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    Delphi/AHP-based method for biomass sustainable assessment in the sugar industry
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024-09-01)
    Multi-criteria methods are highly attractive tools to address the inherent complexity of evaluating problems in various scientific areas. The combination of methods such as Delphi/AHP is emerging as a robust alternative to evaluate the sustainability of renewable energy sources. In this theoretical-descriptive research, the use of the Delphi method is proposed to select criteria and sub-criteria to obtain a high level of reliability, while the AHP method is used to establish an order of preference among the alternatives analyzed. This process requires the support of a committee of experts, whose role is to identify the various biomass alternatives that can be used in the sugar industry, considering aspects related to sustainability. The selected experts have identified energy, exergy, and emergetic indicators, in which economic, environmental, and social aspects are integrated. The multi-criteria analysis shows that the V1 variant was the most satisfactory in terms of biomass sustainability, representing 45% and 53% of the overall priorities in the evaluated case studies. In addition, the sensitivity analysis under an equal-weighted scenario for both study cases evidenced that variant V1 acquired the highest score (38.17%) among all alternatives. Variant V4 achieved the second highest score (31.79%), while alternative V2 achieved only 29.04%, respectively. The integration of Delphi/AHP methods emerges as a novel tool to assess sustainability in different industries of the energy sector.
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    Manure Recoverability Governs the Available Biogas Resource and Emissions: Peruvian Livestock as a Case Study
    (Multidisciplinary Digital Publishing Institute (MDPI), 2026-08-28)
    National estimates of the bioenergy potential of livestock manure still rest on static inventories that apply conversion yields to the gross mass of manure, ignoring the fraction that is actually recoverable under each production system and the substrate-specific nature of anaerobic co-digestion. This study develops a category-level predictive model of the technical biogas potential of livestock manure in Peru, projected to 2030, resolving seven livestock categories: dairy and non-dairy cattle, broilers and layers, swine, guinea pigs (Cavia porcellus) and goats. Recoverability is formulated as a time-dependent factor tracking the progressive confinement of production systems; the technical potential is bounded between a mono-digestion floor and a co-digestion ceiling constrained by a co-location criterion that admits synergy only when the co-substrate originates within the same production system; and a greenhouse-gas layer quantifies avoided emissions from methane conversion factors. All coefficients are reported as intervals and propagated jointly by Monte Carlo simulation. Two yield hypotheses are carried throughout: experimental biochemical methane potential and the IPCC-consistent digester ceiling. The national net technical potential is 1975 GWhpyr−1 under mono-digestion (731 GWhe; 95% credible interval 1628–2404 GWhp, Monte Carlo N=100,000) and 2093 GWhpyr−1 under co-digestion. The gross approach exceeds the recoverable resource by a factor of 3.94, equivalently a contraction of 74.6% (95% CI 68.9–79.1%), and a symmetric Shapley decomposition attributes 76.1% of that contraction to recoverability rather than to conversion yield—a share that is stable across both yield hypotheses. The greenhouse-gas layer yields a result that reverses the expected policy ordering: broilers rank first by recoverable energy but last by avoided methane, whereas swine rank first by mitigation because liquid slurry storage is the only baseline system emitting enough methane for anaerobic digestion to displace. Below a digester leakage of 4.6%, methane abatement is negative at the national scale.
      1
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    Environmental and Energy Sustainability in Wastewater Transportation: Integration of ISO 50001 and ISO 14040/14044 in the Replacement of Diesel with Compressed Natural Gas, Lima, Peru
    (Multidisciplinary Digital Publishing Institute (MDPI), 2026-08-01)
    Evidence combining energy management and life cycle assessment of diesel-to-CNG substitution under real fleet operation remains limited. The energy and environmental assessments were jointly applied over a common functional unit—the transport of 30 m3 of non-hazardous wastewater per documented service—with an annual reference flow of 82,422 m3·km derived from 38 services (1140 m3; 5905.2 km) in Lima, Peru. A single primary dataset fed both the energy baseline (characteristic monthly consumption of 22,828 ± 1435 MJ month−1; service-level intensities of (Formula presented.) vs. (Formula presented.) MJ (m3·km)−1, (Formula presented.), (Formula presented.)) and the life cycle inventory, assessed in SimaPro v9.6.0.1 (ReCiPe 2016 Midpoint (H)) under an extended tank-to-wheel boundary with Pedigree–Monte Carlo uncertainty propagation. The transition—fuel substitution combined with Euro V-to-Euro VI platform renewal—reduced energy intensity by 45.3% and direct-combustion GWP100 by 61.1%; this integrated effect is not attributable to the fuel change alone. Methane slip contributed 1.3% of the CNG GWP100, and only an upstream leakage of 15.5% of the delivered gas would cancel the climate benefit. Tire replacement remained the dominant hotspot (64.5%/51.7%); immediate 30-vehicle fleet conversion would avoid 2530 t CO2-eq over ten years.
