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Important Considerations for Establishing a Secondary Ozone Standard to Protect Vegetation
Authors:Allen S Lefohn  Victor C Runeckles  Sagar V Krupa  Douglas S Shadwick
Institution:1. A. S. L. &2. Associates , Helena , Montana , USA;3. University of British Columbia , Vancouver , British Columbia , USA;4. University of Minnesota , St. Paul , Minnesota , USA;5. NSI Technology Services Corporation , Research Triangle Park , North Carolina , USA
Abstract:Air quality standards are established to prevent or minimize the risk of adverse effects from air pollution to human health, vegetation, and materials. In order to develop standards which provide an adequate measure of protection to vegetation, it is necessary to define, in as precise terms as possible, the relationship between ambient air quality and the potential for adverse effects on vegetation. Based on recent evidence published in the literature, as well as retrospective studies using data from the National Crop Loss Assessment Network (NCLAN), cumulative indices can be used to describe exposures of ozone for predicting agricultural crop effects. However, the mathematical form of the standard that may be proposed to protect crops does not necessarily have to be of the same form as that used in the statistical or process oriented mathematical models that relate ambient ozone exposures with vegetation effects. This paper discusses the limitations associated with applying a simple statistic that may take the place of a more biologically meaningful exposure parameter. While the NCLAN data have been helpful in identifying indices that may be appropriate for establishing exposure-response relationships, the limitations associated with the NCLAN protocol need to be considered when attempting to apply these relationships in the establishment of a secondary national ambient air quality standard. The Weibull model derived from NCLAN experiments must demonstrate its generality and universal applicability. Furthermore, its predictive power must be tested using independent sets of field data.
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