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Record W4309162488 · doi:10.1007/s11356-022-24077-3

Life cycle assessment of photovoltaic electricity production by mono-crystalline solar systems: a case study in Canada

2022· article· en· W4309162488 on OpenAlexafffundabout
Ehsan Alam, Xiaohong Xu

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPhotovoltaic Systems and Sustainability
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLife-cycle assessmentEnvironmental sciencePhotovoltaic systemEcotoxicityEutrophicationElectricityEnvironmental engineeringFossil fuelWaste managementEnvironmental protectionEngineeringProduction (economics)ChemistryEcologyBiology

Abstract

fetched live from OpenAlex

Photovoltaic (PV) system is widely recognized as one of the cleanest technologies for electricity production, which transforms solar energy into electrical energy. However, there are considerable amounts of emissions during its life cycle. In this study, life cycle assessment (LCA) was used to evaluate the environmental and human health impacts of PV electricity production in Canada. The PV potential varies considerably among the provinces, with higher values in Manitoba (MB), Saskatchewan (SK), Alberta (AB), and southern Ontario (ON). A grid-connected slanted-roof mono-crystalline silicon (mono-Si) PV system with a capacity of 3 kWp (the peak power of the system in kilowatts) in Toronto, Ontario, was considered as the case study system. Ten impact categories were considered including (1) acidification, (2) carcinogenic, (3) ecotoxicity, (4) eutrophication, (5) fossil fuel depletion, (6) global warming, (7) non-carcinogenic, (8) ozone depletion, (9) respiratory effects, and (10) smog. Among the four components of the PV system, i.e., mono-Si panel, mounting system, inverter, and electric installation, the mono-Si panel production was the highest contributor in seven out of ten impact categories, including acidification (68%), eutrophication (60%), fossil fuel depletion (81%), global warming (77%), ozone depletion (88%), respiratory effects (74%), and smog (70%). For the other three processes, the electric installation contributed most to ecotoxicity at 58%, followed by the mounting system in the carcinogenic category (29%), and the inverter in the non-carcinogenic category (31%). By normalizing the impacts based on the reference scores in Canada, it was found that the ecotoxicity and carcinogenic categories had dominant contributions to the overall impact by 53% and 42%, respectively. The global warming potential impact was estimated as 79 gr CO2 eq /kWh, which is close to the mean value of 79.5 gr CO2 eq /kWh, reported in the literature. The sensitivity analysis indicated that a 10% increase in the panel and mounting system area will increase the ozone depletion and carcinogenic categories by 8.1% and 2.8%, respectively.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.293
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2022
Admission routes3
Has abstractyes

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