Global Change Biology Bioenergy最新文献

Quantifying the carbon (C) uptake of Miscanthus × giganteus (M × g) in both aboveground and belowground structures (e.g., net primary productivity (NPP)) and differences among methodological approaches is crucial. Our objectives were to directly measure Mxg NPP and evaluate the effects of nitrogen application, location, and belowground biomass sampling methods. We hypothesize that increased nitrogen application increases the overall NPP of M × g and that quantifying rhizome biomass using excavations will produce the lowest variability between replicates. We collected biomass from mature M × g stands from three locations in Iowa with three nitrogen application rates and one site in Illinois. We destructively sampled at two time points, when rhizome mass is anticipated to be at a minimum (initial) and anticipated to be at its maximum (peak). Biomass was collected from 1 × 1 m quadrats in which one in-clump and one beside-clump cores were collected and then excavated to 30 cm depth to extract all rhizomes. We found that aboveground M × g NPP ranged from 15.4 Mg Da ha^–1 year^–1 to 36.4 Mg Da ha^–1 year^–1 and belowground M × g NPP ranged from 4.4 Mg Da ha^–1 year^–1 to 19.6 Mg Da ha^–1 year^–1. M × g NPP varied across sites, fertilization, and calculation assumptions. Aboveground NPP (yield) was on average 68.7% of the total NPP. Root-to-shoot ratios at peak biomass decreased with nitrogen application rate, from an average of 1.9 for 0 N plots to 0.89 for 224 N fertilized plots. There was more variation in core data than from excavations; however, when in-clump and beside-clump cores were averaged together, core and excavation averages were not different. Overall, these results show that the range of mature M × g NPP is driven by aboveground productivity, influenced by nitrogen application and site. Our results provide useful data to constrain agro-ecosystem models and provide crucial insights for future perennial belowground sampling.

The recognition of bioethanol as a key strategy for mitigating greenhouse gas (GHG) emissions is closely linked to the accuracy of N₂O emission factors (EF) used in life cycle assessments. However, previous studies have shown that the default N₂O EF values recommended by the IPCC do not accurately reflect the diverse edaphoclimatic conditions found in Brazil, leading to uncertainties in GHG inventories. Therefore, establishing regional N₂O EF is essential for improving the precision of bioethanol emission estimates. In this study, we conducted a systematic literature review compiling 293 measurements from 45 field studies across different regions of Brazil. This study focuses on sugarcane (20 studies) and corn (25 studies), which are the primary crops used for bioethanol production in Brazil. Our findings indicate that the average N₂O EF for these crops is 0.72%, lower than the value reported for the tropics and sub-tropics (1.6%). When analyzed separately, sugarcane showed an average N₂O EF of 0.65%, with higher emissions from the combined use of mineral and organic N fertilizers (0.79%) compared to mineral (0.55%) or organic fertilizers alone (0.77%). For corn, the average N₂O EF was 0.84%, with mineral N fertilizers presenting the lowest EF (0.40%), while emissions increased with the combination of mineral and organic sources (0.82%), reaching the highest levels with pig slurry application (1.72%). These variations highlight the limitations of using IPCC default values for mineral and organic N fertilizers in Brazil. Our results reinforce the need for Tier 2 methodologies incorporating region-specific data to enhance GHG inventory accuracy and support targeted mitigation strategies. Although Brazil's latitudinal range spans tropical and subtropical zones, regional stratification was not applied due to the limited number of studies within each climate category, especially when further disaggregated by crop type and N fertilizer source. Despite covering key crops, fertilizer types, and multiple biomes, the current dataset still lacks representation for important agricultural regions such as Brazil's midwest, north, and northeast regions. This study represents a significant step toward refining N₂O EF estimates for bioethanol crops, contributing to more precise assessments of the sector's climate impact. However, further research is needed to cover underrepresented areas, understand long-term field dynamics, and evaluate other crop systems and management practices. Future studies should also incorporate modeling tools and real-time monitoring to reduce uncertainties and support the development of Tier 3 estimates.

