Global Change Biology Bioenergy最新文献

{"title":"Genetic Mapping for Winter-Hardiness in a Miscanthus sacchariflorus × M. sinensis (Hardy × Non-Hardy) F2 Population","authors":"Xuying Zheng,&nbsp;Nick Labonte,&nbsp;Hongxu Dong,&nbsp;Shailendra Sharma,&nbsp;Katarzyna Glowacka,&nbsp;Lindsay V. Clark,&nbsp;John A. Juvik,&nbsp;Dessireé Zerpa-Catanho,&nbsp;Erik J. Sacks","doi":"10.1111/gcbb.70175","DOIUrl":"https://doi.org/10.1111/gcbb.70175","url":null,"abstract":"<p>Winter survival remains a primary limitation to the deployment of <i>Miscanthus</i> biomass cultivars in temperate climates. To investigate the genetic architecture underlying this trait, we studied an F₂ population (<i>n</i> = 247) derived from a cross between the winter-hardy <i>M. sacchariflorus</i> ‘Robustus’ and the non-hardy <i>M. sinensis</i> ssp. <i>condensatus</i> ‘Cosmo Revert’. Phenotypic data on overwintering ability, hardiness score, and summer vigor were collected following the establishment year winter (2015–2016) and after an especially cold winter in 2018–2019, during which the soil temperature at 10 cm reached −4.2°C. Composite interval mapping (CIM) with a high-density SNP linkage map identified 14 quantitative trait loci (QTL), and genome-wide association studies (GWAS) incorporating both additive and dominant models detected an additional 23 loci, resulting in a total of 37 QTLs. Six QTL regions on five chromosomes were detected repeatedly across traits and/or analyses. In all cases, alleles inherited from the hardy <i>M. sacchariflorus</i> parent were associated with increased winter-hardiness, whereas alleles from the non-hardy <i>M. sinensis</i> parent were associated with decreased hardiness. We identified fourteen candidate genes within 10 kb of QTL peaks and that were orthologs of genes previously implicated in cold stress tolerance, including glycosyl and oxidoreductases, rare-cold-inducible (RCI) genes, peroxidase proteins, LRR sensors, cytochrome P450s, and stress-responsive transcription factors. Largely non-overlapping QTL sets for first-year versus mature-plant winter-hardiness suggested distinct physiological mechanisms underlying differing strategies of overwintering. The consistently favorable effects of the hardy-parent’s alleles, together with high heritability, suggest that marker-assisted selection can accelerate the development of winter-hardy <i>Miscanthus</i>.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 10","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting and Explaining Ethanol Price Through Shapley Additive Explanations: Evidence From Two Decades of Panel Agroeconomic Data in Brazil","authors":"Marilaine Colnago,&nbsp;Lucas A. B. de Matos,&nbsp;José Nuno Fidalgo,&nbsp;Rogério G. Negri,&nbsp;Wallace Casaca","doi":"10.1111/gcbb.70164","DOIUrl":"https://doi.org/10.1111/gcbb.70164","url":null,"abstract":"<p>Understanding the complex dynamics of the sugar–biofuel market is challenging due to the multifaceted effects of economic, agronomic, and policy-related factors, with sugar and ethanol fuel competing for the same sugarcane input. In this paper, we propose a comprehensive eXplainable Artificial Intelligence (XAI) framework to predict and interpret ethanol price formation in Brazil, leveraging a rich, multi-source agroeconomic panel database spanning nearly two decades of indicators across economic, fiscal, energy, and global commodity domains. Our approach integrates machine learning, exploratory data analysis, and XAI techniques to uncover the key drivers behind price fluctuations. Forecasting experiments demonstrate that deep learning networks show superior performance at capturing temporal dependencies and nonlinear trends from the data, while interpretability tools such as Shapley Additive Explanations and Permutation Feature Importance reveal gasoline prices, sugarcane quality, and VAT taxation as primary drivers, with inflation and exchange rates exerting moderating influences. We show that the proposed framework provides interpretable insights to support evidence-based decision-making for policymakers and industry actors in the sugar–biofuel sector.