a b s t r a c tAir cleaning techniques have been applied worldwide with the goal of improving indoor air quality. The effectiveness of applying these techniques varies widely, and pollutant removal efficiency is usually determined in controlled laboratory environments which may not be realized in practice. Some air cleaners are largely ineffective, and some produce harmful by-products. To summarize what is known regarding the effectiveness of fan-driven air cleaning technologies, a state-of-the-art review of the scientific literature was undertaken by a multidisciplinary panel of experts from Europe, North America, and Asia with expertise in air cleaning, aerosol science, medicine, chemistry and ventilation. The effects on health were not examined. Over 26,000 articles were identified in major literature databases; 400 were selected as being relevant based on their titles and abstracts by the first two authors, who further reduced the number of articles to 160 based on the full texts. These articles were reviewed by the panel using predefined inclusion criteria during their first meeting. Additions were also made by the panel. Of these, 133 articles were finally selected for detailed review. Each article was assessed independently by two members of the panel and then judged by the entire panel during a consensus meeting. During this process 59 articles were deemed conclusive and their results were used for final reporting at their second meeting. The conclusions are that: (1) None of the reviewed technologies was able to effectively remove all indoor pollutants and many were found to generate undesirable by-products during operation. (2) Particle filtration and sorption of gaseous pollutants were among the most effective air cleaning technologies, but there is insufficient information regarding long-term performance and proper maintenance. (3) The existing data make it difficult to extract information such as Clean Air Delivery Rate (CADR), which represents a common benchmark for comparing the performance of different air cleaning technologies. (4) To compare and select suitable indoor air cleaning devices, a labeling system accounting for characteristics such as CADR, energy consumption, volume, harmful by-products, and life span is Atmospheric Environment 45 (2011) 4329e4343 necessary. For that purpose, a standard test room and condition should be built and studied. (5) Although there is evidence that some air cleaning technologies improve indoor air quality, further research is needed before any of them can be confidently recommended for use in indoor environments.

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In order to evaluate the impacts of volatile organic compounds (VOCs) emissions from building materials on the indoor pollution load and indoor air quality beyond the standard chamber test conditions and test period, mechanistic emission source models have been developed in the past. However, very limited data are available for the required model parameters including the initial concentration (Cm0), in-material diffusion coefficient (Dm), partition coefficient (Kma), and convective mass transfer coefficient (km). In this study, a procedure is developed for estimating the model parameters by using VOC emission data from standard small chamber tests. Multivariate regression analysis on the experimental data are used to determine the parameters. The Least Square and Global search algorithm with multi-starting points are used to achieve a good agreement in the normalized VOC concentrations between the model prediction and experimental data. To verify the procedure and estimate its uncertainty, simulated chamber test data are first generated by superposition of different levels of "experimental uncertainties" on the theoretical curve of the analytical solution to a mechanistic model, and then the procedure is used to estimate the model parameters from these data and determine how well the estimates converged to the original parameter values used for the data generation. Results indicated that the mean value of the estimated model parameters Cm0 was within-0.04%+/-2.47% of the true values if the "experimental uncertainty" were within +/-10% (a typical uncertainty present in small-scale chamber testing). The procedure was further demonstrated by applying it to estimate the model parameters from real chamber test data. Wide applications of the procedure will result in a database of mechanistic source model parameters for assessing the impact of VOC emissions on indoor pollution load, and for evaluating the effectiveness of various IAQ design and control strategies.