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Record W4386754777 · doi:10.9734/bpi/eieges/v1/10956f

Discovery of Artificial Photolysis that Influences Air Pollution in Urban Versus Rural Areas in Changing Climate

2023· book-chapter· en· W4386754777 on OpenAlexaffabout
Uthayan Thurairajah

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicImpact of Light on Environment and Health
Canadian institutionsWSP (Canada)
Fundersnot available
KeywordsLight pollutionEnvironmental sciencePollutionAir pollutionAir quality indexSustainable developmentParticulatesClimate changeMeteorologyEnvironmental planningGeographyEcology

Abstract

fetched live from OpenAlex

The study aims to identify what influences the increase in air pollution in an urban area, mitigation methods, and possible sustainable development in a changing global climate. The critical environmental hazards are artificial light at night (ALAN) and air pollution with ambient fine particulate matter (PM2.5). People use nighttime outdoor environments for their needs, and the nocturnally migrating birds are attracted to urban ALAN during seasonal migration, which could increase the birds' exposure to PM2.5. A comparative study examines PM2.5 concentrations and the spatial correlation between ALAN and PM2.5 within urban versus rural areas. The essence of the research is to find the ALAN influence on PM2.5 concentration. The author used the nighttime data of the artificial light on the Earth's surface and the PM2.5 concentration level to estimate the extent of air pollution associated with PM2.5 in the ground-level atmosphere. The study uses a light meter, a sky quality meter, and a PM2.5 meter to measure the relationship between air and light pollution simultaneously. The significant contributions of this study's findings revealed that the ALAN influences increased PM2.5 concentration in urban Toronto. The results can assist in determining the required PM2.5 control areas and designing and executing environmental conservation planning. The results are not only beneficial to understanding accurately the regional differences of spatiotemporal PM2.5 emission dynamics and helpful for proposing alleviation policies in air pollution control and providing scientific support for regional sustainable development in changing climate. The integrated hazards of ALAN and air pollution are most significant and likely to increase within the urban and decrease within rural areas. This study was undertaken and built upon the context of the academic, scientific, and technological challenges to identify the PM2.5 concentration in urban and rural areas and the expected outcomes. This is the first comparative study to find that artificial photolysis influences air pollution in an urban nocturnal environment. Therefore, this research finding is original, not repetitive, historical, and ground-breaking research in environmental, climate lighting science, and technology. This research will help researchers, scientists, engineers, consultants, architects, lighting designers, and government agencies seeking to improve outdoor lighting for safety, health, well-being, and quality of life in the built environment.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.257
Teacher spread0.225 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes2
Has abstractyes

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