Advancements in efficient energy sources have played a pivotal role in determining the present world energy structure. Renewable biomass energy has been incorporated in industrial regulations and ...policies in many European countries. Based on the statistics, more than one-seventh of the total world energy consumption is generated from biomass.The renewable energies movement was prompted by two important factors: a) growing world energy consumption and b) the abundance of generated biomass residues, especially in agriculture. In the case of the first, batteries containing different metals are considered, as is the production of items for human consumption (food, clothing, home comfort, etc.). In the second case, the biomass waste from plants and animals, as byproducts of cultivating and production processes, is the main source of generated waste.
This study presents the thermo-kinetics and thermodynamic analyses of date palm surface fibers (DPSFs) using thermogravimetric analysis. DPSFs were heated non-isothermally from 20 to 800 OC at a ramp ...rate of 10 OC/min in nitrogen atmosphere. Thermogravimetric analysis indicated that there have been two stages for pyrolysis of DPSFs. Kinetic and thermodynamic parameters have been calculated for the second stage which is further subdivided into two mass-loss regions. The low-temperature stable components were decomposed in a temperature range of 270–390 OC and high-temperature stable components were degraded in a temperature range of 390–600 OC. The Coats–Redfern integral method was employed with 21 different kinetic models from four major solid-state reaction mechanisms. Among all models, the two diffusion models: Ginstling–Brounshtein and Ginstling diffusion were the best fitted models with highest regression coefficient values (R2 > 0.99) in both mass-loss regions. For mass-loss regions: I (270–390 OC) and II (390–600 OC), the activation energy values were found to be 96–98 and 113–114 kJ/mol, respectively. Thermodynamic parameters (ΔH, ΔG, ΔS) were calculated using kinetic data. The findings reported herein are helpful in characterizing date palm fibers as a source of energy, designing reactors, producing chemicals, and understanding the properties of surface fibers for making composites.
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•Kinetic and thermodynamic analysis of date palm surface fibers using Coats Redfern method.•Kinetic mechanisms from chemical reactions and diffusion, geometric, and nucleation models.•Two-stage mechanism has been observed in pyrolysis of date palm surface fibers.•Coats-Redfern method showed that palm fibers pyrolysis follows diffusion mechanism.•Ginstling–Brounshtein equation and Ginstling equation (4-D diffusion) are best fitted models.
The present study reviews the status of research on biomass supply chain modeling. Biomass has become increasingly important as a renewable alternative energy source. One of the most critical aspects ...associated with the use of biomass is its supply chain and all the elements that are part of it. Indeed, in order for the use of this type of energy resource to become viable, its supply chain, from collection and transport to storage and distribution, needs to be well structured and optimized. Modeling is a critical step in developing understanding that leads to improved supply chain efficiency. Thus far, investigations that utilize supply chain models have focused on assessing specific supply chain scenarios, usually with an objective of minimizing cost. Significant opportunity exists to improve and expand the modeling process to allow for efficient supply chain design and operation. During this article will be analyzed several models presented by recent research that approach different situations and scenarios. At the end it is shown that biomass for energy supply chain models must include the analysis of several different variables and include the main disadvantages of its use as well.
•The status of research on biomass supply chain modeling is reviewed.•The importance of biomass as a renewable alternative energy source is presented.•The most critical aspects associated with the use of biomass and its supply chain are analyzed.•Several models presented by recent research that approach different situations and scenarios are discussed.•Biomass for energy supply chain models include several different variables and disadvantages that shown in the end.
Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of ...vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.
Food versus fuel Rosillo-Calle, Frank; Johnson, Francis
2010., 2010, 2013-04-04, 2010-09-23, 20100101
eBook, Book
Presents an introduction to the science and economics behind a well-worn debate, that debunks myths and provides quality facts and figures for academics and practitioners in development studies, ...environment studies, and agricultural studies.
Estimates of the magnitude and distribution of aboveground carbon in Earth's forests remain uncertain, yet knowledge of forest carbon content at a global scale is critical for forest management in ...support of climate mitigation. In light of this knowledge gap, several upcoming spaceborne missions aim to map forest aboveground biomass, and many new biomass products are expected from these datasets. As these new missions host different technologies, each with relative strengths and weaknesses for biomass retrieval, as well as different spatial resolutions, consistently comparing or combining biomass estimates from these new datasets will be challenging. This paper presents a demonstration of an inter-comparison of biomass estimates from simulations of three NASA missions (GEDI, ICESat-2 and NISAR) over Sonoma county in California, USA. We use a high resolution, locally calibrated airborne lidar map as our reference dataset, and emphasize the importance of considering uncertainties in both reference maps and spaceborne estimates when conducting biomass product validation. GEDI and ICESat-2 were simulated from airborne lidar point clouds, while UAVSAR's L-band backscatter was used as a proxy for NISAR. To estimate biomass for the lidar missions we used GEDI's footprint-level biomass algorithms, and also adapted these for application to ICESat-2. For UAVSAR, we developed a locally trained biomass model, calibrated against the ALS reference map. Each mission simulation was evaluated in comparison to the local reference map at its native product resolution (25 m, 100 m transect, and 1 ha) yielding RMSEs of 57%, 75%, and 89% for GEDI, NISAR, and ICESat-2 respectively. RMSE values increased for GEDI's power beam during simulated daytime conditions (64%), coverage beam during nighttime conditions (72%), and coverage beam daytime conditions (87%). We also test the application of GEDI's biomass modeling framework for estimation of biomass from ICESat-2, and find that ICESat-2 yields reasonable biomass estimates, particularly in relatively short, open canopies. Results suggest that while all three missions will produce datasets useful for biomass mapping, tall, dense canopies such as those found in Sonoma County present the greatest challenges for all three missions, while steep slopes also prove challenging for single-date SAR-based biomass retrievals. Our methods provide guidance for the inter-comparison and validation of spaceborne biomass estimates through the use of airborne lidar reference maps, and could be repeated with on-orbit estimates in any area with high quality field plot and ALS data. These methods allow for regional interpretations and filtering of multi-mission biomass estimates toward improved wall-to-wall biomass maps through data fusion.
