Access to affordable, reliable, and sustainable energy remains one of the most pressing challenges in humanitarian settings. Aggregator funds serve as financial intermediaries that pool capital from multiple sources, repackage it into MSME-appropriate instruments, offering the potential to transform fragmented transactions into an investable asset class. This study draws upon expert interviews (n = 12), a practitioner workshop with 40 last-mile energy distributors in Uganda, and two in-depth case studies of emergent aggregator mechanisms (the Refugee Environmental Protection Fund and the P-REC Aggregation Facility) to examine their potential for addressing financing gaps for energy distributors operating in humanitarian settings. Guided by a novel analytical framework grounded in financial intermediation theory, institutional theory, and market-shaping literature, the analysis identifies five financing gaps (scale, risk, information, capacity, and time) and assesses the market-building potential of aggregator funds. The findings revealed systemic barriers restricting MSME access to finance, especially the timing misalignment between the short humanitarian funding cycles and the long-term capital needs. The case studies point to genuine innovation and growing private sector appetite to serve last-mile settings, although findings remain largely exploratory and only indicative of real market trends. They also show how institutional environments hamper execution, and complex funds may distract from the basic need for patient working capital. It concludes that aggregator funds offer promise but require institutional reform to achieve scale or sustainability.
To improve the hybrid renewable cooling system, it is necessary to test the effects of additional key operational factors on its performance. In this study, a comprehensive sensitivity analysis of a solar-biomass thermoelectric-adsorption cooler was conducted to establish the priority of the effects of design and operational parameters on the system efficiency using high-fidelity EES simulation and Artificial Neural Network (ANN) surrogate modelling. The thermodynamic model of the hybrid system was created using the Engineering Equation Solver (EES). A Latin Hypercube Sampling (LHS) plan was employed to create 50 input parameter variations (solar irradiance, fuel biomass, TE current, and adsorption cycle duration). The System Coefficient of Performance (COP) was predicted by the EES model for every combination, producing COP values that ranged from 0.6036 to 0.6307 with a mean of 0.6143. Then, this functionally trained and efficient ANN surrogate model can predict the COP rapidly without hundreds of costly calls to the computationally intensive EES. The ANN model achieved strong prediction performance, with an overall Mean Squared Error (MSE) of 2.12×10−6, a correlation coefficient (R) of 0.99478 and a coefficient of determination (R2) of approximately 0.9896 for the complete dataset. Sensitivity analysis performed using ANN examines the effect of the system parameters. Within the investigated design space, permutation-based sensitivity analysis ranked biomass feed rate highest in normalised importance (42.3%), followed by adsorption-cycle time (31.2%), solar irradiance (17.6%) and thermoelectric (TE) current (8.9%). These percentages describe the relative importance assigned by the ANN-based analysis. Overall, this study provides a strong correlation and significant sensitivity analysis. Furthermore, an integrated detailed regression analysis supports the ANN surrogate for an efficient design sensitivity evaluation. Calculations from the study showed that the thermal component (adsorption cycle) operation contributes the most to the overall system efficiency, whereas the impact of the electrical components (TE current) diminishes at high load values. The trained ANN provides predictions on a millisecond timescale, substantially reducing the computational burden associated with repeated EES simulations and supporting rapid design-space screening and sensitivity analysis. The maximum observed COP among the 50 simulated cases is 0.630744608 at run 18, corresponding to a biomass rate of 0.000222222 kg/s and an adsorption-cycle time of 81.99 min. The research findings offer a platform for maximum efficiency optimization for future experimental and smart hybrid cooling system development.
This study assesses electric vehicle (EV) readiness and prospective impacts in 15 Caribbean Small Island Developing States (SIDS) to inform policies for extending adoption beyond initial uptake. An EV Readiness Index comprising ten indicators and an EV Impact Index comprising six indicators provide a comparative assessment of national enabling conditions and potential benefits. Chasm theory provides an interpretive lens for examining the transition from early adopters to the early majority. The findings indicate that favorable operating-energy-cost conditions coexist with uneven public charging provision and financing environments, while the assessed electrification scenario identifies a common requirement for additional electricity generation. Integrating the indices distinguishes three readiness–impact profiles: Market-Driven Adopters, Government-Led Initiators, and Structure Developers. These profiles inform differentiated priorities for addressing remaining market constraints, establishing enabling conditions, and strengthening the wider benefits of electrification. The principal implication is that favorable aggregate readiness should not be equated with preparedness for mainstream adoption, and that conditions supporting adoption are distinct from those determining its sustainable-development contribution. The study provides a diagnostic framework for identifying policy priorities relevant to “jumping the chasm” in Caribbean SIDS and for informing comparative assessments in other small-island contexts.
Brazil hosts the largest inventory of announced hydrogen projects in Latin America, but the maturity of these announcements and the role of the 2024 policy framework require closer examination. This review analyses 70 Brazilian projects in the October 2024 release of the International Energy Agency (IEA) Hydrogen Production and Infrastructure Projects Database and relates their development status, technology, principal product, declared end use and location to the national legal framework. Concept- and feasibility-stage projects account for 87% of the inventory. Only 67 MWel had reached final investment decision (FID) or construction and 3.9 MWel was operational, compared with 68.4 GWel announced. Hydrogen is the most common principal product, whereas ammonia is the most frequently declared end use; announced capacity is also concentrated in a small number of port-industrial clusters. These results support two practical priorities: implementation instruments should favour projects with verifiable offtake and site readiness, and existing industrial demand for ammonia and other feedstocks may provide an initial market. The study treats October 2024 as a fixed analytical snapshot and reports later project developments separately. It therefore describes project maturity and policy implementation conditions rather than estimating a causal effect of the legal framework on project progression.
Vertical farming offers high land-use efficiency but is energy-intensive. Coupling it with photovoltaics can mitigate this energy burden, yet year-round performance data remain scarce. We conducted a one-year rooftop PV-integrated vertical farming experiment in Jinhua, China, using Hippeastrum as the model crop and testing three light intensities and two planting configurations. Productivity, energy efficiency, and economic viability were evaluated using three indicators: Land Equivalent Ratio, Energy Contribution Index, and net present value. We combined measured crop yield and energy use with PVGIS-simulated photovoltaic generation and a 40-county regional simulation to examine spatial heterogeneity. Under the set light intensities, the measured yield of Hippeastrum was 1467.41–2259.31 cm·m−2, far exceeding the literature-derived greenhouse benchmark. The measured energy consumption was 691.3 kWh·m−2·yr−1, of which LED lighting accounted for the largest share (73.6%). Combining simulated generation with measured consumption gives an estimated hybrid measured-simulated annual ECI of 37.3%. Simulations further indicated that at a daily light integral of 2.89 mol·m−2·d−1, the four-layer vertical farming system reached a net present value of 166,886 CNY and a model-estimated energy contribution index of 25.4%. Sensitivity analysis identified crop price and yield as the dominant economic drivers. Overall, high-value species were central to the viability of photovoltaic-integrated vertical farming.
