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 m 3 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 × 10 4 and 2.14 × 10 2 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 × 10 3 to 8.82 × 10 3 and from 5.03 × 10 1 to 1.30 × 10 2 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; R 2 = 0.860) was found between the model predicted results (x; 3.25 × 10 2 –1.57 × 10 3 ng min –1 ) and the field sampling results (y; 1.36 × 10 2 –2.92 × 10 2 ng min –1 ), indicating the plausibility of using the proposed approach to establish a long-term exposure databank for the cooking industry.
All Science Journal Classification (ASJC) codes
- Environmental Chemistry