Status of Existing Biomass Gasification and Pyrolysis Facilities in North America
Notice bibliographique
Résumé
A search of websites for firms in the United States and Canada identifying themselves as gasification or pyrolysis system suppliers indicates that there are a number of existing facilities where their technologies are installed. According to the websites, the companies’ existing installations focus on processing biomass and industrial residuals, rather than mixed refuse. The biomass processed, according to the websites includes yard waste, wood, and wastewater treatment sludge. The existence of these facilities provides a potential opportunity for communities in areas with a high density of development, who experience difficulties in siting “traditional” facilities for processing these biomass wastes. Such traditional facilities include yard waste and sludge composting, wood mulching, sludge drying, chemical treatment or pelletization, and combustion-based waste-to-energy. As a result of these facility siting difficulties, these communities often resort to long-haul trucking of the biomass wastes to processing facilities or landfills. Certain potential advantages associated with gasification and pyrolysis technologies could ease the siting difficulties associated with the traditional technologies, due to smaller facility footprints, reduced odors, and the potential for energy production through combustion of syngas/synfuel to power internal combustion engines or produce steam using boilers. Lower stack emissions may result as compared to direct combustion of biomass wastes. Locally sited biomass gasification facilities could reduce the environmental impacts associated with long-haul trucking and generate an energy product to meet nearby demand. Research has been conducted by the Author on behalf of client communities to identify gasification and pyrolysis facilities in the United States and Canada that are in actual operation in order to assess their potential for processing biomass wastes and for providing the advantages listed above. Website reviews, interviews with company representatives, and facility visits were conducted in order to assess their potential for development to meet the biomass management objectives of the communities. The information sought regarding design and operating parameters included the following: • Year of start-up. • Availability. • Process description. • Design throughput. • Actual throughput. • Energy product. • Energy generation capability and technology. • Residuals production and characteristics. • Emissions. • Construction and operating costs. In addition, the system suppliers’ business status was addressed in terms of their readiness and capabilities to participate in the development of new facilities. Confidentiality requirements imposed by the system suppliers may prevent the identification of the company name or facility location and certain details regarding the system designs.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,007 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».