• Energy Research
• 15. Life on land close

AbstractThe phenomenon of the abandonment of terraced landscapes compromises environmental well-being and is a preamble to hydrological instability and, consequently, the collapse of terrace retain...

Abstract Biomass is a renewable energy resource; however, its exploitation raises concerns about its ability to sustain the growing demand and its negative impacts on the environment, particularly in developing countries. These concerns are more prominent on the African continent where high population growth rates is leading to high rates of deforestation due to expansion of agricultural land and increased demand for bioenergy. Use of traditional and inefficient bioenergy technologies and appliances also exacerbate the problem. This paper presents a review of the efforts and progress made by different organisations in promoting improved bioenergy technologies in Uganda. The study was based on an extensive review of available literature on improved bioenergy technologies introduced in the country. It was found that there is high level of wastage of biomass resources since an estimated 72.7% of the population use traditional cooking stoves with efficiency estimated to be less than 10%. Inefficient cooking stoves are also blamed for indoor air pollution and respiratory illness reported amongst its users. Modern bioenergy technologies such as biomass gasification, cogeneration, biogas generation, biomass densification, and energy-efficient cooking stoves have been introduced in the country but have certainly not been widely disseminated. The country should pursue policies that will accelerate proliferation of more efficient bioenergy technologies in order to reduce the negative environmental impacts of bioenergy utilisation and to ensure sustainability of biomass supplies.

Campania region is undergoing a new and important land use change (LUC). Large areas under tobacco are experiencing a severe economic crisis and cereal areas, especially in the hill, are cultivated with increasing difficulty, with poor economic results (yield value of 2.5 t/ha/year) and under the risk of erosion. No-food crops suitable in these contexts are the perennial and in this case, the land use change would certainly lead to a positive impact on reducing erosion, but also on the reduction of nutrient requirement, on fuel consumption and perhaps it would also lead to an increase in profitability. The aim of this work is to identify the areas in which the land use change could be realistic and ecologically compatible and to evaluate the main consequence of the LUC. The study area includes the entire Campania region. It has been assumed that the areas that will undergo the LUC will be the hilly, not-irrigated cereal crop, with altitudes between 400 and 750 m a.s.l., not included in natural parks, in the Site of Community Importance and in the Special Protection Areas. Through the climate model, inferred from the Ground Water Protection Plan, the area to be examined was classified as ‘cold Lauretum’, which is a good area for the Arundo donax crops up to 750 m a.l.s., with recoverable biomass yield of about 12.6 t/year. The erosion has been estimated with RUSLE applied to the whole region. Using the ESRI ArcGis 10.0 software, seven large areas, partially convertible, were identified. The area that is realistic to convert amounted to approximately 500 km2. The value of the biomass production has been evaluated in the order of 25 million euro a year; actual wheat production would be 33 million euro a year but the production costs are far greater. With LUC there is a reduction in soil erosion in the order of 300000 t/year. This would lead a saving, on global scale, in the order of 10 million tonnes of CO2 per year.

Hyperspectral satellite missions, such as PRISMA of the Italian Space Agency (ASI), have opened up new research opportunities. Using PRISMA data in land cover classification has yet to be fully explored, and it is the main focus of this paper. Historically, the main purposes of remote sensing have been to identify land cover types, to detect changes, and to determine the vegetation status of forest canopies or agricultural crops. The ability to achieve these goals can be improved by increasing spectral resolution. At the same time, improved AI algorithms open up new classification possibilities. This paper compares three supervised classification techniques for agricultural crop recognition using PRISMA data: random forest (RF), artificial neural network (ANN), and convolutional neural network (CNN). The study was carried out over an area of 900 km2 in the province of Caserta, Italy. The PRISMA HDF5 file, pre-processed by the ASI at the reflectance level (L2d), was converted to GeoTiff using a custom Python script to facilitate its management in Qgis. The Qgis plugin AVHYAS was used for classification tests. The results show that CNN gives better results in terms of overall accuracy (0.973), K coefficient (0.968), and F1 score (0.842).

Abstract Biomass is the major source of energy in most developing countries. However, there are concerns about the sustainability of biomass supplies and the environmental impacts resulting from their use. Use of residues could contribute to ensuring sustainable supply of biomass energy. This study presents findings of an evaluation of the energy potential of agricultural and forest residues in Uganda using census data of the year 2008/2009. Annual productions of crop and forest residues were estimated using residue-to-product ratio (RPR) method. Energy potential of each residue class was then determined basing on their respective lower heating values. The biogas generation potential of each animal category was used to evaluate the energy potential of animal manure. Results showed that the total energy potential of the residues amount to 260 PJ y −1 , which is about 70% of gross biomass energy requirement of Uganda for the year 2008. Crop residues had the highest contribution of about 150 PJ y −1 , followed by animal residues with a potential of 65 PJ y −1 . Maize residue is the predominant crop residue with energy potential of 65 PJ y −1 followed by beans and banana, each at 16 PJ y −1 . This study indicates that agricultural and forest residues can be a major renewable energy source for Uganda. When sustainably utilised, biomass residues could contribute to reduction in environmental degradation in the country.