Abstract: In Latin America, sustainable commitments towards decarbonizing hard-to-abate industrial sectors have identified hydrogen (H2) as a key enabler for the energy transition. This study develops a policy analytical framework to enhance the green H2 economy, using Argentina as the central case study. Key insights from the study include identifying often-overlooked social challenges within the H2 economy and proposing the integration of social indicators into policy design, with a particular focus on the territorial dynamics of Patagonia, labor conditions, indigenous participation, governance, and community impacts. Drawing from Social Life Cycle Assessment (S-LCA) guideline standards and H2 approach, this study highlights key social hotspots that existing S-LCA tools overlook due to their lack of specific focus on regional territories and their communities. The analysis combines six social impact categories, namely, human rights, working conditions, health and safety, cultural heritage, governance, and socio-economic repercussions as recommended by the United Nations Environmental Program (UNEP), analyzed at a three-level dimension, and complemented by the H2 justice approach for Argentina's potential green H2 production sector. These policy recommendations aim to foster a more resilient and sustainable development of the green H2 industry.

Abstract: The increasing prevalence of rooftop photovoltaics on European buildings has sparked interest in using façades and balconies as alternative surfaces for generating solar energy. This study examines the technical and economic performance of building-integrated photovoltaic (BIPV) installations on façades and balconies under real operating conditions. Four case studies from Poland are analysed using a combination of measured energy production data and simulations performed with the PVGIS tool. The analysis focuses on annual and seasonal energy yield, self-consumption potential, system costs, simple payback time and the role of module-level power electronics (MLPE) in mitigating the effects of shading and non-optimal orientations. The results demonstrate that, while façade-mounted PV systems generally have lower annual yields than optimally tilted rooftop installations, balcony and façade BAPV systems with MLPE can achieve high self-consumption rates, short payback periods (3–10 years) and favourable winter performance. These findings demonstrate that BIPV and BAPV systems on façades should be assessed using distinct technical and economic criteria, and highlight their potential to extend prosumer participation to apartment dwellers, thereby supporting a more inclusive urban energy transition.

Abstract: Bioeconomy policy requires timely, economy-wide evidence; however, two persistent measurement constraints remain: official input–output (IO) tables are published with substantial time lags, novel start-up and novel prospective or hybrid bio-based activities are rarely identified as separate sectors in national accounts. This paper develops an applied methodology that addresses both limitations by combining IO nowcasting with a reduced-dimensional sector-embedding procedure. Using Ireland’s national IO system and an existing bioeconomy IO framework as the accounting backbone, we update the 2015 table to 2022 through calibration to macroeconomic control totals, providing a timely structural baseline. We then introduce a transparent method for constructing new bioeconomy sectors based on dominant input shares, import intensity, and output allocation, while preserving national accounting identities. The approach is demonstrated for aquaculture systems, anaerobic digestion scenarios, and plant-based protein value chains. Demand-driven Leontief multipliers reveal substantial heterogeneity in domestic propagation effects across activities and development stages. The framework offers a resource-efficient and replicable tool for evaluating bioeconomy strategies under real-world data constraints.

Abstract: The mutually reinforcing synergy between the development of the new energy industry and comprehensive land remediation is crucial for integrating ecologically fragile areas into the national "dual carbon" goals and supporting regional high-quality development. Based on an analysis of the challenges and opportunities facing the new energy industry in ecologically fragile areas, as well as the mechanisms for mutual promotion between new energy industry development and land remediation, this paper explores pathways for comprehensive land remediation coordinated with new energy development. Drawing on local practices, it further distills five typical models. The results show that: 1) The development of the new energy industry in ecologically fragile areas faces multiple challenges, including a fragile ecological environment, inadequate infrastructure, a mismatch between resource supply and demand, and land use conflicts. Against the backdrop of the energy transition, breakthroughs in key technologies, and the guidance of territorial spatial planning, the value of wind and solar resources in these areas is becoming increasingly prominent, offering broad prospects for the new energy industry. 2) The development of the new energy industry and comprehensive land remediation in ecologically fragile areas are mutually reinforcing. Factors such as resource endowment, ecological (environmental) constraints, new quality productive forces, and investment and financing mechanisms interact and integrate, leading to differentiated pathways for synergy. 3) Based on the focus of new energy industry development and the primary objectives of remediation, five remediation models are identified: ecological restoration-led land reclamation model, resource development-led land consolidation model, industry collaboration-led land consolidation model, technology innovation-led land consolidation model and integrated development model. Each model has distinct priorities and applicable scenarios. This study will provide a reference for new energy development and sustainable development in ecologically fragile areas, including desertified and Gobi desert areas, coal mining subsidence areas, and areas rich in wind, solar, and hydro energy resources.

