Regional Energy Integration to Reduce GHG Emissions and Improve Local Air Quality
Bibliographic record
Abstract
Greenhouse industry is a fast growing and energy-intensive industry in Canada. The average greenhouse requires about 2.85 GJ/m2/year primarily from natural gas combustion for providing both heat and CO2for stimulating plant growth, with a total annual CO2emission in the order of 2.5 million tones. The substitution of natural gas by biofuels will have a great potential for GHG emission reduction. The deterioration of local air quality in regions with intensive agricultural activities, on the other hand, is closely related to the emissions from animal barns, from manure storage, handling and land spreading. Approaches to address energy and emission issues for each industry in isolation have failed in the past because of the higher emissions associated with biomass fuel combustion and higher waste management cost for manure. In this paper, we present a systems approach for solving the demand of low-cost energy in greenhouse operation and the emission control associated with manure disposal by constructing a local eco-industrial network (EIN). In the new integrated operation, the manure waste from the barn will be used as a renewable fuel source for the greenhouse heating, while the increased air emission from the green houses is compensated by the reduction of emissions from manure storage, handling and land spreading. A preliminary analysis based on an average greenhouse of 1000 m2in size showed that a net reduction of 320 tonnes/year CO2eq. can be achieved in the integrated system, translating into an potential reduction of 1.2 million tonnes per year in BC and 3.2 million tones per year nationwide if all existing greenhouses are converted to the integrated system. On the other hand, odor gas emissions including NH3and H2S can be eliminated in the integrated system. For manure-to-biogas energy conversion option, capital and operational cost will be a major concern and needs to be analyzed in the future. For direct manure combustion option, emission control equipment is needed to reduce emissions of particulate matters, SOxand CO to levels acceptable for greenhouse operations before the flue gas CO2can be directly utilized in greenhouse for stimulating plant growth.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".