Affordable Energy Research Articles

Enhancing the Predictability of Wintertime Energy Demand in The Netherlands Using Ensemble Model Prophet-LSTM

Energy demand forecasting is crucial for maintaining stable and affordable energy supplies, especially for vulnerable populations most affected by shortages and high costs. In the Netherlands, transmission system operator TenneT has raised concerns about potential electricity shortages by 2030. Rising energy prices and the impact of climate change on the energy demand further complicate today’s energy market. Policymakers lack clear insights into demand patterns, which complicates the optimization of energy use and the protection of at-risk communities. Accurate and timely forecasts are essential for addressing these issues and supporting sustainable energy management. This research focuses on enhancing the accuracy and lead time of wintertime energy demand forecasts in the Netherlands using advanced machine learning. The ensemble model Prophet-LSTM is trained on hourly load consumption data combined with climate change-related and energy price predictors. The results demonstrate significant improvements over baseline models, achieving a Pearson correlation coefficient of r=0.93 compared to r=0.50 in prior studies, as well as accurate forecasts up to 180 days ahead, compared to 2 months. Incorporating climate change-related predictors is challenging due to multicollinearity, highlighting the importance of careful predictor selection. Including energy price predictors yielded modest yet hopeful results, suggesting their ability to optimize energy demand forecasting.

Literature review on optimization of transboundary water for irrigation

ABSTRACT Transboundary water resources are essential for agricultural sustainability and regional development, and they are intrinsically linked to achieving the United Nations' SDGs and the water-food-energy nexus (WFE-NEXUS) concept. Despite challenges such as conflicting allocation and climate change impacts, effective transboundary water management for irrigation is crucial to meeting the SDGs of eradicating hunger, providing clean water and sanitation, offering affordable and sustainable energy, and taking climate action. This work synthesizes approaches to transboundary water for irrigation optimization, highlighting the significance of a holistic plan that considers both technical and social factors. Remote-sensing technologies, data forecasting, hydrology and hydraulic modelling, and water resource modelling all contribute to maximize water allocation and policy creation, particularly when paired with collaborative government features. This integrated approach to transboundary water for irrigation optimization fosters long-term development by improving livelihoods, resilience, and inclusive growth through efficient resource management.

Nationwide Assessment of Solar PV Power Potential Using Geospatial Data and Collaborative Research with Higher Education Institutions: Case of the Philippines

Abstract. Geospatial technologies present a significant opportunity to assess solar photovoltaic (PV) power potential through remote sensing techniques and geospatial analysis. This aligns with the goal of ensuring access to affordable, reliable, and sustainable energy, one of the Sustainable Development Goals (SDG) that the Philippine National Economic and Development Authority (NEDA) aims to achieve. In support of the said SDG, a research project, called Project SINAG, has developed a method for estimating solar PV power resources utilizing high-temporal remotely-sensed data. The primary objectives of this study are twofold: first, to develop a webGIS platform for solar energy resource information access and decision support; second, to conduct information dissemination and capacitybuilding activities for various stakeholders in the solar energy sector. The localized assessment of solar PV power potential incorporates meteorological and geomorphological factors such as high temperature, dust deposition, and slope. Collaboration with academic institutions, government agencies, and the solar energy industry has been instrumental in providing capacity-building through training workshops, internships, and on-the-job training. Moreover, the project has produced information, education, and communication (IEC) materials, launched a webGIS portal, and supported data requests and student research. The webGIS platform serves as the primary information dissemination tool for the project, enabling rapid sharing of research outputs with end-users. To enhance the platform, future developments may include additional functionalities such as community forums, client feedback mechanisms, mobile application development, and the integration of real-time data for map layers and forecasting tools.