Abstract: Municipal waste management is one of the most pressing challenges today, with the UN report (2024) estimating that global waste volumes will increase to 3.8 billion tons by 2050. This scenario highlights the need to implement the circular economy and ef-fective waste reduction tools. At the European level, Directive 2008/98/EC establishes the waste hierarchy, where prevention is central, and the Pay-as-you-throw (PAYT) system, based on the "polluter pays" principle, proves to be a fiscal mechanism capable of stimulating recycling and reducing the volume of mixed waste. The paper proposes the development of an integrated framework for smart waste management, including emerging technologies such as the Internet of Things, Artificial Intelligence, and Web 3.0. The first part of the research establishes the hypotheses and objectives: cost reduc-tion, increased efficiency, and process traceability. The second part analyses the use-fulness of digital technologies and the role of smart containers in collection, as well as the structure of processing and management costs, highlighting the framework's direct contribution to achieving SDG 11 and SDG 13. The third part describes a closed system with digital key-based access that monitors the number of disposals and assigns re-sponsibility for the waste deposited. By combining PAYT with advanced technological solutions, the research demonstrates the practical applicability and legal basis of an innovative model designed to support sustainability and strengthen European circular economy policies.

Abstract: As Germany advances toward its 2030 energy transition targets, large‑scale battery systems are widely promoted as a key instrument to manage the volatility of wind and solar power. This paper develops a data‑driven simulation framework to quantify how much grid‑scale batteries can realistically contribute to Germany’s power system in 2024 and in a 2030 expansion scenario, in terms of backup energy reduction, system costs, and carbon footprint. The analysis uses 15‑minute data for generation and load from 2022–2025 and constructs future scenarios by upscaling photovoltaics, onshore wind, offshore wind, and demand in line with the Study "Climate‑neutral Germany 2045". Volatility is decomposed into a slowly varying component, covered by backup plants, and a normalized residual load that feeds the batteries; for each battery capacity, an optimal moving‑average window is determined to maximize annual battery output and minimize backup energy. Model validation against 2024 pumped‑storage operation shows that the framework reproduces observed annual storage output well. Across both 2024 and 2030, battery benefits scale approximately with the logarithm of installed capacity, while costs and battery‑related emissions increase linearly. Under optimistic assumptions, about 300 GWh of batteries can supply only 4–6% of annual demand and cannot replace firm backup capacity, implying that batteries are valuable for short‑term balancing but have limited potential for seasonal adequacy.

Abstract: The minimisation of substances of concern in packaging is a key objective of the European Union’s Packaging and Packaging Waste Regulation (PPWR). Per- and polyfluoroalkyl substances (PFAS) present particular challenges due to their persistence, chemical diver-sity, and widespread use in food contact materials. Article 5 of the PPWR requires pack-aging to be designed and manufactured to minimise such substances throughout the life cycle. This study develops a structured, material-based PFAS risk matrix to support com-pliance screening for food packaging under Article 5. The approach combines scientific evidence on PFAS occurrence, functional applications, and analytical detection with ma-terial classification systems used in recyclability assessments. Packaging materials are categorised by their likelihood of PFAS relevance, enabling proportionate prioritisation of minimisation and documentation efforts. Application of the matrix shows that PFAS relevance is strongly material dependent. Fi-bre-based materials with grease- or water-resistant treatments exhibit higher relevance than glass, untreated paper, or polyethylene terephthalate (PET). The framework also clar-ifies the role of total fluorine (TF) and extractable organic fluorine (EOF) as supportive, material-specific indicators rather than standalone compliance metrics. By integrating PFAS considerations into design, sourcing, and portfolio management, the framework promotes proactive chemical risk governance aligned with circular economy objectives.

