Are the Exposure Models Used for REACh Wrong?

Dr Joonas Koivisto and 16 others, including this writer, have recently authored what I believe is a very important paper:  Source specific exposure and risk assessment for indoor aerosols.    It sounds a bit like a paper focused on aerosol assessment but it is actually a comprehensive look at inhalation exposure models and the quality of these models to make decisions relative to chemical regulation and risk assessment.   The reality is that aerosols represent the most challenging scenarios for modeling because of their added properties compared to gases.  If one can accurately model aerosols then gases are relatively simple to model.  

The publication outlines the current state of the science and available models.  It also makes a developing case for the use of first principle mathematical mass balance models versus other types of models (knowledge-based models, and statistical models of exposure determinants) especially for regulatory decisions such as those mandated by REACh.

The Europeans are much more advanced than the US in the application of exposure models because they have to be.   The REACh regulation requires a risk assessment for literally thousands of chemicals and a risk assessment requires an exposure assessment.  There is not nearly enough measured exposure data available, so they have turned to models.   It is clearly evident that the inputs to and data bases for the mathematical mass balance models have not been sufficiently developed so the European Regulators have turned to knowledge-based and statistical models of exposure determinants.  These models are more easily applied because the inputs are relatively simple.   The paper implies that these models are not performing up to the task and that there is a real need to develop the input data necessary to feed the more competent first principle mathematical mass balance models.  

The paper points to an earlier paper I did with Tom Armstrong and Mike Taylor in which we challenged the mass balance 2 zone Near-field/Far-field (NF/FF) model to the Daubert legal criteria which is widely used by the Courts to assess whether expert witnesses scientific testimony is methodologically valid.   In that paper we concluded the NF/FF model fulfils the Daubert criteria and when it is used within its stated limitations, it adequately estimates the exposure as applied to legal decisions.  The implication is that the models currently used for making decisions for REACh would, most likely, not pass the Daubert criteria, which requires that these models:

1) Are applicable and have been tested.

2) Have been subjected to peer-review and are generally accepted.

3) The rate of error is known and acceptable.

4) have maintenance of standards and controls concerning their operation.

5) Are generally accepted in the relevant scientific community.

This Daubert paper is:  Jayjock, M.A., Armstrong, T., Taylor, M., 2011. The Daubert Standard as applied to exposure assessment modeling using the two zone (NF/FF) model estimation of indoor air breathing zone concentration as an example. J. Occup. Environ. Hyg. 8, D114–D122.   I will email an electronic copy to anyone requesting it: mjayjock@gmail.com.

What Dr. Koivisto and the other authors are asserting in this paper is somewhat striking; namely, the currently used REACh models need to be explicitly challenged by the Daubert (or similar objective) criteria and, if found wanting, better alternatives should be developed and employed.   This would, most likely, result in something this writer has been advocating for many years; specifically, comprehensive research and compilation of exposure source data bases.

This should be a straightforward objective scientific exercise; that is, a technically competent and empowered group of scientists would set open and objective criteria and test the currently used regulatory sanctioned models to those standards.   The reality, as I see it, is that there are strong vested interests and forces at work in this case that may resist this sort of effort.   Change is never easy but, hopefully, scientific integrity, good judgement and established facts will ultimately work to improve the public health, partisan politics notwithstanding.

The paper was published online this week at https://doi.org/10.1016/j.scitotenv.2019.02.398 as gold open access, which means that the full pdf text is a free download from the publisher Elsevier.