Technical & Economic Feasibility Study of Proposed Pump Storage Power Plants at Kuda Oya, Mul Oya, Gurugal Oya, and Dambagasthalawa

This paper presents a Technical and Economic Feasibility Study of proposed Pumped Storage Power Plants (PSPPs) at KM (Kuda Oya, Mul Oya), KMG (Kuda Oya, Mul Oya, Gurugal Oya), KG (Kuda Oya, Gurugal Oya), and Dambagasthalawa. Sri Lanka aims to transition away from a coal-dominant electricity sector within the next decade, aligning with sustainability goals outlined by the United Nations. In pursuit of affordable and clean energy sustainability, the Sri Lankan government has opted to shift its long-term energy policy towards renewable sources, departing from fossil fuels. Despite this shift, a significant portion of Sri Lanka's electricity consumption—approximately 600 MW from oil and 900 MW from coal—persists. The country now aims to source 80% of its energy from renewable sources, necessitating a focus on underutilized opportunities. In selecting the best candidate sites for Pumped Storage Power Plant (PSPP) design, comprehensive hydrological and sedimentation studies play a pivotal role. In this endeavor, we endeavor to re-rank the selected candidate sites for pumped storage power plants considering technical & financial feasibility by conducting comprehensive hydrological and sedimentation studies. These studies are pivotal for assessing the feasibility and long-term viability of potential sites, aiming to select the most sustainable candidate site in every aspect. Therefore, the primary objective of this research is to conduct a thorough hydrologic study of the proposed KMG and Dambagastalawa pump storage power plants, focusing on identifying potential energy-saving opportunities in pumping when these plants operate as open-loop systems. This study will analyze the hydrology of the upper ponds of the Kuda Oya, Mul Oya, and Gurugal Oya (KMG) pump storage power plants, and the Dambagastalawa Oya pump storage power plant, assessing the potential reduction in pumping energy. Such insights are essential for optimizing the design and operation of PSPPs to ensure economic viability and sustainable energy generation. Furthermore, this research addresses the importance of studying sedimentation in both the upper and lower ponds of the KMG and Dambagastalawa pump storage power plants. Sedimentation calculations will be performed to determine reservoir lifetimes, offering critical insights into the long-term feasibility and maintenance requirements of these projects. The findings of this study are expected to provide valuable guidance to policymakers, investors, and PSPP designers in selecting the most suitable sites for addressing Sri Lanka's peak power demands and urgent electricity needs. By emphasizing the significance of hydrological and sedimentation studies, this research underscores the importance of thorough site assessment in optimizing the design and operation of Pumped Storage Power Plants.

The role of the construction industry in the recovery of processing enterprises during the crisis

The article discusses the consequences of the crisis period for the work of processing enterprises in Ukraine. It is established that hostilities on the territory of our state and general instability lead to a decrease in production and force processing enterprises to cease their activities. Many enterprises are experiencing serious financial difficulties due to work restrictions, problems with the supply of raw materials, and the loss of industrial facilities. In the summer of 2022, the percentage of companies that closed or were in the process of ceasing operations was 46.8 %. A significant consequence of the war for the Ukrainian economy at the moment is the rapid changes in the territorial location and the change in the symmetry of the processing industry of Ukraine. The war also affected the sectoral structure of the processing industry, producing significant shifts and changes in the volume of products sold. The current political situation in Ukraine and the severance of business chains with the temporarily occupied territories require processing enterprises to search for new markets for products, sources of supply of raw materials, change logistics links, increase the production of raw materials and their own products. During the study, it was found that certain key aspects of the impact on the activities of processing enterprises were previously insufficiently studied. It is determined that the construction industry is of critical importance for the processing industry of the State during the crisis, which is designed to contribute to the recovery of this industry: to develop infrastructure, to build and modernize production facilities, which allows to introduce new technologies and optimize production processes, to improve the conditions of production itself, to build energy facilities to provide processing enterprises with stable and affordable energy supply, to apply modern construction technologies that will create environmentally friendly and energy-efficient production. For the restoration and development of the processing industry of Ukraine, taking into account the impact of the construction industry, we propose to apply the following measures: widespread implementation of the enterprise relocation program with the expansion of state support; the use of state programs for the reconstruction of property and lending, the development of international communications and the European vector for the recovery of the post-war industry based on the ESG concept and the principles of building back better, compliance with the principles of energy efficiency and energy saving, and the application of decarbonization measures. These tools are designed to provide stimulating processes in the processing industry to achieve and exceed the prewar level of the volume of competitive and high-quality products. The development of the construction industry plays an important role in the restoration of processing enterprises in Ukraine, so it is important to create favorable conditions for their cooperation, to develop comprehensive development strategies aimed at ensuring sustainable economic growth and support.

