Towards Development of a Performance Standard for Assessing the Effectiveness of Wall-Window Interface Details to Manage Rainwater Intrusion

ABSTRACT Performance standards state requirements in terms of required results, with criteria for verifying compliance but without stating the methods for achieving required results. A performance standard may define functional requirements for the item, operational requirements, or interface and interchangeability characteristics. A performance standard may be viewed in juxtaposition to a prescriptive standard, which may specify design requirements, such as materials to be used, how a requirement is to be achieved, or how an item is to be fabricated or constructed. A performance standard for spill prevention specifies the outcome required, but leaves the specific measures to achieve that outcome up to the discretion of the regulated facility. In contrast to a design standard or a technology-based standard that specifies exactly how to achieve compliance, a performance standard sets a goal and lets each regulated facility owner or operator decide how to meet it. Since 1993, U.S. Federal regulations complied with Executive Order 12866, which specifies the use of performance standards. Thus, it is not surprising that the 2002 revisions of U.S. Environmental Protection Agency'S Oil Pollution Prevention regulation, which was first published in 1973, included several performance-based provisions. The regulation requires nearly every significant oil storage facility in the nation to prepare a Spill Prevention Control and Countermeasure Plan. Regulatory provisions that had set prescriptive standards or design requirements in 1973, allow much more flexibility today. This poster presentation briefly examines the trend toward performance-based environmental regulations in the U.S. and the evolution of the Oil Pollution Prevention regulation.

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A Statistical Model for Assessing Performance Standards for Quantitative and Semiquantitative Disinfectant Test Methods

Journal of AOAC International ◽

10.5740/jaoacint.13-105 ◽

2014 ◽

Vol 97 (1) ◽

pp. 58-67 ◽

Cited By ~ 4

Author(s):

Albert E Parker ◽

Martin A Hamilton ◽

Stephen F Tomasino

Keyword(s):

Error Rate ◽

Performance Standards ◽

Test Methods ◽

Error Rates ◽

Test Method ◽

Performance Standard ◽

Type I ◽

Multiple Tests ◽

Log Reduction ◽

A Performance

Abstract A performance standard for a disinfectant test method can be evaluated by quantifying the (Type I) pass-error rate for ineffective products and the (TypeII) fail-error rate for highly effective products. This paper shows how to calculate these error rates for test methods where the log reduction in a microbial population is used as a measure of antimicrobial efficacy. The calculations can be used to assess performance standards that may require multiple tests of multiple microbes at multiple laboratories. Notably, the error rates account for among-laboratory variance of the log reductions estimated from a multilaboratory data set and the correlation among tests of different microbes conducted in the same laboratory.Performance standards that require that a disinfectant product pass all tests or multiple tests on average, are considered. The proposed statistical methodology is flexible and allows for a different acceptable outcome for each microbe tested, since, for example, variability may be different for different microbes. The approach can also be applied to semiquantitative methods for which product efficacy is reportedas the number of positive carriers out of a treated set and the density of the microbes on control carriers is quantified, thereby allowing a log reduction to be calculated. Therefore, using the approach described in this paper, the error rates can also be calculated for semiquantitative method performance standards specified solely in terms of the maximum allowable number of positive carriers per test. The calculations are demonstrated in a case study of the current performance standard for the semiquantitative AOAC Use-Dilution Methods for Pseudomonas aeruginosa (964.02) and Staphylococcus aureus (955.15), which allow up to one positive carrier out of a set of 60 inoculated and treated carriers in each test. A simulation study was also conducted to verify the validity of the model's assumptions and accuracy. Our approach, easily implemented using the computer code provided, offers a quantitative decision-making tool for assessing a performance standard for any disinfectant test method for which log reductions can be calculated.

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