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DDC: 624 × Type: Text × Publisher: Amsterdam [u.a.] : Elsevier ×

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Now showing 1 - 7 of 7
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    Experimental evaluation and application of genetic programming to develop predictive correlations for hydrochar higher heating value and yield to optimize the energy content
    (Amsterdam [u.a.] : Elsevier, 2022) Marzban, Nader; Libra, Judy A.; Hosseini, Seyyed Hossein; Fischer, Marcus G.; Rotter, Vera Susanne
    The hydrothermal carbonization (HTC) process has been found to consistently improve biomass fuel characteristics by raising the higher heating value (HHV) of the hydrochar as process severity is increased. However, this is usually associated with a decrease in the solid yield (SY) of hydrochar, making it difficult to determine the optimal operating conditions to obtain the highest energy yield (EY), which combines the two parameters. In this study, a graph-based genetic programming (GP) method was used for developing correlations to predict HHV, SY, and EY for hydrochars based on published values from 42 biomasses and a broad range of HTC experimental systems and operating conditions, i.e., 5 ≤ holding time (min) ≤ 2208, 120 ≤ temperature (°C) ≤ 300, and 0. 0096 ≤ biomass to water ratio ≤ 0.5. In addition, experiments were carried out with 5 pomaces at 4 temperatures and two reactor scales, 1 L and 18.75 L. The correlations were evaluated using this experimental data set in order to estimate prediction errors in similar experimental systems. The use of the correlations to predict HTC conditions to achieve the maximum EY is demonstrated for three common feedstocks, wheat straw, sewage sludge, and a fruit pomace. The prediction was confirmed experimentally with pomace at the optimized HTC conditions; we observed 6.9 % error between the measured and predicted EY %. The results show that the correlations can be used to predict the optimal operating conditions to produce hydrochar with the desired fuel characteristics with a minimum of actual HTC runs.
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    Severe climate change risks to food security and nutrition
    (Amsterdam [u.a.] : Elsevier, 2022) Mirzabaev, Alisher; Bezner Kerr, Rachel; Hasegawa, Toshihiro; Pradhan, Prajal; Wreford, Anita; Tirado von der Pahlen, Maria Cristina; Gurney-Smith, Helen
    This paper discusses severe risks to food security and nutrition that are linked to ongoing and projected climate change, particularly climate and weather extremes in global warming, drought, flooding, and precipitation. We specifically consider the impacts on populations vulnerable to food insecurity and malnutrition due to lower income, lower access to nutritious food, or social discrimination. The paper defines climate-related “severe risk” in the context of food security and nutrition, using a combination of criteria, including the magnitude and likelihood of adverse consequences, the timing of the risk and the ability to reduce the risk. Severe climate change risks to food security and nutrition are those which result, with high likelihood, in pervasive and persistent food insecurity and malnutrition for millions of people, have the potential for cascading effects beyond the food systems, and against which we have limited ability to prevent or fully respond. The paper uses internationally agreed definitions of risks to food security and nutrition to describe the magnitude of adverse consequences. Moreover, the paper assesses the conditions under which climate change-induced risks to food security and nutrition could become severe based on findings in the literature using different climate change scenarios and shared socioeconomic pathways. Finally, the paper proposes adaptation options, including institutional management and governance actions, that could be taken now to prevent or reduce the severe climate risks to future human food security and nutrition.
