Current and projected freshwater needs of the African energy system

Africa’s expected rapid economic development and population growth will increase in all likelihood the stress on water and energy resources in the coming decades. A number of studies have addressed the water needs of the energy sector, both at global scale or for certain developed countries. However, very few of them have focused on Africa, often overshadowed by other industrialised regions with a much higher water use for energy. Contrary to other studies, this report also addresses hydropower and fuelwood, not only due to the important role they play in many African countries but also because they consume large amounts of water and are therefore extremely vulnerable to water scarcity. The methodology used to assess hydropower in this study differs from other analyses, which would normally obtain the reservoirs' areas needed to estimate the evaporation losses from global databases. In this report, the assessment of hydropower relies on the more accurate information provided by the Global Surface Water Dataset (Pekel et al., 2016), a JRC product based on satellite data, which provides monthly water surfaces at 30 m spatial resolution. In this study, the current and future water needs (consumption and withdrawals) of the African energy sector have been estimated on a country-by-country basis. Primary energy production (fuel extraction), energy transformation (oil refining and electricity generation) and power plant construction have been evaluated. The results of this analysis reveal that in the year 2016, 42 bcm[1] of water were lost through evaporation in hydropower reservoirs, 4.5 bcm were used for fuelwood production and 1.2 bcm were consumed by the rest of the energy types combined. Non-hydro renewable energies such as wind and solar have a negligible effect on water use, making them an interesting alternative to conventional energy sources for the sustainable development in Africa, especially given their large untapped potential in the continent. Future projections of freshwater use at country level are also analysed, based on three energy scenarios for Africa, aligned with the JRC’s Global Energy and Climate Outlook (GECO) 2018 (Keramidas et al., 2020; Pappis et al., 2019): i) a reference scenario (hereafter denoted R) that extrapolates the current situation into the future, ii) a 2.0 °C scenario in which new policies and emission targets are implemented to keep global mean temperature increase to 2.0 °C over pre-industrial levels with a 67% probability, and iii) a 1.5 °C scenario that assumes a stronger climate objective pursuing a reduction in carbon dioxide emissions to levels lower than in the reference and the 2.0 °C scenarios with a 50% probability of reaching 1.5 °C warming by 2100. These projections indicate that by 2030, depending on the scenario, the water loss allocated to hydropower due to evaporative losses will be 93.8 bcm (R), 94.8 bcm (2.0 °C) and 93.1 bcm (1.5 °C ); the water consumption for fuelwood production: 7.6 bcm (R), 7.7 bcm (2.0 °C) and 7.8 bcm (1.5 °C); and the water consumption for the other energy types: 1 bcm (R) and 0.8 bcm (1.5 °C and 2.0 °C). By 2050, hydropower water losses will rise up to: 139 bcm (R), 155 bcm (2.0 °C) and 160.7 bcm (1.5 °C ); water consumption for fuelwood production: 7.2 bcm (R), 7.4 bcm (2.0 °C) and 7.9 bcm (1.5 °C) bcm; and water consumption for the other energy types: 1.3 bcm (R), 0.7 bcm (2.0 °C) and 0.5 bcm (1.5 °C). The low carbon policies will not only have a positive effect on emissions but also on the water consumption in some energy sub-sectors, reducing the use of water for primary energy production and transformation, and increasing the penetration of some renewable energies such as solar, wind and geothermal. However, other more water-intensive renewables (e.g.: hydropower and biomass) are also expected to increase their share in the future energy mix, causing significant impacts on water use. The penetration of oil and gas to substitute fuelwood use in households will reduce the water use in the continent. At the same time, despite the large untapped potential of hydropower in Africa, the water impacts of new hydropower developments need to be effectively considered, especially in regions characterised by severe water scarcity. New ways to limit evaporation from hydropower reservoirs need to be deployed in order to mitigate their impact on water stress.JRC.C.2-Energy Efficiency and Renewable

INFLUÊNCIA DO PISOTEIO DO GADO NA ALTERAÇÃO DAS PROPRIEDADES FÍSICAS DE HORIZONTES SUPERFICIAIS EM SANTO ANTÔNIO DE PÁDUA

A degradação dos solos é um fenômeno comum no Brasil e em muitos locais do planeta. Entre as diversas formas de degradação, as alterações das características físicas do solo devido ao uso agrícola ou com pecuária parecem ser uma das formas mais frequentes. Em Santo Antônio de Pádua (RJ), a degradação dos solos foi iniciada ainda no século XVIII, com a remoção das florestas para plantio de cana-de-açúcar e café e, posteriormente, com a introdução da pecuária no século XX. O trabalho foi conduzido de forma a caracterizar fisicamente os horizontes superficiais sob fragmentos florestais, pastagem e em trilha de boi. Os resultados obtidos mostraram que não há diferença significativa entre os horizontes superficiais sob fragmentos florestais e pastagens com relação ao teor de matéria orgânica, densidade do solo e porosidade total. Porém, na comparação entre os horizontes superficiais nos fragmentos florestais e nas trilhas de boi, a diferença é significativa com relação à densidade do solo e à porosidade total. Entre as pastagens e as trilhas de boi, a diferença não é significativa. A avaliação global dos resultados mostrou que os horizontes superficiais nas pastagens se constituem em um ambiente intermediário entre os fragmentos florestais e as trilhas de boi. Com um manejo mais adequado, a atividade de criação de bovinos poderia ser praticada com um impacto menor do que o verificado nas propriedades do município

