acids which inhibits methanogenesis as a result of rapid acidification. The rapid acidification of the bioreactors that are used to treat FW results in the inhibition of the methanogenesis process. The co-digestion of the substrates could have improved the process parameters by reducing acidity caused by the high C/N ratio, reducing the inhibitory range, and increasing the buffer capacity which enhanced the bio-methane potential and the microbial activity. The batch experiments were set in triplicate for both cases of FW, WH, mixtures, and Inoculum. The results showed that the average gas yields after 81 days for the various mix proportions were 256.27and 357.69 ml/g-VS for mono-digestion of WH and FW respectively. For the mixtures of WH: FW the average reported biogas production were 305.01, 280.27, 548.91,616.01 and 270.87 ml/g-VS for mixtures of 15:85, 30:70, 55:45,70:30 and 85:15 respectively. The modified Gompertz model showed that the digesters with WH and FW alone had lag times of 2.599 and 1.052 days respectively. The mix substrates of WH: FW 85:15, 70:30, 55:45, 30:70 and 15:85 shown lag times of 2.456, 3.777, 2.574, 1.956 and 1.75 days respectively. A mix (WH: FW) of 70:30 had the highest maximum specific biogas production Rmax and the maximum biogas production potential of 18.19 mlCH4/gVS per day and 607.7mlCH4/gVS respectively. The R2 and RSME values ranged from 0.9867 to 0.9963 and 2.663 to 9.359 respectively in all the digesters. The study shows that the co-digestion of WH and FW in the mix ratio of 70:30 improved the volume of biogas produced and organic matter removal efficiency reached 79%.
  • Publication
    Publication
    Stochastic Drought Forecasting Exploration for Water Resources Management in the Upper Tana River Basin, Kenya
    (Engineering Science Reference (an imprint of IGI Global), 2015-01) Wambua, Raphael M.; Mutua, Benedict M.; Raude, James M.
    This chapter presents the trend of drought as a stochastic natural disaster influenced by the climate variability for the upper Tana River basin in Kenya. Drought frequency, duration and intensity in the upper Tana River basin have been increasing over the years. To develop measures for mitigating impacts of drought, the influencing hydro-meteorological parameters and their interaction are necessary. Drought definitions, fundamental concepts of droughts, classification of droughts, types of drought indices, historical droughts and application of artificial neural networks in analyzing impacts of drought on water resources with special focus on a Kenyan river basin is presented. Gaps for more focused research are identified. Although drought forecasting is very vital in managing key sectors such as water, agriculture and hydro-power generation, drought forecasting techniques in Kenya are limited. There is need therefore to develop an effective drought forecasting tool for on-set detection, classification and drought forecasting. The forecasting is necessary for decision making on matters of drought preparedness and proper water resources planning and management