IAQ 2016 Defining Indoor Air Quality: Policy, Standards and Best Practices Co-Organized by ASHRAE and AIVC

In France, various controls and measurements are performed in order to assess the performance of ventilation system, such as visual controls, airflow and pressure measurements at terminal devices and ductwork airleakage measurement. Those tests are performed according to several protocols, which might conduct to different results with different uncertainties. In this context, 8 French organisms participate to the PROMEVENT program, which is supported by the French Ministry for Construction and ADEME (French Agency for Energy). It aims to make the practices more uniform and to improve ventilation systems inspection protocols for both single-family houses and multi-family dwellings. In order to test the reliability of those protocols, various measurements have been performed on 2 multi-family dwellings with humidity demand controlled ventilation system and 10 single-family houses with balanced ventilation with heat recovery systems. For airflow and pressure measurements at terminal devices, tests have been performed by different operators, with different types of material, on different types of terminal devices, on repeatability conditions and with different applications of the protocol. The same method has been applied for ductwork airleakage measurements, with also different ductwork preparation and different parts of the ductwork tested. The analysis of these different measurements points out the weaknesses of the protocols and/or the minimum specifications the instruments should achieve to assure reliable results. In particular, for airflow measurement at terminal devices, the position of the material around the terminal could induce very important errors if the material is not centered or not airtight with the wall around the terminal. Moreover, the type of material used may induce uncertainties due to the technology (not all technologies might be used with all types of terminal) and due to the material it-self (important impact of the correction with calibration data). For ductwork airleakage measurements, important differences of the results have been noticed with different obstructions of the ductwork at terminal devices. Results could also be different between a measurement performed in one time (one section) or in two times (the same section divided in two sections). Therefore, all the tests performed during these campaigns confirm the need for a unique and more reliable protocol. Those results are consistent with the results of tests performed during the laboratory campaign of the program. A new protocol will be proposed and tested during the next phases of the PROMEVENT project, including uncertainties evaluation for each type of measurement.

The paper 'The Zero Pressure Paradox' (Bink et al, 2015), explains the theoretical limitations and some practical issues of the zero pressure compensation method as used by a powered flow hood. It was shown that the needed pressure compensation for supply and exhaust are fundamentally different. Furthermore, based on published results from others and on our own unpublished results, we claimed that the measuring accuracy depends on the type of air terminal device and how and where the pressure to be compensated is measured in the instrument. To minimize these effects we developed the 'extended' zero pressure method. To follow up on this and for further clarification, this paper presents the evaluation of a large number measurements with a powered flow hood. Both measurements of supply and exhaust at a large number of grids are presented together with an uncertainty analysis of measuring ventilation.

Chamber, Air duct, and test house experiments were carried out in order to characterize performance of a new “green” air tracing technology. Chamber experiments measured tracer broadcast control and safety. Sensor experiments tested multi instrument precision and tracer-sensor performance in ducts and ambient space. Building experiments included air change rate measurements using both the new tracer and sulfur hexafluoride (SF6) tracer. In-duct ventilation air supply ratio was measured in real time using sensors located before and after the mixed air supply. Three-hour and 18-hour room measurements showed greater decay of LIPA tracer versus SF6. PID measurements showed good agreement between multiple continuous reading sensors over these time periods. Good safety, broadcast control, real-time sensing, and multi-sensor precision were demonstrated. The strengths of this new method over previous tracer technologies demonstrated in these experiments include the ability to rapidly measure changes in labeled air levels in real-time, using relatively low cost sensing instruments. Examples of uses for real-time air tracing include commissioning, test and balance air distribution systems and ventilation effectiveness surveys, as well as verifying exhaust systems performance and air leakage testing.

Considerable focus on intelligent building control has expanded interest in incorporating more sensors into buildings, including ones for measuring indoor air quality. In commercial buildings with automation systems, adding more indoor air sensing in more locations could enable more effective ventilation control through dynamic and spatial fine-tuning, helping to save energy, improve air quality, or both. But how necessary and how useful is adding more than one air quality sensor per mechanical zone in typical commercial buildings with air-mixing mechanical systems, given the accuracy of available sensors? We assessed two approaches for locating from one up to 10 sensors for measuring carbon dioxide (CO₂) and the sum of volatile organic compounds (ΣVOC) in typical offices. One placement approach was intended to determine the best possible performance, using optimal clustering of locations by their concentration profiles; the second simply sited each additional sensor in the mechanical system’s return duct and averaged readings. Each approach was assessed at three levels of sensor accuracy in four different office cases that combined high or low air recirculation rates and open or private layouts. The analysis was conducted within a Monte Carlo framework in which dozens of other parameters—including spatially resolved emission rates, air mixing parameters, schedule profiles, and envelope and wind characteristics—were varied for each case. The results indicated that, in an office environment with at least some mechanical air recirculation, concentrations are reasonably homogeneous within a mechanical zone. The spatial coefficient of variation (the spatial standard deviation normalized by the mean concentration) was almost always less than 20%, even when spatial emissions variability was highly elevated. The spatial variation that did exist was generally overwhelmed by sensor error when typical building grade sensors were modeled. The implications are that: 1) for typical office spaces served by a common air-based system with at least a small amount of mechanical air recirculation, a well-mixed model is a reasonable representation of the bulk air concentration (though not necessarily personal exposure); 2) attempting to capture spatial distribution is less important than improving sensor accuracy, and without better accuracy can actually increase network inaccuracy; 3) if using and maintaining better sensors is not possible, placing more typical building grade sensors in the return duct to provide redundancy can help reduce overall error.