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 10","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70164","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transgenic Mixed-Linkage-Glucan Enhancement Affects Root Characteristics and Decomposition in Soils of Contrasting Vegetation History","authors":"Majid Mahmoodabadi,&nbsp;Sang-Jin Kim,&nbsp;Poulamee Chakraborty,&nbsp;Andrey Guber,&nbsp;Alexandra Kravchenko,&nbsp;Federica Brandizzi","doi":"10.1111/gcbb.70176","DOIUrl":"https://doi.org/10.1111/gcbb.70176","url":null,"abstract":"<p>Development of transgenic bioenergy sorghum [<i>Sorghum bicolor</i> (L.) Moench] with increased contents of mixed-linkage (1,3;1,4)-β-glucan (MLG) is an important step towards enhancing quality of bioenergy feedstocks. Since MLG-enhancement leads to greater biomass digestibility, our overarching hypothesis is that root residues of MLG-enhanced plants may be more readily decomposed in the soil, potentially creating new opportunities for optimizing soil carbon (C) sequestration, nutrient cycling, and overall agricultural sustainability. The study examined morphological, chemical, and enzymatic characteristics of fine and coarse roots of four bioenergy sorghum genotypes. Then, we incubated the roots within soils with contrasting vegetation histories while measuring C mineralization, microbial biomass C (MBC), and activity of hydrolytic enzymes and calculating vector length and vector angle enzymatic stoichiometry parameters. The results indicated that MLG-enhancing transformations increased root total nitrogen (N) contents, decreased C/N ratios, and were associated with higher MLG concentrations in fine than in coarse roots. Incubations with transgenic roots led to 16%–38% higher MBC and 19%–41% lower microbial metabolic quotient (qCO₂). While enzyme activity differed markedly among the studied genotypes, it did not directly respond to MLG levels in root tissues. The increase in MBC without concurrent increases in C mineralization or hydrolytic enzyme activities in transgenic genotypes suggests that MLG enhancement promoted microbial anabolic retention of root-derived C rather than stimulating catabolic decomposition. Enzymatic vector results indicated that these parameters reflect a variety of drivers behind microbial enzyme production, including availability of specific substrates, such as MLG here, and/or deficiency in specific nutrients, such as phosphorus (P). The study confirms the positive impacts from the roots of engineered MLG-enhanced bioenergy plants on soil microbial activity and highlights the interactive influences on the MLG-enhancement effects from root size and inherent soil properties.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 10","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70176","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148856708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Illusions of Accuracy: Widespread Data Leakage Distorts Machine Learning Results in Biochar Research","authors":"Ho Jun Jang,&nbsp;Wartini Ng,&nbsp;Songchao Chen,&nbsp;Raj Setia,&nbsp;Budiman Minasny","doi":"10.1111/gcbb.70173","DOIUrl":"https://doi.org/10.1111/gcbb.70173","url":null,"abstract":"<p>Machine learning (ML) is increasingly used in biochar research to predict yield, material properties, and adsorption performance. Yet, this review reveals that much of the reported success in ML-driven biochar studies may be overstated due to data leakage, the inadvertent transfer of information between training and testing datasets. We systematically examined 64 of the most-cited studies published between 2015 and 2025 and found that all studies exhibited potential leakage, commonly arising from hierarchical or grouped data structures, multi-source compilations, or temporal and concentration dependencies. Nearly all studies (98%) employed random point-level data splits for training and testing, disregarding dependencies among samples, while only one adopted a group-based split approach. Re-analysis of five representative datasets showed that random point-level splitting can inflate predictive accuracy by up to 86%, often yielding test-set <i>R</i>² (coefficient of determination) values exceeding 0.90 even when model generalisation fails. Leakage risks were particularly severe in adsorption studies and in those using very small datasets (&lt; 35 samples), where overfitting further distorted model performance. To ensure methodological rigour and reliable generalisation, biochar ML research must adopt grouped or study-level data-splitting strategies, maintain strict separation of preprocessing steps, and incorporate hierarchical or domain-aware validation frameworks. Future progress requires automated leakage-detection tools, benchmark datasets with explicit metadata on dependencies, and hybrid models that integrate physical constraints. Addressing data leakage systematically is essential to restore credibility, enhance reproducibility, and realise the full potential of ML as a reliable tool for environmental research.