Many jurisdictions within the boreal and temperate biomes have adopted targets to increase the contribution of forest bioenergy for climate change mitigation. Using residual forest biomass as feedstock is considered, but the carbon emission reductions associated with this practice remain controversial. Our study evaluated how intensifying wood procurement for bioenergy production, alongside supplying fiber for conventional wood industries, can support low-carbon forest management. We used six sites established in eastern Canada as a case study. We compared the carbon balance of four harvesting scenarios with increasing wood procurement intensity (from procuring sawtimber only to procuring sawtimber, pulpwood and biomass) to three scenarios of unharvested forests, two of which experienced natural disturbances. We modeled carbon fluxes over a 100-year simulation period, considering biogenic and fossil emissions from aboveground forest ecosystems, harvested wood products, and wood supply and manufacturing. We assessed the mitigation potential of procuring biomass to produce bioenergy in the form of stemwood, treetops (including branches) or pulpwood. We found that forest harvesting, regardless of the wood procurement intensity, offered limited carbon benefits compared to the referenced undisturbed mature stands in most cases. However, increasing wood procurement can reduce the carbon footprint of wood supply chains, with pulpwood identified as a key feedstock. Compared with harvesting roundwood for conventional industries only, procuring biomass for bioenergy is likely to increase carbon emissions unless it substitutes high-emission energy sources on markets or enhances the next-rotation stand yield, which seems achievable in the context we studied. Bioenergy displacement factors should range from 0.072 to 0.701 tonne of carbon emission reduction per tonne of carbon in the bioenergy product, depending on stand characteristics, biomass feedstock, and cutting cycle length. Our findings provide a foundation for assessing the GHG reduction potential of harvesting activities at a broader scale, considering varying feedstock recovery intensities.

Achieving European climate neutrality by 2050 will require an increase in energy production from renewable sources. Silage maize (Zea mays L.), the most commonly used crop in Germany, is increasingly subject to yield losses associated with soil degradation and nutrient depletion. The perennial cup plant (Silphium perfoliatum L.) has emerged as an alternative to reduce nutrient losses, mainly nitrogen (N), while maintaining similar biomass production. A lysimeter experiment was conducted to evaluate N dynamics between plant, soil, and leaching for maize and cup plant under moderate drought and well-watered conditions over 4 years. After the first year of growth, cup plant had higher shoot and root biomass than maize regardless of the watering conditions (e.g., in 2021 mean shoot biomass of maize was 266 g m⁻¹ compared to 2696 g m⁻¹ of cup plant). Notably, moderate drought did not affect shoot biomass in either crop (except in 2021 and 2022 for the cup plant). The higher biomass production of the cup plant was associated with higher N concentration in the shoot tissue compared to maize, likely due to its more efficient soil N utilization. This result was further supported by the lower soil dissolved N concentration and a reduction of nitrate leaching of 88% in 2021 and by up to 99% in 2022 under cup plant compared to maize. A higher microbial biomass N under cup plant suggests enhanced N immobilization by microorganisms. This is further supported by a higher microbial C/N imbalance under cup plant than maize in 2022, indicating a stronger N relative to C limitation. Our results showed that cup plant can provide high shoot and root biomass and significantly reduced nitrate leaching, indicating its potential as an alternative to maize and thus as a bioenergy crop for environmental sustainability in a changing climate.

Considering biochar's potential for carbon sequestration and healthy soils, this study evaluates the economic viability of biochar projects for private landowners in the southeastern United States. Our analysis incorporates biochar manufacturing (as a co-product) in existing paper mills, its transportation and application costs, along with federal incentives and carbon credit revenues (via carbon offset transactions with profit-sharing for landowners). Baseline economic analysis, with average parameters, found a modest net profit of approximately $242.5 per hectare (or about $12 per metric ton of biochar applied) for landowners. Economic simulations of 10000 scenarios incorporating randomized +/$��-�$20% variability in key parameters demonstrate that the highest costs arise from biochar manufacturing and transportation. At the same time, significant revenue sources include federal support and carbon market income. Sensitivity analysis reveals that net profit is most associated with manufacturing costs (correlation of −0.64), federal incentives (correlation of 0.68), carbon credit pricing (correlation of 0.32), and transportation costs (correlation of −0.1). Findings indicate that 95% of simulated scenarios yield positive profits for a hypothetical property of 1 ha, with 73.8% and 38.29% of the scenarios showing a net profit of more than $500 and $1000, respectively. On the other hand, the current average values of manufacturing costs, federal support, and carbon prices are very close to the limits when landowners do not make any profit. This emphasizes that lower manufacturing costs, more federal support, and higher carbon credit prices are essential for landowners' profitability. This study's insights into the economic dynamics of biochar can guide policymakers and other stakeholder groups, especially private landowners, in creating more resilient, profitable biochar markets.

