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.
