Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach

Abstract

Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis of the multi-endpoint toxicities using the multi-criteria decision-making method (MCDM). To obtain the multi-endpoint toxicities of PM2.5 sources, cell mortality, reactive oxygen species (ROS), inflammation and mutagenicity were measured for diesel exhaust particles (DEP), gasoline exhaust particles (GEP), rice straw burning particles (RBP), coal combustion particles (CCP) and tunnel dust particles (TDP). The integrative toxicity score (ITS) of the PM2.5 source was calculated using MCDM, which consist of four steps: (1) defining the decision-making matrix, (2) normalization and weighting, (3) calculating the ITS (linear aggregation) and (4) a global sensitivity analysis. The indicator of cell mortality had the highest weight (0.3780) followed by inflammation (0.2471), ROS (0.2178) and mutagenicity (0.1571). Additionally, the ITS based on the sources contributing to PM2.5 resulted in the following order: DEP (0.89), GEP (0.44), RBP (0.40), CCP (0.23) and TDP (0.06). The relative toxicity index (RTI), which represents the ratio of toxicity due to the difference in sources, increases as the contribution of the highly toxic sources increases. The RTI over 1 is closely associated with an increased contribution from highly toxic sources, such as diesel exhaust, gasoline exhaust and biomass burning. It is necessary to investigate the toxicity of various PM2.5 sources and PM2.5 risk based on the sources.

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Acknowledgements

This research was supported by the National Research Foundation (NRF) of Korea (2014M3C8A5030618).

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Correspondence to Sang Don Kim.

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Appendix

Appendix

See Tables 5, 6, 7 and 8 and Figs. 3 and 4.

Table 5 Correlation between the cytotoxicities used in the decision-making matrix
Table 6 Integrative toxicity score (ITS) and ranking of PM2.5 sources by weighting method
Table 7 Global sensitivity analysis for the ranking orders by weighting method
Table 8 Normalized decision-making matrix, indicator weight and integrative toxicity score (ITS) for ambient particulate matter of three sizes in the eight sites of the Netherlands (raw data of in vitro toxicity is reported by Steenhof et al. 2011)

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Kim, I., Park, K., Lee, K. et al. Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach. Environ Geochem Health 42, 1775–1788 (2020). https://doi.org/10.1007/s10653-019-00469-2

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Keywords

  • PM2.5 sources
  • Cytotoxicity
  • Toxicity index
  • Risk assessment
  • Decision-making
  • Objective weighting