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Record W6998440580

Accelerating Climate Action: A just transition in a post-Covid era. Book of abstracts, 9th SISC Annual Conference (online, 22-24 Set 2021)

2021· article· en· W6998440580 on OpenAlexaboutno aff

Bibliographic record

VenueARCA (Università Ca' Foscari Venezia) · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCOVID-19 impact on air quality
Canadian institutionsnot available
Fundersnot available
KeywordsAerosolAERONETShortwavePlumeAlbedo (alchemy)Atmosphere (unit)Radiative transferHYSPLITSatelliteArctic
DOInot available

Abstract

fetched live from OpenAlex

Extended and intense biomass burning fires occurred in Northern Canada and on the Greenlandic West coast during summer 2017. The smoke plume emitted into the atmosphere was transported and spread in the Arctic, producing one of the most significant impacts ever observed in the region. Evidence of Canadian and Greenlandic wildfires was recorded at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5°N, 68.8°W, www.thuleatmos-it.it) by a suite of instruments managed by ENEA, INGV, Univ. of Florence, and NCAR. Chemical tracers such as CO, HCN, H2CO, C2H6, and NH3 were measured in the atmospheric column above Thule from 19 August to 23 August by an FTIR. The aerosol optical depth measured by the AERONET sunphotometer was dominated by the fine fraction, reaching a peak value of about 0.86 on 21 August. An air sampler monitored several wildfire compounds at a 48-hour resolution. Groundbased radiometers allowed the quantification of the surface radiation budget at THAAO. Backward trajectories produced through HYSPLIT simulations (Stein et al., 2015) were also employed to understand the atmospheric dynamics indicating the origin of the transported smoke. MODTRAN6.0 radiative transfer model (Berk et al., 2014) was used to estimate the aerosol radiative effect (ARE) and the heating rate profiles at 78° SZA. Measured temperature profiles, integrated water vapour, surface albedo, spectral AOD and aerosol extinction profiles from CALIOP onboard CALIPSO satellite were used as model input. The shortwave ARE at the surface was -43.7 W/m2 at 78° solar zenith angle (SZA) for AOD=0.626. The peak aerosol heating rate (+0.5 K/day) was reached within the aerosol layer between 8 and 12 km, while the maximum radiative effect (-45.4 W/m2) was found at 3 km, below the most extensive aerosol layer.
\nThe regional impact of the event observed between 15 and 25 August was investigated using MODTRAN to model the aerosol radiative effect efficiency (AREE) with measurements of AOD and surface albedo over land retrieved from MODIS. Instead, albedo data over the ocean were obtained from Jin et al. (2004). The radiative transfer model was fed with the atmospheric properties used in the ARE simulation at THAAO. The values of aerosol radiative effect efficiency (AREE) span from -3 W/m2 to -132 W/m2, depending on surface albedo and solar zenith angle. The fire plume covered a vast portion of the Arctic, with large values of the AOD reaching the eastern Greenlandic coast and with the shortwave ARE lasting for a few days. In particular, we calculated a cumulative ARE during the considered period and found a negative peak value of -120 TW on 21-22 August over the Arctic sector between 60°N - 80°N and 110°W - 0°E. Instead, the mean daily ARE shows values between -65 and -25 W/m2 between 15 and 25 August, being influenced by really large AOD values mainly during the first part of the period over northern Canada. This large amount of aerosol is also expected to influence cloud properties in the Arctic, producing significant indirect radiative effects.
\n
\nReferences
\nBerk, A., P. Conforti, R. Kennett, T. Perkins, F. Hawes and J. van den Bosch (2014), "MODTRAN6: a major upgrade of the MODTRAN radiative transfer code", Proc. SPIE 9088, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XX, 90880H, 9088, 1-7.
\nStein, A.F., R.R. Draxler, G.D. Rolph, B.J.B. Stunder, M.D. Cohen and F. Ngan (2015), “Noaa’s hysplit atmospheric transport and dispersion modeling system”, Bulletin of the American Meteorological Society, 96(12), 2059–2077.
\nJin, Z., T.P. Charlock, W.L. Smith and K. Rutledge (2004), “A parameterization of ocean surface albedo”, Geophysical Research Letters, 31(22), 1–4.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.713
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.000

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 head0.060
GPT teacher head0.310
Teacher spread0.251 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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