CARBON FOOTPRINT ANALYSIS: A COMPARATIVE STUDY OF FOSSIL FUEL AND RENEWABLE POWER GENERATION IN EDMONTON, ALBERTA
Bibliographic record
Abstract
Addressing climate change in Alberta, Canada, is imperative for sustainable development, especially considering the significant contributions in the province of greenhouse gas emissions. Using Python-based methodologies, this stud is a comprehensive comparative analysis of carbon footprints, fossil fuel, and renewable energy systems in Edmonton, Alberta. Our analysis reveals the substantial environmental impact of fossil fuel-based energy generation, highlighting the urgent need for transitioning towards renewable energy to mitigate climate change. Our proposed renewable systems show that a natural gas genset emits 1,275,320 kg of CO2 annually, while solar panels avoid approximately 14,095,500 kg of CO2 emissions over 25 years. Wind energy systems achieve nearly 98.5% lower GHG emissions than natural gas gensets. We offer nuanced insights into each energy source's environmental impacts and economic considerations, emphasizing the critical role of renewable energy in achieving carbon emissions reduction targets and promoting sustainable development in Alberta.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".