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 9","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70173","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive Review on Green Transformation of Organic Waste Into Bioenergy Using Microbial Enzymes: Advances, Challenges, and Future Strategies","authors":"Divya Divakaran,&nbsp;Indran Suyambulingam,&nbsp;Ananth Selvan,&nbsp;Nadir Ayrilmis,&nbsp;P. Merlin Christy,&nbsp;M. Gomathi,&nbsp;P. Senthamaraikannan","doi":"10.1111/gcbb.70168","DOIUrl":"https://doi.org/10.1111/gcbb.70168","url":null,"abstract":"<p>Sustainable waste management is a substantial global challenge emerging in this eco-concerned scenario, and appropriate management or recycling strategies are indispensable to counteract all the socio-ecological issues allied with it. The advanced energy-efficient organic waste conversion techniques are needed to ensure sustainability, as most of the conventional management practices cannot meet current environmental policies. Microbial enzyme-mediated waste treatment is a promising green strategy that can be implemented on a large-scale to transform organic waste into renewable energy supplies and biofertilizers. In this review, current waste treatment affairs, the significance of enzyme treatment, the dynamics and role of degradative enzymes, challenges and prospects of enzyme-mediated waste management are discussed in detail. Recent advances in enzyme pretreatment, specific enzyme cocktails, and integrated enzyme-chemical mediated process concepts have marked improved hydrolysis efficiency and energy conversion rate. It is apparent that enzyme addition exhibited significant effects in waste conversion in terms of enhanced biogas (79%), bioethanol (29.1 g/L), and biodiesel (98%) production. However, there are a few challenges that impede the functioning of this technology extensively, which include feedstock divergency, enzyme inhibition, low process stability, and high production cost. There are still critical knowledge gaps existing with the development of low-cost enzyme systems with high-loading rate, immobilized enzyme systems, on-site synthetic consortia, and integrated hybrid systems, to enable sustainable, enzyme-mediated waste degradation and eco-friendly bioenergy generation in future. In outlook, profitable, substrate-specific, microbial enzymes–driven, waste-to-energy models with high-bioconversion rate are recommended for resource-efficient waste valorization and energy recovery in temporal dimensions, by sustainable means.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 9","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70168","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148848783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Biochar and Nitrogen-Enriched Biochar on Tree Growth in Scots Pine Stands","authors":"Kjersti Holt Hanssen,&nbsp;Jogeir Stokland,&nbsp;Rasmus Astrup","doi":"10.1111/gcbb.70148","DOIUrl":"https://doi.org/10.1111/gcbb.70148","url":null,"abstract":"<p>Biochar, a carbon-rich product of pyrolysis, is increasingly considered for soil amendment and climate change mitigation due to its potential to enhance soil properties and sequester carbon. However, its effects on tree growth in forest ecosystems remain uncertain. This study investigated the impact of biochar and nitrogen-enriched biochar on the growth of two middle-aged (approximately 60-year-old) Scots pine stands in southeastern Norway. Both stands were characterized by medium site indices and podzolic soils. In replicated field experiments, we applied four treatments consisting of an unfertilized control, and addition of biochar (2.5 t ha⁻¹), nitrogen fertilizer (150 kg N ha⁻¹), or biochar loaded with nitrogen (2.5 t biochar +150 kg N ha⁻¹). The biochar was produced by pyrolysis of Norway spruce wood chips at 600°C. After 5 years, only treatments containing added nitrogen (either as mineral fertilizer or as nutrient-enriched biochar) significantly increased basal area and volume growth compared to control. No significant difference in timing or magnitude of effects was observed between the nitrogen and biochar + nitrogen treatments, except better annual growth in the combined treatment the third year after fertilization, indicating rapid nitrogen release and uptake regardless of carrier. Pure biochar did not stimulate tree growth. While biochar did not negatively affect growth, its direct role as a growth stimulant was not supported under these conditions, at least in the short-term with the dose of 2.5 t ha⁻¹. Further research is needed across different forest ages, site types, and application rates to fully understand biochar's potential in forestry.