To investigate large-scale patterns of above-ground and below-ground biomass partitioning in grassland ecosystems and to test the isometric theory at the community level. Northern China, in diverse ...grassland types spanning temperate grasslands in arid and semi-arid regions to alpine grasslands on the Tibetan Plateau. We investigated above-ground and below-ground biomass in China's grasslands by conducting five consecutive sampling campaigns across the northern part of the country during 2001-05. We then documented the root : shoot ratio (R/S) and its relationship with climatic factors for China's grasslands. We further explored relationships between above-ground and below-ground biomass across different grassland types. Our results indicated that the overall R/S of China's grasslands was larger than the global average (6.3 vs. 3.7). The R/S for China's grasslands did not show any significant trend with either mean annual temperature or mean annual precipitation. Above-ground biomass was nearly proportional to below-ground biomass with a scaling exponent (the slope of log-log linear relationship between above-ground and below-ground biomass) of 1.02 across various grassland types. The slope did not differ significantly between temperate and alpine grasslands or between steppe and meadow. Our findings support the isometric theory of above-ground and below-ground biomass partitioning, and suggest that above-ground biomass scales isometrically with below-ground biomass at the community level.
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.
•Torrefied biomass was found to have much lower chlorine content than raw biomass.•Torrefaction was found to preferentially reduce the chlorine content of low alkali biomass.•Most of the biomass ...chlorine was released as HCl during torrefaction.•HCl emissions from burning torrefied biomass were significantly lower than those from raw biomass.•HCl emissions from burning low-alkali torrefied biomass were drastically lower than those from raw biomass.
Elevated emissions of hydrogen chloride (HCl) from combustion of biomass in utility boilers is a major issue as it can cause corrosion and, in combination with the high alkali content often encountered in these fuels, it can also deposit molten alkali chloride salts on the boiler’s water tubes. Such deposition can impede heat transfer and cause further corrosion. This work torrefied and then burned herbaceous biomass (corn straw) as well as crop-derived biomass (olive residue and corn-based Distillers Dried Grains with Solubles, DDGS), all pulverized in the size range of 75–150µm. It monitored the HCl emissions from torrefaction of biomass and, subsequently, the comparative HCl emissions from combustion of both raw and torrefied biomass. Results showed that during torrefaction most of the chlorine of biomass was released in the gas phase, predominately as HCl. Consequentially, combustion of torrefied biomass, which contained less chlorine than raw biomass, generated significantly lower HCl emissions than raw biomass, particularly so for biomass of low alkali content. This observation complements previous findings in this laboratory that torrefied biomass also generated lower SO2 emissions than raw biomass, albeit by a smaller factor. Both of these findings enhance the appeal of torrefied biomass as a substitute fuel in utility boilers.
•We examine bioethanol production potential of Malaysia’s most agricultural wastes.•Malaysia’s oil palm biomass potentially yields bioethanol more than 9 million tonnes.•Malaysia’s paddy biomass ...provides potential of averagely 600kt bioethanol annually.•Pineapple biomass potentially yields 40kt bioethanol, banana biomass 115kt yearly.•Durian seed potentially yields bioethanol 13 million litres, and 35kt from durian rind.
Rising global temperature, worsening air quality and drastic declining of fossil fuel reserve are the inevitable phenomena from the disorganized energy management. Bioethanol is believed to clear out the effects as being an energy-derivable product sourced from renewable organic sources. Second generation bioethanol interests many researches from its unique source of inedible biomass, and this paper presents the potential of several selected biomasses from Malaysia case. As one of countries with rich biodiversity, Malaysia holds enormous potential in second generation bioethanol production from its various agricultural and forestry biomasses, which are the source of lignocellulosic and starch compounds. This paper reviews potentials of biomasses and potential ethanol yield from oil palm, paddy (rice), pineapple, banana and durian, as the common agricultural waste in the country but uncommon to be served as bioethanol feedstock, by calculating the theoretical conversion of cellulose, hemicellulose and starch components of the biomasses into bioethanol. Moreover, the potential of the biomasses as feedstock are discussed based on several reported works.
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.
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.
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.
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