Predicting gas-phase air-cleaning system efficiency at low concentration using high concentration results: Development of a framework

Granular activated carbon filters (GAC) have been used for industrial air and water filtration for long time. This technology has recently been recommended for the design of energy-efficient and immune buildings. The existing standard recommends the test to be carried out at 100 ppm, which is for the accelerated tests but much higher than the actual contaminant concentrations in buildings. Therefore, there is a need to develop a framework to evaluate the performance of these technologies at low concentration using the available high concentration experimental data. This paper briefly reviews the existing methods for predicting the performance of granular activated carbon, and then suggests a procedure to estimate the performance of GAC for indoor air gas contaminants removal at low concentration using high concentration results. The method is based on the application of a set of isotherm and breakthrough models as a tool for extracting the data from higher concentrations and translating them into the low level concentrations. Results show that stoichiometric breakthrough times, the adsorption rate constants (in Wheeler–Jonas equation) and product constants (in Yoon–Nelson equation) do not strongly depend on concentration, demonstrating some indicators for simulating the experiments at indoor air level conditions.