Unveiling the potential of lithium fluoride phosphate (Li2MPO4F, M = Fe, V, Mn) for the next generation of lithium-ion batteries: A comparative study based on first principles and molecular dynamic simulations

LiFePO4 (LFP) cathode with olivine crystal structure has been a key player in safe and affordable energy storage, owing to its low-cost iron and high electrochemical stability within a voltage range of commercial electrolytes (2.8–3.4 V). To maintain these benefits while enhancing its energy density, Li2MPO4F was developed by introducing fluorine (F) and replacing iron with other transition metals (M). However, previous studies on these materials primarily measured performance within a limited voltage window (e.g., 2.5–4.5 V), making it challenging to analyze their performance under advanced electrolytes with a broader voltage range. In this study, we took a novel approach by utilizing first principles and molecular dynamic calculations to investigate the electrochemical performance of Li2MPO4F with three types of transition metals (M = V, Fe, Mn). This unique methodology, which includes calculations on theoretical voltages, atomic structures, and diffusion coefficient after structural optimization, allowed us to predict the impact of transition metals on cathode performance. By closely comparing the expected results, this study discusses the pros and cons of each cation substitution and suggests suitable cathode materials for batteries with high energy density and superior rate capability.

Hybrid renewable energy systems for sustainable power supply in remote location: Techno-economic and environmental assessment

Electricity supply is inconsistent and unreliable in many remote areas of India, where depending solely on a single renewable energy source is impractical. In this context, this study investigates the potential of off-grid hybrid renewable energy systems (HRES) to meet the energy needs of a village community in India. Techno-economic analysis and life cycle assessment have been employed to compare eleven HRES combinations which combine photovoltaic (PV), wind turbine (WT), battery (BAT), diesel generator (DG), biogas generator (BG), converter (CONV), and electrolyser (ELEC). By optimising the size and capacity of each component in HRES, this study aims to identify the combination with the lowest levelised cost of electricity (LCOE). This research aligns with United Nations Sustainable Development Goal No. 7 to seek “Affordable and Clean Energy”. The findings highlight that HRES comprising PV/WT/BAT/CONV/DG exhibits the lowest LCOE (0.319 $/kWh) and net present cost (6.81 M$) among all combinations. In systems with partial reliance on diesel, integrating both PV and WT could reduce diesel consumption and increase the renewable fraction to 87.4 %. For HRES involving PV, a significant contribution to greenhouse gas emissions occurs during the construction stage. The WT/DG combination, with its high diesel dependency, has the largest global warming potential. The efforts from this study provide valuable insights into determining the optimal HRES for remote communities by considering their economic and environmental factors.

Domestic and foreign cap-and-trade regulations, carbon tariffs, and product tariffs during international trade conflicts: A multiproduct cost-efficiency analysis

This paper develops a down-and-out call option model with structural breaks to examine the effects of domestic environmental policies on carbon-intensive firms amid international trade conflicts. The findings reveal that stricter cap-and-trade regulations, carbon tariffs, and product tariffs exacerbate pollutant-specific diseconomies of scale, limit economies of scope, and reduce firm equity. The positive impact on pollutant-specific diseconomies of scale leads to higher pollution, hindering progress toward Sustainable Development Goal 7 (SDG 7: Affordable and Clean Energy) from a multiproduct cost-efficiency perspective. Meanwhile, the negative impact on economies of scope results in fewer products and pollutants, aligning with SDG 7 but conflicting with Sustainable Development Goal 8 (SDG 8: Decent Work and Economic Growth), as the scope measure accounts for efficiency in both products and pollutants. Additionally, the negative impact on firm equity discourages progress toward both SDGs, especially during trade conflicts. In summary, environmental policies distinctly affect firm multiproduct cost efficiency and equity, particularly under varying trade conflict conditions.

