There is a growing trend toward the use of renewable sources to produce clean energy and mitigate the effects of climate change. Second-generation lignocellulose biomasses, such as agro-residues, comprise a potential energy source as a byproduct of agriculture. Ecuador has optimal climate conditions that allow for the cultivation of different types of crops. This makes agriculture a relevant economic activity in the country; however, the residues obtained from agriculture have not been investigated for the establishment of a bioenergy industry. This study evaluated the potential of three varieties of sugarcane bagasse, named PR 980, CC 85-92, and CB 40-59, for bioenergy production in the Ecuadorian Andes. The bagasse was quantified by means of weighing, and then evaluated via calorimetry and thermogravimetric analysis as well as proximal and elemental analysis. The results showed that these materials met the criteria for direct combustion, exhibiting both a low nitrogen content of 0.30 ± 0.12% and ash values of 6.20 ± 1.20%. Among the analyzed varieties, CB 40-69 stood out as the most suitable for power generation within the cogeneration system; this was attributed to its superior dry calorific value of 17.37 ± 1.45 MJ kg⁻¹, greater presence of volatile materials, and negligible ash content. Variety CB 40-69 (157.91 t ha⁻¹) reported the highest biomass and bagasse production (56.32 t ha⁻¹). Analysis of the SCB structure concluded that the three varieties did not differ significantly in their contents of lignin, hemicellulose, and cellulose, which is essential to implementing an industrial process for bioethanol production.

Building-Integrated and Building-Attached Photovoltaic (BIPV/BAPV) systems are increasingly being adopted in metropolitan areas worldwide, driven by international commitments to reduce greenhouse gas emissions and the declining cost of PV technology. A promising application involves the vertical integration of PV panels into building facades, which offers architectural and energy benefits, particularly in urban environments with limited roof space. This study experimentally evaluates the energy behavior of 12 vertically mounted 5 W PV panels (model SP005P) installed on university buildings in Ibarra, Ecuador, across four azimuth orientations (−135° SE, −45° NE, 45° NW, 135° SW). A continuous 8-month monitoring campaign was conducted using a custom-designed Arduino-based data logger, validated with multimeter measurements (error < 5%). The dataset was used to develop MATLAB version 2025b forecasting models based on Sum-of-Sine functions, achieving R² values between 0.83 and 0.98 and RMSE values between 0.024 and 0.082 W. The 45° (NW) orientation achieved the highest annual energy yield of 48% STC, reaching up to ≈440 kWh/kWp in the best-performing facade, while 135° (SW) also exhibited favorable performance compared with the northeast and southeast orientations. These findings provide significant evidence for facade-integrated PV design in equatorial latitudes, offering performance benchmarks and validated forecasting tools that can support architectural planning, BIPV feasibility analysis, and urban solar-energy strategies in regions with similar conditions.

Understanding microclimatic variability at the land–atmosphere interface is essential for improving knowledge of atmospheric moisture dynamics in heterogeneous mountainous ecosystems. This study analyzes atmospheric relative humidity and soil moisture variability in an experimental Juglans neotropica Diels plantation located in the Ecuadorian Andes under real field conditions. An autonomous photovoltaic-powered monitoring system equipped with low-cost environmental sensors was deployed continuously for 60 days, generating more than 86,000 environmental measurements of atmospheric relative humidity above and below the canopy, together with soil moisture observations. The results revealed persistent vertical humidity stratification associated with canopy structure, characterized by systematically higher atmospheric humidity beneath the canopy compared to the upper atmospheric layer (ΔRH ≈ −36%). Strong intersensor coherence was observed between canopy levels (r = 0.8535), indicating stable temporal consistency in atmospheric variability patterns throughout the monitoring period. Soil moisture exhibited comparatively more stable temporal dynamics than atmospheric humidity, suggesting partial microclimatic decoupling between atmospheric and edaphic layers. The observed humidity gradients remained temporally stable during both daytime and nighttime conditions, supporting the interpretation of canopy-mediated atmospheric buffering processes within the plantation environment. From an ecological perspective, the results indicate that vegetation structure contributes to localized moisture retention, attenuation of short-term atmospheric fluctuations, and regulation of near-surface microclimatic conditions under heterogeneous Andean environmental conditions. Rather than focusing on instrumentation performance, the study provides empirical evidence of persistent canopy-related atmospheric regulation and moisture stratification in a native Andean forest species under continuous field monitoring conditions. These findings contribute to the understanding of land–atmosphere interactions, ecohydrological dynamics, and vegetation-mediated microclimatic regulation in mountainous ecosystems.

So far, about 770.1 million confirmed cases of COVID-19 have been counted by August 2023, and around 7 million deaths have been reported from these cases to the World Health Organization. In Ecuador, the first confirmed COVID-19 case was registered on 19 February 2020, and the country’s mortality rate reached 0.43% with 12986 deaths, suggesting the need to establish a mechanism to show the virus spread in advance. This study aims to build a dynamic model adapted to health and socio-environmental variables as a multivariate model to understand the virus expansion among the population. The model is based on Susceptible-Infected-Recovered (SIR), which is a standard model in which the population is divided into six groups with parameters such as susceptible S(t), transit stage E(t), infected I(t), recovered R(t), deceased Me(t), infected asymptomatic Ia(t), infected symptomatic Is(t) and deceased by other causes M(t) to be considered and adapted. The model was validated by using consistent data from Chile and run by inconsistent data from Ecuador. The forecast error was analyzed based on the mean absolute error between real data and model forecast, showing errors within a range from 6.33% to 8.41% for Chile, with confidence a interval of 6.17%, then 3.87% to 4.70% range for Ecuador with a confidence interval of 2.59% until 23rd December 2020 of the database. The model forecasts exponential variations in biosecurity measures, exposed population, and vaccination.