TREES-3 - Forest cover change assessment for tropical South and Central America based on a systematic sampling of medium resolution satellite imagery - data, methods and first results for year 2010

The TREES-3 project of the European Commissions Joint Research Centre has monitored tropical forest cover change with medium to high resolution satellite imagery for the reference years 1990, 2000 and 2010 on basis of a regular grid of 10 km x 10 km samples located at every full degree confluence, giving a total of 1230 sample sites for tropical South and Central America and the Caribbean. For the years 1990 and 2000, imagery from the Landsat sensors covered 99% of all sample sites, and for the year 2010, 86% of all sample, a further 13% of the sample sites are covered by imagery from other sensors, leaving 1% of the sample sites not covered due to the lack of good quality (cloud-free) images. All satellite images are pre-processed, including a check for geo-location, conversion to top-of-atmosphere reflectance, atmospheric correction (haze-correction and masking of cloud and cloud shadow) and normalized by a pseudo-invariant feature approach on basis of dense evergreen humid forest areas. Land cover maps are produced for each sample site and for each reference year with the following classes: tree cover, tree cover mosaic, other wooded land, other land and water. The first estimates of forest cover change between the years 1990 and 2010 have been produced by extrapolation of 175 samples to the study area of the Brazilian Cerrado biome. The resulting yearly deforestation rates for the Cerrado for the periods 1990-2000 and 2000-2010 were 0.6% and 1.0% respectively.Pages: 3374-338

Updating an object-based pan-tropical forest cover change assessment by automatic change detection and classification

The TREES-3 project of the European Commission’s Joint Research Centre is producing estimates of tropical forest cover changes during the period 1990 to 2010. Three reference years are considered: 1990, 2000 and 2010. This paper presents the method developed for the automatic processing of year 2010 with the assessment of performance of this method. The processing of imagery of year 2010 includes automatic segmentation, change detection and object spectral classification. The validated maps of forest cover changes for the period 1990-2000 are used as thematic input layer into the segmentation and classification process of the year 2010 images. Object-based change detection (OBCD) technique is applied using Tasselled Cap (TCap) parameters and spectral Euclidian Distances (ED). Objects detected as changed are classified by change vector analysis. The segmentation approach was tested on a subsample of 568 sample units over Brazil. The segmentation results for year 2010 are consistent with segmentation of imagery for the period 1990-2000, the segmentation statistics (number of objects, average objects size, average number of objects per sample site) remain stable between the two approaches. A two-step method of (a) change detection and (b) classification of changed objects was developed on basis of thresholding TCap variance and Euclidian Distance. The approach was tested over 281 sample units in the Brazilian biome of the Amazon, for which validated land cover information for the year 2010 was already available. The resulting overall accuracy of classification for the 281 sample units was 92.2%.JRC.H.3-Forest Resources and Climat

Automatic updating of an object-based tropical forest cover classification and change assessment

The TREES-3 project of the European Commission’s Joint Research Centre is producing estimates of tropical forest cover changes for two time periods: 1990–2000 and 2000–2010. This paper presents the method developed for the automatic change detection and classification of year 2010 imagery from the existing segmentation and classification results of first period 1990–2000. The imagery of year 2010 is processed in three steps: automatic segmentation, change detection and object spectral classification. The validated maps of forest cover changes for the period 1990–2000 are integrated in vector format as thematic input layer into year 2010 imagery segmentation and classification process. Object-based change detection technique is applied using Tasselled Cap components and spectral Euclidian Distances. Objects detected as changed are classified in two steps: supervised classification and change vector analysis for unclassified remaining objects. The training areas for supervised classification are selected as objects identified as ‘unchanged’ and spectral signatures are extracted from 2010 imagery. Change vectors are defined according to available classification of year 2000, by spectral differences of land cover classes from year 2000 imagery. The segmentation approach was tested on 568 sample units spread over Brazil. The segmentation results for year 2010 demonstrated consistency with segmentation of imagery for the period 1990-2000. The resulting overall accuracy of this automatic classification was estimated for the 281 sample units of Brazilian Amazonian region and for 201 sample units of three more complex biomes at 92% and 91% respectively.JRC.H.3-Forest Resources and Climat

Land cover changes in the Brazilian Cerrado and Caatinga biomes from 1990 to 2010 based on a systematic remote sensing sampling approach