Optimal planning for hybrid renewable energy systems under limited information based on uncertainty quantification

Developing hybrid renewable energy systems (HRES) is crucial for ensuring affordable, sustainable, and reliable energy access in remote rural and island regions. Rich and detailed data play a pivotal role in the optimal design of HRES. However, remote areas often face data limitations due to inadequate metering infrastructure, which further increases uncertainties in HRES design. This paper proposes a planning optimization method that quantifies multiple uncertainties, requiring only limited information for the optimal HRES design. First, uncertainties in HRES planning are classified into different types based on intrinsic randomness, data availability, and impact level. Then, by integrating uncertainty quantification with credibility theory, knowledge-based scenario generation models are developed to leverage limited available information to generate extreme and typical operating conditions for a tailored HRES design. Finally, a fuzzy credibility-constrained stochastic-robust optimization model is proposed to optimize the design of HRES. A practical case facing significant data scarcity and gaps is used to validate the effectiveness of the proposed method. The proposed approach reduces the loss of load probability for HRES to 0.02% and lowers the levelized cost of energy to $0.16/kWh—33% lower than that of the deterministic method and 79% lower than that of the traditional stochastic method.

Smart Grids: Integrating AI for Efficient Renewable Energy Utilization

The urgent global shift from fossil fuels to renewable energy sources necessitates innovative solutions to address energy system management challenges. Smart grids, equipped with sophisticated infrastructures, play a crucial role in this transition. This study integrates Artificial Intelligence (AI) into smart grids to enhance their efficiency and reliability, directly supporting the United Nations Sustainable Development Goals (SDGs), particularly SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 11 (Sustainable Cities and Communities). Employing a mixed-methods approach, the research utilizes historical and real-time data, applying machine learning algorithms such as Linear Regression, Support Vector Regression (SVR), Recurrent Neural Networks (RNN), and Long ShortxTerm Memory (LSTM) for predictive accuracy in energy management. Optimization techniques like Genetic Algorithms and Particle Swarm Optimization (PSO) are also implemented for resource scheduling and grid balancing. The results demonstrate significant improvements, with an 11.76% increase in energy efficiency and grid stability, a 66.67% reduction in prediction errors, and a 20% decrease in operational costs compared to conventional systems. These enhancements highlight the transformative potential of AI in smart grids, promoting more efficient and sustainable energy utilization. The study concludes that AI-driven smart grids are pivotal in achieving the SDGs by providing scalable and efficient solutions for renewable energy integration, thereby fostering sustainable development and reducing environmental impacts.

Evaluation of Clustering Techniques for Solar Irradiance Prediction for Optimal Design of Microgrids in Rural Communities

Abstract The electrification of rural communities is crucial from both social and economic perspectives, aligned with Sustainable Development Goal 7: “Affordable and Clean Energy”. This study presents a comprehensive comparison of clustering techniques, including k-means, Gaussian Mixture Models (GMM), Hierarchical Clustering, Density-based Spatial Clustering of Applications with Noise (DBSCAN), and Agglomerative Clustering, aimed at enhancing solar irradiance prediction. Leveraging historical climate data from a rural community in the coastal region of Ecuador, each technique is evaluated using error metrics such as Mean Absolute Error (MAE) and Coefficient of Determination R2. This assessment identifies the most effective clustering technique in this specific context. In order to delve deeper into these comparisons, simulations are conducted in AMPL to validate and refine the selection of techniques. In this process, it is considered the sizing and design of a microgrid within the Barcelona community, Ecuador, which integrates various energy sources, including solar. Additionally, a penalty system is introduced for unmet energy demands during less critical periods, thereby optimizing efficiency and enhancing energy availability within the community. In conclusion, this paper introduces a scalable methodology to improve solar irradiance prediction, emphasizing the significance of comparing clustering techniques as its main contribution. This advancement in prediction accuracy has the potential to enhance the feasibility and efficiency of renewable energy systems for rural communities, thereby fostering sustainable economic growth and bolstering efforts in climate change mitigation and adaptation.

Recent advances in H2 purification and CO2 capture: Evolving from flat sheet to hollow fiber membranes

