Measuring and modelling the land‐use intensity and land requirements of utility‐scale photovoltaic systems in the Canadian province of Ontario
Bibliographic record
Abstract
Abstract This paper summarizes the land‐use impacts and land requirements of utility‐scale photovoltaic (U‐PV) systems in the Canadian province of Ontario. The empirical research is based on an analysis of approximately 95 projects representing over 1000 MW of U‐PV systems province‐wide. Findings from this empirical assessment are combined with information about future technological advances in order to develop a modelling framework that can forecast land requirements of U‐PV systems within evolving market and technology contexts. Specifically, the model is used to estimate the land requirements of U‐PV systems in a hypothetical future in which U‐PV systems supply all mid‐day electricity needs in Ontario, including added demands from a completely electrified light‐duty vehicle fleet. Under this scenario, on an installed capacity basis and assuming that 20% of mid‐day electricity demand is met with rooftop PV, an area equivalent to 0.5% to 8.5% of Ontario's agricultural land would be required, depending on panel efficiencies and system packing factors. These land requirements are manageable, particularly as more land‐efficient technologies are deployed and as regulations are designed to mitigate the land‐use impacts of U‐PV systems.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".