Abstract: Heavy metal contamination of soil and water continues to pose persistent environmental and public health challenges, particularly in regions affected by rapid industrialization, mining, and intensive agriculture. Conventional remediation strategies—such as chemical precipitation, adsorption, soil washing, and bioremediation—have contributed significantly to pollution control; however, their implementation often relies on empirical optimization, prolonged experimentation, and site-specific trial-and-error approaches. These limitations restrict scalability, increase operational costs, and slow the development of sustainable remediation solutions. In recent years, the integration of machine learning (ML) and data science has emerged as a transformative direction in environmental engineering, offering predictive, data-driven alternatives to traditional remediation planning. This review critically examines the application of supervised, unsupervised, and deep learning models in metal remediation systems. Emphasis is placed on regression algorithms, artificial neural networks, support vector machines, ensemble techniques, clustering methods, and advanced deep neural architectures that enable prediction of metal removal efficiency, optimization of operational parameters, and modeling of adsorption and kinetic behaviors. The review further explores how data science workflows—including data acquisition, preprocessing, feature engineering, and multi-source data integration—support robust environmental decision-making. Particular attention is given to machine learning applications in bioremediation and phytoremediation, where predictive modeling enhances understanding of microbial performance and plant–metal interactions while reducing experimental time and cost. Despite promising advancements, significant challenges remain, including data scarcity, model interpretability, overfitting risks, lack of standardized environmental datasets, and computational constraints. Addressing these issues will require integration with real-time monitoring systems, Internet of Things (IoT) technologies, explainable artificial intelligence (XAI), and global environmental databases. The review concludes that transitioning from empirical remediation frameworks to predictive and adaptive systems represents a crucial step toward sustainable, scalable, and intelligent heavy metal management strategies. By synthesizing current developments and identifying research gaps, this article provides a comprehensive foundation for future interdisciplinary innovation at the intersection of environmental science, machine learning, and sustainable remediation engineering.

Abstract: The accelerating climate crisis, driven by annual CO₂ emissions exceeding 37 billion metric tons, necessitates the rapid advancement of Carbon Capture and Storage (CCS) and Direct Air Capture (DAC) technologies. Metal–Organic Frameworks (MOFs) have emerged as highly promising sorbents due to their tunable pore architectures and exceptional surface areas; however, exploration of their vast chemical design space remains computationally prohibitive. This review systematically examines the expanding role of Machine Learning (ML) in accelerating CO₂ capture research within MOFs. Using a structured evaluation protocol, we assess state-of-the-art models across four key dimensions: predictive performance, descriptor physical relevance, mechanistic interpretability, and process-level applicability. Recent advances in Machine Learning Interatomic Potentials (MLPs) demonstrate that framework flexibility significantly influences adsorption thermodynamics and diffusivity, challenging conventional rigid-lattice assumptions. Generative approaches—including Deep Reinforcement Learning and transformer-based architectures—enable inverse design of high affinity frameworks, while physics-informed descriptor engineering improves predictive accuracy across pressure regimes (R² > 0.90). Importantly, the field is transitioning from isolated property prediction toward multiscale, process-integrated optimization, where ML models couple material features with industrial performance metrics such as CO₂ purity and recovery in pressure swing adsorption systems. Collectively, these developments indicate that future progress will depend on physics informed, interpretable architectures capable of bridging molecular-scale discovery with experimentally robust and water-stable materials suitable for industrial deployment.