Hydrogen (H2) production and demand have steadily increased, leading to a rise in carbon dioxide (CO2) emissions since fossil fuels are the current raw material for H2 production. Thin film composite (TFC) hollow fiber membranes have become significant in H2 purification and CO2 capture, playing a critical role in developing next-generation fuels and supporting the United Nations Sustainable Development Goal 7 (SDG 7) – Affordable and Clean Energy, with the goal of providing universal access to clean, advanced, and renewable energy for all. However, the polymeric selective layer of TFC membranes faces a trade-off between permeability and selectivity, as well as challenges including CO2 plasticization and physical aging. Additionally, H2/CO2 separation remains particularly challenging because H2, being diffusivity-selective, permeates more quickly through the membrane due to its smaller molecular size and higher kinetic energy, while CO2, being solubility-selective, has a high affinity for dissolving in most polymeric membranes. Herein, this review provides an in-depth exploration of innovative modification strategies designed to overcome these challenges in glassy polymeric membranes and enhance H2 separation performance in the recent 10 years. Various nanofillers, such as metal-organic frameworks (MOFs) such as University of Oslo (UiO), Materials Institute Lavoisier (MILs), and Zeolitic Imidazolate Frameworks (ZIFs), have shown remarkable potential in boosting gas separation capabilities due to their superior compatibility with polymer matrices and tunable properties. The review also explores different types of hollow fiber membranes, including single layer, dual-layer, and TFC, alongside fabrication techniques like interfacial polymerization and dip-coating. Critically, the analysis highlights cutting-edge strategies to improve membrane performance, such as (i) thermal cross-linking, (ii) chemical cross-linking, (iii) ultraviolet (UV) cross-linking, (iv) polymer blends, and (v) modified fillers, along with their objectives and expected outcome. Furthermore, the review spotlights breakthroughs in H2/CO2, H2/CH4, and H2/N2 separation technologies, emphasizing the critical need for continued innovation to drive sustainable H2 production and meet the growing clean energy demand.

Harnessing biomass waste-to-energy for sustainable electricity generation: prospects, viability, and policy implications for low-carbon urban development

AbstractBiomass waste-to-energy (WtE) generation is a potential pathway for green urban transition in developing countries which can contribute significantly to sustainable development goal 7: affordable and clean energy. However, unlike fossil fuel energy systems, the economic returns from WtE systems are low because WtE generation is capital-intensive and requires subsidies. This study examines the prospects of a sustainable biomass electricity generation from rice husk (RH) using a large dataset of rice milling activities in a fast paced urban transition economy. The study analyzes the viability of several RH biomass electricity generation scenarios using indicators such as net electricity output, economic returns (benefits), and levelized cost of electricity (LCOE). The results show that several mills/mill clusters generate sufficient daily RH that can power between 0.8 and 2.2 MW plant with a combined electricity output of about 500,000 MWh per annum. The economic analyses show that all RH biomass electricity generation scenarios return positive economic benefits under reduced social discount rates of 2–6%. Moreover, the LCOE of all scenarios are less than those of electricity generated from other sources. These results demonstrate that biomass waste-to-energy generation is viable for green urban development through low-carbon decentralized energy systems. Several policy implications of the findings are highlighted, including the need for policymakers and energy stakeholders to adopt sustainable biomass energy generation models such as “design, build, and operate” (DBO) to achieve sustainable WtE generation regimes that ensure green urban transition. Such a model will contribute to a circular economy and facilitates sustainable urban development that satisfies climate-related SDGs. Graphic abstract

Current development, optimisation strategies and future perspectives for lead-free dielectric ceramics in high field and high energy density capacitors.

To meet the United Nations' sustainable development goal of affordable and clean energy, there has been a growing need for low-cost, green, and safe energy storage technologies. High-field and energy-density capacitors have gained substantial attention from academics and industry, particularly for power electronics, where they will play a key role in optimising the performance of management systems in electric vehicles. The key figure of merit, energy density (Wrec), for high-field applications has dramatically increased year-on-year from 2020 to 2024, as evidenced by over 250 papers, demonstrating ever larger Wrec values. This review briefly introduces the background and principles of high energy density ceramics, but its focus is to provide constructive and comprehensive insight into the evaluation of Wrec, Emax, ΔP, and η, and more importantly, the normalised metrics, Wrec/Emax and Wrec/ΔP in lead-free dielectric ceramics. We also present several optimisation strategies for materials modification and process innovation that have been recently proposed before providing perspectives for the further development of high-field and high-energy density capacitors.

