Possibilities of Using Industrial Waste Heat for Heating Greenhouses in Northern Greece
Bibliographic record
Abstract
The possibility of using the rejected heat from lignite-fired power plants for heating greenhouses in northern Greece has been examined. Although currently industrial waste heat is used for district heating in a few towns in Greece, its use in agriculture has not been reported so far. Due to many environmental and economic benefits symbiosis of industrial and agricultural activities is promoted in many countries. Greenhouses in northern Greece utilize mainly natural gas as heating fuel. However heat recovery from the existing power plants and its use in greenhouses could increase their energy efficiency and reduce the thermal pollution. It will also decrease the use of fossil fuels in greenhouses and the resulting carbon emissions as well. Their heating requirements have been estimated at 170 W/m2 and the required hot water temperatures are 50-60 oC below the required water temperature in district heating systems, at 120 oC. Currently the price of heat sold in the district heating system in the town of Kozani is 0.0435 €/KWh, which is very attractive for heating greenhouses compared with other existing methods or fuels. It has been estimated that the heat recovery from the power plants at 70 MWth could cover the heating needs of 41.2 ha of modern agricultural greenhouses in northern Greece. Recycling of industrial waste heat in greenhouses in northern Greece, apart from the resulting environmental benefits, will offer a competitive advantage, increasing the profitability of those enterprises.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".