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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2022

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing will provide relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The feedstocks will be prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks and current status for this two-year research project are: Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill and shipped to Sotacarbo’s test facility in Italy. Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. Gasifier Testing: Tests are currently being performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also include work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results to be reported. The results will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. This paper will be summarize the pelletizing procedure that insures the viability of the tri-fuel pellets for the gasification runs that are being performed at Sotacarbo’s 30mm up draft moving bed gasifier. Initial gasification tests have been conducted, and all the lab scale tri-fuel pellet gasification runs will be completed by the fall of 2022. Performance data will enable modeling of a full-scale HMI industrial scale gasifier supporting both CHP and Hydrogen production.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends with Washed and Unwashed Legacy Coals and Other Waste Fuels to Generate White Hydrogen

The objective of this effort, primarily funded by the United States Department of Energy (DOE), and led by the Electric Power Research Institute, Inc. (EPRI), with support by Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), has been to qualify coal, biomass, and plastic waste blends based on performance testing of selected fuel pellet compositions in a pilot-scale updraft moving-bed (UDMB) gasifier. The testing provided relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are the focus. The gasifier used for testing is HMI’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips (biomass). However, mixtures of these fuels with plastic wastes have not been prepared and gasified together. The three feedstocks were densified and pelletized by California Pellet Mill (CPM) to meet the feedstock size required by Sotacarbo’s 30mm ID UDMB gasifier, under contract to HMI. The technical tasks and results from this two-year research project included: (1) Feed Procurement and Preparation: Nine different tri-fuel pellets were prepared from varying compositions of fresh mined PRB coal, corn stover biomass, and car fluff waste plastics. Tri-fuel pellets were produced by CPM and shipped to Sotacarbo’s test facility in Carbonia, Sardinia, Italy. (2) Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different UDMB gasification tests to be performed in Sotacarbo’s 12-inch ID pilot scale gasifier, the process monitoring instrumentation used, and the extractive samples recovered for analysis of the total gasification process mass and energy balance. (3) Gasifier Testing: Nine different gasification runs were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstock compositions generated from varying mixtures of PRB coal, biomass, and plastic wastes. The testing generated performance data on gasification reaction efficiency and performance, yielding relevant data for models used to scale up the gasifier design. This task also included work to refurbish and reassemble the pilot gasifier at Sotacarbo and perform a baseline 100% PRB coal run. (4) Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results are reported in the project’s final report, published in March 2024. The results show that all tri-fuel pellets gasified well and maintained structural integrity throughout the gasification process. The syngas generated can be shifted to hydrogen by using commercial syngas shifting technologies. (5) High Fidelity computational fluid dynamics (CFD) Simulation: The National Energy Technology Laboratory (NETL) team performed CFD simulations of the UDMB gasifier for two of the tri-fuel pellets gasified in Sotacarbo’s pilot scale gasifier. The kinetic mechanisms for the pyrolysis of each constituent, PRB coal, corn stover biomass, and waste plastics are based on thermogravimetric analysis performed by Sotacarbo. The gasification model was validated by comparing the predicted syngas composition at the exit of the gasifier with the measured syngas composition. In addition, the reactor’s measured internal temperature profile agreed well with the predicted internal reactor temperature profile. These results validate that the model can be used to predict the performance of the updraft moving bed gasifier for different feedstocks and operating conditions. This paper summarizes the results of the completed work in which the pelletizing procedure was validated to ensure the viability of the tri-fuel pellets for the gasification runs performed at Sotacarbo’s 30 mm UDMB gasifier. The gasification performance data from this series of nine runs will enable modeling of a full-scale HMI industrial scale gasifier supporting both combined heat and power, and Hydrogen production from coal (both fresh mined and legacy) combined with various biomass and waste plastics. Additionally, plans and progress on a follow-up project, being executed by the same project team, will be presented. In this project, a total of twenty (20) different feedstocks are being prepared from varying compositions of biomass (both woody biomass and corn stover) with a mixture of legacy coal waste, plastic waste, and refuse-derived fuel (RDF). The testing will provide information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design to 50 megawatt electric (MWe) (equivalent hydrogen production). Tests will also be performed on a bench-scale fluidized-bed gasifier for comparison purposes. The results of this testing will be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends.