Greenwashing by the fossil fuel industry: impediments to SDGs

Abstract The fossil fuel industry, a major commercial determinant of public and environmental health, constitutes a central challenge to the achievement of the SDGs. Motivated by profit, the industry has contributed to establishing the current global reliance on fossil fuel as the primary energy source and essential raw material in global production. Major oil companies have purposefully hindered the research and transition towards renewable energy. This was achieved through an intricate web of interference and mechanisms that fall under the corporate playbook, such as political interference through lobbying to stagnate carbon emission reduction, influences on carbon pricing policies, and hinderances to environmental protection legislation. These practices known as ‘greenwashing’ have resulted in misinformation, interfered with climate action in an aim to increase demand for their products, to decrease the pressure from society on the industry, and portray a green image to consumers. Using the commercial determinants of health framework and focusing on the Middle East, this presentation will illustrate how fossil fuel companies falsely advertise their products as environmentally friendly, resulting in environmental degradation, and impede the achievement of most SDGs, especially SDG 3 (good health and wellbeing), SDG 7 (affordable and clean energy), and SDG 13 (climate action).

Innovation in distributed energy services for sustainable development: case studies from sub-Saharan Africa

Abstract In this work, we explore how locally led innovations can advance sustainable energy access in low-income regions of Africa. Given the emphasis of the Sustainable Development Goals on the importance of affordable, reliable, and sustainable energy, we critically assess how local innovations can address the unique challenges of regions characterized by informality and low purchasing power and where existing grid-based electricity supply is weak. Through case studies, we highlight successful initiatives in expanding energy services access, including product bundling, pay-as-you-go financial models, leveraging existing supply chains, and securing strong funding support. Our findings underscore the importance of local ownership, contextual knowledge, and the adaptation of innovations to specific socio-economic and cultural conditions. By comparing the case studies, we identify common strategies that can contribute to the effectiveness of local innovations in improving energy access and sustainability that can inform efforts to replicate and scale up such initiatives. We conclude by identifying common elements contributing to the success of these cases and their significance, focusing on those crucial for achieving speed, scale, and impact.

7.C. Scientific session: Commercial determinants of health: impeding attainment of the Sustainable Development Goals

Abstract The commercial determinants of health (CDOH) and the adverse impacts they have on health equity globally, have recently emerged as an innovative growing field of research in public health. The corporate playbook comprises a myriad of strategies and tactics that aim to enhance profitability for the commercial actors, while harming health and posing grave risks to planetary health for current and future generations. The literature however, rarely explicitly makes the connection between commercial determinants and the impact they have on the attainment of the Sustainable Development Goals (SDGs) set out by the United Nations in 2015. This workshop aims to use the commercial determinants of health framework as a new approach to draw attention to, and make linkages between, commercial determinants and the challenges they pose to the attainment of several if not all the global SDGs. The four presentations showcase exemplars of the commercial determinants to include the firearms industry, fossil fuel industry, food industry and the tobacco industry focusing on impacts in low- and middle-income countries (LMICs). The workshop will start with a brief overview of the CDOH framework, their corporate playbook, and the progress in SDG attainment globally while presenting the first case on the firearms industry trade impacting armed conflicts that impede SDG 3 (good health and wellbeing), 10 (reduced inequalities), and 16 (peace, justice and strong institutions). The second presentation will discuss how the fossil fuel industry uses greenwashing tactics to conceal its harmful activities thereby compromising SDGs 7 (affordable and clean energy), 11 (sustainable cities and communities), and 13 (climate action). The third presentation will address how the tobacco industry impedes the advancement of SDG 3, 8 (decent work and economic growth), 13 (climate action) and 17 (partnerships for the goals) perpetuated by national system level attributes. The last presentation will showcase how the food industry challenges SDG 3 in its production of ultra-processed foods. The workshop will draw on evidence from LMICs, but is also eye opening for high-income countries of Europe which face industry interference in social and health policymaking progress in SGD attainment. The audience will be engaged in a short warm-up exercise at the start of the workshop through an app for real-time feedback accessed through a QR code on the screen, and will interact with the presenters at the end of the workshop if time permits. Key messages • All commercial actors pose a direct or indirect threat to progress in attaining the SDGs. • The commercial determinants of health pose are in direct contradiction to the SDG 17 through their corporate playbook.

