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Record W2122966642 · doi:10.1109/eicccc.2006.277213

Regional Energy Integration to Reduce GHG Emissions and Improve Local Air Quality

2006· article· en· W2122966642 on OpenAlexaffabout
Ziting Huang, Hsiaotao T. Bi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSustainable Industrial Ecology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGreenhouse gasRenewable energyEnvironmental scienceGreenhouseBiomass (ecology)BiofuelBarnManureAir quality indexEmission inventoryWaste managementBioenergyManure managementEnvironmental engineeringEngineeringMeteorologyAgronomyCivil engineeringEcologyGeography

Abstract

fetched live from OpenAlex

Greenhouse industry is a fast growing and energy-intensive industry in Canada. The average greenhouse requires about 2.85 GJ/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /year primarily from natural gas combustion for providing both heat and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> for stimulating plant growth, with a total annual CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emission 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 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in size showed that a net reduction of 320 tonnes/year CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> eq. 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 NH <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> S 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, SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> and CO to levels acceptable for greenhouse operations before the flue gas CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> can be directly utilized in greenhouse for stimulating plant growth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.259
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2006
Admission routes2
Has abstractyes

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