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    Circular Recovery of Organic Waste from Mining Canteens for the Production of Biofertilizers: Life Cycle Assessment and Circularity Indicators in High-Andean Regions
    (Multidisciplinary Digital Publishing Institute (MDPI), 2026-08-01)
    The management of organic waste in high-altitude mining poses a distinctive circularity challenge: waste is generated at sites decoupled from agricultural systems, while the same operations are legally required to revegetate the land they disturb. This study provides, to the best of our knowledge, the first primary-data environmental characterization of a real system that valorizes dining-facility organic waste from a high-altitude mining unit in northern Peru into a solid biofertilizer and a liquid biol, both applied in situ for land reclamation. Unlike methanogenic digesters, the system operates under a lactic (acidogenic) fermentation regime inoculated with effective microorganisms and does not recover biogas. A cradle-to-gate life cycle assessment (ISO 14040/14044) with Monte Carlo uncertainty propagation was combined with a well-established family of five circular economy indicators, adapted to the non-energy-recovery case by redefining the Energy Self-Sufficiency Ratio (ESSR) and the Decarbonization Circularity Indicator (DCI). The principal contribution is methodological: the framework is extended to a circularity archetype that previous, biogas-centered formulations could not represent, showing that a system can close its material and nutrient loops robustly (WVI = 0.97) while the energy loop is absent by design (ESSR = 0). The climate result is conditional and is a first-order greenhouse-gas (GHG) screening balance, not a physical carbon-sequestration claim: under the upper-bound assumption of full fertilizer substitution, the avoided fertilizer credit outweighs non-methane process emissions only below a narrow fugitive-methane threshold (≈0.32 kg CH4 per ton), a margin that narrows further once agronomic equivalence is discounted. The measured product acidity suggests that this condition is plausible, but, because methane was not measured directly, the low-emission interpretation is presented as a hypothesis requiring confirmation rather than as a demonstrated result. The environmental burden is driven by material and electricity inputs—chiefly the polypropylene containers and grid electricity—rather than by the biological process, which broadens the set of improvement priorities beyond methane management to include capital-good reuse and electricity decarbonization, without implying that methane can be neglected.
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    Transition to a Circular Bioeconomy in the Sugar Agro-Industry: Predictive Modeling to Estimate the Energy Potential of By-Products
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-06-01)
    The linear economy model in the sugar agroindustry has generated multiple impacts due to the underutilization of by-products and reliance on fossil fuels. Through predictive modeling and anaerobic digestion, the circular bioeconomy of sugarcane biomass enables the generation of biogas and electricity in an environmentally sustainable manner. This theoretical-applied research proposes a predictive model to estimate the energy potential of by-products such as bagasse, vinasse, molasses, and filter cake, based on historical production data and validated technical coefficients. The model uses milled sugarcane as a baseline and projects its energy conversion under three scenarios through 2030. In its most favorable configuration, the model estimates energy production of up to 15.5 billion Nm3 of biogas in Cuba and 9.9 billion in Peru. The model's architecture includes four residual biomass flows and bioenergy conversion factors applicable to electricity generation. It is validated using national statistical series from 2000 to 2018 and presents relative errors below 5%. Cuba, with a peak of over 13,000 GWh of electricity from bagasse, and Peru, with a stable output between 6500 and 7500 GWh, reflect the highest and lowest projected energy utilization, respectively. Bagasse accounts for over 60% of the total estimated energy contribution. This modeling tool is fundamental for advancing a transition toward a circular economy, as it helps mitigate environmental impacts, improve agroindustrial waste management, and guide sustainable policies in sugarcane-based contexts.