Switchgrass (Panicum virgatum L.) is a potential source of producing bioenergy from lignocellulosic biomass. Bioenergy traits are quantitatively inherited. This study localized variation in bioenergy traits estimated via near infrared spectroscopy using quantitative trait loci (QTL) mapping. Eight hybrid populations (30 to 96 F1s) developed by crossing lowland cultivars, Alamo and Kanlow, were evaluated in two environments in Tennessee using a randomized complete block design with two replications per location in 2020 and 2021. The hybrid populations exhibited significant variation for all the studied traits (p ≤ 0.05). A linkage map including 17,251 single nucleotide polymorphisms (SNPs) generated through genotype-by-sequencing was used for the QTL mapping. The QTL analyses were performed on the traits across populations in each and across environments (years and locations) and detected a total of 74 significant QTL peaks with the logarithm of odds (LOD) scores ranging from 3.0 to 6.9. Phenotypic variability explained (PVE) by QTL varied from 2.1% to 7.4%. Ten QTL for predicted ethanol yield were identified on chromosomes 4N, 5K, 5N, 8K, 8N, and 9N, respectively, in which the major QTL resided on chromosome 5N with the highest PVE value (7.4%). Four cellulose and three hemicellulose QTL were identified on chromosomes 1K, 1N, 2N, 5K, 5N, 7K, and 8N, with PVE ranging from 2.1% to 5.8%. The chromosomal regions of 1N, 4K, 5N, and 7K had pleiotropic effects affecting multiple bioenergy traits. SNPs linked to QTL will be useful for improving bioenergy traits through marker-assisted breeding.

Short rotation coppice (SRC) willow is a second-generation lignocellulosic energy crop with a background of research and breeding programmes carried out globally for more than three decades. While commercial standards include planting in mixtures of 6–8 willow genotypes of genetic diversity, much research to date has focused on monoculture trials. Research has found significant differences in willow performance through different management methods, soil properties and environmental interactions (GxE), when applied locally. However, global analysis of these interactions remains a challenge. We present a global SRC willow dataset to facilitate researchers and growers with a resource not available to date to help in closing the gap between research and industry. Data has been collected through literature review and personal communications with key researchers on willow in the United Kingdom. Global annual average yield is 9 Mg Dry Matter (DM) ha⁻¹ year⁻¹ with 17 genotypes, including two types of mixtures, above the economic threshold of 10 Mg DM ha⁻¹ year⁻¹. Canada and the United States are the best and worst performers with 10.6 and 6.7 Mg DM hr⁻¹ year⁻¹, respectively. We expect this dataset to provide an efficient way of estimating yields at a smaller scale by multiple combinations of GxE interactions. Biomass production from 1-year-old stems in the first harvest cycle is significantly lower than for the second and third year of the first harvest cycle (ANOVA, p < 0.001). Harvest cycles of 2 and 3 years did show significant but small differences in final yield (t = 3.87, p < 0.001). A random forest statistical procedure was applied to test for the association of the predictor variables with biomass production. The model explained up to 63.65% of the variance observed in yield for all genotypes and sites, with genetic diversity among the most important variables.

