Climate change is a major environmental and socioeconomic challenge in Ethiopia in recent decades. The study site is one of the climate change prone areas affected by climate variability and extreme events. Therefore, a better understanding of area-specific and adaptation is crucial to develop and implement proper adaptation strategies that can alleviate the adverse effects of climate change. Therefore, this work was aimed to identify determinants of farmers' adoption of climate change adaptation strategies in Gondar Zuria District of northwestern Ethiopia. Primary data were collected through semi-structured questionnaires, observation, and interviews. Besides, the secondary data were also obtained from journal articles, reports, governmental offices, and the internet. The Multinomial and Binary logistic regression models with the help of the Statistical Package for Social Sciences (SPSS) (21 th edition) were used to analyze the data. The multinomial logistic regression model was used to estimate the influence of the socioeconomic characteristics of sample households on the farmer's decision to choose climate change adaptation strategies. The result showed that age, gender, family size, farm income, and farm size had a significant influence on the farmers' choice of climate change adaptation strategies. The result also revealed that crop failure, severe soil erosion and shortages of water are major climate change-related problems than others. In order to alleviate these problems, farmers have implemented mixed farming, mixed cropping, early and late planting (changing sowing period), use of drought-resistant crop varieties, application of soil and water conservation techniques, shifting to non-farm income activities and use of irrigation. In contrast, access to climate information, total annual farm income, and market access variables are significant adoption determinants of climate change adaptation strategies by farmers' in the study site. Therefore, we recommend future adaptationrelated plans should focus on improving climate change information access, improving market access and enhancing research on the use of rainwater harvesting technology.

HIGHLIGHTSBiodiesel is a renewable energy source produced from natural oils and fats, and is being used as a substitute for petroleum diesel. The aim of this study was to investigate the potential of using spent coffee grounds for biodiesel production and its byproducts to produce pelletized fuel, which is expected to help the biodiesel production process achieve zero waste. For this experiment, spent coffee grounds sample was collected from Kaldis coffee, Addis Ababa, Ethiopia. Extraction of the spent coffee grounds oil was then conducted using n-hexane, ether and mixture of isopropanol to hexane ratio (50:50 %vol), and resulted in oil yield of 15.6, 17.5 and 21.5 %w/w respectively. A two-step process was used in biodiesel production with conversion of about 82 %w/w. The biodiesel quality parameters were evaluated using the American Standard for Testing Material (ASTM D 6751). The major fatty acid compositions found by Gas chromatography were linoleic acid (37.6%), palmitic acid (39.8%), oleic (11.7%), and stearic acid (8.6%). In addition, solid waste remaining after oil extraction and glycerin ratio (glycerin content from 20-40%) was evaluated for fuel pellet (19.3-21.6 MJ/Kg) applications. Therefore, the results of this work could offer a new perspective to the production of biofuel from waste materials without growing plants and/or converting food to fuel.

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The study was conducted in Wof-Washa Forest in the central highlands of Ethiopia, aiming at determining the impact of altitude and anthropogenic disturbance on plant species composition, structure, and diversity of the forest. Eighteen transect lines with 632 meters apart from each other were established from top to bottom. A total of 115 main plots for all communities with 20 × 20 m, were established along transect lines from the upper part of the forest to the river's edge. To collect data on seedlings and saplings, 5 m × 5 m and 10 m × 10 m subplots were laid respectively within the main sampling plots. For each plot the plant species were counted, diameter at breast height and height of trees and shrubs were measured. The human disturbance data were visually estimated for each plot in each community. Plant community classification was made following Ethiopia agro-ecological zones. Plant species diversity and richness were found related to human disturbance and altitude. A total of 108 species belonging to 99 genera and 57 families were identified. The results revealed that Asteraceae was the most diverse higher plant family with nine species (8.3%) followed by Fabaceae, Euphorbiaceae, and Rosaceae with six (5.5%) species each. The overall Shannon diversity and evenness index of the forest were 4.02 and 0.86 respectively. Tree/shrub, sapling and seedling densities were 664.4, 757.2 and 805.7 individual's ha −1 respectively. The total basal area of the forest was 55.99 m 2 ha -1 . About 25.7% of the importance values index was contributed by four species, Juniperus procera, Podocarpus falcatus, Ilex mitis, and Erica arborea . The similarity in species composition within the forest was low, indicating that the different parts of the forest had different floras. The presence of strong human disturbance indicates the need for immediate conservation in order to ensure sustainable utilization and management of the forest.

Abstract. A deterministic forecast of surface precipitation involves solving a time-dependent moisture balance equation satisfying conservation of total water substance. A realistic solution needs to take into account feedback between atmospheric dynamics and the diabatic sources of heat energy associated with phase changes, as well as complex microphysical processes controlling the conversion between cloud water (or ice) and precipitation. Such processes are taken into account either explicitly or via physical parameterisation schemes in many operational numerical weather prediction models; these can therefore generate precipitation forecasts which are fully consistent with the predicted evolution of the atmospheric state as measured by observations of temperature, wind, pressure and humidity. This paper reviews briefly the atmospheric moisture balance equation and how it may be solved in practice. Solutions are obtained using the Meteorological Office Mesoscale version of its operational Unified Numerical Weather Prediction (NWP) model; they verify predicted precipitation rates against catchment-scale values based on observations collected during an Intensive Observation Period (IOP) of HYREX. Results highlight some limitations of an operational NWP forecast in providing adequate time and space resolution, and its sensitivity to initial conditions. The large-scale model forecast can, nevertheless, provide important information about the moist dynamical environment which could be incorporated usefully into a higher resolution, ‘storm-resolving’ prediction scheme. Keywords: Precipitation forecasting; moisture budget; numerical weather prediction

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Most rural communities in developing countries, rely heavily on traditional biomass for cooking and lighting. Furthermore, a large area of forest land has been changed to other land-use types like agricultural land is becoming a serious problem in Wondo Genet district. This situation largely contributed to deforestation and forest degradation. Hence, assessing the efficiency of adopting an alternative source of energy was found to be very important. This study was carried out to examine the role of biogas technology in fuelwood saving and carbon emission reduction in Wondo Genet district, southern Ethiopia. The multi-stage sampling procedure was followed to select sample households. A total of 152 households (54 adopters and 98 non-adopters) were involved in the household survey. Moreover, 25 test subjects were taken randomly from both adoption categories to conduct Kitchen Performance Test. Descriptive statistics and independent-sample t-test were used to analyze the data. Results showed that the major fuel sources for domestic use were plantation forest, natural forest, crop residue, and animal dung, accounting 46.71 %, 30.92 %, 15.13 %, and 7.24 %, respectively. Among the 54 sampled biogas plants, 32 (59.26 %) were a digester size of 6 m 3 whereas the remaining 22 (40.74 %) were of 8 m 3 . The annual fuelwood saving potential of the technology was found to be 1423.06 kg with an emission reduction potential of 2.1 tons of CO 2 e per biogas plant annually. Accordingly, all functional biogas plants were estimated to reduce about 91.63 tons of carbon emission annually. Generally, the biogas was found to be a promising technology in combating the pressure on forest resources and mitigating climate change. Therefore, the energy sector of the country should encourage households to adopt biogas plants that have more than 8 m 3 digester size to improve the fuelwood and carbon emission reduction potential.

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