To burn or valorise bark from a pulp mill: Environmental sustainability analysis using prospective consequential life cycle assessment

The Science of The Total Environment, Год журнала: 2025, Номер 976, С. 179234 - 179234

Опубликована: Апрель 9, 2025

Bark represents 10 % dry weight of spruce trees and is a major side stream from pulp production. Currently, mills burn bark to produce energy with low economic value, directly emitting biogenic carbon dioxide the atmosphere. Biorefining using continuous flow-through fractionation process generates high added-value compounds (tall oil, starch, phenol, pulp) that allow for extended storage durations. This study assesses potential future environmental impacts valorising instead burning it. We conduct LCA combining prospective consequential modelling perspective an input-related functional unit account effects storing in bark-based products. Our findings show biorefining maintains lower than combustion, reducing time-differentiated climate by up 30 %, but only when used pulping recirculated processes are integrated co-located mill supplying surplus waste energy, considered have no associated impacts. Storing longer period time has positive effect on mitigating short-term However, our analysis reveals while time-dependent decrease, there increase human toxicity ecotoxicity impacts, combustion performing better these categories. highlights importance expanding scope studies include beyond change. Overall, this work demonstrates relevant approach emerging biorefineries thus supports development sustainable circular bioeconomy.

Язык: Английский

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Python-Based Algorithm for Calculating Physical Properties of Aqueous Mixtures Composed of Substances Not Available in Databases

ACS Omega, Год журнала: 2025, Номер 10(16), С. 16683 - 16694

Опубликована: Апрель 15, 2025

In this study, we developed a Python-based open-source algorithm compatible with the aqueous physical property models provided in electrolyte templates of AspenTech software. To validate accuracy model, results obtained from proposed were compared to experimental data for 37 binary mixture systems covering properties such as density, heat capacity, viscosity, and thermal conductivity. The input variables included our previous research on pure component prediction nonrandom two-liquid (NRTL) model parameters based UNIFAC simulations. This is mean absolute percentage errors (MAPE) conductivity 2.88, 0.355, 12.1, 10.1%, respectively. case density actual trends could not be accurately reflected under high-concentration conditions certain substances. addition, it was confirmed that inaccurate predictions viscosity commercial-scale falling-film evaporator simulation l-valine production led overall transfer coefficient. Therefore, caution required when predicting missing using approach significant may occur. Nevertheless, can provide an initial parameter value are existing databases without any commercial package.

Язык: Английский

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A critical evaluation of the progression in industrial waste utilization to achieve energy transition targets: technological obstacles, carbon footprint reduction, and life cycle assessment

Renewable Energy, Год журнала: 2025, Номер unknown, С. 123469 - 123469

Опубликована: Май 1, 2025

Язык: Английский

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Energy and Techno-economic Analysis of Aviation Fuel Production via Biomass Gasification, Olefins Synthesis and Oligomerization

Energy, Год журнала: 2025, Номер unknown, С. 136736 - 136736

Опубликована: Май 1, 2025

Язык: Английский

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Life cycle assessment and techno-economic analysis of maleic anhydride hydrogenation to 1,4-butanediol through biomass gasification coupling with chemical looping hydrogen production

Renewable Energy, Год журнала: 2024, Номер 237, С. 121623 - 121623

Опубликована: Окт. 16, 2024

Язык: Английский

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