Decarbonization via long-distance transmission of hydropower is cost-effective
Bibliographic record
Abstract
Hydropower is associated with substantially lower carbon emissions than fossil fuels and can satisfy baseload electricity demand unlike wind and solar power. In the northern United States, imports of Canadian hydropower account for a large and growing share of the electricity portfolio. For example, in New England, Canadian hydropower increased from 10% to 21% of electricity supplied to consumers between 2010 and 2020. These imports are increasingly dependent on capital-intensive long-distance transmission projects between the Canadian border and U.S. urban centers. While costs of these projects are clearly defined in dollars, benefits accrue in diverse forms, ranging from avoided air pollution and greenhouse gas emissions to reduced fuel and operation costs. This severely complicates cost-benefit analysis and has led to controversy over the role of Canadian hydropower in U.S. renewable energy transitions. We develop a probabilistic, multiattribute economic valuation model to explicitly compare direct and environmental costs and benefits of energy transition scenarios. We apply this model to the New York City area, where the recent closure of a ~2,000 MW nuclear power plant has increased demand for fossil fuel generation, and a proposed $4-billion long-distance hydropower transmission project has caused disagreement among environmental groups and other stakeholders. We find that coupling long-distance hydropower transmission with planned build-out of wind and solar reduces net total costs over 2021-2050 on the order of tens of billions of dollars, primarily due to avoided greenhouse gas emissions and air pollution whose economic value outweighs the added upfront capital costs. Long-distance hydropower transmission averts health and property impacts of air pollution from fossil fuel generators associated with an economic value on the order of hundreds of millions of dollars concentrated in vulnerable communities facing disproportionate environmental risks. These findings are robust to an extensive sensitivity analysis. This model provides a novel, transparent framework for supporting decision-making about long-distance hydropower transmission elsewhere.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".