Optimised production of tailored syngas from municipal solid waste (MSW) by sorption-enhanced gasification

Martínez, Isabel Casabona; Grasa, Gemma; Callén, M.S.; López, Javier Fernández; Murillo, R.

doi:10.1016/j.cej.2020.126067

Cited by 34 publications

(31 citation statements)

References 31 publications

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“…Gasification also shows high flexibility in feedstock variation (Saidi et al 2020 ). The common feedstock for gasification includes biomass (Putro et al 2020 ; Sittisun et al 2019 ), coal (Grabowski et al 2020 ), carbonized products (Chen et al 2019 ; He et al 2019 ), plastics (Nanda and Berruti 2020b ), and municipal solid waste (Martínez et al 2020 ).…”

Section: Recent Progress In Refuse-derived Fuel Gasification For Enermentioning

confidence: 99%

Gasification of refuse-derived fuel from municipal solid waste for energy production: a review

et al. 2021

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Dwindling fossil fuels and improper waste management are major challenges in the context of increasing population and industrialization, calling for new waste-to-energy sources. For instance, refuse-derived fuels can be produced from transformation of municipal solid waste, which is forecasted to reach 2.6 billion metric tonnes in 2030. Gasification is a thermalinduced chemical reaction that produces gaseous fuel such as hydrogen and syngas. Here, we review refuse-derived fuel gasification with focus on practices in various countries, recent progress in gasification, gasification modelling and economic analysis. We found that some countries that replace coal by refuse-derived fuel reduce CO 2 emission by 40%, and decrease the amount municipal solid waste being sent to landfill by more than 50%. The production cost of energy via refuse-derived fuel gasification is estimated at 0.05 USD/kWh. Co-gasification by using two feedstocks appears more beneficial over conventional gasification in terms of minimum tar formation and improved process efficiency.

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Section: Recent Progress In Refuse-derived Fuel Gasification For Enermentioning

confidence: 99%

Gasification of refuse-derived fuel from municipal solid waste for energy production: a review

et al. 2021

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“…This involves that the same reactor has been utilised for all experiments, and in this particular case, no literature data have been considered. Furthermore, given that the gasification facility has a significant technology readiness level (TRL4), with a fluidised bed reactor of 3-m height and 0.20-m internal diameter [32][33][34], the application of statistical tools and outlet gas modelling tools could help to reduce the number of experiments to be performed, simplifying the process and reducing time and expense in biomass gasification research. In fact, other of the expectations of this research relies on the modelling of the tar content that is a variable affecting negatively to the gasification and involves, not only the sampling, but also the further analysis with analytical techniques such as gas chromatography with mass spectrometer detection.…”

Section: Introductionmentioning

confidence: 99%

Principal component analysis and partial least square regression models to understand sorption-enhanced biomass gasification

Callén

Martínez

Grasa

et al. 2022

Biomass Conv. Bioref.

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Gasification represents a potential technology for the conversion of biomass into usable energy. The influence of the main gasification parameters, i.e. the type of biomass used and its composition, as well as the composition of the outlet gas, were studied by a multivariate statistical analysis based on principal component analysis (PCA) and partial least square (PLS) regression models in order to identify the main correlations between them and to the contents of methane, ethylene and tar in the outlet gas. In this work, the experimental data used as input for the multivariate statistical analysis came from a TRL-4 gasification plant running under sorption enhanced conditions, i.e. using steam as the gasifying agent and CaO as the bed material. The composition of the biomass feed played an important role in the quality of the outlet gas composition. In fact, biomasses with high ash and sulphur contents (municipal solid waste) increased ethylene content, while those with high-volatile matter content and fixed C content (wood pellets, straw pellets and grape seeds) mainly increased CO and CO2 formation. By increasing the gasification bed temperature and the CaO/C ratio, it was possible to reduce the methane and the collected tar contents in the outlet gas. Other light hydrocarbons could also be reduced by controlling the Treactor and TFB. Methane, ethylene and tar contents were modelled, cross-validated and tested with a new set of samples by PLS obtaining results with an average overall error between 8 and 26%. The statistically significant variables to predict methane and ethylene content were positively associated to the thermal input and negatively to the CaO/C ratio. The biomass composition was also remarkable for both variables, as mentioned in the PCA analysis. As far as the tar content, which is undesirable in all gasification processes, the decrease in the tar content was favoured by high bed temperature, low thermal input and biomass with high-volatile matter content. In order to produce an outlet gas with adequate quality (e.g. low tar content), a compromise should be found to balance average bed temperature, sorbent-to-mass ratio, and ultimate and proximate analyses of the biomass feed. Graphical abstract

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“…Certain flexible technologies allow to modify the final composition of the syngas [13,14], but, in general terms, biomass-derived syngas, or bio-syngas, is known to be rich in CO 2 [15,16]. In fact, the concentration of CO 2 in the biomass-derived syngas can be as high as that of CO when the feedstock used is palm oil wastes, or even twice as high when the bio-syngas is produced from empty fruit bunch, α-cellulose or municipal solid waste [12,17]. The latter has been demonstrated to produce a syngas with a CO 2 /CO ratio of 1.9 when subjected to sorption-enhanced gasification [17].…”

Section: Introductionmentioning

confidence: 99%

“…In fact, the concentration of CO 2 in the biomass-derived syngas can be as high as that of CO when the feedstock used is palm oil wastes, or even twice as high when the bio-syngas is produced from empty fruit bunch, α-cellulose or municipal solid waste [12,17]. The latter has been demonstrated to produce a syngas with a CO 2 /CO ratio of 1.9 when subjected to sorption-enhanced gasification [17]. The high CO 2 content in the syngas obtained from biomass represents a drawback in the use of bio-syngas as feedstock for the production of methanol.…”

Section: Introductionmentioning

confidence: 99%

In Situ Conditioning of CO2-Rich Syngas during the Synthesis of Methanol

et al. 2021

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The synthesis of methanol from biomass-derived syngas can be challenging because of the high CO2 content in the bio-syngas, resulting in lower kinetics and higher catalyst deactivation. This work explores the in situ pre-treatment of a CO2-rich syngas with a CO2/CO ratio equal to 1.9 through the reverse-water gas shift reaction with the aim of adjusting this ratio to a more favorable one for the synthesis of methanol with Cu-based catalysts. Both reactions take place in two catalytic beds placed in the same reactor, thus intensifying the methanol process. The water produced during syngas conditioning is removed by means of a sorbent zeolite to prevent the methanol catalyst deactivation and to shift the equilibrium towards the methanol formation. The combination of the CO2 shifting and the water sorption strategies lead to higher productivities of the catalytic bed and, under certain reaction conditions, to higher methanol productions.

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Optimised production of tailored syngas from municipal solid waste (MSW) by sorption-enhanced gasification

Cited by 34 publications

References 31 publications

Gasification of refuse-derived fuel from municipal solid waste for energy production: a review

Gasification of refuse-derived fuel from municipal solid waste for energy production: a review

Principal component analysis and partial least square regression models to understand sorption-enhanced biomass gasification

In Situ Conditioning of CO2-Rich Syngas during the Synthesis of Methanol

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