MétaCan
Menu
← Back to cohort
Record W2261002769 · doi:10.1002/2015jd024183

From nuclear power to coal power: Aerosol‐induced health and radiative effects

2015· article· en· W2261002769 on OpenAlexaff
Tero Mielonen, Anton Laakso, Anni Karhunen, Harri Kokkola, Antti‐Ilari Partanen, Hannele Korhonen, Sami Romakkaniemi, K. E. J. Lehtinen

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsConcordia University
FundersLeibniz-Institut für TroposphärenforschungLeibniz-GemeinschaftForschungszentrum JülichEidgenössische Technische Hochschule ZürichAalto-YliopistoAcademy of FinlandUniversity of Oxford
KeywordsEnvironmental scienceAerosolCoalAtmospheric sciencesRadiative transferClimate changeCoal combustion productsGreenhouse gasPopulationClimate modelAir quality indexNuclear powerGlobal warmingClimatologyMeteorologyWaste managementEnvironmental healthPhysicsNuclear physicsEngineering

Abstract

fetched live from OpenAlex

Abstract We have investigated what would be the climate and PM‐induced air quality consequences if all nuclear reactors worldwide were closed down and replaced by coal combustion. In a way, this presents a “worst‐case scenario” since less polluting energy sources are available. We studied simultaneously the radiative and health effects of coal power emissions using a global 3‐D aerosol‐climate model (ECHAM‐HAMMOZ). This approach allowed us to estimate the effects of a major global energy production change from low carbon source to a high carbon one using detailed spatially resolved population density information. We included the radiative effects of both CO2 and PM2.5 but limited the study of health effects to PM2.5 only. Our results show that the replacement of nuclear power with coal power would have globally caused an average of 150,000 premature deaths per year during the period 2005–2009 with two thirds of them in Europe. For 37 years the aerosol emissions from the additional coal power plants would cool the climate but after that the accumulating CO2 emissions would accelerate the warming of the climate.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.071
GPT teacher head0.389
Teacher spread0.319 · 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 designSimulation or modeling
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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Geophysical Research Atmospheres→Same topicAir Quality and Health Impacts→French-language works237,207→