Incremental Evaluation Model for the Analysis of Indoor Air Measurements

Abstract

The investigation of the cleaning effectiveness of air cleaners under realistic conditions is challenging. Mathematical models are needed to extract characteristic properties of the air cleaning system from experimental data. An incremental evaluation model based on a source term and a total first-order loss coefficient in each segment was developed to analyze indoor particle measurements. The application of the model is demonstrated using two scenarios, one in a well-mixed testing room and another in a fully equipped aircraft cabin at 750 hPa with a typical aircraft ventilation system. In the first scenario, a normalized version of the model is used to eliminate the source's influence. For the investigation in the aircraft cabin, the model served to extract temporal and spatial resolved source terms and first-order loss coefficients. The incremental evaluation model is applicable to enhance the certification of air cleaners. The application of the model is not only limited to particles; measurements of gaseous compounds like ozone, carbon dioxide, or volatile organic compounds can be evaluated analogously. The model's utility for the data analysis of experiments with complex flow conditions should be studied in further investigations.

Effects of increased recirculation air rate and aircraft cabin occupancy on passengers’ health and well-being – Results from a randomized controlled trial

“…For example, Shen et al (2021) could show an infection risk reduction of HEPA filter equivalent to risk reduction of 100% outside air. However, Schmohl et al (2022) conducted tests in a realistic cabin with and without HEPA filter in the recirculation line and showed that two factors impact the particle and hence aerosol concentration distribution in the aircraft: 1) the distance from the emitter and 2) the use of HEPA filtration. Especially seats farther away from the aerosol emitter show to benefit from the HEPA filtration, that is, similar to other indoor or outdoor environments being physically (very) close to an emitter increases the risk of infection by airborne viruses.…”

Predicting aerosol transmission in airplanes: Benefits of a joint approach using experiments and simulation

“…The experimental tests were conducted in the Fraunhofer Flight Test Facility (see, e.g., References 17,35,36), henceforth FTF, located in Holzkirchen, Germany. The FTF is a full‐size demonstrator (see Figure 1) consisting of a front section of a long‐range twin‐aisle aircraft with a diameter of 9.6 m and a length of 30 m. It has a circulating air extraction in the triangle area (cheeks), corresponding exhaust air in the bilge section, and original ceiling air inlets.…”

“…To make faster predictions, various numerical simulation models have also been proposed. A lot of work has been done both from the perspective of general modeling of aerosol spread, [6][7][8][9][10] and for making predictions in specific scenarios, ranging from hospital rooms, [11][12][13] classrooms 14 and restaurants, 15,16 to aircrafts, 17 cars 18 and buses. 19,20 We refer to References 21-23 for comprehensive reviews of different computational models for aerosol transmission.…”

“…Potentially virus‐laden aerosol particles from this passenger are then traced throughout the cabin. Our experiments were carried out by Fraunhofer IBP at the Fraunhofer Flight Test Facility (FTF, see Reference 17) in Holzkirchen, Germany. Simulations of the same scenario were done by Fraunhofer ITWM using the in‐house CFD software suite MESHFREE 24 .…”

Particulate Matter versus Airborne Viruses—Distinctive Differences between Filtering and Inactivating Air Cleaning Technologies

“…Therefore, the setup differed from the normative requirements for the calculation of the CADR for filtering air cleaners or HADR (hygienic air delivery rate) for inactivating devices [17,53]. Instead of that, the determination of the air cleaner loss coefficient k AC and the natural loss coefficient k nat was implemented by an evaluation model that is based on Equation (1) and consists of various calculation segments [54][55][56]. Each segment represents a characteristic part of the concentration curve and corresponds to a phase of the analyzed experiment.…”