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A statistical approach to determining the uncertainty in power-law model estimates of emissions based on time-dependent chamber concentration measurements
Citation:
MARR, D., M. A. MASON, AND L. Stefanski. A statistical approach to determining the uncertainty in power-law model estimates of emissions based on time-dependent chamber concentration measurements. In Proceedings, Indoor Air 2011, Austin, TX, June 05 - 10, 2011. International Society of Indoor Air Quality and Climate (ISIAQ), Santa Cruz, CA, 6 p, (2011).
Impact/Purpose:
symposium paper
Description:
The use of models for estimating emissions from products beyond the timeframe of an emissions test is a means of managing the time and expenses associated with product emissions certification. This paper presents a discussion of (1) the impact of uncertainty in test chamber emissions measurements and (2) the impact of the number of sampling periods on the uncertainty of modeled emissions determined from use of a power law curve fit, a modeling procedure and curve fit that is often employed in evaluating diffusion-controlled emissions from products. This is accomplished through a theoretical analysis that determines modeled emission relative standard deviation (RSD) based on the RSD of measurements used to generate the model equation. Final results show the dependency of estimated emission RSD on the RSDs of concentration measurements, the number of experimental data points and where they are located in the time domain.
