Characterization of alloying components in galvanic anodes as potential environmental tracers for heavy metal emissions from offshore wind structures
Bibliographic record
Abstract
The impact of offshore constructions on the marine environment is unknown in many aspects. The application of Al- and Zn-based galvanic anodes as corrosion protection results in the continuous emission of inorganic matter (e.g. >80 kg Al-anode material per monopile foundation and year) into the marine environment. To identify tracers for emissions from offshore wind structures, anode materials (Al-based and Zn-based) were characterized for their elemental and isotopic composition. An acid digestion and analysis method for Al and Zn alloys was adapted and validated using the alloy CRMs ERM®-EB317 (AlZn6CuMgZr) and ERM®-EB602 (ZnAl4Cu1). Digests were measured for their elemental composition by ICP-MS/MS and for their Pb isotope ratios by MC ICP-MS. Ga and In were identified as potential tracers. Moreover, a combined tracer approach of the elements Al, Zn, Ga, Cd, In and Pb together with Pb isotope ratios is suggested for a reliable identification of offshore-wind-farm-induced emissions. In the Al anodes, the mass fractions were found to be >94.4% of Al, >26200 mg kg−1 of Zn, >78.5 mg kg−1 of Ga, >0.255 mg kg−1 of Cd, >143 mg kg−1 of In and >6.7 mg kg−1 of Pb. The Zn anodes showed mass fractions of >2160 mg kg−1 of Al, >94.5% of Zn, >1.31 mg kg−1 of Ga, >254 mg kg−1 of Cd, >0.019 mg kg−1 of In and >14.1 mg kg−1 of Pb. The n(208Pb)/n(206Pb) isotope ratios in Al anodes range from 2.0619 to 2.0723, whereas Zn anodes feature n(208Pb)/n(206Pb) isotope ratios ranging from 2.0927 to 2.1263.
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) | 0.007 | 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".