Abstract: The valorization of underexploited biomass in arid regions represents an important pathway for decentralized energy production and sustainable soil management. Although biomass pyrolysis has been widely investigated, most studies are conducted under controlled laboratory conditions, with limited assessment of low-technology systems operating under real domestic use. This study evaluates the thermochemical behavior and energy performance of locally available biomasses using a multifunctional household oven. Millet stalks, cashew nut shells, cashew nut shell cake, and rumen contents were subjected to slow pyrolysis. Temperature evolution in the pyrolysis and combustion chambers was continuously monitored using type ‘K’ thermocouples, and mass and energy balances were applied to assess product distribution and process efficiency. Pyrolysis temperatures ranged between approximately 270 and 350 °C, while combustion temperatures reached up to 800 °C depending on the biomass. Product yields varied significantly according to feedstock characteristics. Cashew nut shells showed the highest energy efficiency (about 71%), followed closely by millet stalks, whereas rumen contents presented lower performance. Thermal profiles consistently revealed four successive phases governed by biomass composition and reactor–biomass interaction. These findings confirm the technical feasibility of household-scale pyrolysis for combined energy recovery and biochar production under realistic operating conditions.

Abstract: This study presents a comparative evaluation of Environmental Product Declarations (EPDs) within the traditional ceramic industry, emphasizing the intersection of energy use, environmental performance, and policy-relevant data structures. Four product categories—ceramic tiles, sanitary ware, clay bricks, and clay roof tiles—were analyzed using datasets from One Click LCA and the International EPD System. Environmental indicators assessed include fossil-based and total Global Warming Potential (GWP), freshwater consumption, and energy demand, standardized per 1 kg of product. The analysis reveals significant discrepancies in data provenance and methodological consistency across platforms, with One Click LCA offering harmonized datasets for tiles and sanitary ware, while the International EPD System permits variable sources, particularly evident in brick EPDs. These inconsistencies hinder comparability and dilute the strategic value of EPDs in guiding low-carbon market transitions. The study highlights that energy-intensive production stages in tiles and sanitary ware contribute to elevated environmental burdens, underscoring the need for harmonized software tools, transparent reporting formats, and standardized background databases. Confidentiality regarding energy sources and firing temperatures remains a barrier to optimization, while the absence of fossil fuel-specific GWP guidance and high EPD development costs limit broader market uptake. By expanding comparative assessments across production sites and product types, the research supports the development of robust benchmarks and tailored Product Category Rules (PCRs), reinforcing the role of EPDs as actionable instruments in energy policy and sustainable market design.

Abstract: Early warning systems support hazard detection, forecasting, and communication, yet U.S. Gulf Coast warning practice often treats hazards, coastal ecosystem change, and vulnerability constraints as separate domains. This paper maps operational early warning systems for climate hazards across Louisiana, Texas, Mississippi, Alabama, and Florida, and assesses whether ecosystem protective functions and social vulnerability are integrated into warning thresholds, dissemination design, and response planning. Web of Science Core Collection and Scopus were searched (timespan limit 2020 to 2026), alongside targeted searches of NOAA/NWS/NHC, FEMA IPAWS, CDC/ATSDR Social Vulnerability Index, IOOS (GCOOS), USGS, and state coastal agencies including CPRA. Searches ran from 15 September 2025 to 18 January 2026. Three independent reviewers screened records and resolved disagreements by consensus. Data were charted using a standardized matrix covering hazard focus, geography, lead organizations, products, dissemination channels, ecosystem indicators, equity features, and governance arrangements. 861 records were identified; 440 duplicates were removed and 421 abstracts were screened. Full text was unavailable for 300 records, leaving 121 reports assessed for eligibility. Ninety were excluded for lacking U.S. Gulf Coast focus and six Spanish language reports were excluded, resulting in 25 sources for charting and synthesis. Socio-ecological integration was inconsistently operationalized, with uneven documentation of how ecosystem condition and vulnerability constraints informed thresholds, accessible messaging, and preparedness supports. End-to-end warning effectiveness can be strengthened through interoperable interfaces between monitoring programs, warning operations, and emergency management, paired with equity and accessibility workflows that translate forecasts into feasible protective actions.

