Exposure Conversion Factors (ECFs) were calculated based on exposure to 3 ppm ACN in air for 5 and for 60 minutes. Note that our reported ECFs apply only for linear relationships, when there are no saturation effects in the biotransformation or when the saturated biotransformation pathway does not have a significant influence on the ACN concentration in blood.
In our model simulations we considered that Km and Vmax were uncertain only, as the data by Sweeney et al. (2003) did not provide sufficient insight to distinguish between variability and uncertainty in these metabolic parameters. However, interindividual variability in biotransformation may also be relevant. Consequently, the variation as a result of uncertainty may be overestimated while the variation originating from variability may be underestimated in our case study. Though, in practice this will have little effect since Km and Vmax values cannot be determined easily on an individual basis, meaning that this source of interindividual variability will always cause variation in the reconstructed external exposure concentration.
Based on the reconstructed data it is shown that additional information about individual physiological parameters from the workers, such as body weight and alveolar ventilation, can reduce the variation by 20% in the reconstructed air concentrations for the measurements that were collected after 25 days and 5 to 8%
in the reconstructed air concentrations for the measurements after 85 days. Usually, these physiological parameter values can be easily retrieved. The magnitude of the reduction in the range of reconstructed air concentrations depends on the modeled chemical and the moment of data collection. In previous studies, the importance of human physiological data has also been demonstrated, especially during and shortly after exposure (Huizer et al. 2012; 2014). The shorter after the incident measurements are performed, the more relevant it is to collect individual physiological data.
Similarly, exposure duration appears to have a relatively large influence on the reconstructed air concentration of ACN in this case study. As a consequence, it is considered very important to determine the exposure duration accurately, preferably by asking the individuals involved shortly after the incident.
The decrease of CEV in the measured data varies over time (from day 25 to day 85 after the incident) from 28% in ‘Worker 3’ to 87% in ‘Worker 2’. This finding clarifies the increase of the overall predicted relative variation in the air exposure concentration that were recalculated based on the data from 85 days after the incident, as variability in the life span of erythrocytes (the elimination route of CEV) is found to be the most important factor of variation in this scenario.
Note that in our simulations no inhalation protection was considered, although it was described by Bader and Wrbitzky (2006) that one worker used this
Uncertainty and variability in the exposure reconstruction of chemical incidents – the case of acrylonitrile
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type of protection. It is, however, unknown which of the workers used inhalation protection. A second aspect not included in the simulations, is the dermal exposure route. Since ACN is known to penetrate easily through the skin, the absence of the dermal route in our simulations may have overestimated the ECF-values and thereby the reconstructed air concentrations. In particular because the workers reported skin contact with soaked working clothes of their unconscious colleague (Bader and Wrbitzky, 2006)
Recommendations
Based on the results of the model simulations for acrylonitrile, it is recommended to document the exact exposure duration of all the individual exposed after the accident.
Furthermore, collecting human biomonitoring data as soon as reasonably possible after the incident will minimize uncertainty. In addition, collecting (biological) measurements at different points in time can support modeling results. Unfortunately, the reconstructed results from our study could not be validated with measured air concentrations and known exposure duration. To get a better understanding and more confidence in the modeled results, it is meaningful to perform a similar study for a situation in which both external and internal concentrations, as well as exposure duration are known.
Further applicability of reversed dosimetry in combination with human biomonitoring may include the comparison of reconstructed concentrations with limit values, risk communication, interventions and decision making for follow-up health investigation among highly exposed individuals. When biomonitoring data become available quickly after a chemical incident, techniques that support a fast and reliable exposure reconstruction are desirable. This may include mobile measuring and analysis devices and pre-parameterized PBPK models for typical industrial chemicals.
Supplementary information
Supplementary information is available in Appendix C.
Conflict of interest statement
The authors declare that there are no conflicts of interest.
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