08 HYDROGEN↗
DOE OSTI2026

Tar Formation and Mitigation in Pressurized Biomass and Cofired Gasification

Biomass gasification with CO2 capture has the potential to provide carbon-negative heat, power, and feedstock for sustainable hydrocarbon fuels. In a pressurized gasifier, precombustion solvent systems can capture CO2 with less energy than needed for amine-based postcombustion CO2 capture, and pressurized syngas is generally more suitable for fuel synthesis. Although precombustion capture has been used for many decades in large-scale fossil-based plants, it has not been well-demonstrated in smaller-scale biomass gasification. Precombustion solvents and product streams could be particularly impacted by tar and other organic compounds that tend to form in high concentrations during low-temperature biomass gasification. A pressurized pilot-scale gasifier was used to examine tar formation and fate when using CO2 capture with various blends of biomass and coal. The syngas was fully conditioned to remove particulate matter; capture sulfur; adjust syngas chemistry using water-gas shift; quench out moisture and condensable organics; and capture CO2. Tar concentrations were measured in the raw syngas, the product gas, and in the liquid streams over the course of several weeks. The gasifier was operated both as a high-pressure oxygen-blown system to mimic large-scale centralized gasification and at lower pressures under air-blown conditions to mimic a more likely small-scale system. A second high-temperature stage with oxidant injection was used to crack tars. The overall results showed how gasifier and CO2 capture performance change as fuel is blended between coal to biomass and what the fate of tar is through a precombustion CO2 capture system.

Strege, Josh [University of North Dakota EERC] (OR↗
DOE OSTI2026

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗
DOE OSTI2021

Reburning of Animal Waste Based Biomass with Coals for NO x Reduction, Part II: Dairy Biomass (DB) and Coal–DB Blends

Concentrated animal feeding operations (both slaughter and dairy cattle) lead to land, water, and air pollution if waste storage and handling systems are not effectively managed. At the same time, cattle biomass (CB), which includes both slaughter/feedlot biomass (FB) and dairy biomass (DB), have the potential to be a source of green energy at coal-fired power plants. Part I presented results on NOx reductions with pure FB or Coal: FB blends as reburn fuels. Part II deals with results from reburning with pure DB or Coal: DB blends as reburn fuels. A mixture of NG with a small amount of NH3 was used to generate the baseline NOx of 400–420 ppm (or 185–194 g/GJ). NOx emissions were found to be reduced by as much as 96% when reburning with FB. The effects of reburn fuel type, equivalence ratio (ER RBZ ) in the reburn zone, vitiated air, several injection configurations of reburn fuel and initial NO concentrations on NOx emissions were investigated. The ER RBZ shows a significant effect on the NOx reduction. The 20% heat input by reburning was the better operating condition for the long-term operation due to its ash production. The results reveal that reburn with DB fuels is an effective technology for NOx emission control when the initial NOx emission is higher than 275 ppm (or 127 g/GJ or 0.3 lb/MMBtu).

09 BIOMASS FUELS↗
DOE OSTI2022

Assessing the efficiency implications of renewable fuel policy design in the United States

Abstract Obligated parties have chosen to comply with the Renewable Fuel Standard (RFS) by increasing the blending of biomass‐based biodiesel beyond originally targeted levels rather than increasing blending/consumption of ethanol to targeted levels that would have required pricing higher blends of ethanol (E85) at or below an energy‐equivalent level to E10. This paper develops a welfare‐economic framework to analyze the extent to which the nested design and the accompanying cellulosic waiver credit and biodiesel tax credit contributed to a compliance strategy by blenders that favored blending of biodiesel instead of inducing consumption of E85, and its implications for social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Characterization of Biomass-Based Fuels and Fuel Blends for Low-Emissions, Advanced Compression Ignition Engines (Final Report)

The goal of the Co-Optima program was to accelerate deployment of co-optimized fuels and engines that will reduce fuel consumption, and criterion pollutants and greenhouse gas (GHG) emissions for both spark and compression-ignited engines. In this project, combustion measurements from a constant pressure flow rig (CPFR) with optical access were used to assess fundamental combustion behavior of number of different candidate fuels and fuel blends. This chamber and its peripheral systems allowed stable control of ambient air pressure and temperature and fuel injection pressure and timing for hundreds of repeat injections allowing statistical interpretation of the results. The optical diagnostics enabled capturing of liquid length, vapor length, ignition timing, lift-off length as well as localized (temporal and spatially resolved) mixture refractive index, flame structure, and soot mass. The operating conditions allowed the study of combustion conditions promoting lean lifted flame combustion (LLFC), a mixing-controlled low-temperature combustion (LTC) strategy to reduce soot production in Advanced Compression Ignition (ACI) engines.

