Abstract: Adequate waste management is essential not only to ensure healthy living conditions but also to mitigate climate change. Accordingly, the research on developing strategies to boost the circularity of waste management systems is ongoing. In this context, two waste streams are concurrently managed to recover energy and materials in the present study. Specifically, real leachate collected from a full-scale mature landfill site was preliminarily treated through active filtration to remove inhibitory substances partially and then tested, at the laboratory scale, as a nutrient solution for semi-continuous anaerobic digestion of a carbonaceous substrate represented by market waste. The results demonstrate that, at an organic loading rate of 1.0 gVS∙L-1∙d-1, the process was impossible without using the nutrient solution, while the nitrogen present in the pretreated leachate could balance the carbon content of the market waste and provide the system with the necessary buffering capacity, ensuring process stability. The average methane yield (approximately 0.29 NL∙gVS-1) was satisfactory and consistent with the literature. Despite the increases in both the organic loading rate (up to 1.5 gVS∙L-1∙d-1) and volume of added pretreated leachate (up to 100% of the dilution medium), the process remained stable with a slightly lower methane yield of 0.21 NL∙gVS-1, thanks to nitrogen supplementation. The potential use of produced methane as a renewable energy source and residual digestate as fertilizer would close the loop of managing these waste streams.
Abstract: Energy may be generated in large quantities from fossil fuels, but this comes with environmental concerns. Thus, renewable resources like biogas, comprising carbon dioxide and methane, should be used alone or in combination with fossil fuels to mitigate the environmental footprints of energy generation systems. In this study, a new concept of hybrid solvent was presented, which combines 1-octyl-3-methylimidazolium tetrafluoroborate with aqueous mono diethanolamine for biogas upgrading process to provide high purity (≥ 99 wt%) and recovery (≥ 99 wt%) of biomethane. The process was simulated in ASPEN Plus® V.11. The thermodynamic framework was validated against experimental data, and rigorous regression was conducted to obtain binary parameters. To establish the efficacy of the suggested hybrid solvent, three scenarios were studied by altering the concentration of ionic liquid (5–20 wt%) linked with amine and compared to aqueous mono diethanolamine as the base case (50 wt%). The results showed that a hybrid solvent with 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate could increase CH4 purity to 99% (mol%). The hybrid solvent led to an energy saving of 64.94% compared to the amine-based system. Thermodynamic irreversibilities showed that 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate improved exergy efficiency by 54% over the amine-based procedure. Environmentally, the hybrid solvent system also achieved a higher capture rate (99%) and lower emissions (0.017 kW/kmol). Comparing the economic prospects, 5 wt% 1-octyl-3-methylimidazolium tetrafluoroborate saved 56% on total capital cost, making it competitive from an investment perspective.
Abstract: Thermochemical treatment is a promising technique for biomass disposal and valorization. Recently, machine learning (ML) has been extensively used to predict yields, compositions, and properties of biochar, bio-oil, syngas, and aqueous phases produced by the thermochemical treatment of biomass. ML demonstrates great potential to aid the development of thermochemical processes. The present review aims to 1) introduce the ML schemes and strategies as well as descriptors of the input and output features in thermochemical processes; 2) summarize and compare the up-to-date research in both ML-aided wet (hydrothermal carbonization/liquefaction/gasification) and dry (torrefaction/pyrolysis/gasification) thermochemical treatment of biomass (i.e., predicting the yields, compositions, and properties of oil/char/gas/aqueous phases as well as thermal conversion behavior or kinetics); and 3) identify the gaps and provide guidance for future studies concerning how to improve predictive performance, increase generalizability, aid mechanistic and application studies, and effectively share data and models in the community. The development of biomass thermochemical treatment processes is envisaged to be greatly accelerated by ML in the near future.
Abstract: Bio-based materials have been used traditionally for millennia. Their use was overtaken in recent times by the discovery and utilization of fossil-based resources for materials and energy. However, concerns about the non-renewability of fossil resources and greenhouse gas and other emissions associated with their use have brought forth a renewed interest in using bio-based materials in recent years. The environmental advantages of bio-based materials cannot be taken for granted without a rigorous scientific assessment. Many tools based on energy, economics, and environmental impacts have been used. Life cycle assessment is one such tool developed and successfully utilized for the environmental assessment of biofuels and bioproducts. However, many methodological challenges, among other things related to system boundaries, functional units, allocation, and carbon accounting, still need further research and consideration. In this work, the related issues are summarized, and the directions for addressing them are discussed. Despite the methodological challenges in their assessment, biofuels and bioproducts show promise in terms of their environmental advantages compared to their fossil-oriented counterparts. These advantages can be further enhanced by utilizing all parts of the feedstock biomass, especially for value-added materials and chemicals via biorefineries.
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