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Record W6990191656

DERIVATION OF FIRST-ORDER DECAY HEAT GENERATION FUNCTION AND PREDICTION OF THERMAL ENERGY POTENTIAL FOR A MUNICIPAL SOLID WASTE LANDFILL

2021· dissertation· en· W6990191656 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLandfill gasMethaneHeat generationWork (physics)Municipal solid wasteThermal energyElectricity generationThermal
DOInot available

Abstract

fetched live from OpenAlex

As the consequences of green house gas production at landfills become more apparent to both the public and private sector, work has been performed at many landfills over the last two decades to explore the mechanisms controlling gas and heat generation within buried solid waste. Mechanisms and numerical models of the physical, chemical, and biological processes have been studied in order to better predict the conditions within the waste fill and the rates of gas and heat production. These models are useful tools for operators and designers to develop plans for mitigating some negative environmental impacts of landfilling, by collecting and using the recoverable natural gas or thermal energy to supplement conventional energy sources.\nThe Northern Landfill near Saskatoon, SK is a private landfill where the methane and thermal energy potential of the site is of interest. The landfill has been in operation since 1987 and contains approximately 2.5 megatonnes of waste. Vertical temperature distribution within the buried waste was measured using thermistors installed in boreholes, which were advanced using a sonic drill rig. Transient temperature data was collected from four locations across the top of the landfill, with two of the locations providing daily average temperatures with depth over a period of 800 days (2.2 yr). A 1D heat transport model was developed to compare calculated outputs to in-situ site temperature data over a 1-year period. The model was also used to simulate cell construction, waste placement, and heat generation over the life of the landfill.\nThe background and theory describing anaerobic landfill gas generation available in the literature was reviewed. Research completed to date in the literature predicting or estimating heat generation and transport within landfills was also reviewed. In the literature, heat generation is stated to be related to gas generation through anaerobic digestion, though no exact conversion factor was agreed upon. Empirically derived equations that define transient heat generation were reviewed however it was found that the variables and methodology did not relate heat generation to gas generation or degradable organic matter of the waste. Climatic factors of annual precipitation and average annual temperature were two of the variables governing the empirical heat generation function, however the climate experienced by the Northern Landfill did not produce a useable curve. Therefore, a first-order decay function was derived to represent the transient heat generation rate associated with the anaerobic digestion of organic matter in the landfill environment. This offers a mechanistic approach to defining heat generation in landfills, as opposed to empirical definitions which are available in the literature. The two variables defining the function are biochemical heat potential (BHPULT), comparable to biochemical methane potential (BMP or L0) in the gas generation literature, and a decay rate k.\nThe results of the 1D heat transport model which used a first-order decay function for heat generation suggest that a single k value representing the average decay rate poorly defined the dependency of heat generation to microbial populations and environmental conditions within the landfill. As a result, heat generation rates predicted by the derived function over the 2018 to 2019 monitoring period were significantly higher than those estimated through model calibration. Nonetheless, the model was able to simulate waste placement and the accumulation of thermal energy at the Northern Landfill, reaching temperatures at depth equivalent to those measured in the field in the year 2019. Two locations were modelled within the core of the landfill. BHPULT was predicted to be between 115 and 240 MJ per cubic metre of waste (MSW). BMP and equivalent cellulose content (Ceq) of the MSW was calculated from BHPULT, resulting in ranges of 19 to 120 LCH4/kgMSW and 4 to 27 % weight respectively. Peak heat generation rates from the first-order decay function were between 0.13 and 0.28 W/m3. The lower limits of the ranges results from the location within older average MSW age (16.2 y) and the higher limits from the younger location (6.6 y). Calibrated present-day heat generation rates were between 0.020 and 0.148 W/m3 at the older location and 0.009 and 0.205 W/m3 at the younger location.\nIt is recommended that an improvement to the first-order decay function be implemented which incorporates a stepwise function governing the value of k, dependent on the temperature of the surrounding waste. The k value should be limited by a maximum potential decay rate of 0.12 y-1 (3.3 x 10-4 d-1) at temperature values reported in the literature optimal for mesophilic microbial activity (20 to 45 °C). The k value should decrease until a threshold temperature reported in the literature at which no methanogenesis takes place (a k value of zero). A dependency of the decay rate to moisture availability should also be included, as well as the inclusion of updated modelling parameters or waste layer geometries as they are investigated further.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.162
Teacher spread0.155 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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