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 9","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70148","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Crop Cultivation of Miscanthus × giganteus on Biochar-Amended Marginal Soils With Conventional and Waste-Derived Fertilization: Biomass Allocation and Nutrient Dynamics Toward Closing Nutrient Loops","authors":"Nicole Nawrot,&nbsp;Joanna Strycharz,&nbsp;Muhammad Mohsin,&nbsp;Suvi Kuittinen,&nbsp;Karolina Matej-Łukowicz,&nbsp;Jacek Kluska,&nbsp;Ari Pappinen,&nbsp;Emil Jespersen,&nbsp;Carlos A. Arias,&nbsp;Jarosław Borowiak,&nbsp;Katarzyna Tarasewicz,&nbsp;Ewa Wojciechowska","doi":"10.1111/gcbb.70167","DOIUrl":"https://doi.org/10.1111/gcbb.70167","url":null,"abstract":"<p>Sustainable production of lignocellulosic biomass on marginal lands requires strategies that enhance yield while minimizing nutrient losses and supporting circular resource use. In this study, a two-year (2023–2024) greenhouse meso-scale experiment was conducted using <i>Miscanthus</i> × <i>giganteus</i> cultivated on nutrient-poor soil amended with wood- or straw-derived biochar (450°C) and fertilized with either mineral fertilizer (NPK) or spent coffee grounds (Cof). Biomass production and allocation, nutrient mobility in leachates, elemental composition of plant biomass and resulting phyto-ashes, root anatomy, and plant physiological status were evaluated. Total biomass ranged from 250 to 491 g d.w. m⁻² in the first growing season and reached 1495 g d.w. m⁻² after two growing seasons. Biomass allocation was dominated by belowground fractions (58%–89% of total biomass), particularly in Cof-amended plots. The highest biomass production was observed in the plot amended with straw biochar and Cof, indicating potential complementarity between biochar amendment and organic fertilization under marginal soil conditions. Some biochar-amended plots (wood biochar + Cof) showed lower and more stable event-based nitrogen loads in leachates, consistent with reduced nitrogen mobility. Cof-amended plots exhibited higher chlorophyll-related indices, while the highest TKN concentration, 9726 mg kg⁻¹ d.w., was recorded after the second growing season, indicating differences in nitrogen availability and allocation among amendment scenarios. Root anatomical organization also varied among plots. Endpoint Fv/fm values ranged from 0.72 to 0.77 and were below the range commonly reported for non-stressed plants, while Fm/Fo and Y(II) indicated that PSII photochemical activity was maintained. Here, we demonstrate that biochar combined with organic residues (Cof) modifies biomass partitioning and nutrient dynamics in <i>Miscanthus</i> × <i>giganteus</i> cultivated on marginal soil. In addition, the resulting phyto-ashes were characterized by elevated K and P concentrations and low levels of potentially toxic elements, supporting their potential relevance for circular nutrient management.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 9","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70167","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Highly Thermally Stable and Efficient Ru/MAFO Catalysts for Glucose Hydrogenolysis to 1,2-Propylene Glycol","authors":"Qingsong Wang,&nbsp;Xin Wang,&nbsp;Yunkai Zhou,&nbsp;Wenjia Li,&nbsp;Jia Wang,&nbsp;Dongbing Li","doi":"10.1111/gcbb.70172","DOIUrl":"https://doi.org/10.1111/gcbb.70172","url":null,"abstract":"<p>The catalytic hydrogenolysis of glucose to produce 1,2-propylene glycol (1,2-PG) has opened promising avenues for sustainable chemical production. However, traditional Ru-based catalysts suffer from issues such as high metal loading, poor dispersion, and a tendency to agglomerate under harsh conditions, leading to rapid deactivation. This work reports a highly dispersed, low-loading Ru catalyst supported on a magnesium–aluminum ferrite (MAFO) spinel to address these limitations. Strong covalent metal–support interactions (CMSI) between Ru species and the MAFO support not only achieve efficient stabilization of Ru nanoparticles but also promote their redispersion. Under optimized reaction conditions (518 K, 5 MPa H₂, and 1 h), the Ru/MAFO catalyst achieves 100% glucose conversion and 59.3% selectivity to 1,2-PG. Notably, the catalyst maintains outstanding activity and stability after six consecutive reaction cycles. This study provides an efficient and robust catalytic strategy for 1,2-PG production from glucose, offering significant insights for designing high-performance and stable catalysts for biomass valorization.