BIPV/BAPV Barriers to Adoption: Architects' Perspectives from Canada and the United States
Bibliographic record
Abstract
Solar photovoltaic technology (PV) is a promising clean energy source that assists in climate change mitigation. This is due to solar PV having minimal greenhouse gas emissions when operating compared to burning fossil fuel. Solar PV is also a versatile technology owing to its multiple applications within the built environment. \nBuildings are responsible for nearly half of the world’s energy consumption; thus, reducing buildings’ energy usage through environmentally-responsive design techniques, in addition to the application of PV products, can not only assist in reducing the energy consumed by buildings, but also contributes to mitigating the adverse effects of climate change. Architects, in particular, play a substantial role in achieving sustainable/environmentally responsive designs; hence, their collaboration is essential. \nThis study investigated American and Canadian architects’ level of awareness and interest in Building Integrated Photovoltaic (BIPV) and Building Applied Photovoltaic (BAPV) products. It also aimed to shed light on the barriers that are responsible for slowing down the adoption process. This study was conducted in two phases: a) a web-based survey questionnaire administered to architects who have an active membership in the Royal Architectural Institute of Canada (RAIC), and the American Institute of Architects (AIA); b) in-depth interviews with architects and key informants in the solar industry. \nThe results indicated that architects are aware of PV benefits and the products available for buildings’ application; however, they lack essential practical knowledge. Furthermore, the results indicated that PV systems’ capital cost is the major perceived barrier to PV adoption in the building industry. Other reported barriers are: the lack of government financial incentives in some jurisdictions, the problematic grid connection process and the lengthy application lead times. \nRecommendations based on this study’s results include, but are not limited to, providing financial support mechanisms, simplifying the administrative procedures of financial support mechanisms and grid access permits, and offering education and training to architects through architectural associations and academic institutions.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".