Quantitative Assessment of Air Pollutants and Construction Accidents: Developing Risk-Based Concentration Groups

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The construction sector is predominantly characterized by outdoor work, where workers are continuously exposed to environmental factors such as air pollution. Air pollutants, including particulate matter (PM10) and sulfur dioxide (SO2), are well known for their health impacts, but their potential influence on workplace safety has been underexplored. According to the World Health Organization, air pollutants kill 7 million people annually worldwide. This study investigates the association between air pollutant concentrations and construction site accidents, focusing on whether higher pollution levels are linked with greater accident risk, and proposes new concentration groups considering the probability of accidents. This study was carried out in four phases: (i) collection of data; (ii) classification of data; (iii) probabilistic analysis of air pollutant concentration and accidents; and (iv) clustering of air pollutant concentration groups. As a result, it was identified that the probability of accident occurrence increased with the increase in SO2 and PM10 concentration. Thus, SO2 and PM10 significantly impact construction accidents based on their concentration changes. The new groups of SO2 and PM10 have been developed based on accident probability, and these groups can be utilized to assess the accident risk level of construction sites based on air pollutant concentration.

Original languageEnglish
Article number3305
JournalBuildings
Volume15
Issue number18
DOIs
StatePublished - Sep 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • K-means clustering
  • air pollutants
  • construction accidents
  • construction safety management
  • hierarchical clustering
  • relative probability

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