Agricultural activities in Spain are increasingly vulnerable to water scarcity and soil degradation, exacerbated by farming intensification and climate change. Alongside, the need for renewable energy generation expansion and negative emission technologies risk increasing land use conflicts. Sustainable strategies to reconcile measures to improve agricultural resilience with the renewable energy transition should be explored. This study evaluates the life-cycle environmental performance of integrating biochar production from residues from the local olive oil value chain with agrivoltaic systems in Andalusian olive groves. Five scenarios consider various constraints for regional biomass availability and for agrivoltaic deployment. A spatial analysis identifies the olive groves that are most suitable for agrivoltaic installation and prioritizes high-erosion groves for biochar application. Integrating these technologies delivers climate change mitigation, in some cases achieving net negative emissions and reducing global warming potential by up to 173% relative to conventional farming. Biochar-induced soil carbon storage transforms the agroecosystem from a net source of emissions (2.14 t CO₂-eq ha^-1) to a carbon sink (-7.90 t CO₂-eq ha^-1), while reducing soil erosion and improving water retention. Agrivoltaic systems further decrease irrigation demand and provide up to 53 TWh of renewable energy. Trade-offs occur with terrestrial ecotoxicity and freshwater eutrophication, but using more advanced and efficient panels can mitigate these burdens. Overall, the combined implementation of biochar and agrivoltaics can co-deliver across multiple environmental challenges, from local valorization of residue streams to enhanced agroecosystem resilience, climate change mitigation, adaptation, and renewable energy generation.

The cotton and textile sector are among the most energy- and emission-intensive global production systems, but studies on the carbon footprint of cotton and textile products remain fragmented. Substantial inconsistencies exist in system boundaries, methodological choices, and data sources, which limit study results comparability and policy setting. Here, we systematically clarify lifecycle system boundaries spanning cotton cultivation, textile manufacturing, product use, and end-of-life management, with particular attention to the treatment of foreground and background emissions, transportation processes, and soil carbon dynamics. Across stages, we identify consistent emission hotspots driven by fertilizer-induced N₂O emissions, energy-intensive dyeing and finishing processes, consumer laundering behavior, and recycling pathways. Looking ahead, we highlight key priorities for advancing the field, including the development of harmonized global cotton-textile life cycle assessment databases, the adoption of digital and dynamic carbon accounting tools, the establishment of unified product carbon labeling systems, and the integration of circular economy principles toward low- and zero-carbon textile value chains.

Agricultural soils are vital for reducing atmospheric CO₂; however, the effectiveness of farmland carbon sequestration, including soil organic carbon (SOC) and inorganic carbon (SIC), typically requires a lengthy period and varies with different farming practices. In a long-term study on the North China Plain, SOC and SIC changes due to farming practices involving N fertilization, organic materials, irrigation, and no-tillage were tracked. Four experimental treatments, including no N fertilizer input (CK), local farmer operation (FRM), optimized farming (OPT), and no-tillage (NoT), were selected for the study. From 2008 to 2024, the fertilized treatments sequestered SOC at rates of 0.35-0.63 Mg C ha^-1 yr^-1 in the 0-20 cm layer, which quadrupled in the 0-100 cm layer. Long-term high irrigation with N fertilization accelerated the leaching of SIC into the subsoil, and SIC losses ranged from 0.46 to 0.71 Mg C ha^-1 yr^-1 at 0-20 cm and from 1.88 to 2.42 Mg C ha^-1 yr^-1 at 0-100 cm. Organic materials and N fertilization interactively help sequester SOC, but excessive organic material input results lower conversion efficiency. Crucially, the substantial depletion of SIC across the whole profile largely counteracted the observed SOC gains, leading to a diminished or even negative net carbon balance. Ultimately, this study reveals that failing to account for whole-profile SOC-SIC co-dynamics leads to an overestimation of carbon sequestration in intensive agricultural systems, highlighting the necessity of integrated accounting for accurate climate mitigation assessments.

Bioenergy from forests (BEF) is widely promoted as a significant contributor to the global renewable energy transition and a primary pathway of achieving climate goals. However, the climate effects of BEF remain deeply contested due to the complexity of the BEF system that requires a multitude of methodological choices and assumptions to contextualize. The resulting divergent conclusions across studies generated scientific disagreement and policy concerns. This review provides a holistic synthesis of the environmental, economic, and social contexts shaping the climate effects of BEF. We first conducted a bibliometric analysis of BEF-related articles to map research trends and dominant paradigms, resulting in four major research clusters spanning forestry systems, bioenergy production, bioeconomy interactions, and emerging climate solutions. Building on this overview, we identifies six key areas of concern and disagreement that critically influence BEF climate assessments: system boundaries, spatial and temporal scales, reference systems, feedstock sourcing, effects of market changes, and social impacts. We provide methodological recommendations for the six aspects. For each area, we articulate contrasting perspectives, underlying assumptions, and empirical evidence, highlighting how methodological choices can lead to fundamentally different conclusions regarding BEF’s climate performance. We provide methodological recommendations to improve comparability, transparency, and policy relevance of BEF assessments. By clarifying sources of disagreement and framing BEF within a broader sustainability context, this work aims to reduce confusion and support more informed, evidence-based decision-making on the future role of BEF in climate mitigation strategies.

