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With a growing global population and accelerating climate change, systematic assessment and monitoring of crop diseases is urgently required to ensure food security and production. However, current...

The number and sizes of informal settlements are expected to increase drastically in the future, and dramatically so in Sub-Saharan Africa, where migration from rural to urban areas is increasing, and poverty and food insecurity threaten livelihoods. Data sources explaining livelihood factors in informal settlements are scarce, and often highly disputed. In this study, Kibera is investigated, one of the largest informal settlements in Africa. The main aim is to analyze differences in livelihood factors across the villages in Kibera, and to explain some of the existing discrepancies in food security levels among its population. In particular, livelihood factors such as tribe, welfare and trust can explain some of the variation in food security across 12 of the 13 villages located in Kibera. The analyses inform of significant differences across the villages when it comes to, among others, income, food insecurity, ownership of land in rural areas, tribal background and trust levels in strangers and community leads. To reach the millions of people living in informal settlements now, and increasingly so in the future, it is advised that research and implementation go hand in hand, with enhanced understanding of the complexities within rural–urban food systems to ensure solutions that are affordable and accessible to low-income groups. On this pathway to fight poverty and hunger in the future, today’s policies and programs must take such complexities into account to positively contribute to strengthening the resiliency and sustainability of rural–urban food systems by ensuring an increase in welfare levels with zero climate impact.

Globally, many policymakers and extension professionals have advocated for the privatization of extension services in order to reduce the burden of funding faced by the state as well as to adequately respond to the low productivity problem of farmers as they endeavor to tackle productivity problems. This study assessed willingness-to-pay (WTP) for private extension services by farmers and identified the determinants of their WTP using Gibi District of Liberia as a case study. A multistage sampling technique was used in selecting 296 smallholder rice farmers in the district while the double-bounded dichotomous choice contingent valuation method was used to elicit maximum WTP value for farmers. Descriptive statistics were computed and the double-bounded logit model used to analyze the data. The findings revealed that 78.7% of the rice farmers were willing to pay for privatized extension services and on average, a farmer was willing to pay US$11.21 per farm visit, almost twice the average daily wage rate of a skilled worker in Liberia. The results from the model showed that WTP was significantly positively influenced by the household head’s age, years of schooling, household size, annual income, and distance to extension service provider. The study recommends that the Liberian government and its development partners should encourage the private sector to invest more in extension services to take advantage of the relatively high farmers’ WTP and effective demand. In addition, the government should design and implement programs that reduce transaction costs in addition to increasing farmers’ income in order to enhance their capacity to pay for privatized extension services.

Approaches to providing sustainable energy in cities have generated considerable interest in academic and policy circles. The development of this body of work, however, has not shed much light on the modes of intermediation that are needed to reconfigure urban energy systems towards sustainability in energy-poor countries. This paper focuses on the role of academics as knowledge intermediaries who can trigger cross-sector collaborations around innovations for a sustainable energy transition in African cities. The research presented here was generated by an interdisciplinary research team made up of partners in Kenya, Uganda and South Africa. The research partners set out to better understand how sustainable energy transitions can be achieved through collaborative efforts between community members, experts and policy actors in the three countries. This paper provides evidence-based reflections on how the research partners used participatory methods to facilitate solution co-design and knowledge co-production over a period of two years under the Leading Integrated Research for Agenda 2030 in Africa (LIRA 2030) program. A key knowledge outcome of the research partnership is an improved understanding of how transdisciplinary research across the sub-region can be used to unearth the socio-spatial, cultural and political dimensions of energy in relation to other urban services such as health and housing. Based on this understanding, the paper proposes transdisciplinary co-design as a promising approach to providing sustainable energy in urban informal settlements in Sub-Saharan Africa.

Poor households in urban informal settlements face a big challenge in accessing clean energy for cooking, heating, and lighting. We use Kenya’s Mathare informal settlement as a landscape site to better understand how cross-sector collaboration can enhance access to sustainable energy in informal settlements. We also demonstrate that academics are well-placed in facilitating multi-stakeholder engagements between community members, experts, and policy actors. This is pursued by drawing on the results of two energy research projects (CoDEC and AfriCLP). We employ a landscape governance framework to re-conceptualise the findings from the CoDEC and AfriCLP projects. Specifically, we use the ecological, socio-cultural, and political dimensions of landscape governance to discuss the relationships between energy demands and other landscape issues in the case study. In conclusion, the paper recommends landscape governance as a promising approach for integrating energy issues with other competing landscape interests, while also encouraging cross-sector collaboration.

There has been the use of geothermal energy across the world for centuries. Although other types of power generation are not as eco - friendly as geothermal energy, some aspects of the development of geothermal energy can have detrimental environmental, economic and social consequences. This research was aimed at investigating the effect of the Menengai Geothermal Development Project on the adjacent community. The effects of topographical change, demographic change, environmental degradation and project - related social responsibility on the livelihoods of surrounding communities have been reviewed in this research. The target population of the study comprised of 1120 households situated in a 5 KM radius of the Menengai Geothermal Project. From this population, clustered random sampling method was used to select 104 participants. Structured questionnaires were used to collect data, and analyzed using descriptive and the Pearson correlation technique. For the data analysis, the statistical program for social sciences (SPSS) was used. Results indicated that project-related landscape alteration, project-related environment pollution and project-related population change had negative but statistically insignificant effect on the livelihood of local communities. Project social responsibility activities had a positive and statistically substantial effect on the livelihoods of local communities. The finding led to the conclusion that implementation of geothermal project has both positive and negative implications on how the local communities live their lives. Project managers should thus find strategies for minimizing the negative effects and maximizing the positive impacts. The study recommends that geothermal project implementing companies should invest more in social responsibility activities in order to optimize impact on community livelihoods. The companies should also develop project designs and technologies that minimize landscape alterations, environmental pollution, and population change as these were found to have a negative effect on livelihood although the effect was no significant.

