Global Change Biology Bioenergy最新文献_第6页

IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-05-04

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IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-05-04

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IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-23

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IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-23

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IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-22

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IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-22

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Biowaste Composting as a Sustainable Platform for Bacterial CO Production: Evidence From cooS Gene Expression and Microbial Community Profiling 生物垃圾堆肥作为细菌CO生产的可持续平台：来自cooS基因表达和微生物群落分析的证据

IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-10 DOI: 10.1111/gcbb.70116

Karolina Sobieraj, Aneta Urbanek, Zofia Steczkiewicz

{"title":"Biowaste Composting as a Sustainable Platform for Bacterial CO Production: Evidence From cooS Gene Expression and Microbial Community Profiling","authors":"Karolina Sobieraj, Aneta Urbanek, Zofia Steczkiewicz","doi":"10.1111/gcbb.70116","DOIUrl":"10.1111/gcbb.70116","url":null,"abstract":"Current industrial carbon monoxide (CO) production depends mainly on fossil fuels. Composting offers a sustainable alternative, where CO can be produced by compost-inhabiting bacteria synthesizing the CO dehydrogenase (CODH) enzyme. This study aimed to characterize the microbial community and, for the first time, to investigate the expression of the cooS gene encoding CODH during biowaste composting under laboratory conditions. Composting was performed at mesophilic (45°C) and thermophilic (70°C) temperatures to evaluate CO production under conditions known to stimulate elevated CO emissions. The results confirmed biotechnological potential for microbial CO production within the mesophilic range, potentially reducing costs compared with thermophilic composting. Although the study revealed higher CO concentrations under thermophilic conditions (average 208 ppm; maximum 818 ppm) compared to mesophilic conditions (average 102 ppm; maximum 499 ppm), the compost obtained at 45°C exhibited a more diverse and balanced microbial community than that observed at higher temperatures. In the 45°C compost, bacteria previously reported as CODH or CO producers were identified, including Bacillus licheniformis and representatives of Alphaproteobacteria and Streptomyces. The cooS gene expression analysis showed a significant increase during composting at 45°C, reaching an 11,016-fold rise within the week. The expression was likely induced by CO and not inhibited by oxygen. This first report demonstrating cooS expression during composting confirmed the biological origin of CO under mesophilic conditions through the activity of anaerobic Ni, Fe-CODH.","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 5","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70116","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683637","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}

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What Is the Best Use of Biomass? A Harmonized LCA-TEA Framework Quantifying Economic and Environmental Metrics for Bioenergy Pathways 生物质的最佳用途是什么？一个统一的LCA-TEA框架量化生物能源途径的经济和环境指标

IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-08 DOI: 10.1111/gcbb.70115

Saurajyoti Kar, Troy R. Hawkins, Doris Oke, Udayan Singh, Ling Tao, Arpit Bhatt

{"title":"What Is the Best Use of Biomass? A Harmonized LCA-TEA Framework Quantifying Economic and Environmental Metrics for Bioenergy Pathways","authors":"Saurajyoti Kar, Troy R. Hawkins, Doris Oke, Udayan Singh, Ling Tao, Arpit Bhatt","doi":"10.1111/gcbb.70115","DOIUrl":"10.1111/gcbb.70115","url":null,"abstract":"Bioresource utilization is expected to play a pivotal role in complementing existing energy pathways and enhancing energy resilience. This study develops a harmonized life cycle assessment (LCA) and techno-economic analysis (TEA) framework to evaluate the greenhouse gas (GHG) reduction potential, minimum fuel selling price (MFSP), and marginal abatement cost (MAC) of bioenergy pathways. We analyze 19 pathways, including liquid biofuels (via catalytic fast pyrolysis, Fischer–Tropsch synthesis, and gasification), bioelectricity, and biomass-to-hydrogen, with and without carbon capture and storage (CCS). The GHG impacts are assessed using the GREET 2022 model, while U.S. Billion-Ton 2016 biomass availability projections are used to estimate scale-up potential. Additionally, we evaluate the influence of a low-carbon electricity grid on pathway performance. Our results show that CCS implementation reduces carbon intensities (CI) to net-negative values for several pathways, with MAC ranging from $32 to $600 per metric ton (MT) CO2e avoided. Bioelectricity pathways with CCS achieve the lowest MAC ($32–$68/tCO2e), while liquid biofuels and hydrogen pathways remain critical for hard-to-abate sectors like aviation and heavy industry. Pathways with net-positive electricity demand benefit from a low-carbon grid, whereas those co-producing electricity experience increased MAC under lower electricity grid CI scenarios. This open-source framework provides a robust tool for harmonized evaluation of bioenergy pathways, enabling policymakers and stakeholders to identify cost-effective strategies for biomass utilization and carbon abatement at scale. The findings underscore the importance of CCS, co-product credits, and feedstock availability in optimizing bioenergy deployment for a low-carbon economy.","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 5","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683496","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}

