Greenhouse Gas Emissions Calculation Methodology in Thermal Power Plants: Case Study of Iran and Comparison With Canada
Bibliographic record
Abstract
Nowadays, the global climate change has been a worldwide concern and the greenhouse gases (GHG) emissions are considered as the primary cause of that. The United Nations Conference on Environment and Development (UNCED) divided countries into two groups: Annex I Parties and Non-Annex I Parties. Since Iran and all other countries in the Middle East are among Non-Annex I Parties, they are not required to submit annual GHG inventory report. However, the global climate change is a worldwide phenomenon so Middle Eastern countries should be involved and it is necessary to prepare such a report at least unofficially. In this paper the terminology and the methods to calculate GHG emissions will first be explained and then GHG emissions estimates for the Iranian power plants will be presented. Finally the results will be compared with GHG emissions from the Canadian electricity generation sector. The results for the Iranian power plants show that in 2005 greenhouse gas intensity for steam power plants, gas turbines and combined cycle power plants were 617, 773, and 462 g CO2eq/kWh, respectively with the overall intensity of 610 g CO2eq/kWh for all thermal power plants. This GHG intensity is directly depend on efficiency of power plants. Whereas, in 2004 GHG intensity for electricity generation sector in Canada for different fuels were as follows: Coal 1010, refined petroleum products 640, and natural gas 523 g CO2eq/kWh, which are comparable with same data for Iran. For average GHG intensity in the whole electricity generation sector the difference is much higher: Canada 222 vs. Iran 610g CO2eq/kWh. The reason is that in Canada a considerable portion of electricity is generated by hydro-electric and nuclear power plants in which they do not emit significant amount of GHG emissions. The average GHG intensity in electricity generation sector in Iran between 1995 and 2005 experienced 13% reduction. While in Canada at the same period of time there was 21% increase. However, the results demonstrate that still there are great potentials for GHG emissions reduction in Iran’s electricity generation sector.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".