      4
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    Technical, Economic, and Environmental Assessment of Hybrid Solar Photovoltaic–Thermal Systems in Hospitals: A Comprehensive Climate Change Mitigation Strategy
    (Multidisciplinary Digital Publishing Institute (MDPI), 2026-02-01)
    The high dependence on fossil fuels for energy supply in hospitals compromises their operational sustainability, increases costs, and contributes significantly to polluting emissions. This study evaluates the technical, economic, and environmental feasibility of integrating photovoltaic and solar thermal systems in a hospital located in a tropical Caribbean environment, characterized by continuous operation and high energy demand. The methodology combines advanced simulation using PVsyst for the photovoltaic subsystem and the f-chart method for the solar thermal system, using real data on electricity and domestic hot water demand. The proposed system achieves an installed photovoltaic power of close to 390 kWp, with an annual production of around 0.7 GWh and an average performance ratio of 0.80, demonstrating high technical performance. The solar thermal subsystem covers approximately two-thirds of the annual domestic hot water demand, supported by thermal storage suitable for hospital operation. From an economic standpoint, the total estimated investment is recovered in less than 10 years, with a positive net present value, confirming the system's profitability over its useful life. In environmental terms, hybrid integration avoids more than 400 t of CO2 per year, contributing significantly to the decarbonization of the health sector and the strengthening of energy security. The results obtained demonstrate that photovoltaic–thermal integration in tropical hospitals is technically and economically viable and constitutes a replicable solution for regions with high solar radiation and energy vulnerability. This research provides a comprehensive and reproducible methodological framework that can support sustainable energy planning and the design of public policies aimed at low-emission healthcare infrastructure.
    Scopus© Citations 5  1
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    Methodological Framework for the Integrated Technical, Economic, and Environmental Evaluation of Solar Photovoltaic Systems in Agroindustrial Environments
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-08-01)
    The transition to sustainable energy systems in the agroindustrial sector requires rigorous methodologies that enable a comprehensive and quantitative assessment of the technical and economic viability and environmental impact of photovoltaic integration. This study develops and validates a hybrid multi-criteria methodology structured in three phases: (i) analytical modeling of the load profile and preliminary sizing, (ii) advanced energy simulation using PVsyst for operational optimization and validation against empirical data, and (iii) environmental assessment using life cycle analysis (LCA) under ISO 14040/44 standards. The methodology is applied to a Cuban agroindustrial plant with an annual electricity demand of 290,870 kWh, resulting in the design of a 200 kWp photovoltaic system capable of supplying 291,513 kWh/year, thereby achieving total coverage of the electricity demand. The economic analysis yields an LCOE of 0.064 USD/kWh and an NPV of USD 139,408, while the environmental component allows for a mitigation of 113 t CO2-eq/year. The robustness of the model is validated by comparison with historical records, yielding an MBE of −0.65%, an RMSE of 2.87%, an MAPE of 2.62%, and an R2 of 0.98. This comprehensive approach demonstrates its superiority over previous methodologies by effectively integrating the three pillars of sustainability in an agroindustrial context, thus offering a scientifically sound, replicable, and adaptable tool for decision-making in advanced energy projects. The results position this methodology as a benchmark for future research and applications in emerging production scales.
      2
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    Mathematical Model to Improve Energy Efficiency in Hammer Mills and Its Use in the Feed Industry: Analysis and Validation in a Case Study in Cuba
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025-05-01)
    The feed industry is characterized by high energy consumption during the grinding stage, where hammer mills can account for up to 50% of total electricity usage; furthermore, efficiency analyses are based only on the classical equations reported in the literature. In this context, the present theoretical-applied research aimed to improve the efficiency of a plant operating below its nominal capacity. To achieve this, a comprehensive mathematical model was developed, integrating power and grain disintegration equations while overcoming the limitations of classical comminution theories. The model incorporates key factors such as feed rate, moisture content, absorbed power and hammer wear. Additionally, specific correction factors for temperature (Kt) and mechanical degradation (Kd) were introduced to accurately represent real operating conditions. The study was based on extensive measurements of electrical current, power factor, energy consumption, particle size distribution and thermal variations under different load conditions. The statistical analysis, which included ANOVA, ANCOVA and multiple regressions, demonstrated a predictive accuracy of 98% (R2) and a pseudo-R2 of 89%. This high correlation allowed for an 18% reduction in energy consumption equivalent to 4 kWh/t and up to a 30% improvement in particle size uniformity, surpassing typical factory performance. The findings highlight that integrating operational, thermodynamic and wear-related factors enhances the robustness of the model, promoting more reliable energy-management practices in hammer mills. Consequently, the results confirm that the developed model serves as a scientifically robust, efficient and applicable tool for improving energy efficiency and reducing environmental impacts in the agri-food industry.
