Thermal Depolymerisation of Digestate for Biofuel and Biomaterial Production
Notice bibliographique
Résumé
The global upsurge in the application of anaerobic digestion technologies to simultaneously manage agricultural waste and generate cheap bioenergy has resulted in the generation of large masses of the associated biogas digestate.This digestate must be processed and the liquid and solid fractions treated to eliminate zoonotic agents [1], recover useful water and recover cheap fertiliser respectively.Crucially however, existing digestate processing technologies are very costly and complex [2] with minimal value extractions achieved.To facilitate a cheaper and less complex digestate handling process, the present study has identified hydrothermal processing as a sufficiently green and sustainable digestate handling technological alternative.This is because the hydrothermal processing technology will facilitate the production of valuable products from high moisture containing digestate, circumventing the need for preliminary energy drying operations while also eliminating the need for additional digestate sterilisation steps, due to the conditions of high temperature and high pressure typically imposed.An investigation into the hydrothermal processing of digestate for optimal co-production of insoluble biochar product as a soil additive, which enhances soil physicochemical properties, and hydrophobic biocrude product, which has a higher heating value (30-38 MJ/kg [3]) comparable to petroleum crude 1 (~43 MJ/kg), has therefore been undertaken in the present study.Experimental investigations established that optimal co-production masses of the desired product streams namely, energy dense biocrude and insoluble solid biochar of 205 g and 1,377 g respectively are feasible when 100 kg of high moisture digestate containing only 3.02 % wt.total solids is utilised as the feedstock.Other hydrothermal liquefaction products namely soluble solids in the post-HTL water phase and gaseous products are measured to be 559 g and 878 g, respectively.The poor optimal biocrude yield is expected since the mass of biocrude formed during the hydrothermal liquefaction process is largely dependent on the presence of lipid molecules in the feedstock [4].This implies that since the original digestate sample contains only 1.6 wt.% lipids (on a dry digestate basis), a small mass of the biocrude product is anticipated.The measured high biochar yield is also expected, because the original digestate sample contains high concentrations of carbohydrates (41.4 wt.%) and ash (39.53 wt.%) on a dry digestate basis with previous studies establishing a strong correlation between the carbohydrate and ash contents of the feedstock and biochar yield [5].We have also investigated the degree of carbonisation of digestate-sourced biocrude in order to amplify compositional similarities between the biocrude products and liquid fossil sourced fuels.For completeness an investigation into the chemical compound composition of the optimally produced biocrude has been undertaken as a basis for providing an improved understanding of its usefulness as a petroleum crude replacement.Some crucial agronomic properties of the optimally generated biochar product, namely, the thermal stability, pH value, electric conductivity, porosity and nutrient content have also been investigated as a precursor to an exploration of the sufficiency of biochar in the amelioration of agricultural soils.
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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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».