The carbon footprint (CF) is widely used as a proxy indicator for the overall environmental impacts of entities such as countries, organizations, and products. However, since CF is by definition limited to greenhouse gas emissions, an important question arises: to what extent is CF a reliable predictor of other environmental impacts, including ozone layer depletion, acidification, eutrophication, and toxicity? This question has been examined in previous studies, yielding mixed results. In this paper, we argue that the analytical methods employed in earlier work may lead to misleading conclusions. We therefore propose the use of methods from directional statistics as an alternative approach. We analyze the correlation between life-cycle environmental impacts across approximately 4,000 products using a range of metrics, including linear, logarithmic, and rank-based regression, as well as directional statistics-based measures. Our findings are consistently negative: CF does not serve as a reliable predictor for any of the other environmental impact categories considered. Moreover, we show that traditional metrics used to assess such relationships can be misleading. Overall, relying on CF as a measure of total environmental burden is likely to introduce substantial uncertainty, even in cases where conventional correlation indicators suggest otherwise.

Dynamic Life Cycle Assessment (LCA) ranges in temporal complexity, with fully dynamic approach requiring full life-cycle chronologies for both foreground and background systems. For instance, LCAs based on Environmental Product Declaration (EPDs), required by the French RE2020 regulation, are partially dynamic, since only the foreground timeline is available. The goal of this research is to provide a user-friendly and rigorous method to conduct partially dynamic LCAs for climate change impact based on EPDs. Delay factors are built as coefficient depending on the time distribution of emissions, to define the dynamic characterization factor as a function of the static one. Compatibility constraints between static and dynamic imposes an observation time T equal to the sum of the Life Cycle Duration (LCD) and the Time Horizon of the Impact (THI). Literal mathematical expressions of delay factors and their behaviors are provided for Global Warming Potential (GWP) and Global Temperature Potential (GTP). The application scope of these delay factors covers all greenhouse gases (GHG) and large temporal range of LCD and THI. A case study based on three background products and randomly generated foreground emissions shows that the RE2020 regulation dynamic factors overestimate benefits obtained by delaying emissions compared to present method. This happens because the method ignores compatibility constraints between static and dynamic approaches and because it does not differentiate delay factors for distinct GHGs. However, delaying emissions reduces GWP but still raises GTP, questioning the use of GWP as a dynamic indicator, as it may falsely suggest a declining impact when it is actually increasing.

Advancing the energy sector’s sustainable transformation requires structural optimization of the green financial system. Differentiating between bank- and market-dominated systems, this study categorizes green financial instruments into indirect financing (green credit) and direct financing (green bonds, green stocks, and green funds). It examines pathways to enhance green total factor productivity (GTFP) of energy firms by shifting from credit hegemony to market diversification. The findings indicate that: (1) Green finance significantly promotes GTFP in energy firms; however, the effect of market-dominated direct financing is notably stronger than that of bank-dominated indirect financing, revealing the advantages of market diversification; (2) The positive effect of green credit (indirect financing) is limited to state-owned enterprises and the new energy sector, showing a clear credit preference. In contrast, direct financing mitigates ownership discrimination and benefits all energy firms, especially non-state-owned and new energy companies, demonstrating greater market inclusiveness; (3) Mechanism tests show that green finance enhances GTFP of energy firms by improving green innovation quality and reducing carbon emissions. This study clarifies the logic by which green finance drives transformation of energy firms, providing a scientific basis for policy design that shifts from reliance on a single credit channel toward incentivizing collaboration among diverse market participants.

Environmental impacts associated with botanical extracts used in nutraceutical and substance-based medical device formulations remain insufficiently characterized due to fragmented and non-comparable life cycle inventory (LCI) data. This study develops and applies a harmonized cradle-to-gate life cycle assessment (LCA) framework to quantify the environmental impacts of selected botanical extracts using primary industrial data collected from Italian, European, and extra-European suppliers, in accordance with ISO 14040/14044 standards. Across the analyzed extracts, climate change impacts range from 2.59 kg CO₂-eq per kg to 3.33 kg CO₂-eq per kg, with most values clustered within a relatively narrow interval. Energy- and emission-related indicators show moderate variability across extracts, whereas land use and eutrophication impacts, particularly freshwater eutrophication, exhibit higher variability due to crop-specific agricultural characteristics. Contribution analysis reveals a consistent life-cycle structure across all extracts, with process energy consumption representing the dominant contributor to climate change impacts (67%-84%). Auxiliary materials contribute up to 14% of total impacts, while cultivation contributes from < 0.1% to approximately 9%, and transport remains marginal. Sensitivity analysis confirms that modelling assumptions have a limited influence on the results, with all variations remaining below 5% across impact categories. Product-level validation of three pharmaceutical formulations demonstrates that formulation and packaging choices may outweigh extract-level differences under a functionally equivalent dose. Overall, the study provides robust primary-data-based evidence to support eco-design and emissions accounting in nutraceutical supply chains.

The construction industry is a significant contributor to global carbon emissions, with embodied carbon accounting for a growing proportion of building life-cycle emissions. Comparative analyses that assess various structural systems within a single, controlled building design remain limited, despite increasing interest in building information modelling- life cycle assessment (BIM-LCA) integration. This study addresses this gap by providing a BIM-based assessment framework that quantifies and compares the embodied carbon of three structural systems (steel, reinforced concrete, and timber) applied to an identical conceptual two-storey residential structure in the UK. Material quantities were extracted from a parametric Revit model and integrated with emission factors within a cradle-to-gate (A1-A3) system boundary. The results indicate that total embodied carbon amounts to 104,165.16 kgCO₂eq for a traditional steel house, 84,640.06 kgCO₂eq for a traditional reinforced concrete house, and 51,255.87 kgCO₂eq for a traditional timber house. By employing low-carbon material alternatives, embodied carbon is reduced by 40.4% in the steel house, 32.2% in the concrete house, and 19.7% in the timber house, respectively. Thus, encouraging early-stage sustainable design decisions can make a substantial contribution to the decarbonisation of the built environment.