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Record W4366602871 · doi:10.1007/s43630-023-00371-y

Stratospheric ozone, UV radiation, and climate interactions

2023· article· en· W4366602871 on OpenAlexaboutno aff
G. Bernhard, Alkiviadis Bais, P. J. Aucamp, Andrew Klekociuk, Ben Liley, Richard McKenzie

Bibliographic record

VenuePhotochemical & Photobiological Sciences · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersAristotle University of Thessaloniki
KeywordsOzoneAtmospheric sciencesEnvironmental scienceOzone layerRadiationOzone depletionUltraviolet radiationClimatologyAstrobiologyMeteorologyGeographyPhysicsChemistryRadiochemistryGeologyOptics

Abstract

fetched live from OpenAlex

Abstract This assessment provides a comprehensive update of the effects of changes in stratospheric ozone and other factors (aerosols, surface reflectivity, solar activity, and climate) on the intensity of ultraviolet (UV) radiation at the Earth’s surface. The assessment is performed in the context of the Montreal Protocol on Substances that Deplete the Ozone Layer and its Amendments and Adjustments. Changes in UV radiation at low- and mid-latitudes (0–60°) during the last 25 years have generally been small (e.g., typically less than 4% per decade, increasing at some sites and decreasing at others) and were mostly driven by changes in cloud cover and atmospheric aerosol content, caused partly by climate change and partly by measures to control tropospheric pollution. Without the Montreal Protocol, erythemal (sunburning) UV irradiance at northern and southern latitudes of less than 50° would have increased by 10–20% between 1996 and 2020. For southern latitudes exceeding 50°, the UV Index (UVI) would have surged by between 25% (year-round at the southern tip of South America) and more than 100% (South Pole in spring). Variability of erythemal irradiance in Antarctica was very large during the last four years. In spring 2019, erythemal UV radiation was at the minimum of the historical (1991–2018) range at the South Pole, while near record-high values were observed in spring 2020, which were up to 80% above the historical mean. In the Arctic, some of the highest erythemal irradiances on record were measured in March and April 2020. For example in March 2020, the monthly average UVI over a site in the Canadian Arctic was up to 70% higher than the historical (2005–2019) average, often exceeding this mean by three standard deviations. Under the presumption that all countries will adhere to the Montreal Protocol in the future and that atmospheric aerosol concentrations remain constant, erythemal irradiance at mid-latitudes (30–60°) is projected to decrease between 2015 and 2090 by 2–5% in the north and by 4–6% in the south due to recovering ozone. Changes projected for the tropics are ≤ 3%. However, in industrial regions that are currently affected by air pollution, UV radiation will increase as measures to reduce air pollutants will gradually restore UV radiation intensities to those of a cleaner atmosphere. Since most substances controlled by the Montreal Protocol are also greenhouse gases, the phase-out of these substances may have avoided warming by 0.5–1.0 °C over mid-latitude regions of the continents, and by more than 1.0 °C in the Arctic; however, the uncertainty of these calculations is large. We also assess the effects of changes in stratospheric ozone on climate, focusing on the poleward shift of climate zones, and discuss the role of the small Antarctic ozone hole in 2019 on the devastating “Black Summer” fires in Australia. Additional topics include the assessment of advances in measuring and modeling of UV radiation; methods for determining personal UV exposure; the effect of solar radiation management (stratospheric aerosol injections) on UV radiation relevant for plants; and possible revisions to the vitamin D action spectrum, which describes the wavelength dependence of the synthesis of previtamin D 3 in human skin upon exposure to UV radiation. Graphical abstract

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.269
Teacher spread0.244 · 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 teacher head, not a consensus.

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

Citations117
Published2023
Admission routes1
Has abstractyes

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