Indoor particle dynamics in schools: Determination of air exchange rate, size-resolved particle deposition rate and penetration factor in real-life conditions

2015 ◽  
Vol 26 (10) ◽  
pp. 1335-1350 ◽  
Author(s):  
Dinh Trinh Tran ◽  
Laurent Y Alleman ◽  
Patrice Coddeville ◽  
Jean-Claude Galloo

Indoor and outdoor airborne particles, CO, CO2 levels and comfort parameters were monitored at two naturally ventilated elementary schools (S1 and S2). This paper studies the variation of ventilation rate during lectures, recreations, lunchtime and after class. Additionally, mass balance equations were used to estimate the particle deposition rates and penetration factors for different particle size fractions. The originality of the present work resides in taking advantage of occupants’ activities as sources of indoor particles and tracer gas CO2 used to simultaneously estimate the above-mentioned parameters in different scenarios. This simple approach makes the determination of indoor particle dynamics more effective, and allows reducing the cost of indoor air quality studies. During the class, the ventilation rates at S1 and S2 fluctuated largely from day to day, with respective average values of 10.08 m3/h/p and 7.92 m3/h/p, significantly lower than the ASHRAE acceptable value (18 m3/h/p) in classrooms. The particle deposition loss rate coefficients for 0.3–10 µm particles dramatically increased from 0.16–0.18 h−1 for the 0.3–0.5 µm fraction to 1.81–2.31 h−1 for the 7.5–10 µm fraction, while their corresponding penetration factors declined from 0.94 to 0.30, respectively. The difference in deposition rate between schools was probably associated to discrepancies in particle density.

2020 ◽  
pp. 1420326X2094442 ◽  
Author(s):  
Yonghang Lai ◽  
Ian Ridley ◽  
Peter Brimblecombe

Particle deposition and penetration in buildings has been widely studied, but the effect of indoor characteristics merits further investigation, so improved experimental methods may be needed. The present study measured indoor and outdoor concentrations of PM2.5 and estimated PM2.5 deposition rates and penetration factors under a variety of different indoor situations, with a novel method (blower-door method). The blower-door method is compared with the standard decay and rebound method for an idealized room (a portable building test cell; 6.08 m [Formula: see text] 2.40 m [Formula: see text] 2.60 m) under eight testing scenarios (empty, cardboard boxes in three arrangements, terry cloth wall covering, and three sets of window holes); run three times to establish the coefficient of variation representing precision. Results show that higher induced indoor–outdoor pressure differences cause a larger variation of estimated effective deposition rate on different indoor surfaces. The deposition rate and penetration factor may be influenced by indoor surface materials. The blower-door method gives higher precision for the estimates, and detects subtle differences in penetration factors, which may be difficult using the decay and rebound method.


Urban Science ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 2
Author(s):  
Yonghang Lai ◽  
Ian A. Ridley ◽  
Peter Brimblecombe

Ingress of air from neighboring apartments is an important source of fine particulate matter (PM2.5) in residential multi-story buildings. It affects the measurement and estimation of particle deposition rate and penetration factor. A blower-door method to measure the particle deposition rate and penetration factor has previously been found to be more precise than the traditional decay-rebound method as it reduces variability of PM2.5 ingress from outside. CONTAM is a multi-zone indoor air quality and ventilation analysis computer program to aid the prediction of indoor air quality. It was used in this study to model the indoor PM2.5 concentrations in an apartment under varying PM2.5 emission from neighboring apartments and window opening and closing regimes. The variation of indoor PM2.5 concentration was also modeled for different days to account for typical outdoor variations. The calibrated CONTAM model aimed to simulate environments found during measurement of particle penetration factor, thus identifying the source of error in the estimates. Results show that during simulated measurement of particle penetration factors using the blower-door method for three-hour periods under a constant 4 Pa pressure difference, the indoor PM2.5 concentration increases significantly due to PM2.5 generated from adjacent apartments, having the potential to cause an error of more than 20% in the estimated value of particle penetration factor. The error tends to be lower if the measuring time is extended. Simulated measurement of the decay-rebound method showed that more PM2.5 can penetrate inside if the PM2.5 was generated from apartments below under naturally variable weather conditions. A multiple blower-door fan can be used to reduce the effects of neighboring emission and increase the precision of the penetration estimates.


Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad

In a chemical system with many chemical species several questions can be asked: what species react with other species: in what temporal order: and with what results? These questions have been asked for over one hundred years about simple and complex chemical systems, and the answers constitute the macroscopic reaction mechanism. In Determination of Complex Reaction Mechanisms authors John Ross, Igor Schreiber, and Marcel Vlad present several systematic approaches for obtaining information on the causal connectivity of chemical species, on correlations of chemical species, on the reaction pathway, and on the reaction mechanism. Basic pulse theory is demonstrated and tested in an experiment on glycolysis. In a second approach, measurements on time series of concentrations are used to construct correlation functions and a theory is developed which shows that from these functions information may be inferred on the reaction pathway, the reaction mechanism, and the centers of control in that mechanism. A third approach is based on application of genetic algorithm methods to the study of the evolutionary development of a reaction mechanism, to the attainment given goals in a mechanism, and to the determination of a reaction mechanism and rate coefficients by comparison with experiment. Responses of non-linear systems to pulses or other perturbations are analyzed, and mechanisms of oscillatory reactions are presented in detail. The concluding chapters give an introduction to bioinformatics and statistical methods for determining reaction mechanisms.


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