Techniques for Predicting Exposures to Polycyclic Aromatic Hydrocarbons (PAHs) Emitted from Cooking Processes for Cooking Workers

Cooking oil fumes contain polycyclic aromatic hydrocarbons (PAHs), which are known to cause chronic human health effects; hence long-term exposure data is required for determining workers’ exposure profiles and the resultant health risks. However, due to both time and cost constraints, previous studies were performed on a cross-sectional basis. To date, mathematical models have been widely used for predicting long-term exposures in the industrial hygiene field. The aims of this study were to develop suitable predictive models for establishing long-term exposure data on cooking workers. The whole study was conducted in a test chamber with an exhaust hood installed 0.7 m above a deep-frying pan and operated at flow rates of 2.64–5.16 m3 min–1. The cooking process that we selected for testing used peanut oil to deep-fry chicken nuggets at 200°C. An IOM inhalable sampler and an XAD-2 tube were successively used to collect particle- and gas-phase PAHs, respectively. All of the collected samples were analyzed for 21 PAHs using a gas chromatograph (GC) with tandem mass spectrometry (MS/MS). The results showed that the emission rates of the total-PAHs in the gas-phase and the particle-phase were 1.45 × 104 and 2.14 × 102 ng min–1, respectively. The capture efficiencies of the exhaust hood for the total-PAHs were 39.1–76.5%. The resultant fugitive emission rates of the gas-phase and the particle-phase ranged from 3.41 × 103 to 8.82 × 103 and from 5.03 × 101 to 1.30 × 102 ng min–1, respectively. As no significant difference in the sampling results of the total-PAHs was detected between the chef-zone (i.e., the near zone) and the helper-zone (i.e., the far zone), the well-mixed room (WMR) model was adopted for estimating the exposures of all workers. A good correlation (y = 0.134x + 75.3; R2 = 0.860) was found between the model predicted results (x; 3.25 × 102–1.57 × 103 ng min–1) and the field sampling results (y; 1.36 × 102–2.92 × 102 ng min–1), indicating the plausibility of using the proposed approach to establish a long-term exposure databank for the cooking industry.