Methanol, a sustainable and abundant one-carbon (C1) feedstock, has emerged as a promising raw material for green biomanufacturing, offering a pathway to carbon neutrality. Natural methylotrophic yeasts such as Pichia pastoris (syn. Komagataella phaffii) and Ogataea polymorpha are increasingly recognized as attractive hosts due to their high methanol utilization rates and established roles in industrial protein and chemical production. However, their large-scale application faces critical challenges, such as low methanol assimilation efficiency, carbon loss, and methanol toxicity. This review highlights recent progress in the engineering of natural methanol cell factories, with a focus on strategies to overcome these bottlenecks. Topics include engineering the methanol assimilation and dissimilation pathways, adaptive laboratory evolution, metabolic compartmentalization, and C1/Cn cosubstrate utilization. By addressing these challenges and exploring innovative approaches, natural methylotrophic yeasts can be further developed as efficient platforms for methanol-based biomanufacturing, thus accelerating progress toward sustainable and carbon-neutral industrial processes.

Many policies for reducing the emissions intensity of transportation fuels rely on the outputs of life-cycle assessment (LCA) models to incentivize the production of biofuels and other alternative fuels. This approach is essential to account for greenhouse gas emissions, sequestration, and avoidance throughout the supply chain and use of each fuel. Since the creation of the United States' Renewable Fuel Standard and California's Low Carbon Fuel Standard, there has been broader adoption of LCA-based regulations and incentives, accompanied by an evolution in modeling approaches. There is general agreement that regulatory impact assessment and policy design/implementation are distinct, where the latter benefits from transparent models that capture clear cause-and-effect relationships between measures taken to reduce emissions and a fuel's carbon intensity score. However, there is not yet convergence on a range of methodological choices that impact LCA outputs relevant for fuels and a host of other emerging applications, such as private carbon markets. Numerous recent studies have explored existing LCA methods and developed new approaches for applications where consensus has not yet been reached, such as soil organic carbon accounting, forest biomass carbon accounting, crediting of avoided emissions, and defining wastes. Simultaneously, new and revised LCA-based biofuel policies have leveraged these approaches, and in some cases, used fit-for-purpose solutions. This article reviews the state of policy-relevant biofuel LCA methods and tools, compares and contrasts established and emerging approaches within current policies at the state, federal, and international levels, and identifies key challenges that require further research and coordination to establish best practices. These issues have implications beyond biofuel policies, extending to power generation and carbon dioxide removal crediting.

Biogas, a renewable energy source produced from the anaerobic digestion of biomass and/or organic residues, contains a mixture of methane (CH₄) and carbon dioxide (CO₂). To be used as a fuel, biogas must be upgraded to increase its CH₄ content to over 90%. Traditional upgrading methods, such as amine scrubbing and membrane separation, are energy-intensive, costly, and environmentally burdensome. This study explores the potential of electrochemical technologies as sustainable alternatives for biogas upgrading from the aspects of energy, environment, economics, and engineering. Recent advances in promising electrochemical approaches including pretreatment, microbial conversion enhancement, CO₂ capture, CO₂ reduction reactions, and methanation are first reviewed. The performance of these approaches is then systematically compared based on operational characteristics and efficiency metrics. Our findings indicate that microbial and bioelectrochemical systems can achieve CH₄ purities over 92%. Also, electrochemical technologies offer > 99.9% hydrogen sulfide removal (desulfurization). State-of-the-art electrochemical CO₂ reduction technologies demonstrate Faradaic efficiencies generally 50%–80%, with the selectivity of CH₄ up to 99.7%. From the environmental aspect, integrating renewable electricity into microbial, electrochemical (or -based), and bioelectrochemical upgrading systems yields roughly 10%–74% life-cycle GHG reductions relative to conventional fossil-energy pathways, with certain renewable power-to-methane configurations achieving net-negative emissions. Lastly, this study identifies several priority research directions, such as (1) advanced catalyst and electrode development, (2) system integrations with air pollutant control facilities, (3) life-cycle environmental and techno-economic assessment, and (4) digestate valorization for multiple product ecosystems. Electrochemical approaches offer a promising path toward clean, efficient, and decentralized biogas utilization, contributing to global decarbonization and energy transition goals toward a circular bioeconomy.