Clean energy strategies and pathways to meet British Columbia's decarbonization targets
Bibliographic record
Abstract
Abstract British Columbia (BC) recently released the CleanBC policy framework to promote clean energy and mitigate greenhouse gas (GHG) emissions. However, CleanBC lacks concrete measures to reverse the growth of energy demand. Although BC has rich biomass and hydroelectric resources, it remains unclear whether these renewable resources will be enough to meet future energy demand. In this work, the potential in BC for increasing production and use of bioenergy, renewable electricity, and low‐carbon hydrogen was assessed, and the most efficient measures were identified. Energy scenarios were constructed to explore BC's future renewable energy demands for meeting GHG mitigation targets. The results show that CleanBC will drastically raise renewable energy demands but fail to achieve the 2030 target without radical demand reduction. Seen as the core strategy in CleanBC, electrification will require at least 60 PJ of additional electricity supply for 2030 and 160 PJ for carbon neutrality in 2050. This implies implementing wind and solar generation in capacities comparable to massive hydroelectric projects. Alternative to electrification is the bioenergy‐centred strategy. Existing waste biomass must be fully exploited; even then, roughly 250 and 460 PJ of additional primary bioenergy will be needed for 2030 and 2050, respectively, well beyond any foreseeable waste supply within BC. Hence, it is essential to utilize all the available biomass and renewable electricity resources and promote a diversified renewable energy portfolio. Hydrogen used as an energy carrier must be produced from natural gas with carbon capture to avoid competition for the limited renewable energy resources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".