The main objective of our study was to provide consistent information on land cover changes between the years 1990 and 2010 for the Cerrado and Caatinga Brazilian seasonal biomes. These areas have been overlooked in terms of land cover change assessment if compared with efforts in monitoring the Amazon rainforest. For each of the target years (1990, 2000 and 2010) land cover information was obtained through an object-based classification approach for 243 sample units (10km x 10km size), using (E)TM Landsat images systematically located at each full degree confluence of latitude and longitude. The images were automatically pre-processed, segmented and labelled according to the following legend: Tree Cover (TC), Tree Cover Mosaic (TCM), Other Wooded Land (OWL), Other Land Cover (OLC) and Water (W). Our results indicate the Cerrado and Caatinga biomes lost (gross loss) respectively 265,595 km2 and 89,656 km2 of natural vegetation (TC + OWL) between 1990 and 2010. In the same period, these areas also experienced gain of TC and OWL. By 2010, the percentage of natural vegetation cover remaining in the Cerrado was 47% and in the Caatinga 63%. The annual (net) rate of natural vegetation cover loss in the Cerrado slowed down from -0.79% yr-1 to -0.44% yr-1 from the 1990s to the 2000s, while in the Caatinga for the same periods the rate increased from -0.19% yr-1 to -0.44% yr-1. In summary, these Brazilian biomes experienced both loss and gains of Tree Cover and Other Wooded Land; however a continued net loss of natural vegetation was observed for both biomes between 1990 and 2010. The average annual rate of change in this period was higher in the Cerrado (-0.6% yr-1) than in the Caatinga (-0.3% yr-1).JRC.H.3-Forest Resources and Climat

Correction : renal cell carcinoma alters endothelial receptor expression responsible for leukocyte adhesion

Present: Due to an error in the production process, figures 5 and 6 were switched. Each figure legend is correct, but is associated with the wrong figure

Renal cell carcinoma alters endothelial receptor expression responsible for leukocyte adhesion

Renal cell carcinoma (RCC) escapes immune recognition. To elaborate the escape strategy the influence of RCC cells on endothelial receptor expression and endothelial leukocyte adhesion was evaluated. Human umbilical vein endothelial cells (HUVEC) were co-cultured with the RCC cell line, Caki-1, with and without tumor necrosis factor (TNF)-alpha. Intercellular cell adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1), endothelial (E)-selectin, standard and variants (V) of CD44 were then analysed in HUVEC, using flow cytometry and Western blot analysis. To determine which components are responsible for HUVEC-Caki-1 interaction causing receptor alteration, Caki-1 membrane fragments versus cell culture supernatant were applied to HUVECS. Adhesion of peripheral blood lymphocytes (PBL) and polymorphonuclear neutrophils (PMN) to endothelium was evaluated by co-culture adhesion assays. Relevance of endothelial receptor expression for adhesion to endothelium was determined by receptor blockage. Co-culture of RCC and HUVECs resulted in a significant increase in endothelial ICAM-1, VCAM-1, E-selectin, CD44 V3 and V7 expression. Previous stimulation of HUVECs with TNF-alpha and co-cultivation with Caki-1 resulted in further elevation of endothelial CD44 V3 and V7 expression, whereas ICAM-1, VCAM-1 and E-selectin expression were significantly diminished. Since Caki-1 membrane fragments also caused these alterations, but cell culture supernatant did not, cell-cell contact may be responsible for this process. Blocking ICAM-1, VCAM-1, E-selectin or CD44 with respective antibodies led to a significant decrease in PBL and PMN adhesion to endothelium. Thus, exposing HUVEC to Caki-1 results in significant alteration of endothelial receptor expression and subsequent endothelial attachment of PBL and PMN

Forest Cover Changes in Tropical South and Central America from 1990 to 2005 and Related Carbon Emissions and Removals

This paper outlines the methods and results for monitoring forest change and resulting carbon emissions for the 1990–2000 and 200–2005 periods carried out over tropical Central and South America. To produce our forest change estimates we used a systematic sample of medium resolution satellite data processed to forest change maps covering 1230 sites of 20 km by 20 km, each located at the degree confluence. Biomass data were spatially associated to each individual sample site so that annual carbon emissions could be estimated. For our study area we estimate that forest cover in the study area had fallen from 763 Mha (s.e. 10 Mha) in 1990 to 715 Mha (s.e. 10 Mha) in 2005. During the same period <em>other</em> <em>wooded</em> <em>land</em> (<em>i.e</em>., non-forest woody vegetation) had fallen from 191 Mha (s.e. 5.5 Mha) to 184 Mha (s.e. 5.5 Mha). This equates to an annual gross loss of 3.74 Mha∙y<sup>−1</sup> of forests (0.50% annually) between 1990 and 2000, rising to 4.40 Mha∙y<sup>−1</sup> in the early 2000s (0.61% annually), with Brazil accounting for 69% of the total losses. The annual carbon emissions from the combined loss of forests and <em>other wooded land</em> were calculated to be 482 MtC∙y<sup>−1</sup> (s.e. 29 MtC∙y<sup>−1</sup>) for the 1990s, and 583 MtC∙y<sup>−1</sup> (s.e. 48 MtC∙y<sup>−1</sup>) for the 2000 to 2005 period. Our maximum estimate of sinks from forest regrowth in tropical South America is 92 MtC∙y<sup>−1</sup>. These estimates of gross emissions correspond well with the national estimates reported by Brazil, however, they are less than half of those reported in a recent study based on the FAO country statistics, highlighting the need for continued research in this area