Évaluation de l'impact de l'opération des systèmes de puits à colonne permanente sur la qualité géochimique et microbiologique des eaux souterraines
Bibliographic record
Abstract
RÉSUMÉ: « RÉSUMÉ:Dans le contexte mondial de la réduction des gaz à effet de serre et de la recherche de solutions énergétiques durables, la géothermie, notamment par l’utilisation de puits à colonne permanente, apparaît comme une approche prometteuse pour la décarbonisation des bâtiments. Ces échangeurs de chaleur souterrains sont constitués de forages profonds ouverts dans le roc fracturé, utilisant l’eau souterraine comme fluide caloporteur. Cette eau est pompée, réinjectée dans le même puits sous le niveau dynamique, et sert au chauffage et à la climatisation des bâtiments. En période de pointe, une technique appelée "saignée" peut être mise en oeuvre pour dévier une partie de l’eau pompée vers un puits d’injection, stimulant ainsi l’écoulement et optimisant l’efficacité énergétique ainsi que l’utilisation des ressources en eau et température. Cependant, l’usage de l’eau souterraine comme fluide caloporteur, tout comme dans les systèmes en boucle ouverte, soulève des préoccupations importantes. L’exploitation de cette ressource peut altérer sa qualité géochimique et microbiologique. Les variations de température, de pression et d’oxygénation lors du fonctionnement des puits à colonne permanente peuvent modifier la composition chimique de l’eau et des communautés microbiennes, ce qui peut entraîner des défis opérationnels et environnementaux, tels que le colmatage des puits, la corrosion ou l’apparition de pathogènes. L’objectif principal de ce mémoire est d’évaluer l’impact des échangeurs de chaleur à puits à colonne permanente sur la qualité géochimique et microbiologique de l’eau souterraine. Pour atteindre cet objectif, un système composé de cinq puits à colonne permanente, utilisé pour le chauffage et la climatisation d’une école primaire à Mirabel, Québec, a été étudié sur une période de deux ans. L’échantillonnage a consisté à prélever l’eau souterraine directement dans les puits à colonne permanente afin de refléter la qualité de l’eau en entrée du système, ainsi que dans un réseau de puits d’observation aménagé en aval (comprenant sept puits, dont trois ont été échantillonnés).» ABSTRACT: «ABSTRACT:In the global context of reducing greenhouse gas emissions and seeking sustainable energy solutions, geothermal energy, particularly through the use of standing-column-wells, emerges as a promising approach for building decarbonization. These underground heat exchangers consist of deep open boreholes in fractured rock, utilizing groundwater as a heat-transfer fluid. The water is pumped, reinjected into the same well below the dynamic water level, and used for heating and cooling buildings. During peak periods, a technique known as "bleed" may be implemented, where a portion of the pumped water is diverted to an injection well, thereby enhancing flow and optimizing energy efficiency as well as the use of water and temperature resources. However, using groundwater as a heat-transfer fluid, as in open-loop systems, raises significant concerns. Exploitation of this resource may alter its geochemical and microbiological quality. Variations in temperature, pressure, and oxygenation during the operation of standing column wells can modify the chemical composition of the water and its microbial communities, potentially leading to operational and environmental challenges such as well clogging, corrosion, or the emergence of pathogens. The primary objective of this thesis is to assess the impact of standing column well heat exchangers on the geochemical and microbiological quality of groundwater. To achieve this goal, a system consisting of five standing column wells used for heating and cooling a primary school in Mirabel, Québec, was studied over a two-year period. Sampling involved collecting groundwater directly from the standing column wells to reflect the inlet water quality of the system, as well as from a downstream network of monitoring wells (comprising seven wells, three of which were sampled). Low-flow sampling was performed to measure in situ physicochemical parameters such as pH, temperature, and specific conductivity. Samples were collected for advanced chemical and microbiological analyses. These analyses encompassed a wide range of parameters and employed cutting-edge techniques, including Next-Generation Sequencing. This method, based on 16S rRNA gene sequences, allowed the identification of a wide diversity of bacteria and archaea in the environmental samples.»
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 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 | 0.000 | 0.000 |
| 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) | 0.004 | 0.001 |
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".