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 9","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70172","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-Driven Strategies for Automated Microalgae Production Systems: Enhancing Yield, Efficiency, and Commercial Viability","authors":"Angela Paul Peter,&nbsp;Wan Adibah Wan Mahari,&nbsp;Sharoen Yu Ming Lim,&nbsp;Abdirahman Yasin Ibrahim,&nbsp;Revathy Sankaran,&nbsp;Kalaimani Markandan,&nbsp;Theeba Rajasegran","doi":"10.1111/gcbb.70174","DOIUrl":"https://doi.org/10.1111/gcbb.70174","url":null,"abstract":"<p>Microalgal bioproducts hold significant promise for sustainable applications, but the high production costs associated with cultivation systems remain a major barrier to commercialization. The optimal growth of microalgae depends on a range of factors, including light, temperature, pH, nutrients, and mixing. Each strain of microalgae has unique cultivation requirements, necessitating tailored systems to maximize yield. Traditional cultivation systems, such as open ponds, photobioreactors, and fermentation tanks, each have distinct advantages and limitations. Open ponds rely on natural conditions but are difficult to control, while photobioreactors offer precise environmental control for maximum yield, albeit at higher costs. Fermentation tanks, which exploit heterotrophic growth, reduce operating expenses compared to photobioreactors. Machine learning-driven automation and smart technologies offer a promising strategy to reduce these costs by optimizing cultivation processes through electronic data logging, automated control, and minimal human intervention. This review explores the role of automation in the cultivation, harvesting, extraction, and post-processing of microalgae. It examines recent advancements in automated technologies and their potential to enhance the efficiency and scalability of microalgal bioproduct production. Key considerations for automation in microalgae production include system requirements, technological advancements, and integration across various stages of the production chain. The review emphasizes the mechanical aspects of automation, focusing on technologies that can be automated to improve yield and reduce operational costs, and highlights the need for further innovation in this field to facilitate the widespread commercialization of microalgae-based products.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 9","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70174","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148784052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Consequential Climate Impact of Bioenergy and Wood Products: A New Framework for the Assessment of Biogenic Carbon","authors":"Stefan Füchsl,&nbsp;Hubert Röder","doi":"10.1111/gcbb.70169","DOIUrl":"https://doi.org/10.1111/gcbb.70169","url":null,"abstract":"<p>The utilization of woody biomass plays a key role in the path towards a sustainable future for many stakeholders. To assess the climate impact of wood energy and products, it is essential to assess the impact of biogenic carbon, which has become a topic of increasing interest. The goal of this study is to build on existing approaches for the assessment of biogenic CO₂ and provide a new framework termed the Green Carbon Cycle (GCC) Approach. This new framework brings together key methods for biogenic carbon assessment into one consistent framework for practitioners of LCA to follow. The GCC Approach includes the whole life cycle of biogenic carbon from the removal from the atmosphere by forest growth, harvesting and use of wood products and fuelwood until the end of life by natural decay or combustion. It covers five steps: (1) Analysis of the biomass source and affected GCC flows, (2) formulation of use- and counterfactual scenario, (3) simulation or calculation of emission profiles, (4) application of dynamic LCA to calculate emission factors, and (5) implementation of emission factors in LCA. Beyond presenting this framework, its implementation compared to existing methods and generic emission factors for wood is shown. To calculate forestry based biogenic emission factors the carbon dynamics of five representative forest stands typical for Germany were simulated with different harvest intensities compared to a non-harvest scenario. Forest residues were analyzed in contrast to a non-use natural decay scenario. From the differences to the baseline scenarios global warming potential (GWP)_bio20 and GWP_bio100 factors were calculated. The generic emission factors show a strong impact of harvest intensity and species mix in a forest stand. With high harvest intensities leading to consistently higher emission factors and in most cases resulting in climate-positive factors for coniferous wood and climate negative ones for deciduous species.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 9","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}