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    Corrigendum to “Dynamics of rural livelihoods and rainfall variability in Northern Ethiopian Highlands” [Clim. Risk Manage. 25 (2019) 100195](S2212096318300378)(10.1016/j.crm.2019.100195)
    (Amsterdam [u.a.] : Elsevier, 2020) Adamseged, Muluken E.; Frija, Aymen; Thiel, Andreas
    The authors regret for not properly acknowledging the contribution of the Consortium Research Program (CRP) on Livestock, led by ILRI with contribution of ICARDA. Funding from the CGIAR Research Program on Livestock (flagship 5 on “Livestock livelihoods and agri-food systems flagship”) is acknowledged for their support of staff time of Dr. Aymen Frija. The authors thank all donors and organizations who globally support the work of the CGIAR Research Program on Livestock through their contributions to the CGIAR system. The authors would like to apologise for any inconvenience caused. © 2020 The Author(s)
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    Dynamics of rural livelihoods and rainfall variability in Northern Ethiopian Highlands
    (Amsterdam [u.a.] : Elsevier, 2019) Adamseged, Muluken E.; Frija, Aymen; Thiel, Andreas
    [No abstract available]
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    Understanding adaptive capacity of smallholder African indigenous vegetable farmers to climate change in Kenya
    (Amsterdam [u.a.] : Elsevier, 2020) Chepkoech, Winifred; Mungai, Nancy W.; Stöber, Silke; Lotze-Campen, Hermann
    Understanding the adaptive capacity (AC) of farmers is crucial to planning effective adaptation. Action to promote farmers’ AC is required because climate change (CC) is resulting in unpredictable alterations in weather patterns. Based on the sustainable livelihoods framework (SLF), this study explored how access to natural, physical, financial, social and human capitals enhances the AC. Quantitative data from 269 African indigenous vegetable (AIV) farmers in three selected agro-climatic zones in Kenya were analysed. Four indicators in each capital were selected based on previous studies and judgments collected from an expert online ranking survey (n = 35). The Kruskal-Wallis H test and an independent sample t-test were used to test the independence of AC scores and access to the different resources. The findings showed that the majority of farmers (53%) had a moderate AC, while fewer (32%) and (15%) had low or high AC levels respectively. Disparities in adaptive capacity scores were recorded between respondents in terms of their age, marital status and location. Farmers had high access to social capital but low access to financial, natural and human capitals. Female farmers showed lower capacities in the areas of financial, human and natural resources, while their male counterparts had low access to some human and social capitals. Resilient interventions that target individuals with low adaptive capacities are required. © 2020 The Authors
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    How modelers construct energy costs: Discursive elements in Energy System and Integrated Assessment Models
    (Amsterdam [u.a.] : Elsevier, 2019) Ellenbeck, Saskia; Lilliestam, Johan
    Energy system and integrated assessment models (IAMs) are widely used techniques for knowledge production to assess costs of future energy pathways and economic effects of energy/climate policies. With their increased use for policy assessment and increasing dominance in energy policy science, such models attract increasing criticism. In the last years, such models – especially the highly complex IAMs, have been accused of being arbitrary. We challenge this view and argue that the models and their assumptions are not arbitrary, but they are normative and reflect the modelers’ understanding of the functioning of the society, the environment-societal relations and respective appropriate scientific tools and theories – in short: models are shaped by discursive structures, reproducing and reinforcing particular societal discourses. We identify 9 distinct paths, all relating to crucial model decisions, via which discourses enter models: for each of these decisions, there are multiple “correct” answers, in the sense that they can be justified within a particular discourse. We conclude that decisions of modelers about the structure and about assumptions in energy modeling are not arbitrary but contingent to the discursive context the modeler is related to. This has two implications. First, modelers and consumers of model output must reflect on what a model and its assumptions represent, and not only whether are they correct. Second, models hardly need to add more (mathematical) complexity, but rather be reduced and simplified so that they can continue to fulfill their main function as formalized and powerful instruments for thought experiments about future energy pathways.
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    Challenges of data availability: Analysing the water-energy nexus in electricity generation
    (Amsterdam [u.a.] : Elsevier, 2019) Larsen, M.A.D.; Petrovic, S.; Engström, R.E.; Drews, M.; Liersch, S.; Karlsson, K.B.; Howells, M.
    Water is paramount for the operation of energy systems, for securing food supply and for the industry and municipalities. Intersectoral competition for water resources can negatively affect water scarce regions by e.g. power plants shutdowns, poor agricultural yields, and lack of potable water. Future economic and population growth as well as climate change is likely to exacerbate these patterns. However, models used for energy system management and planning in general do not properly include water availability which can lead to improper representations of water-energy interlinkages. The paper initially highlights the water usage rates of current technologies within electricity generation and technologies with a potential to reduce water usage, electricity consumption or GHG emissions. Secondly, the paper presents currently available data on current and future projected water resources as well as data on energy statistics relevant to water-energy nexus studies. Thirdly, implementation cases are presented showing examples of water-energy nexus studies for the data presented. Finally, the paper highlights main challenges in studying the linkage between water and energy. We find a substantial gap in the general availability and quality of regional and global data for detailed quantitative analyses and also identify a need for standardization of formats and data collection methodologies across data and disciplines. An effort towards a coordinated, and sustained open-access data framework with energy sector water usage at fine spatio-temporal scales alongside hydro-climatic observation and model data using common forcings and scenarios for future projections (of climate, socio-economy and technology) is therefore recommended for future water-energy nexus studies. © 2019 The Authors