Technical challenges involved in implementation of VOC reactivity-based control of ozone.

Controlling VOC emissions on the basis of their individual contribution to ozone formation has been subject to extensive discussion and research in past years, and the concept has gained some acceptance in the air pollution community for certain product categories and industrial operations. Despite its potential to decrease ozone formation, there are some technical challenges that still remain before we can confidently apply the concept of reactivity in the most beneficial manner to reduce ozone concentrations. The goal of this paper is to (1) assess how existing science in this area supports the use of reactivity, particularly, the maximum incremental reactivity, for VOC control under a national policy application and (2) identify where uncertainties exist that could affect such a policy. Box model and air quality model results are used to show that there are ways to describe a chemical's reactivity that are relatively robust across large geographic areas. Modeling results also indicate that the choice of metric is important in determining the potential benefits and detriments of a reactivity-based emission control policy.

Testing extrapolation of a biologically based exposure-response model from in vitro to in vivo conditions.

Models of carcinogenesis may become so flexible as to preclude the possibility of being falsified by data. This problem is removed in part by stronger biophysical specification of processes and parameters within the model prior to fitting to in vivo data on the relationship between exposure and cancer incidence. This paper explores the use of a biophysical model of chromosomal damage, cellular transformation, repair, mitosis, initiation, promotion, progression, and cytotoxicity in developing exposure-response models for radiation-induced cancer. Many of the aspects of model form and parameter values are developed from in vitro data, and the model then is extrapolated to the in vivo setting using a dosimetric model to account for dose inhomogeneity within the lung tissue of rats exposed to radon progeny in air. The ability of the model to predict cancer incidence in the rats is assessed and is shown to be problematic at higher doses. This calls into question whether a full claim may be made about the ability of first-principle models to fully constrain models applied to in vivo data at present. Possible explanations for the discrepancy, and implications for extrapolation, are provided.

Significance of cell-cycle delay, multiple initiation pathways, misrepair and replication errors in a model of radiobiological effects.

PURPOSE: To advance a biomathematical model of radiocarcinogenesis by describing multiple pathways for initiation, a radiologically induced cell-cycle delay, misrepair and spontaneous DNA damages caused by replication. It was investigated whether the incorporation of these biological features would improve the fit of the model to data showing plateaus in in vitro irradiations of different cell lines and whether the fit parameters were then more biologically realistic. MATERIALS AND METHODS: A biomathematical submodel was developed based on a previous State-Vector Model that mathematically described enhanced DNA repair and radical scavenging following irradiation. RESULTS: With the two initiation pathways and cell-cycle delay, the simulations better explained the mouse data but not the rat data, and for both data sets the fit parameters were biologically more realistic than previously assumed. Inclusion of misrepair and replicational errors did not significantly affect the fit. CONCLUSIONS: A plateau in the dose-effect relationship for in vitro irradiation of different cell lines can be explained by radioprotective mechanisms. The plateau-type dose-response relationships point to a non-linear dose- effect relationship at low doses and indicate that linear extrapolation from moderate (or high) to low doses may not be justified for in vitro studies of these cell lines.