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

Minsu Lee, Jaewook Jeong, Louis Kumi

Research output: Contribution to journalArticlepeer-review

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

Keywords

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

Fingerprint

Dive into the research topics of 'Quantitative Assessment of Air Pollutants and Construction Accidents: Developing Risk-Based Concentration Groups'. Together they form a unique fingerprint.

Cite this