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A new empirical equation for the gas/particle partitioning of OPFRs in ambient atmosphere

  • Man Li
  • , Wenhao Hou
  • , Lina Qiao*
  • , Hong Zhang
  • , Mengdan Wang
  • , Yonghui Wen
  • , Zejiang Jia
  • *Corresponding author for this work
  • Shandong University
  • School of Marine Science and Technology, Harbin Institute of Technology Weihai

Research output: Contribution to journalArticlepeer-review

Abstract

Gas/particle (G/P) partitioning is a core process governing the atmospheric transport of organophosphate flame retardants (OPFRs). However, accurately predicting the G/P partition performance of OPFRs remains a challenge. In this study, four independent models were employed to estimate the characteristics of OPFR G/P partitioning within the octanol–air partition coefficient range of 4.7 (TMP) to 14.2 (TMPP). The results showed that in the maximum partition domain, the Li–Ma–Yang steady-state model fitted the best, with 85.2% of the predicted G/P partition quotient (log KP) values within an acceptable deviation range of ±1 log units for OPFRs. Accordingly, no significant deviations were observed between the predicted (0.56 ± 0.32) and monitored (0.52 ± 0.11) values of the average particle-bound fraction (4P) for the Li–Ma–Yang model in the maximum partition domain. Large deviations were observed between the monitored values and predicted log KP values by these four models in the equilibrium domain. Several factors responsible for the significant deviations observed in G/P partitioning values of OPFRs were discussed. These identified factors were used to develop a new empirical equation, which substantially improved log KP predictions for OPFRs to 75.8% in the equilibrium domain.

Original languageEnglish
Pages (from-to)202-210
Number of pages9
JournalEnvironmental Science: Processes and Impacts
Volume27
Issue number1
DOIs
StatePublished - 17 Dec 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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