Bioenergy Production from Pretreated Wood Sawdust
Notice bibliographique
Résumé
Every year around the world, a massive amount of wood waste (233 M m3) is produced by the wood processing industry which is underused and can be exploited for added value products. Canada, among the wood waste producers generates 8.8 M m3. The wood pellet industry is well-established, and it has solved many of the logistical challenges associated with the large-scale handling, transportation, and processing of biomass such as wood sawdust. Furthermore, the effect of pre-treatments such as steam treatment and torrefaction on the quality of wood pellets for fuel and energy applications is of huge importance. Hence, the overall goal of this study is preparing woody biomass for production of biofuel pellets using steam explosion and torrefaction pre-treatment methods. Additionally, final application of these pretreated pellets in combined heat and power plant (CHP) is targeted as another purpose of this study. There are two types of pre-treatments for this study: steam explosion and torrefaction. For each method, the physical (bulk, particle and pellet densities, dimensional stability), mechanical (tensile strength) and fuel (ash and higher heating values (HHV)) properties of pretreated biomass/pellet were determined. The steam explosion process was performed at three different temperatures (180, 200 and 220 °C) and times (3, 6 and 9 min). The majority of the qualities were improved with high temperature and residence time. According to the analysis of variance (ANOVA), as a result of steam treated sawdust, temperature had more impact on responses than time; also, the diametral compression experiment demonstrated better tensile strength of treated pellets over non-treated pellets. The optimized conditions for steam treatment of sawdust were set at 215 °C for 9 min. The quality of this treated sample for example its pellet density was 1266 kg/m3 which was exceptional. The second pre-treatment of wood sawdust was torrefaction which was conducted through two different sets of recorded temperatures including the inside and outside temperature of the batch torrefaction unit (BTU). The residence times of sawdust inside the reactor were kept at 15, 30 and 45 min for various temperatures (230, 260 and 290 °C). Before pelletization, biochar was conditioned with water to reach a moisture content of 10% and then it was mixed with or without binders such as steam treated sawdust (optimized at 215 °C for 9 min) at various proportions. After determining the physical and mechanical properties of torrefied sawdust or pellets, it was found that the tensile strength of pellets with 10 and 20% steam-treated (ST) binder were enhanced remarkably (around 30% and 340%) compared to the control pellet without binders. As a result of using the outside temperature (OT), torrefied samples had higher heating values (roughly 8, 12 and 32% corresponding to 230, 260 and 290 °C OT, respectively) compared to selected torrefied samples based on the inside temperature (230 °C IT). The most preferable pre-treatment conditions for torrefied samples were temperature of 230 °C for 45 min using the outside temperature of the reactor. The mass yields of such samples were 72% for biochar and 13% for torrefaction liquor. From the liquor, useful by-products such as acetic acid and furfural can be extracted (17 and 30%, respectively). In order to ascertain the feasibility of the above mentioned processes in a bioenergy system, the technical and economical evaluations were performed using the generated flowsheets in SuperPro designer. The flowsheets demonstrated several possible scenarios of producing pellets, heat and electricity or a combination of all products and utilities. As a result of techno-economic analysis (TEA) of these processes, torrefied pellets and accompanied by-products (furfural, acetic acid, etc.) along with heat and electricity had the most favorable indices (net present value: US$38.29 million, internal rate of return: 33.2% and payback time: 3.38 yr); Although the conventional method of using sawdust for only pellet production had less payback time of 2.5 yr. Valorization of waste streams from steam explosion or torrefaction liquors introduced new added value products which could be sold in regional/overseas markets. Before implementation of any bioenergy project, its environmental footprint needs to be evaluated and taken into account along with its economic feasibility. For this purpose, produced pellets (from untreated, steam treated or torrefied sawdust) in one group and combined heat and electricity production from raw sawdust and pretreated pellets in another group were assessed and compared in terms of environmental impact categories and weighed/normalized damage indices. The results showed that in both groups (with/without electricity generation), steam treated pellets caused more damage to the environment in contrast to torrefied pellets which were the safest alternative (e.g. in the group without electricity production: global warming (0.56 and 4.8 x 10-3 kg CO2 eq, respectively) compared to the group with electricity production (0.38 and -0.79 kg CO2 eq, respectively)). The weighed damage indices of steam treated and torrefied pellets without CHP incorporation (e.g. climate change (56.88 and -0.83 µPt, respectively)) was far less than those with CHP incorporation (e.g. climate change (0.038 and -0.79 mPt, respectively)). The result of the life cycle assessment indicated that torrefied pellet production (without integrated CHP) was the most environmentally friendly bioenergy process among others. This research contributed to the academic knowledge regarding a suitable substitute to current fossil-based solid fuels such as coal for producing heat and electricity. Additionally, the outcome of this study proved that woody biomass after pre-treatment and densification can be exploited economically along with novel added-value products to meet the growing demand for energy and bioproducts. The eco-friendly torrefied wood pellets with high mechanical and physical quality as well as high energy value may play a major role in the future of this industry.
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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».