Development of a GIS based Multicriteria Decision Support System for Organic Waste Management: Izmir Case Study
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".