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Predicting Biochar-Induced Changes in Soil Organic Carbon With Ensemble Machine Learning 用集合机器学习预测生物炭引起的土壤有机碳变化

IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-06 DOI: 10.1111/gcbb.70112

Avedananda Ray, Xin Li, Yujuan Chen, Xinyao Yang, Wenju Zhang, Dafeng Hui

{"title":"Predicting Biochar-Induced Changes in Soil Organic Carbon With Ensemble Machine Learning","authors":"Avedananda Ray, Xin Li, Yujuan Chen, Xinyao Yang, Wenju Zhang, Dafeng Hui","doi":"10.1111/gcbb.70112","DOIUrl":"10.1111/gcbb.70112","url":null,"abstract":"Biochar is a promising soil amendment for enhancing soil organic carbon (SOC), but accurately predicting its effect under diverse environmental conditions remains challenging due to complex, nonlinear interactions among biochar properties, soil characteristics, climate, and management practices. To address this research gap, we developed an ensemble machine learning (ML) framework, combining Extremely Randomized Trees (ExtraTrees), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost) regressors, to model SOC responses to biochar application using a globally curated dataset of 800 field observations. The ensemble model showed strong predictive performance (R2 = 0.86, RMSE = 0.11) and generalized well across a wide range of conditions. Shapley Additive exPlanations (SHAP) analysis identified biochar addition rates, crop types, soil type, and soil pH were the most influential predictors of SOC changes. The most effective biochar application rate was about 40 t/ha, and the saturation point was 121.7 t/ha. Partial dependence plots revealed nonlinear and threshold effects of pyrolysis temperature, initial SOC levels, and nitrogen content. To facilitate practical application, we also developed a user-friendly graphical interface for SOC prediction under various biochar-soil-climate scenarios. This work highlights the predictive power and interpretability of ML tools in digital soil carbon modeling and supports data-driven strategies for optimizing biochar use in climate-smart agriculture.","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 5","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683215","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}

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Emerging Technologies for Biobutanol Production via Syngas Fermentation 合成气发酵生产生物丁醇的新兴技术

IF 4.1 3区工程技术

Global Change Biology Bioenergy Pub Date : 2026-04-06 DOI: 10.1111/gcbb.70114

Xuemei Wang, Luiza C. Campos, Zifu Li, Werner Fuchs

{"title":"Emerging Technologies for Biobutanol Production via Syngas Fermentation","authors":"Xuemei Wang, Luiza C. Campos, Zifu Li, Werner Fuchs","doi":"10.1111/gcbb.70114","DOIUrl":"10.1111/gcbb.70114","url":null,"abstract":"Biobutanol offers significant advantages over ethanol as an advanced biofuel, but its large-scale production via syngas fermentation faces critical challenges including low product titers, carbon inefficiency, and microbial toxicity. To address these limitations and evaluate technological progress, this review summarizes recent progress in syngas-based butanol synthesis, focusing on microbial catalysts, metabolic pathways, and process optimization strategies. Particular emphasis is placed on acetogenic bacteria and the role of the Wood–Ljungdahl pathway in carbon fixation and energy conservation. Key factors affecting product distribution, including gas composition, reactor configuration, pH, temperature, and trace elements, are discussed in detail. Furthermore, recent developments in enhancement approaches such as metabolic engineering, co-cultivation systems, and electro-fermentation are critically examined. While several pilot and demonstration-scale ethanol production systems have been established, large-scale biobutanol production via syngas fermentation remains limited due to challenges related to low titers, carbon inefficiency, and product toxicity. Advancing this technology will require a multidisciplinary effort integrating microbial physiology, systems engineering, and process intensification. This review aims to provide a foundation for future research and technological development in the field of gas-to-liquid biofuel production.","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"18 5","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.70114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683218","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}

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