Thermogravimetric (TG) analysis was carried out to evaluate the interactions and kinetics of char from biomass gasification, solid digestate and their blends under combustion condition. The ...gasification char was blended with solid digestate in the range of 10–90 wt% to analyze the co-combustion performance. Based on the thermal degradation experiments which were performed at three heating rates 5, 10, and 15 °C/min, the OFW model-free method was used to determine the activation energy, based on which the pre-exponential factor, the enthalpy, the Gibbs free energy and the entropy were also calculated to label the combustion process directly.
Blending gasification char with solid digestate tends to reduce the activation energy, but the overall analysis of combustion, kinetic and thermodynamic parameters reveals the complexity of the degradation process of all blends. Results showed that the blending proportion of 50% was regarded as the optimum blend in according to the limitations of activation energy, comprehensive performance index and Gibbs free-energy.
•Combustion process of biomass gasification char and solid digestate was studied.•A complex synergistic interaction occurred during co-combustion of the blends.•Kinetic and thermodynamic parameters were calculated by using Ozawa-Flynn-Wall method.•The optimum combustion performance was obtained by a blending ratio of 50:50.
•Torrefaction temperature of 260 °C is recommended for upgrading spent coffee grounds.•Acetic acid (4.4 wt% at 260 °C) was the major component in the tar fraction.•CO2 (up to 8.8 wt%) was the main ...non-condensable contributor to deoxygenation of SCG.•Energy yield of 64,4% was achieved with HHV enhancement of 15.4% at 260 °C.
Several studies in Literature have analyzed the torrefaction treatment process of biomass in batch reactors. Nevertheless, in order to check the industrial applicability of a process, it is more interesting to carry out torrefaction tests in continuous pilot plant reactors. Thus, the present study reports the results of continuous semi-industrial scale (500 kg/h) torrefaction experiments employing spent coffee grounds (SCG) as a feedstock in a horizontal rotary reactor. Torrefaction tests were carried out at three different temperatures (210 °C, 235 °C, and 260 °C) for 90 min, in order to evaluate the yields of solid, liquid (water and tar) and gaseous products and their composition. In particular, the effectiveness of the decarbonization and deoxygenation processes was investigated, analyzing the carbon and oxygen distribution. Within the temperature range, torrefaction yielded solid of 55.2–85.8 wt% with an increase of the higher heating value (HHV) of 5.1–15.4% compared to the raw material. Liquid fraction yield was in the range of 11.3–34.3 wt%, with a moisture content of 73.7–91.9% and HHV between 18.8 and 23.4 MJ/kg on dry basis. Gas fraction represented 2.9–10.5 wt% of the raw biomass withHHVbetween 1.95 and 3.55 MJ/Nm3. Acids (mainly acetic acid) were the major compounds in the tar fraction, accounted up to 68 wt%, while CO2 was the main product of the deoxygenation reactions in the gaseous fraction (76.6–86.9 vol%). From the perspective of mass yield and energy density enhancement, 260 °C was considered to be the optimal temperature for torrefaction of SCG.
The aim of the present study is to analyze the influence of independent process variables such as temperature, residence time, and heating rate on the torrefaction process of coffee chaff (CC) and ...spent coffee grounds (SCGs). Response surface methodology and a three-factor and three-level Box-Behnken design were used in order to evaluate the effects of the process variables on the weight loss (W
) and the Higher Heating Value (HHV) of the torrefied materials. Results showed that the effects of the three factors on both responses were sequenced as follows: temperature>residence time>heating rate. Data obtained from the experiments were analyzed by analysis of variance (ANOVA) and fitted to second-order polynomial models by using multiple regression analysis. Predictive models were determined, able to obtain satisfactory fittings of the experimental data, with coefficient of determination (R
) values higher than 0.95. An optimization study using Derringer's desired function methodology was also carried out and the optimal torrefaction conditions were found: temperature 271.7°C, residence time 20min, heating rate 5°C/min for CC and 256.0°C, 20min, 25°C/min for SCGs. The experimental values closely agree with the corresponding predicted values.
•The co-combustion kinetics of sub-bituminous coal and CER was studied.•Blending with cellulosic ethanol residue could improve the combustion performance.•Two isoconversional kinetic models are ...proposed to obtain kinetic parameters.•The lowest average activation energy was obtained by blending 20% CER.
