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Record W3029636709 · doi:10.1186/s40068-020-00169-2

Waste heat: the dominating root cause of current global warming

2020· article· en· W3029636709 on OpenAlex
Qinghan Bian

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueENVIRONMENTAL SYSTEMS RESEARCH · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsGlobal warmingEnvironmental scienceContext (archaeology)Climate changeClimatologyWaste heatGreenhouse gasClimate modelEffects of global warmingAtmospheric sciencesNatural resource economicsHeat exchangerGeographyGeologyEngineeringEconomics

Abstract

fetched live from OpenAlex

Abstract Background Pursuing GHG reductions by means of all resources and efforts has turned out no result to stop or even slow the global warming: the globe still gets warmer and warmer, especially in the recent years, at record-breaking rate almost each single year. Additionally, no definitive relationship has been found between the warming and the atmospheric GHG concentration. The link between them even in IPCC’s report lacks support and is unconvincing. All these imply that something else is responsible for the warming. On the other hand, huge amount of residual heat or waste heat from human activities has been poured into the climate system but has not been considered seriously in the context of global warming or climate change. Results This article features deploying the basic principles of thermodynamics and applying a new model, Equivalent Climate Change Model, to analyse the currently available data on world energy consumption between 1965 and 2017, and to study the relation between the global warming and the waste heat entered the climate system. The results show that the temperature changes in air, oceans and land are definitively correlated to the respective heat allocated from the waste heat stream based on their specific heat capacities, with high certainty and reliability. The observed anomalies in air fall within a range of simulations at an equivalent climate change surface air boundary layer depth between 50 and 100 m (60 ~ 100 m in recent decades due to more establishments of high-rising heat discharging sources); the anomalies in oceans fall within a range of simulations at an equivalent climate change waters surface boundary layer depth between 0.10 and 0.20 m (0.125 ~ 0.20 m in recent decades); and the anomalies in land fall within a range of simulations at an equivalent climate change land surface boundary layer depth between 0.05 and 0.10 m (0.06 ~ 0.10 m in recent decades). The simulation results at the air layer depth of 70 m are almost the same as NASA’s Lowess smoothing trend. Forecast of future global warming based on this model under the scenario of business as usual indicates that the possible air temperature risings will be in the range of 0.68 ~ 1.13 °C in 2030 and 0.73 ~ 1.22 °C in 2040; the possible sea temperature risings will be in the range of 0.61 ~ 0.98 °C in 2030, 0.66 ~ 1.05 °C in 2040; and the possible land temperature risings will be in the range of 1.02 ~ 1.71 °C in 2030, 1.10 ~ 1.84 °C in 2040. However, if the energy conversion efficiency increased by 10% by 2030 and another 10% by 2040, then the possible air temperature risings would be in the range of 0.54 ~ 0.90 °C in 2030 and 0.44 ~ 0.73 °C in 2040; the possible sea temperature risings would be in the range of 0.49 ~ 0.78 °C in 2030, and 0.40 ~ 0.64 °C in 2040; and the possible land temperature risings would be in the range of 0.81 ~ 1.36 °C in 2030 and 0.66 ~ 1.11 °C in 2040. The observed global average air temperature changes and the Lowess Smoothing values in 2018 and 2019 fall within the range set by the air layer depth between 60 and 100 m, are consistent with the forecast under the scenario of business as usual, further confirms the reliability of this approach. Conclusions Greenhouse gases are not the culprit of the current global warming, instead, huge amount of residual heat or waste heat discharged into the environment from human activities has dominated the warming (beside of solar irradiance and volcano eruptions). Pursuing GHG reductions is bound to be ineffective in preventing the globe from further warming but increases unnecessary burdens. Switching to 100% of surface renewable energies is the ideal solution to completely solve further warming problem. However, geotherm does cause global warming although it is a type of renewable energy. Increasing energy’s conversion efficiency can effectively help slow down the warming, it requires vast investment and will embrace breakthroughs in technologies. Changing human’s behavior individually and socially and retrofitting can decrease the energy consumption and the amount of heat entering the environment and thus help mitigate climate change and its impact in the most cost-effective way. Unlike the General Circulation Models that can only simulate the past air temperature changes with greater uncertainty, the Equivalent Climate Change Model can not only trace the past temperature changes in air, oceans and land, but also can predict the future changes in them, respectively, with high certainty and reliability.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.378
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.049
GPT teacher head0.313
Teacher spread0.264 · 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