L'article vise à explorer l'effet de différentes mesures de refroidissement passif utilisant la modélisation et la prédiction thermiques. L'ombrage solaire, les toits verts et les peintures froides ont été incorporés en tant que mesures de refroidissement passif pour évaluer leurs effets combinés sur l'environnement intérieur, le confort thermique et son importance dans la conservation de l'énergie. Une étude expérimentale sur le terrain a été menée dans le climat subsaharien de Kiambu, au Kenya, où des indicateurs de microclimat ont été mesurés pour valider et prédire le comportement thermique. Pour cette étude, la ventilation mécanique et naturelle a été restreinte. La modélisation et la prédiction ont été effectuées dans le logiciel Design Builder et EnergyPlus. Le modèle informatique a été validé avec des données mesurées pendant 20 jours sur le terrain. Une valeur de corrélation de 0,85 entre les valeurs prédites et les valeurs observées a été enregistrée. Ce résultat montre que ce processus de prédiction de l'énergie peut fournir des prédictions raisonnables dans les charges de refroidissement et l'effet du refroidissement passif sur la réduction des gains de température intérieure. El documento tiene como objetivo explorar el efecto de diferentes medidas de enfriamiento pasivo utilizando modelos y predicciones térmicas. El sombreado solar, los techos verdes y las pinturas frías se incorporaron como medidas de enfriamiento pasivo para evaluar sus efectos combinados en el ambiente interior, el confort térmico y su importancia en la conservación de energía. Se realizó un estudio de experimento de campo en el clima subsahariano de Kiambu, Kenia, donde se midieron indicadores de microclima para validar y predecir el comportamiento térmico. Para este estudio, se restringió la ventilación mecánica y natural. El modelado y la predicción se realizaron en el software Design Builder y EnergyPlus. El modelo informático se validó con datos medidos durante 20 días en el campo. Se registró un valor de correlación de 0,85 entre los valores previstos y los valores observados. Este resultado muestra que este proceso de predicción de energía puede proporcionar predicciones razonables en las cargas de enfriamiento y el efecto del enfriamiento pasivo en la reducción de las ganancias de temperatura interior. The paper aims to explore the effect of different passive cooling measures using thermal modelling and predicting.Solar shading, green roofs and cool paints were incorporated as passive cooling measures to evaluate their combined effects on indoor environment, thermal comfort and its importance in energy conservation.A field experiment study was conducted in the sub-Saharan climate of Kiambu, Kenya where microclimate indicators were measured for validating and predicting the thermal behaviour.For this study, both mechanical and natural ventilation were restricted.Modelling and prediction were done in Design Builder and EnergyPlus software.The computer model was validated with data measured for 20 days on the field.A correlation value of 0.85 between the predicted values and the observed values was recorded.This result shows that this energy prediction process can provide reasonable predictions in cooling loads and the effect of passive cooling in reducing indoor temperature gains. تهدف الورقة إلى استكشاف تأثير تدابير التبريد السلبي المختلفة باستخدام النمذجة الحرارية والتنبؤ. تم دمج التظليل الشمسي والأسقف الخضراء والدهانات الباردة كتدابير تبريد سلبية لتقييم آثارها مجتمعة على البيئة الداخلية والراحة الحرارية وأهميتها في الحفاظ على الطاقة. تم إجراء دراسة تجريبية ميدانية في مناخ جنوب الصحراء الكبرى في كيامبو، كينيا حيث تم قياس مؤشرات المناخ المحلي للتحقق من صحة السلوك الحراري والتنبؤ به. بالنسبة لهذه الدراسة، تم تقييد كل من التهوية الميكانيكية والطبيعية. تم إجراء النمذجة والتنبؤ في برنامج Design Builder و EnergyPlus. تم التحقق من صحة نموذج الكمبيوتر ببيانات تم قياسها لمدة 20 يومًا في الميدان. تم تسجيل قيمة الارتباط 0.85 بين القيم المتوقعة والقيم المرصودة. تظهر هذه النتيجة أن عملية التنبؤ بالطاقة هذه يمكن أن توفر تنبؤات معقولة في أحمال التبريد وتأثير التبريد السلبي في تقليل مكاسب درجة الحرارة الداخلية.

In this paper, we perform Bit Error Rate (BER) estimation in a low-voltage indoor power line communication channel. This is done over power line channels impaired with bursty impulsive noise in the broadband frequency range of 1–30 MHz. This method is based on the estimation of the Probability Density Function(PDF) of the soft observed samples. We first of all use the Gaussian Mixture Method (GMM) distribution model to motivate the Expectation-Maximization (EM) algorithm in a fairly informal way. GMM is a simple linear superposition of Gaussian components, aimed at providing a richer class of density models than the single Gaussian. The optimal number of Gaussians is computed by using Mutual Information theory. Simulation results are presented for the proposed BER estimator in the frame work of a multiuser Binary Phase Shift Keying (BPSK) system and shows that attractive performance is achieved. These results show that GMM technique provides a good fit to our data samples and thus provides better performance in the sense of minimum variance of the estimator. This drastically reduces the needed number of samples required to estimate the BER in order to reduce the required simulation run-time, even at low BER.