Abstract: Addressing climate change and food security, this article evaluates ground silicate rocks (remineralizers) as tools for atmospheric CO2 capture and food and nutrition security. The experiments were conducted under controlled conditions using leaching columns (to quantify the leached carbon) and pots (to evaluate the growth and nutrition of three agricultural crops). Five rock types (basalt, kamafugite, chlorite-muscovite calc-schist, hydrothermalized calc-silicate, and biotite-actinolite schist) were applied to a Red Oxisol (S) at 20 t ha⁻¹, with and without organic matter (OM) at 40 t ha⁻¹. The study involved 84 experimental units, including S, S+R, S+OM, S+R+OM, and S, S+OM and NPK controls. Results showed that rock-OM mixtures significantly improved soil pH and electrical conductivity, enhancing the growth and nutritional content of three agricultural crops (beans, arugula, and carrots) compared to controls. Nutrient dynamics varied across leached liquids and in the soils of the columns and pots. While OM increased leached carbon, the direct influence of silicate rocks on CO2 capture was more pronounced in S+R treatments. The findings underscore the vital role of local, innovative strategies in providing sustainable solutions to global challenges.

Abstract: The livestock sector underpins food security, employment, and rural livelihoods across the Southern African Development Community (SADC), contributing up to 50 % of agricultural GDP and supporting more than 60 % of rural households. Yet, climate change poses escalating threats through heat stress, declining pasture productivity, water scarcity, and vector-borne diseases that compromise productivity and economic resilience. This review identifies and locates effective climate change mitigation strategies along the livestock value chain, spanning production, processing, transport, and consumption, to promote sustainable, low-emission, and inclusive growth in the SADC region. A broad review of 46 peer-reviewed and institutional sources (2000 – 2024) was undertaken, focusing on livestock-related mitigation within SADC and comparable agro-ecological systems. Strategies were thematically categorized by value-chain stage and assessed for their emission-reduction and livelihood-enhancement potential. Located strategies include genetic improvement for low-methane and heat-tolerant breeds, adaptive rangeland and feed management, renewable-energy adoption in processing, climate-resilient transport infrastructure, and consumer awareness of low-emission products. Evidence suggests potential GHG-emission reductions of 18–30 %, coupled with productivity gains and improved smallholder incomes. Coordinated implementation through the SADC Regional Agricultural Investment Plan (2021–2030) and national policies can transform the livestock sector into a climate-resilient driver of inclusive growth. Further research should quantify the socio-economic feasibility and scaling potential of these strategies across production systems. Successful integration of climate change mitigation imperatives must be tailored to local biophysical conditions (e.g., rainfall, soil type) and socio-economic contexts (e.g., market access, cultural practices).

Abstract: This study examines the carbonation behavior and CO₂ storage potential of a Ca-rich alkali-activated binder produced entirely from industrial residues, namely ladle furnace slag (LFS), coal ash (CA), and cement kiln dust (CKD). The system was designed as a one-part alkali-activated material (AAM), with CKD acting as an internal activator, and subjected to ambient curing, water curing, and accelerated CO₂ curing at ambient pressure. Phase evolution, microstructural development, and pore-structure characteristics were investigated using X-ray diffraction, FTIR spectroscopy, DSC–TG analysis, scanning electron microscopy, and X-ray micro-computed tomography, together with measurements of density, water absorption, and compressive strength. CO₂ curing fundamentally altered the reaction pathway of the binder, shifting it from hydration-dominated to carbonation-controlled phase evolution, leading to the decomposition of calcium-bearing hydrates and complete carbonation of non-hydraulic γ-belite with the formation of vaterite, aragonite, and calcite. These transformations induced pronounced microstructural densification, reflected in a near-doubling of compressive strength (>48 MPa), increased apparent density, reduced water absorption, and simplified pore-network topology. The results demonstrate that controlled carbonation is an effective post-treatment strategy for waste-derived alkali-activated binders, enabling simultaneous performance enhancement and permanent CO₂ sequestration.

