Lung cancer risk in relation to traffic-related nano/ultrafine particle-bound PAHs exposure: a preliminary probabilistic assessment

J Hazard Mater. 2011 Jun 15;190(1-3):150-8. doi: 10.1016/j.jhazmat.2011.03.017. Epub 2011 Mar 12.

Abstract

Exposures to carcinogenic polycyclic aromatic hydrocarbons (PAHs) have been linked to human lung cancer. The purpose of this study was to assess lung cancer risk caused by inhalation exposure to nano/ultrafine particle-bound PAHs at the population level in Taiwan appraised with recent published data. A human respiratory tract model was linked with a physiologically based pharmacokinetic model to estimate deposition fraction and internal organic-specific PAHs doses. A probabilistic risk assessment framework was developed to estimate potential lung cancer risk. We reanalyzed particle size distribution, total-PAHs, particle-bound benzo(a)pyrene (B[a]P) and PM concentrations. A dose-response profile describing the relationships between external B[a]P concentration and lung cancer risk response was constructed based on population attributable fraction (PAF). We found that 90% probability lung cancer risks ranged from 10(-5) to 10(-4) for traffic-related nano and ultrafine particle-bound PAHs, indicating a potential lung cancer risk. The particle size-specific PAF-based excess annual lung cancer incidence rate due to PAHs exposure was estimated to be less than 1 per 100,000 population, indicating a mild risk factor for lung cancer. We concluded that probabilistic risk assessment linked PAF for limiting cumulative PAHs emissions to reduce lung cancer risk plays a prominent role in future government risk assessment program.

MeSH terms

  • Environmental Exposure*
  • Humans
  • Incidence
  • Lung Neoplasms / epidemiology
  • Lung Neoplasms / etiology*
  • Models, Theoretical
  • Nanoparticles / toxicity*
  • Polycyclic Aromatic Hydrocarbons / toxicity*
  • Risk
  • Risk Assessment
  • Vehicle Emissions / toxicity*

Substances

  • Polycyclic Aromatic Hydrocarbons
  • Vehicle Emissions