This paper discusses two particular points of the buildings airtightness measurement method (EN ISO 9972:2015) in relation with the calculation of the combined standard uncertainty; Zero-flow pressure difference and Line of organic correlation. The zero-flow pressure difference is measured before and after the test in order to calculate the change of pressure caused by the blower door. Actually the zero-flow pressure difference fluctuates during the test in function of the wind and the temperature difference between outside and inside of the tested building. One could therefore consider that all measured values have the same probability of occurrence during the test (rectangular probability distribution) and adapt in consequence the way of calculating the ‘mean’ zero-flow pressure difference. The paper shows how it could be done and taken into account in the calculation of the combined standard uncertainty. The air flow coefficient and air flow exponent are generally determined using an ordinary least-squares regression technique (OLS). This is however generally not the most appropriate technique because there are uncertainties in both the measured air flow rates and the pressure differences. The paper shows how the line of organic correlation (LOC) could be used in order to take these uncertainties into account.

With better insulation of buildings, indoor air pollution is becoming a growing concern for human well-being and human health. Today there is no easy way to determine in real-time indoor air quality because of two main reasons. First, there are thousands of pollutants in indoor air with diverse impacts on human comfort, health and safety. Second, the concentration of these pollutants are generally very low (few ppb). In order to monitor Indoor Air Quality, one can use relatively low cost sensors that give an estimation of the amount of pollution in situ and in real-time but without discriminating harmful pollutants from non-harmful pollutants. It is thus difficult to give accurate advice to reduce the level of indoor pollution. Another way is to sample air and analyze the samples in laboratories with very sensitive but also expensive devices. The last case presents some drawbacks; it takes time, both for sampling (1 hour up to 5 days) and for analyzing (~2 weeks) before knowing if there is any indoor air problem. Then, if there is one, more air samples have to be taken and analyzed in order to identify and locate the pollution emission source and begin to look for a solution to prevent pollution. It is costly. French government estimated indoor air diagnoses cost at around 3,000 euros per school building; It requires a specialist operator to identify the pollution origin. Here, we propose a new way to perform fast, low-cost indoor air quality diagnoses at high added value in buildings by using an innovative photo-acoustic analyzer. Thanks to its ability to measure: a) multiple individual chemical pollutants, b) in real-time c) and in-situ at ppb level. Indoor air diagnosis results can be obtained in few minutes only. In addition the emission sources of air pollution can be easily located. Thanks to the fact that this tool can be used by a non specialist and diagnosis results given in less than an hour, the diagnosis price can be divided by two compared to traditional indoor air diagnoses. The idea is also to save in a cloud contextual collected data during diagnoses (concentration of each monitored pollutant associated with the indoor environment) so that predictions (and some remediation solutions) of indoor air pollution can be made in similar environments.

Inhalation exposure to airborne particulate matter is closely linked to human health and comfort. National regulatory agencies utilize high-precision air quality instruments to monitor ambient air pollution; however, such instruments are often expensive and not practical for widespread building applications. Gathering indoor air data for building occupants can help address occupants' needs and improve public health. The main objective of this study is to validate the performance of a low-cost air quality sensor that monitors both particulate matter and total volatile organic compounds (TVOC). The present study involves experiments with three different environmental settings: 1) 240-L laboratory chamber, 2) one-person office, and 3) highly occupied cafeteria. A popular low-cost sensor, Samyoung’s Dust Sensor Module MDG 501S, was tested. The sensor had a small module with a particle counter and gas sensor inside. The low-cost sensor was validated with laboratory grade sensors: TSI AeroTrak Handheld Optical Particle Counter Model 9306 for particles and ppbRAE PGM-7240 gas sensor for TVOC. The laboratory chamber test results indicate that the low-cost sensor gives accurate readings for high particle concentrations (> 1000/m³) in the chamber. However, the accuracy and sensitivity decrease with lower concentrations that could be easily found in buildings. The sensor readings from the one-person office are highly correlated with occupancy, likely due to particle resuspension from flooring/clothing and skin shedding during occupancy. However, the sensor accuracy observed in a highly occupied cafeteria was the lowest and showed high variations in concentrations. In this environment, increased human activities seem to cause fluctuations in airflow and airborne particle concentrations, which could be difficult for the low-cost sensor to monitor. Nonetheless, the study results imply that the low-cost sensor system has potential applications in indoor air quality monitoring and pollutant control in occupied spaces.