Torrefaction and Steam Explosion of Selected Biomass for Biofuel Production
Notice bibliographique
Résumé
Lignocellulosic biomass has demonstrated great potential as feedstock for pellet production, notwithstanding the fact that the industrial production of pellet is faced with some economic challenges. Pretreatment research has been focused on identifying, evaluating, developing, and demonstrating promising approaches that enhance the physiochemical and mechanical properties of biomass. Assessment of biomass pretreatment processes depends on a parameter called the severity factor, which is defined as the combined effect of temperature and residence time. This study summarizes pretreatment processing methods, namely, steam explosion and torrefaction of selected biomass feedstocks (sawdust and oat straw), processing characteristics, and product properties. The study also discusses the economics of densifying biomass, outstanding challenges, the potential for industrial applications of biomass-pretreated products, and global trends in biomass utilization. Steam explosion pretreatment of sawdust and oat straw was conducted under 3 stages: mild, medium, and severe conditions. The effects of temperature, time, and moisture content on the physiochemical and mechanical properties of pellets formed were examined. The p-values of the regression models for all the response variables (dimensional stability, tensile strength, and pellet density) studied were significant (p < 0.05), except for the pellet density of steam-pretreated oat straw pellets. The interaction of these three factors did not significantly affect the response variables of oat straw pellets. Microstructural examination of the pellets from steam-pretreated biomass revealed that the material contained particles that were more closely bonded and featured a cemented surface with fewer pores when compared to particles from untreated oat straw and sawdust. Microwave-assisted torrefaction was conducted on white spruce sawdust (WSS) at temperatures of 200 °C, 250 °C, and 300 °C and retention times of 5 min, 7 min, and 9 min in an inert environment. Torrefaction pretreatment is a mild form of pyrolysis that has the potential to produce high-quality raw material for making biofuel that serves as a replacement for coal in the bioenergy industry. The torrefaction process produces a solid carbon, commonly known as biochar, and condensable (torrefaction liquid (TL)) and non-condensable gases. In this study, torrefaction characteristics were investigated to observe its effects on the thermal and physiochemical properties of the pellets produced. During the torrefaction process, a significant mass loss associated with the decomposition of hemicellulose was observed. The hemicellulose content drastically reduced to approximately 1.8% from 19.25% and the cellulose content was reduced by approximately 10%, while the lignin gained approximately 35% as the severity increased. This led to an improvement in the higher heating value (HHV), hydrophobicity, bulk, particle density, pellet dimensional stability, and pellet density. However, the pellet tensile strength decreased as the torrefaction severity increased. Therefore, to enhance the tensile strength of the pellets, the introduction of a binder was necessary. Torrefaction liquid and sawdust were used as additives at different proportions during pelletization. The addition of binders (torrefaction liquid and sawdust) to the pellet formulation increased the tensile strength of the torrefied WSS by approximately 50%. The OH groups in the biomass break down to a limited degree due to dehydration. This hinders the formation of H bonds, thereby increasing the chances that the pretreated biomass will become hydrophobic. The Scanning Electron Microscope (SEM) graphs showed that the torrefied WSS pellets demonstrated more firmly glued surfaces with fewer pores spaces when set side by side with the raw pellets. The thermogravimetric analysis conducted showed that the torrefaction of WSS slightly reduced its thermal stability. Technoeconomic analysis of six case scenarios (wood pellet production from raw sawdust in a pellet plant (I), straw pellet production from raw oat straw in a pellet plant (II), integrated torrefied treated sawdust pelletization plant utilizing the torrefaction liquid (TL) as the pellet binder (III), integrated torrefied treated oat straw pelletization plant utilizing the torrefaction liquid (TL) as a pellet binder (IV), integrated steam treated sawdust pellet plant (V), and integrated steam treated oat straw pellet plant (VI)) was carried out to develop a process model for pellet production from sawdust and oat straw that uses torrefaction and steam explosion pretreatments prior to pelletization. The breakdown of equipment purchase cost showed that the torrefaction reactor is the most expensive unit with about 51% of the purchase cost. Scenarios 1, 2, 5, and 6 generated positive net present value at baseline model. Facility-dependent and feedstock costs were the major significant contributors to the pellet production cost. The minimum selling price of pellets obtained from Scenarios 1-6 were $113.4/t, $118.7/t, $283.4/t $298.7/t, $200.5/t, and $208.4/t, respectively. The profitability of pellet production as determined by the net present value (NPV), internal rate of return (IRR), and payback period was found to be sensitive to variations in feedstock cost.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».