      1
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    Integrated Assessment of Photovoltaic Systems in Multi-Family Buildings as a Strategy for Climate Change Mitigation and Urban Energy Sustainability
    (Multidisciplinary Digital Publishing Institute (MDPI), 2026-05-01)
    Decarbonizing the building sector requires integrating on-site renewable generation with systematic energy management. Among the most widely adopted alternatives are photovoltaic (PV) systems in buildings; however, they are often implemented as a standalone technological intervention (size–install–estimate savings), without being formally incorporated into an Energy Management System (EnMS) aimed at continuous improvement. In this context, this research addresses this gap through an integrated methodological framework aligned with ISO 50001, in which PV is explicitly included in energy performance management through energy review, the definition of an Energy Baseline (EnB), and the monitoring of Energy Performance Indicators (EnPIs) within the PDCA cycle. The approach articulates the analytical sizing of the PV system based on electricity demand and solar resources; its validation through simulation to ensure operational consistency and a technical, economic, and environmental assessment that translates PV generation into a verifiable reduction in energy imported from the grid and, consequently, into traceable improvements in EnPI under an audit-compatible scheme. The methodology is demonstrated in a multi-family building in Chorrillos, Lima (Peru), where a 14.5 kWp rooftop PV system (25 modules of 580 Wp) is designed to maximize self-consumption during daylight hours. The results show technical performance consistent with the demand profile, economic viability under the conditions of the case, and environmental benefits from replacing grid electricity, along with offsets associated mainly with the manufacture of PV components. The residual gap between the Post-PV EnPIs and the ISO 50001 target confirms that PV integration is a necessary but not sufficient first-cycle action within a comprehensive building decarbonization strategy, with demand-side management and envelope improvements identified as subsequent PDCA cycle priorities. In summary, the central contribution is not the PV sizing itself, but its operational and traceable integration within ISO 50001, making PV a quantifiable, verifiable, and scalable energy improvement action for residential buildings in emerging economies.
      1
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    Biopolygeneration Diagnostic Index (BDI): An Exergy-Based Framework for Quantifying Maximum Utilization and Thermodynamic Performance in Biomass-Based Bioenergy Plants
    (Multidisciplinary Digital Publishing Institute (MDPI), 2026-06-01)
    The energy recovery of biomass is frequently implemented through single-output systems or passive management schemes, resulting in underutilization of its thermodynamic potential and losses in economic value, climate benefits, and useful co-products. This study formalizes the concept of biopolygeneration as a diagnostic principle aimed at maximizing biomass utilization through the simultaneous production of multiple energy services and the valorization of secondary streams. A dimensionless metric, the Biopolygeneration Diagnostic Index (BDI), is proposed to quantify this concept. The index is bounded within [0,1] and integrates five sub-indices: energy efficiency (IE), thermal integration (IT), energy self-sufficiency (IA), exergetic quality of outputs (IQ), and co-product valorization (IV). Weights were determined using the Analytic Hierarchy Process (w1=0.40, w2=0.24, w3=w4=0.14, w5=0.08; CR=0.007). The BDI was evaluated using six cases, including five operating plants and one validated computational model representing five biomass conversion technologies in four countries. Results ranged from 0.453 for an engine without combined heat and power (CHP) to 0.733 for a cascade trigeneration system. Under identical feed conditions, the incorporation of CHP (C1→C2) increased the BDI from 0.453 to 0.715, representing a 57.7% improvement attributable solely to heat recovery. Current limitations include the small validation sample (n=6) and the reconstruction of IA and IV from technological characteristics due to the absence of standardized reporting in the literature. Although these sub-indices account for only 22% of the total weighting (wIA+wIV=0.22), the present results should be considered a proof of concept rather than a fully empirical validation. The BDI provides a thermodynamically consistent framework for comparing bioenergy systems across technologies and supports technical, regulatory, and investment decision making. Broader validation using larger measurement-based datasets is required before claims of universality can be established.