Fluidised Bed Combustion of Two Species of Energy Crops

Much bio-energy can be obtained from wood pruning operations in forests and fruit orchards. Several spatial studies have been carried out for biomass surveys, and many linear programming models have been developed to model the logistics of bio-energy chains. These models can assist in determining the best alternatives for bio-energy chains. Most of these models use network structures built up from nodes with one or more depots, with arcs connecting the depots. Each depot is a source of a certain biomass type. Nodes can also be biomass storage points or production facilities (e.g., power plants) where biomass is used. The arcs in the networks represent transport between depots. In order to combine GIS spatial studies with linear programming models, it is necessary to build a network from a digital map of biomass production centers, such as orchards. Biomass collection points should therefore be defined as sources in the delivery network model. In this work, a mathematical calculation method is developed to select the actual biomass collection points on a map. The database for this model is composed of area surveys of forest and agricultural biomass storage points given in GIS maps (shape files). The limits of the area studied and different types of biomass are defined and located in different layers of the GIS maps. These energy-biomass production maps are overlaid with a 1 km × 1 km grid of the area studied. The result is a grid in which the different types of total available biomass in each quadrant are known. Harvesting and collection costs are also defined. The connections between all n × m quadrants of the area studied are defined by the available road network. Every quadrant is associated with a point on the road network. The selection criteria for sources of biomass (sub-areas) are the following: firstly, a minimum production of available biomass type is required; and secondly, harvesting and collection costs should be minimal. The algorithm provides the location of points where biomass from the associated area can be concentrated. These biomass collection points are then taken as source nodes in the network during the implementation of the logistics models. In the next step, the network is analyzed by linear programming techniques to supply the optimal position of energy plants or factories, given the available biomass sources.

Thermo-chemical conversion of biomass for sustainable aviation fuel/fuel additives

A review on thermo-chemical characteristics of coal/biomass co-firing in industrial furnace

In this paper a comparison between three different types of techniques to predict the bed agglomeration tendency of a FBC (fluidized-bed combustor) was performed. The three techniques were the standard ASTM ash fusion test, a compression strength based sintering test and a lab-scale combustion test. The tests were performed on 10 different types of biomasses. The results showed significant differences in the predicted bed agglomeration temperatures depending on which technique was used. The ASTM standard ash fusion test generally showed 50−500 °C higher temperatures than the sintering tests or the lab-scale FBC combustion tests. The sintering test showed, in five cases, 20−40 °C lower sintering temperatures than what was detected as the bed agglomeration temperature with the lab-scale FBC. In two cases, a significantly lower sintering temperature than the bed agglomeration temperature was detected, and in three cases, a significantly higher sintering temperature was detected than the bed agglomeration tem...

Development of a System for Electric Energy Production Based on Fuel Cells Fueled by Biogas Produced with Anaerobic Digestion of Biomass

Life cycle assessment with the transition from lignocellulose- to microalgae-based biofuels: A review

Measuring the impact of global tropospheric ozone, carbon dioxide and sulfur dioxide concentrations on biodiversity loss

The European Union recognizes the priority of new bio-based industrial pathways, such as bio-based succinic acid (bio-SA). This study has investigated, through a life cycle method, the cradle-to-factory gate greenhouse gas (GHG) emissions and non-renewable energy use (NREU) of bio-SA from lignocellulosic giant reed (GR) feedstock grown on marginal lands in Southern Italy (GR bio-SA). The aims were to: (1) evaluate the environmental performance of the GR bio-SA and (2) discuss the GR bio-SA profile with respect to its fossil counterparts and alternative bio-SA routes. For 1 kg of GR bio-SA, the gross GHG emissions amounted to 3.9 kg CO2 eq, while through the inclusion of the biogenic C potentially stored in SA molecule (1.47 kg CO2 eq) and soil organic matter (0.44 kg CO2 eq), the final net global warming potential would be nearly halved. Similarly to current starch-based SA supply chains, the GR bio-SA showed: (1) better gross GHG profile compared to the fossil adipic acid (GHG emissions reduced by 55%) and (2) comparable net GHG emissions in comparison with petrochemicals SA and maleic acid. The total NREU for 1 kg of GR bio-SA amounted to 26.6 MJ, with reduced energy consumption by about 55–79% relative to fossil counterparts, thanks to the on-site energetic valorization of lignin and holocellulose residues with relatively high heating values. The soy protein concentrate and the inorganic chemicals used in the co-fermentation showed up the prevailing contributions to the GHG and NREU profiles of the GR bio-SA, suggesting the need to optimize nitrogen and carbon sources of the growth medium.

