Assessing the environmental health and safety risks of solar energy production
Bibliographic record
Abstract
Solar energy production has gained significant traction as a promising alternative to fossil fuels, yet its widespread adoption raises questions regarding its environmental health and safety (EHS) risks. This review presents an overview of the current state of research in assessing these risks associated with solar energy production. Firstly, it examines the environmental impacts of solar energy, including the life cycle assessment of photovoltaic (PV) panels and solar thermal systems. Key considerations include the energy and resources required for manufacturing, transportation, installation, operation, and end-of-life disposal or recycling of solar panels. Furthermore, the potential for land use change, habitat disruption, and biodiversity loss due to large-scale solar installations is addressed. Secondly, the review discusses the safety risks associated with solar energy production, focusing on occupational health and safety hazards for workers involved in manufacturing, installation, maintenance, and decommissioning of solar energy systems. It examines exposure to hazardous materials such as lead, cadmium, and silicon during the manufacturing process, as well as the risks of falls, electrical hazards, and other workplace accidents during installation and maintenance activities. Moreover, the review highlights emerging technologies and best practices aimed at mitigating EHS risks in solar energy production. These include advancements in PV panel recycling technologies, improvements in manufacturing processes to reduce environmental impacts, and enhanced safety protocols and training for workers in the solar energy industry. While solar energy offers numerous environmental and economic benefits as a renewable energy source, it is essential to comprehensively assess and manage its EHS risks throughout the life cycle of solar energy systems. This review underscores the importance of ongoing research, innovation, and regulatory oversight to ensure the sustainable and safe deployment of solar energy technologies in the transition towards a low-carbon future.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".