09 BIOMASS FUELS↗
DOE OSTI2024

Blue Hydrogen – Not A Bad Idea

In this article, we will look at a technology that can generate hydrogen and power from gasification of a blend of biomass and coal with a “net negative” CO 2 footprint. Let us, however, first take a look at an earlier attempt to gasify coal and generate electric power with pre-combustion CO 2 capture. While the attempt was not exactly a stellar success, at least based on what can be gleaned from superficial press articles, the reality is quite different. This is why it deserves a closer look because its demise was a significant factor (by no means the only one, though) in putting an end to the efforts to maintain coal as a viable option for electricity generation (see the 2007 GTW article on that subject.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Nth-plant scenario for forest resources and short rotation woody crops: Biorefineries and depots in the contiguous US

Estimating the US potential of woody material is of vital importance to ensure cost-effective supply logistics and develop a sustainable bioenergy and bioproducts industry. We analyzed a mature conversion technology for woody resources for the contiguous US that takes advantage of economies of scale: the nth-plant. Here, we developed a database to quantify the total accessible woody biomass within a distributed network of preprocessing depots and biorefineries considering both quality specifications for conversion and a target cost to compete with fossil fuels. We considered two categories of woody biomass: 1) forest residues from trees, tops and limbs produced from conventional thinning and timber harvesting operations as well as non-timber tree removal; and 2) short rotation woody crops such as poplar, willow, pine, and eucalyptus. A mixed integer linear programming model was developed to analyze scenarios with woody feedstock blends at variable biomass ash contents and cost targets at the biorefinery. When considering a target cost of 85.51 dollars/dry ton (2016$) at the biorefinery, the maximum accessible biomass from forest residues in 2040 remained constant at 106 million dry tons regardless of ash targets. Including short rotation woody crops as part of the blend increased the total accessible biomass to 153 and 195 million dry tons at ash targets of 1% and 1.75%, respectively. We concluded from our analysis that woody resources could address about 55% of EPA’s (Environmental Protection Agency) target of 16 billion gallons of cellulosic biofuel.

09 BIOMASS FUELS↗
DOE OSTI2025

Distillable amine-based solvents for effective pretreatment of multiple biomass feedstocks

Exploring the potential of advanced distillable solvents as efficient biomass pretreatment agents is critical for biorefineries, enhancing fermentable sugar yields while enabling solvent recovery and recycling without suffering significant losses. Here, we employ distillable amine-based solvents for pretreating a wide range of lignocellulosic feedstocks, aiming to facilitate the industrial release of fermentable sugars from diverse feedstocks through enzymatic hydrolysis. Twenty-two diverse feedstocks, sourced from different geographical regions and representing various biomass categories, were surveyed for chemical (mainly carbohydrates and lignin) and lignin (S, G, and H units) profiles. Several solvents, including ethanolamine, ethanolammonium acetate, butylamine, butylammonium acetate, and triethylamine, were tested for the pretreatment of eight selected biomasses. Among these solvents, butylamine emerged as the most effective due to its favorable sugar release, excellent solvent removal rate, and low boiling point, facilitating solvent recovery and recycling. Extending butylamine pretreatment to all 22 feedstocks demonstrated desirable sugar yields and highly efficient solvent removal in the majority of the biomass sources tested. Agricultural residues and their mixtures showed particularly favorable sugar release. Despite minimal changes in cellulose crystallinity, XRD characterization of sorghum, poplar, and pine before and after butylamine pretreatment showed a decrease in intensity and a slight shift of certain peaks, indicating alterations in cellulose structure. Fourier-transform infrared spectroscopy and thermogravimetric analysis analyses suggested disruption of biomass linkages in hemicellulose and lignin, enhancing enzymatic digestibility. Scale-up experiments of the mixed agricultural feedstocks in a 1 L Parr reactor achieved over 90% glucose liberation and more than 99% butylamine removal, highlighting the scalability of the method. The resulting hydrolysates supported the growth of diverse bacterial and fungal strains, indicating downstream compatibility with commercial fermentation processes. This study presents butylamine as an effective, recoverable pretreatment solvent for a wide range of lignocellulosic feedstocks, offering a promising solution to key biorefinery challenges. The demonstrated scalability and compatibility with various biomass types and blends underscore its potential for industrial application, advancing sustainable biofuel and biochemical production.

