Development of a GIS based Multicriteria Decision Support System for Organic Waste Management: Izmir Case Study
Notice bibliographique
Résumé
The purpose of this research is to develop a geographic information system (GIS) based multicriteria decision support system that can take into account environmental and economic factors for modeling and comparison of incineration, anaerobic digestion and composting technologies in organic waste management system (organic municipal solid waste and livestock manure); and to implement the system by performing a case study for the City of Izmir.Regulations limiting the disposal of organic municipal solid waste at landfills and application of livestock manure to fertilize agricultural lands together with energy and compost production purposes increased the application of various organic waste management technologies.Because organic waste is distributed dispersedly, finding the optimal number, capacity, and sites for organic waste management facilities are key issues to minimize transfer costs and transfer-induced CO2 emissions.GIS combined with multicriteria decision making (MCDM) methods have been used to assess biomass availability and suitable plant sites in some studies, for instance, [1]-[5].However, there is still a need for a decision support system that systematically evaluates qualitative and quantitative criteria for complex multicriteria decisions to design, evaluate and prioritize decision alternatives in order to assess sustainability of organic waste management technologies.An integrated approach of fuzzy logic and analytical hierarchy process MCDM methods and GIS is being used to model incineration, anaerobic digestion and composting technologies for organic waste management.The methodology includes; development of a proper geospatial database for organic waste, analysis of spatial distribution and energy potentials of organic waste, pre-screening process for suitable plant sites, determination of potential plant sites by multicriteria decision analysis, determination of locations and capacities by p-median solution approach, number and capacity of the system in relation to economic sustainability, and cost-benefit analysis.This methodology is being implemented for the first time to determine the optimal number, capacity, and plant sites for various organic waste management technologies through integration of environmental and economic factors.This research represents a big step in establishment of local decision support system on organic waste management.An extensive work put into data collection and development of the geospatial database.Spatial availability and energy potentials of organic municipal solid waste and livestock manure were analyzed.Areas that are environmentally sensitive and limited in use by regulations were excluded with the aid of GIS.Three different organic waste management scenarios were investigated based on the needs of City of Izmir; 1) incineration of mixed municipal solid waste and anaerobic digestion of livestock manure, 2) anaerobic co-digestion of organic municipal waste and livestock manure, and 3) composting of organic municipal waste and livestock manure.Daily energy potentials were calculated as 14.47 TJ and 7.95 TJ for scenario 1 and 2, respectively.8805 ton/day compost production was calculated for scenario 3.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».