A New Approach to Measuring Institutional and Researcher Contributions to the SDGs: Combining Data from Elsevier SciVal and VOSviewer

The Sustainable Development Goals (SDGs), established by the United Nations in 2015, are a comprehensive global framework that addresses social, economic, and environmental challenges through sustainable development. This study examines the role of universities, specifically focusing on the Department of Mechanical Engineering at Universitas Muhammadiyah Magelang (UNIMMA), in contributing to the SDGs. The study utilized data from Elsevier’s SciVal to analyze the department’s contribution to the SDGs through scientific publications in the Scopus database. A total of 97 out of 156 articles published by nine researchers from the department were found to contribute to various SDGs, with a significant focus on Goals 7 (affordable and clean energy), 17 (partnerships for the goals), 9 (industry, innovation, and infrastructure), and 12 (responsible consumption and production). The study highlights the department’s collaborative efforts and alignment with global sustainability goals. In addition, VOSviewer was used to map the research collaboration network within the department, revealing strong contributions to energy efficiency, sustainable technologies, and climate action. However, the department's research shows limited contribution to social SDGs such as poverty alleviation and gender equality. By mapping the university’s contributions to the SDGs, this study helps faculty members identify opportunities for targeted research collaborations, address gaps in SDG contributions, and enhance partnerships with researchers from other institutions, thus broadening the university’s impact on global sustainable development goals.

TACIT EVASION OR A MISPLACED POLICY GAZE: A POLITICAL ECOLOGY OF THE DEFORESTATION AND CHARCOAL CONUNDRUM IN MALAWI

ABSTRACT Although banned in many countries, charcoal production remains a key driver of deforestation in Africa, yet a livelihood source for many, with evidence showing the practice has risen to unprecedented levels. While rural poverty is often framed as the driver, the rise in charcoal consumption among a burgeoning urban population suggests a multiplicity of drivers. Using in-depth interviews with diverse stakeholders in Malawi, this paper examined the underlying drivers of the charcoal conundrum. Although poverty is indeed a driver, our findings suggest the charcoal conundrum is rooted in complex sociopolitical dynamics and class relations at multiple scales. Charcoal production, a highly stigmatized economic activity at the rural scale, is the key source of fuel for a burgeoning urban population lacking affordable alternative energy sources. Our findings further reveal what we theorize as “hierarchical corruption,” featuring an elite class of “big charcoal dealers” who pay bribes to freely transact charcoal while rural people continue to be disproportionately targeted with draconian forest laws. These dynamics suggest a tacit evasion of the real drivers of deforestation and a misplaced policy gaze in forest governance. Contemporary forest policy must look “beyond forest” to address both production and consumption side drivers of deforestation, particularly poverty, and the lack of clean energy alternatives.

AI-Assisted Automated Identification of Human Activities Using Ficus religiosa Leaf-Based Triboelectric Nanogenerator.

Movement monitoring and effective identification of different actions are the keys that help in fitness services, health status, clinical studies, etc. In this technological era, Internet of Things (IoT) technologies, including smart wireless devices and sensors, are very effectively used for monitoring human activities, but the demand for sustainable and green power sources is a crucial issue with these devices. Triboelectric nanogenerators (TENG) are proven to be promising applications in these devices because they harvest energy from the surrounding environment and eliminate the use of batteries as power sources. As a green energy source, this study emphasizes the fabrication of biodegradable materials-based TENGs, which are eco-friendly and are related to clean and green energy as per the UN's sustainable development goals SDG 7 (affordable and clean energy). In the present work, a natural Ficus religiosa leaf (FRL) of the F. religiosa tree is used in designing and fabricating a TENG (FRL-TENG). Also, an approach is discussed to compare the performance of FRL-TENG with TENGs fabricated from other waste biodegradable materials such as garlic tunic, onion tunic, and eggshell membrane (ESM). During the experimental study, it is observed that the FRL-based TENG produced maximum voltage in comparison to other material combinations selected in this study. The generated electric output from these TENG combinations is also used to power an array of tens of green-light-emitting diodes (LEDs). Furthermore, this paper also proposes the use of FRL-TENG as a wearable sensor to collect information and monitor the physical activities of the user, viz., walk, jump, and run. To recognize the movement status, the FRL-TENG sensor is integrated with an extra randomized tree-based machine learning model for accurately distinguishing the user's three activities with an accuracy of 96%. The work showcases an innovative approach to encourage customized uses of TENG sensors in human motion monitoring and permits the development of intelligent, self-powered systems for new applications.