AI Article Synopsis
- The study explores the gas/particle (G/P) partition behavior of polybrominated diphenyl ethers (PBDEs) in size-segregated atmospheric particles, addressing a gap in current research compared to bulk air measurements.
- Researchers collected extensive samples from Harbin, China, to develop a steady-state equation that calculates the G/P partition quotients for PBDEs based on factors like organic matter content.
- The new equation improves predictions of PBDE concentrations in the atmosphere, particularly for high-brominated variants, and aids in assessing health risks associated with airborne exposure to these chemicals.
Article Abstract
Gas/particle (G/P) partition quotients of semi-volatile organic compounds (SVOCs) for bulk air have been widely discussed in experimental and theoretical contexts, but research on size-resolved G/P partition quotients (K) are scarce and limited in scope. To investigate G/P partition behavior of polybrominated diphenyl ethers (PBDEs) for size-segregated particles in the atmosphere, 396 individual size-segregated particulate samples (36 batches × 11 size-ranges), and 108 pairs of concurrent gaseous and bulk particulate samples were collected in Harbin, China. A steady-state equation based on bulk particles is derived to determine G/P partition quotients of PBDEs for size-segregated particles, which depends on the organic matter contents of size-segregated particles (f). This equation can well predict K with knowledge of bulk partition quotient (K), ambient temperature, and f, the results of which match well with monitoring data in Harbin and other published data collected in Shanghai and Guangzhou of China and Thessaloniki of Greece, and remedies a defect of over-estimate K for high-brominated PBDEs by the previous equation. In particular, the new equation contributes to obtaining the PBDEs concentrations in all atmospheric phase from partial phase, then provides a credible path to evaluate healthy exposure dose from the airborne PBDEs, by co-utilization with exposure models.
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| http://dx.doi.org/10.1016/j.jhazmat.2020.123245 | DOI Listing |
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