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Record W4390194648 · doi:10.18280/ijsse.130611

Health Risk Assessment Due to Indoor Air Pollution in Air Conditioning Manufacturing Plants

2023· article· en· W4390194648 on OpenAlexvenueno aff
Ahmed A. Hussien, Kamel K. Al‐Zboon, Walaa Matalqa, Abdullah H. M. AlEssa

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsAir conditioningEnvironmental scienceAir pollutionEnvironmental healthIndoor air qualityEnvironmental engineeringEngineeringMedicine

Abstract

fetched live from OpenAlex

The interplay between workplace air quality and the well-being and productivity of industrial personnel is of paramount importance.This research was undertaken to evaluate the influence of air pollutants on health outcomes and comfort levels within air conditioning manufacturing facilities.A systematic field survey measured indoor levels of carbon monoxide (CO), carbon dioxide (CO2), particulate matter (PM10 and PM2.5), and nitrogen oxides (NOx).It was observed that the mean concentrations of CO, CO2, and NOx were compliant with acceptable standards.In contrast, PM10 and PM2.5 levels frequently surpassed acceptable thresholds, potentially compromising respiratory health and necessitating the implementation of enhanced protective measures, including the mandatory use of appropriate personal protective equipment (PPE), particularly respiratory protection.Hazard Quotient (HQ) assessments yielded values ranging from 0.068 to 0.115 for PM10, 0.007 to 0.008 for NO2, 0.026 to 0.103 for CO, and 0.100 to 0.104 for CO2, all of which were below the threshold of one, suggesting an absence of immediate health risks.However, the average HQ values suggested a hierarchical order of potential impact with CO2 being the highest, followed by PM10, CO, and NO2.The Health Index (HI) values varied across different plant sections, with the highest recorded in cutting and drilling areas (0.3152) and the lowest outside the plant (0.1150).Based on the health risk calculations, the respiratory system was identified as the most vulnerable, followed by the cardiovascular and nervous systems, with eye irritation as a lesser concern.The findings underscore the imperative for continuous air quality monitoring and the establishment of comprehensive awareness programs, alongside robust emergency and evacuation protocols, to mitigate health risks.The study advocates for the integration of occupational health considerations into industrial management strategies and local regulatory policies, emphasizing the critical role of air quality management in the maintenance of worker health and safety in manufacturing settings.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.251
Teacher spread0.245 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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