•GEDI, ICESat-2 and NISAR will collect useful data for estimating forest biomass.•All three missions have increased errors with canopy cover and slope.•Airborne Lidar biomass maps allow consistent multi-mission accuracy assessment.•These missions will produce naturally synergistic datasets.•GEDI models can be applied to ICESat-2 data.
In recent years, the production of pellets derived from forestry biomass to replace coal for electricity generation has been increasing, with over 10 million tonnes traded internationally—primarily ...between United States and Europe but with an increasing trend to Asia. Critical to this trade is the classification of woody biomass as ‘renewable energy’ and thus eligible for public subsidies. However, much scientific study on the net effect of this trend suggests that it is having the opposite effect to that expected of renewable energy, by increasing atmospheric levels of carbon dioxide for substantial periods of time. This review, based on recent work by Europe's Academies of Science, finds that current policies are failing to recognize that removing forest carbon stocks for bioenergy leads to an initial increase in emissions. Moreover, the periods during which atmospheric CO2 levels are raised before forest regrowth can reabsorb the excess emissions are incompatible with the urgency of reducing emissions to comply with the objectives enshrined in the Paris Agreement. We consider how current policy might be reformed to reduce negative impacts on climate and argue for a more realistic science‐based assessment of the potential of forest bioenergy in substituting for fossil fuels. The length of time atmospheric concentrations of CO2 increase is highly dependent on the feedstocks and we argue for regulations to explicitly require these to be sources with short payback periods. Furthermore, we describe the current United Nations Framework Convention on Climate Change accounting rules which allow imported biomass to be treated as zero emissions at the point of combustion and urge their revision to remove the risk of these providing incentives to import biomass with negative climate impacts. Reforms such as these would allow the industry to evolve to methods and scales which are more compatible with the basic purpose for which it was designed.
Trade in wood pellets from forestry biomass to replace coal for electricity generation is increasing dramatically. Critical to this trade is the classification of woody biomass as ‘renewable energy’ and thus eligible for public subsidies. However, scientific studies show that it is having the opposite effect and is increasing atmospheric levels of carbon dioxide for substantial periods of time. We argue that EU regulations and the current United Nations Framework Convention on Climate Change accounting, which both allow imported biomass to be treated as zero emissions at the point of combustion, should be revised to remove incentives to import biomass with negative climate impacts.
Lignocellulosic biomass (LCB) is globally available and sustainable feedstock containing sugar-rich platform that can be converted to biofuels and specialty products through appropriate processing. ...This review focuses on the efforts required for the development of sustainable and economically viable lignocellulosic biorefinery to produce carbon neutral biofuels along with the specialty chemicals. Sustainable biomass processing is a global challenge that requires the fulfillment of fundamental demands concerning economic efficiency, environmental compatibility, and social responsibility. The key technical challenges in continuous biomass supply and the biological routes for its saccharification with high yields of sugar sources have not been addressed in research programs dealing with biomass processing. Though many R&D endeavors have directed towards biomass valorization over several decades, the integrated production of biofuels and chemicals still needs optimization from both technical and economical perspectives. None of the current pretreatment methods has advantages over others since their outcomes depend on the type of feedstock, downstream process configuration, and many other factors. Consolidated bio-processing (CBP) involves the use of single or consortium of microbes to deconstruct biomass without pretreatment. The use of new genetic engineering tools for natively cellulolytic microbes would make the CBP process low cost and ecologically friendly. Issues arising with chemical characteristics and rigidity of the biomass structure can be a setback for its viability for biofuel conversion. Integration of functional genomics and system biology with synthetic biology and metabolic engineering undoubtedly led to generation of efficient microbial systems, albeit with limited commercial potential. These efficient microbial systems with new metabolic routes can be exploited for production of commodity chemicals from all the three components of biomass. This paper provides an overview of the challenges that are faced by the processes converting LCB to commodity chemicals with special reference to biofuels.
NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass ...density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.
•NASA’s GEDI collects spaceborne lidar data used for mapping aboveground biomass.•A global database of field and airborne lidar was compiled.•Models stratified by Plant Functional Type and geographic region outperform a global model.•GEDI04_A models are OLS models predicting biomass as a function of RH metrics.•Maximum forest height is an important predictor of biomass across geographic domains.
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