The influence of the addition of cellulosic ethanol residue (CER) on the combustion of Indonesian sub-bituminous coal was analyzed by non isothermal thermo-gravimetric analysis (TGA). The effect of blends ratio (5%, 10%, 15% and 20%), interaction mechanism, and heating rate (5°C/min, 10°C/min, 15°C/min, 20°C/min) on the combustion process was studied. The results show that the increase of the blending ratio allows to achieve the increase of the combustibility index from 7.49E−08 to 5.26E−07 at the blending ratio of 20%. Two types of non-isothermal kinetic analysis methods (Ozawa–Flynn–Wall and Vyazovkin) were also applied. Results indicate that the activation energy of the blends decreases with increasing the conversion rate. In particular, the blending ratio of 20% confirms to have the better combustion performance, with the average value of the activation energy equal to 41.10kJ/mol obtained by Ozawa–Flynn–Wall model and 31.17kJ/mol obtained by Vyazovkin model.
The aim of the paper was to evaluate the environmental burden of the organic waste management systems implemented in Umbria region in Italy, in order to provide useful information for taking ...strategic decisions aimed at the improvement and optimization. The two most widespread scenarios were analyzed: source-segregated collection followed by organic fertilizer production and not-differentiated collection followed by mechanical and biological treatment and disposal in landfill of the biostabilized material. The environmental performance was assessed through Life Cycle Assessment methodology, assuming one ton of organic waste as functional unit. Most of data for life cycle inventory were provided by actual facilities while background data were obtained from EcoInvent database. The alternative scenarios were compared through the IMPACT 2002+ method and the assessment was carried out on both midpoint and endpoint levels. Results showed that the landfilling of the undifferentiated organic waste has the least impact on the analyzed impact categories, except on the Global Warming, mostly due to the uncollected methane released by the landfill. As regards the aerobic composting of the source-segregated organic fraction, the efforts to reduce the impact should be mainly focused on the reduction of the air emissions (hydrogen sulfide, particulate, ammonia and NMVOC) from the biostabilization process. Furthermore the sensitivity analysis indicated that the increase of the biogas collection efficiency could significantly improve the performance of the not-differentiated collection scenario.
The cradle to grave carbon footprint (CF) and energy footprint (EF) analysis of extra virgin olive oil (EVOO) produced in the Province of Perugia (Umbria, Italy) is assessed. In this study, olive ...orchard cultivation, EVOO extraction, bottling, packaging, storage at −18°C and distribution in the main importing countries were studied from a life cycle assessment perspective, with the main objective of identifying the processes with the largest environmental impacts. The selected functional unit was 1L of EVOO, packaged for distribution. Inventory data was gathered mainly through both direct communication using questionnaires and direct measurements. To determine the CF the ISO/TS 14067:2013 was followed while the EF was evaluated according to ISO standards 14040 and 14044. Results showed that the most impacting process is the distribution, mainly due to the choice of employing air transport. The main other hot spots identified were the olive orchard fertilization, EVOO freezing during its storage at the olive mill factory and the manufacture of glass bottles. Suggested improvement opportunities included shifts in the EVOO transportation policy, the introduction of lighter glass bottles in the bottling process, the use of cooling agent with lower global warming potential and the employment of biodiesel in the farming machineries.
•Carbon footprint and energy footprint are calculated by LCA methodology.•Extra virgin olive oil supply chain is investigated by “cradle-to-grave” analysis.•IPCC approach is used to calculate direct and indirect N2O emissions from fertilizer use.•Product distribution to customer and final disposal are included in system boundaries.•Main GHG emission sources are identified and possibilities for reduction are proposed.
•ANN used as a tool for evaluating energy performance of buildings.•Training, validation, and testing of Neural Network with real energy certificates data.•Global energy performance index was chosen ...as a target of ANN.•A good correlation and a minimum error was found with certificates data.•A new energy index was defined in order to check the energy certificates.
The Energy Performance Buildings Directive (EPBD) was issued to provide a common strategy for all European countries and to implement several actions for improving energy efficiency of buildings, responsible for 40% of energy consumption. Energy Performance Certificates are provided as a tool to evaluate the energy performance of buildings; however, costly and time-consuming controls are necessary to verify the accuracy of the set and declared data.
Useful tools could be the Artificial Neural Networks (ANN), whereby it is possible to estimate the energy consumptions from specific parameters, to evaluate the accuracy of data in the energy certificates, and to identify the certificates needing accurate control.
In this study, an Artificial Neural Network was developed based on approximately 6500 energy certificates (2700 are self-declaration) received by the Umbria Region (central Italy), in order to evaluate the global energy consumption of buildings from several and specific parameters reported in certificates. Data was checked in compliance with energy standards and only the correct certificates were used to train the Neural Network.