biomass composition↗
DOE OSTI2025

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Indirect Liquefaction, Ex Situ Catalytic Fast Pyrolysis, Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2019 State-of-Technology Cases

This technical report describes the supply chain sustainability analysis (SCSAs) for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies: (1) renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of woody lignocellulosic biomass (note that the IDL pathway in this SCSA represents the syngas conversion design in the 2019 SOT); (2) renewable gasoline (RG) and diesel (RD) blendstocks via ex situ catalytic fast pyrolysis of woody lignocellulosic biomass; (3) RD via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (4) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (5) renewable diesel via HTL of a blend of algae and woody biomass; and (6) renewable diesel via combined algae processing (CAP). This technical report focuses on the environmental performance of these six biofuel production pathways in their 2019 SOT cases. The results of these renewable hydrocarbon fuel pathways in these SCSA analyses update those for the respective 2018 SOT cases. They also provide an opportunity to examine the impact of technology improvements in both biomass feedstock production and biofuel production that have been achieved in 2019 SOTs on the sustainability performance of these renewable transportation fuels, and they reflect updates to Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model, which was released in October 2019. These GREET updates include the production of natural gas, electricity, and petroleum-based fuels that can influence biofuels’ supply chain greenhouse gas (GHG) (CO₂, CH₄, and N₂O) emissions, water consumption, and air pollutant emissions. GHG emissions, water consumption, and nitrogen oxides (NO x ) emissions are the main sustainability metrics assessed in this analysis. In this analysis, we define water consumption as the amount of water withdrawn from a freshwater source that is not returned (or returnable) to a freshwater source at the same level of quality. Life-cycle fossil energy consumption and net energy balance, which is the life-cycle fossil energy consumption deducted from the renewable biofuel energy produced, are also assessed.

09 BIOMASS FUELS↗
DOE OSTI2021

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Indirect Liquefaction, Ex Situ Catalytic Fast Pyrolysis, Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2020 State-of-Technology Cases

This technical report describes the SCSAs for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies in the 2020 SOTs: (1) renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of woody lignocellulosic biomass (note that the IDL pathway in this SCSA represents the syngas conversion design); (2) renewable gasoline (RG) and diesel (RD) blendstocks via ex situ catalytic fast pyrolysis of woody lignocellulosic biomass; (3) RD via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (4) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (5) renewable diesel via HTL of a blend of algae and woody biomass; and (6) renewable diesel via combined algae processing (CAP). This technical report focuses on the environmental performance of these six biofuel production pathways in their 2020 SOT cases. The results of these renewable hydrocarbon fuel pathways in these SCSA analyses update those for the respective 2019 SOT cases. They also provide an opportunity to examine the impact of technology improvements in both biomass feedstock production and biofuel production that have been achieved in 2020 SOTs on the sustainability performance of these renewable transportation fuels. The SCSA results also reflect updates to Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET ® ) model, which was released in October 2020. These GREET updates include the production of natural gas, electricity, and petroleum-based fuels that can influence biofuels’ supply chain greenhouse gas (GHG) (CO 2 , CH 4 , and N 2 O) emissions, water consumption, and air pollutant emissions. GHG emissions, water consumption, and nitrogen oxides (NO x ) emissions are the main sustainability metrics assessed in this analysis. In this analysis, we define water consumption as the amount of water withdrawn from a freshwater source that is not returned (or returnable) to a freshwater source at the same level of quality. Life-cycle fossil energy consumption and net energy balance, which is the life-cycle fossil energy consumption deducted from the renewable biofuel energy produced, are also assessed.

09 BIOMASS FUELS↗