Abstract: The transition to a Circular Economy requires assessment tools that capture not only the environmental and economic performance of products, but also their circular design, functionality, and durability. In this study, two types of injection molds for plastic part production are compared: a conventionally manufactured mold and an additively manufactured metal mold produced by Laser Powder Bed Fusion (L-PBF) technology. The comparison integrates Life Cycle Assessment (LCA), Life Cycle Costing (LCC), and a set of Micro-Circularity Indicators, including the Material Circularity Indicator (MCI), Recycling Desirability Index (RDI), Circular Design Guidelines (CDG), Disassembly Effort Index (DEI), Longevity Indicator (LI), and Circular Economy Indicator Prototype (CEIP). Results show that the AM mold exhibits lower environmental impacts across almost all categories, while its slightly higher initial cost is largely offset by reduced indirect costs over the product lifecycle. Micro-circularity indicators reveal that the AM mold achieves higher material circularity and better circular design performance (MCI, CDG, CEIP), but shows only minor improvements in disassembly and recyclability (DEI, RDI) and lower longevity (LI) compared to the conventional mold, indicating potential limitations for remanufacturing and end-of-life recovery. Overall, this study demon-strates that traditional sustainability metrics (LCA and LCC) are insufficient to fully assess product circularity. The integration of micro-circularity indicators provides a comprehensive framework encompassing circular design, repairability, and durability, highlighting the importance of combining LCA, LCC, and circularity metrics to support truly circular design decisions in additive manufacturing.

Abstract: Globally, 30-50% of food produced, approximately 1.3 billion tons, is wasted prior to consumption [1-4]. Food waste at colleges and universities poses a serious concern, as its impact can be compared to that of mini-cities or large corporations. Identifying an institution’s capacity to reduce and redistribute food waste is critical to decreasing its carbon footprint and maintaining sustainability. Understanding the nature of waste produced at a university's buildings is the first step in establishing effective waste management plans; however, campus cafeterias, being the primary source of food waste, are typically the focus. Limited research emphasis has been placed on assessing food waste generated in campus dormitories. This project tests the hypothesis that food waste generated from dormitories at the main campus of Adelphi University, a private liberal arts institution in New York, is a significant component of waste. To analyze post-consumer trash disposal patterns, garbology methods were utilized [5-7]. Trash collected at dormitories between 2022 and 2024 was sorted and weighed. This mixed methods analysis included student interviews of waste perceptions. Food waste was the primary waste type generated in the halls, followed by food and beverage packaging, including containers, napkins, and utensils. In particular, food waste comprised 32.3% of sampled dormitory waste. Interview results integrated with these quantitative results demonstrated student perceptions of food led to food waste, such as perceived level of cooking, portion sizes, and home context. These results suggest that any efforts to improve campus sustainability through management of food waste–such as composting or anaerobic digestion–must encompass dormitories as well as cafeterias.

Abstract: The rapid impacts of climate change call for urgent actions, such as a comprehensive flood risk assessment, to mitigate the increasing threat of flooding. In many tropical countries, like the Philippines, the most frequent disasters are caused by hydrometeorological events such as floods. This research study focuses on evaluating flood risk through the development of a Flood Risk Index and a Flood Risk Map (FRM), guided by the Hazard-Exposure-Vulnerability interpretation of risk. By incorporating the physical characteristics and frequency of flood hazards, the exposure of human populations and infrastructure, and their inherent vulnerabilities, the study aims to provide a detailed and actionable assessment of flood risk. The areas of interest in this study, Cebu City, Mandaue City, and Lapu-Lapu City, are the highly urbanized cities of Metro Cebu, which houses the critical economic and political infrastructures of the Province of Cebu. Flood risk indicators were identified for each dimension of risk, and the cities provided their performance score for each of the flood risk indicator as well as corresponding priority values. The composite flood risk index for Metro Cebu was generated using Rough-FUCOM method and Hamy Mean aggregator. On the other hand, the development of flood hazard maps was done using the values and weights of the spatial flood risk indicators. The spatial flood risk indicators were mapped into ArcGIS, reclassified into layers, and was then combined using a raster overlay function. The study found out that the highly urbanized cities of Metro Cebu have a moderate flood risk index. This means that Cebu City, Mandaue City, and Lapu-Lapu City have moderate susceptibility to flooding but considering the drastic changes to climate, the concerned LGUs should increase their efforts and efficiently allocate resources especially on constructing flood control structures on areas that are classified as high to very high-risk level, as indicated in the flood hazard maps.