The implemented Neural Network was tested with database data and a good correlation was found; in particular the energy performance calculated with the Neural Network presents an error greater than 15kWh/m2year with respect to the real value of global energy performance index in only 3.6% of cases.
Finally, a Neural Energy Performance Index (N.E.P.I.) was defined, in order to verify the accuracy of the energy certificates; the study reported in this paper shows how the new defined index could be an important tool to identify which energy certificates require controls. A refinement of the Neural Network would allow to minimize the error and to define a N.E.P.I. index that could be used by European public administrations as a tool to perform an initial check of certificates.
Beef cattle production is a widespread activity in Italy in the agricultural field and determines an important impact on environment and resources consumption. Carbon footprint evaluation is thus ...necessary to evaluate the contributions of the different stages and the possible improvements of the production chain.
In this study, two typical Italian beef production systems, a conventional and an organic one are investigated in order to evaluate the greenhouse gas emissions from “cradle to gate farm” by a Life Cycle Assessment (LCA) approach; the carbon footprint (CF) per 1kg of live weight meat is calculated.
The contributions from feed production, enteric fermentation, and manure management are taken into account, in order to compare the life cycle of the two productions; also the carbon balance in soil is evaluated, in order to verify the impact in a life cycle perspective.
The results of CF calculation of the two farms show that organic system (24.62kgCO2eq/kg live weight) produce more GHG emissions than the conventional one (18.21kgCO2eq/kg live weight) and that the enteric fermentation is the more heavy contribution, with a range of 50–54% of the global CF value. Improvements of the production chain could be realized by accurate feeding strategies, in order to obtain reduction of methane emissions from enteric digestion of cattles.
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•Organic and conventional beef production are compared by carbon footprint.•Conventional system has lower GHG emissions.•The most impacting phase is represented by enteric fermentation in both scenarios.•Sensitivity analysis evaluates the contribution from changes in soil C.
Olive pomace is an interesting agro-industrial byproduct that can be a potential raw material for densified biomass products. At first, 2-phase (2 PH) and 3-phase (3 PH) olive pomace pellets were ...analyzed in order to evaluate their quality in terms of the main parameters required by the European Standard EN 17225-6.
The characterization of the pure pellets has shown important problems because of out of limits values of nitrogen, durability and copper in the two olive pomace. To improve the properties of olive pomace pellets, the possibility of manufacturing pellets by mixing olive pomace and olive tree pruning (PR) was investigated.
Several blends at different weight ratios were analyzed in order to verify the effect of mixing on the pellet properties. It can be concluded that the physical properties of all mixtures are in compliance with the requirements of the standard.
In particular, two best blends in terms of physical, chemical and mechanical characteristics were identified as becoming potential fuel for combustion and gasification applications: 75PR252 PH (75% pruning and 25% 2-phase pomace) and 50PR503 PH (50% pruning and 50% 3-phase pomace).
•Olive pomace is a potential raw material for pellet production.•Pure olive pomace pellets not respect requirements for pellet quality.•Pellet blends of olive pomace and olive tree pruning were produced and analyzed.•Physical properties of pellet are improved by mixing olive pomace and pruning.•Two blends have the best performance as physical, chemical and energetic features.
•Solid digestate was used as raw material for microwave-assisted direct liquefaction.•The reaction conditions were optimized by applying response surface methodology.•Bio-oil yield of 59.38%, HHV of ...28.48 MJ/kg were obtained under optimum conditions.
Microwave-assisted direct liquefaction of solid digestate was carried out in polyethylene glycol and glycerol employing sulfuric acid as catalyst, in order to convert it into a biofuel. Response Surface Methodology (RSM) coupled with Box-Behnken Design (BBD) with a total of 15 individual experiments was used to optimize the conditions of three independent variables (temperature, reaction time and solvent-to-biomass ratio) related to the bio-oil yield, the higher heating value (HHV) of bio-oil and the energy use of microwave treatment. Desirability function was employed to determine the optimal reaction conditions of the liquefaction process. The results showed that at the optimal conditions the bio-oil yield, the HHV of bio-oil and energy use were respectively 59.38%, 28.48 MJ/kg, and 115.93 Wh. The predicted responses showed a good compliance to the obtained experimental data. The optimized bio-oil was further characterized using FTIR analysis while the properties of the solid digestate and the liquefaction residue were analyzed by means of SEM analysis.
