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A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O 3 ) exposure. ORAM was coupled with the U.S. Environmental Protection Agency's (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O 3 concentration and allows the examination of various scenarios in which emission rates of O 3 precursors (basically, oxides of nitrogen [NO x ] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O 3 season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NO x emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NO x emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.

Effectiveness of alternative selection methods is an important consideration in any plant breeding program. The purpose of this research was to evaluate recurrent phenotypic selection and selection based on both phenotypic performance and a polycross progeny test (phenotypic‐genotypic method) for resistance to rust (Puccinia graminis Pers.) in ‘Sterling’ orchardgrass (Dactylis glomerata L.). Rust resistance was improved by each of three cycles of phenotypic selection. One cycle of phenotypic‐genotypic selection (Cl‐PG) achieved the same level of rust resistance and required the same length of time as did two cycles of phenotypic selection (C2‐P). The mean rust rating of C1‐PG and C2‐P did not change with advancement from the first to the second generation; however, plant to plant phenotypic variation increased. Smaller phenotypic variances in both generations of C1‐PG and C2‐P than in Sterling suggested a decrease in genetic variance with selection; however, significant genetic variation was found in all derived populations. High parent clone‐topcross progeny correlations indicated that progeny testing for rust resistance is unnecessary. The recurrent phenotypic selection method would favor maintenance of greater genetic diversity for resistance than the phenotypic‐genotypic method because more plants could be selected in each cycle.

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