Abstract: Livestock production continues to serve as a critical foundation for livelihoods and economic resilience in the arid and semi-arid lands (ASALs) of northern Kenya, where pastoralism remains the dominant livelihood strategy. In the rangeland ecosystems of Turkana and West Pokot counties, the sustainability of pastoral systems is vital for the socio-economic well-being of local communities. However, these systems face increasing pressure from recurrent droughts and climate variability, which severely threaten forage availability and livestock productivity. These challenges underscore the urgent need for innovative and scalable risk management approaches. This study examines the effectiveness of Index-Based Livestock Insurance (IBLI) as a tool for supporting sustainable rangeland-based pastoral systems in northern Kenya. Specifically, it assesses the empirical impact of IBLI adoption using the Enhanced Vegetation Index (EVI) as a proxy for forage availability. Employing a Difference-in-Differences (DID) approach with fixed effects, we analyze panel data derived from high-resolution MODIS-NASA satellite imagery spanning the years 2003 to 2021. The analysis focuses on determining the causal effects of IBLI adoption on rangeland health and pastoralist resilience in Turkana and West Pokot. Our findings indicate that IBLI adoption is associated with a statistically significant improvement in rangeland conditions, estimated at approximately 4%. Additional DID analyses suggest that this improvement is driven by enhanced forage sustenance, which itself shows a positive effect in the range of 3% to 4%. These results highlight the dual role of IBLI as both a household-level financial risk buffer and an enabler of ecological stability in pastoral systems. Overall, the study provides robust empirical evidence supporting the role of IBLI as an effective climate risk mitigation strategy. It contributes to the growing body of knowledge on sustainable pastoralism in ASALs and offers timely, policy-relevant insights for the expansion of IBLI programs across other drought-prone regions of Sub-Saharan Africa. By fostering both economic and ecological resilience, IBLI represents a promising pathway for strengthening the adaptive capacity of pastoralist communities in the face of escalating climate risks.

Abstract: Background: Modern agriculture is undergoing a paradigm shift toward eco-friendly methodologies that enhance seed material quality while minimizing chemical inputs. This study evaluates the impact of Effective Microorganism (EM) exposure (variants E1 and E2) on the morpho-physiological parameters and phytosanitary health of potato tubers. The primary objective was to determine the efficacy of microbial priming in suppressing the infection rates of Streptomyces scabies (common scab) and Rhizoctonia solani (black scurf) across 14 genetically diverse cultivars. Methods: A three-year field experiment (2019–2021) was conducted using a split-plot design with three replications. The study analyzed the interaction between EM exposure times and the genetic resistance potential of the selected cultivars. Results: Statistical analysis confirmed that pre-planting microbial treatments significantly inhibited pathogen development. EM applications (E1 and E2) reduced the infection rates of both S. scabies and R. solani through an "escape mechanism," whereby treated tubers exhibited accelerated biomass accumulation and reached physiological maturity before peak pathogen pressure. Furthermore, treatments optimized the hormonal status and vigor of the tubers, establishing a robust physiological barrier against soil-borne infections. Conclusions: The application of EM proves to be a highly effective, non-invasive biostimulation method. A significant synergistic effect was observed between EM treatments and the cultivars' innate genetic resistance, particularly in cultivars with higher baseline resistance. The results suggest that microbial priming not only enhances plant growth kinetics but also induces systemic resistance, offering a viable ecological alternative to traditional chemical seed dressings in sustainable potato production.