Coconut shell charcoal has been widely produced as a raw material for biobriquette production. This cause effect on an increase of coconut shell price as a raw material for charcoal production. Wood waste is one of the easier and cheaper biomass to be obtained than coconut shell. However, the quality of charcoal produced from wood waste need to be compared to be used as a substitute of coconut shell. This study aims to discover the effect of pyrolysis as a carbonisation process on coconut shell, wood waste, and a mixture of both biomass on the quality of charcoal produced including yield, proximate analysis, lignocellulose analysis, and calorific value. A completely randomized design was used in this study by taking into account two influencing factors, including the type of sample (biomass sample and charcoal sample) and the type of biomass (coconut shell, wood waste, and a mixture of both). Pyrolysis was carried out at 550℃ for 120 minutes. Pyrolysis of biomass and different types of biomass have giving effects on the characteristics of the biomass and charcoal produced. The results of the analysis showed that the type of coconut shell biomass and a mixture of the two biomasses produced charcoal that qualified on standards. The results of the analysis concluded that charcoal made from a mixture of coconut shell and wood waste could be a solution to substitute charcoal made from coconut shell only.

In recent decades there has been a considerable global increase in urban population, industrial productivity, energy demand, waste generation, and the emission of greenhouse gases from energy conversion. The agricultural, forestry, textile and food sectors generate large amounts of waste and their environmental impact has become a major cause for concern in societies around the world. Current efforts are concerned with maximization of combustion efficiency and energy-related processes in general by making use of industrial residues and reducing particulate matter. The present review addresses the availability of different types of biomass that can be used to produce renewable energy and focuses on agricultural, forestry, urban and industrial residues. It also provides a description of the physical and calorific characteristics of the various raw materials available for the manufacture of briquettes and other fossil fuel alternatives.

While the energy sector is the largest global contributor to greenhouse gas (GHG) emissions, the agriculture, forestry, and other land use (AFOLU) sector account for up to 80% of GHG emissions in the least developed countries (LDCs). Despite this, the nationally determined contributions (NDCs) of LDCs, including Nepal, focus primarily on climate mitigation in the energy sector. This paper introduces green growth—a way to foster economic growth while ensuring access to resources and environmental services—as an approach to improving climate policy coherence across sectors. Using Nepal as a case country, this study models the anticipated changes in resource use and GHG emissions between 2015 and 2030, that would result from implementing climate mitigation actions in Nepal's NDC. The model uses four different scenarios. They link NDC and policies across economic sectors and offer policy insights regarding (1) energy losses that could cost up to 10% of gross domestic product (GDP) by 2030, (2) protection of forest resources by reducing the use of biomass fuels from 465 million gigajoules (GJ) in 2015 to 195 million GJ in 2030, and (3) a significant reduction in GHG emissions by 2030 relative to the business‐as‐usual (BAU) case by greater use of electricity from hydropower rather than biomass. These policy insights are significant for Nepal and other LDCs as they seek an energy transition towards using more renewable energy and electricity.

Both peat utilization and peatlands themselves contribute to increases in greenhouse gas (GHG) emissions. This article examines how peatlands with naturally high GHG emission levels affect net GHG emissions during the life cycle of peat. GHG emissions were measured from three drained peatland sites with high GHG emission levels. The impact of peatland type on the GHG emissions was considered when peat was assumed to replace coal in an energy production facility. The emission reduction levels achieved with the use of peat fuel originating from high-emission level peatlands stood at 35% compared to coal use and 30% compared to the average peat emission value. The findings indicate that GHG emissions can be reduced overall when peat from high-emission peatlands is utilized instead of coal. Lower emissions are primarily achieved because the harvesting of peat from high-emission level peatlands reduces the GHG emission levels of those lands.

This research was conducted to identify the most efficient biomass out of five different types of biomass sources for anaerobic treatment of Olive Mill Wastewater (OMW). This study was first focused on examining the selected biomass in anaerobic batch systems with sodium acetate solutions (control study). Then, the different types of biomass were tested with raw OMW (water-diluted) and with pretreated OMW by coagulation-flocculation using Poly Aluminum Chloride (PACl) combined with hydrated lime (Ca(OH)2). Two types of biomass from wastewater treatment systems of a citrus juice producing company "PriGat" and from a citric acid manufacturing factory "Gadot", were found to be the most efficient sources of microorganisms to anaerobically treat both sodium acetate solution and OMW. Both types of biomass were examined under different concentration ranges (1-40 g l-1) of OMW in order to detect the maximal COD tolerance for the microorganisms. The results show that 70-85% of COD removal was reached using Gadot biomass after 8-10 days when the initial concentration of OMW was up to 5 g l-1, while a similar removal efficiency was achieved using OMW of initial COD concentration of 10 g l-1 in 2-4 days of contact time with the PriGat biomass. The physico-chemical pretreatment of OMW was found to enhance the anaerobic activity for the treatment of OMW with initial concentration of 20 g l-1 using PriGat biomass. This finding is attributed to reducing the concentrations of polyphenols and other toxicants originally present in OMW upon the applied pretreatment process.

Temperature measurement of stored biomass of different types and bulk densities using acoustic techniques

Both agriculture and forestry produce a large amount of biomass waste. Historically much of this has either been sent to landfill or burnt, increasing greenhouse gas emissions and wasting potentially valuable resources. By converting this biomass instead into useful products, we can reduce greenhouse gas emissions, avoid waste and reduce the need for other sources for these products. Introducing the different types of biomass that can be obtained from agriculture and forestry this book looks at the challenges in using them, specific applications and their role in creating a more sustainable and environmentally friendly economy. It will provide useful insights for green chemists, agricultural chemists and anyone interested in biorefinery science.