Slow pyrolysis as a platform for negative emissions technology: An integration of machine learning models, life cycle assessment, and economic analysis

Cheng, Fangwei; Luo, H.; Colosi, Lisa M.

doi:10.1016/j.enconman.2020.113258

Cited by 150 publications

(66 citation statements)

References 47 publications

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“…Table 2 shows several studies that used AI techniques to predict the yields and properties (e.g., HHV and carbon content) of products based on the operating conditions (e.g., temperature, residence time, heating rate) and/or feedstock characterization data. Such prediction allows for the rapid development of process simulation models without expensive and time‐consuming experiments (Cheng et al, 2020). At the reaction level, kinetic models built upon fundamental reaction mechanisms and reaction kinetics can also predict the yields and composition of pyrolysis products.…”

Section: Applications Of Artificial Intelligence To Bioenergy Systemsmentioning

confidence: 99%

Applications of artificial intelligence‐based modeling for bioenergy systems: A review

Ming-yang

Yao

2021

GCB Bioenergy

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Bioenergy is widely considered a sustainable alternative to fossil fuels. However, large‐scale applications of biomass‐based energy products are limited due to challenges related to feedstock variability, conversion economics, and supply chain reliability. Artificial intelligence (AI), an emerging concept, has been applied to bioenergy systems in recent decades to address those challenges. This paper reviewed 164 articles published between 2005 and 2019 that applied different AI techniques to bioenergy systems. This review focuses on identifying the unique capabilities of various AI techniques in addressing bioenergy‐related research challenges and improving the performance of bioenergy systems. Specifically, we characterized AI studies by their input variables, output variables, AI techniques, dataset size, and performance. We examined AI applications throughout the life cycle of bioenergy systems. We identified four areas in which AI has been mostly applied, including (1) the prediction of biomass properties, (2) the prediction of process performance of biomass conversion, including different conversion pathways and technologies, (3) the prediction of biofuel properties and the performance of bioenergy end‐use systems, and (4) supply chain modeling and optimization. Based on the review, AI is particularly useful in generating data that are hard to be measured directly, improving traditional models of biomass conversion and biofuel end‐uses, and overcoming the challenges of traditional computing techniques for bioenergy supply chain design and optimization. For future research, efforts are needed to develop standardized and practical procedures for selecting AI techniques and determining training data samples, to enhance data collection, documentation, and sharing across bioenergy‐related areas, and to explore the potential of AI in supporting the sustainable development of bioenergy systems from holistic perspectives.

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Section: Applications Of Artificial Intelligence To Bioenergy Systemsmentioning

confidence: 99%

Applications of artificial intelligence‐based modeling for bioenergy systems: A review

Ming-yang

Yao

2021

GCB Bioenergy

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“…Biomass is of particular interest in the bioenergy sector because of its carbon neutrality, which could help mitigate the adverse effects of climate change and global warming, if utilized in a sustainable manner. Aside dependence on the carbon-neutrality of biomass to achieve net-zero emission of CO 2 , negative emission technologies (NETs) that include afforestation and reforestation, bioenergy with carbon capture and storage, direct air capture, enhanced weathering and ocean alkalization, biochar-based carbon sequestration could also be deployed in a bid to stabilize the climate 1 . Specifically, biochar, a stable solid carbon-rich material, often produced from biomass pyrolysis, can be applied as soil amendment to sequester carbon.…”

Section: Introductionmentioning

confidence: 99%

“…In the case of lignin, it is the least reactive compound and it degrades over a broad range of temperature; leading to a much less volatilization relative to the other constituents. In terms of the thermal operating conditions, it has been observed that slow heating rates, long residence time and relatively low temperature favor char production 1 . Conversely, bio-oil generation is mostly achieved through rapid heating rates, short vapor residence time and moderate temperature.…”

Section: Introductionmentioning

confidence: 99%

Kinetics modeling, thermodynamics and thermal performance assessments of pyrolytic decomposition of Moringa oleifera husk and Delonix regia pod

Balogun

Adeleke

Ikubanni

et al. 2021

Sci Rep

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A non-isothermal decomposition of Moringa oleifera husk and Delonix regia seed pod was carried out in an N2 pyrolytic condition with the primary objective of undertaking the kinetics modeling, thermodynamics and thermal performance analyses of the identified samples. Three different isoconversional models, namely, differential Friedman, Flynn–Wall–Ozawa, and Starink techniques were utilized for the deduction of the kinetics data. The thermodynamic parameters were deduced from the kinetic data based on a first-order chemical reaction model. In the kinetics study, a strong correlation (R2 > 0.9) was observed throughout the conversion range for all the kinetic models. The activation energy profiles showed two distinctive regions. In the first region, the average activation energy values were relatively higher—a typical example is in the Flynn–Wall–Ozawa technique—MH (199 kJ/mol) and RP (194 kJ/mol), while in the second region, MH (292 kJ/mol) and RP (234 kJ/mol). It was also demonstrated that the thermal process for the samples experienced endothermic reactions thought the conversion range. In summary, both the kinetic and thermodynamic parameters vary significantly with conversion—underscoring the complexity associated with the thermal conversion of lignocellulosic biomass samples.

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“…Pyrolysis is a technology that decompose organic matter at elevated temperature and under anaerobic conditions [14][15][16]. When pyrolysis is applied in sludge treatment, its thermal treatment nature guarantees the rapidness and effectiveness of sludge volume reduction, and its anaerobic nature greatly reduces the formation of hazardous pollutants/wastes, e.g., dioxin, NOX and oxidized heavy metal [17,18].…”

Section: Introductionmentioning

confidence: 99%

Full-scale municipal sludge pyrolysis in China: Design fundamentals, environmental and economic assessments, and future perspectives

Luo

Cheng

Yu³

et al. 2021

Science of The Total Environment

Self Cite

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The increasing amount of municipal sludge in China requires safe and effective management to protect human health and ensure environmental sustainability. Pyrolysis is a thermochemical process that that decompose organic matter at elevated temperature and under anaerobic conditions, and it has attracted an increasing attention in sludge treatment in the recent years. However, comprehensive environmental and economic assessment of sludge pyrolysis in China's context is rare, due to the small quantities of fullscale sludge pyrolysis plant. In this paper, we applied our design and operation parameters of full-scale sludge pyrolysis plants to generate the material and energy consumptions of the pyrolysis system under various of conditions, including sludge organic content and moisture content, system size, system energy distribution, and whether or not heat substitution is applied. Life cycle assessment and techno-economic assessment were then applied to investigate the environmental and economic performance of the system

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Slow pyrolysis as a platform for negative emissions technology: An integration of machine learning models, life cycle assessment, and economic analysis

Cited by 150 publications

References 47 publications

Applications of artificial intelligence‐based modeling for bioenergy systems: A review

Applications of artificial intelligence‐based modeling for bioenergy systems: A review

Kinetics modeling, thermodynamics and thermal performance assessments of pyrolytic decomposition of Moringa oleifera husk and Delonix regia pod

Full-scale municipal sludge pyrolysis in China: Design fundamentals, environmental and economic assessments, and future perspectives

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