Airborne Particles Measurement for IAQ in Residential Buildings

Keywords: Indoor Air Quality (IAQ), airborne particles, CO₂ concentration, Indoor Environmental Quality(IEQ), Energy Performance of Buildings Directive (EPBD), Metrological Reliability

Introduction

This paper presents and analyzes IAQ measurement techniques and devices focusing on airborne particles, in terms of metrological reliability and accuracy. Furthermore, experimental results aimed at assessing if the airborne particle concentration can be somehow predicted by using low-cost sensors for measuring other parameters, such as CO₂ concentration, are presented.

IAQ measurement and monitoring

Indoor air quality (IAQ) is one of the four environmental input parameters for design and assessment of indoor environmental quality (IEQ) together with lighting, acoustics, and thermal environment. Therefore, assessing IAQ in residential buildings represents a crucial issue among the recommendations provided by the EU in the recent recast of the Energy Performance of Buildings Directive (EPBD). Indeed, the revised EPBD promotes high indoor environmental standards by mandating that new non-residential zero-emission buildings, as well as those undergoing major renovations where feasible, to be equipped with indoor air quality monitoring and controlling devices. IAQ in residential buildings is influenced by various factors, strictly related to people's behavior (e.g., use of pollutant sources, manual airing of rooms) and building characteristics (e.g., ventilation systems, envelope airtightness) [1]. The interaction of these factors determines indoor pollutant and contaminant levels, thereby affecting occupant exposure. Since residential buildings become increasingly airtight to enhance energy efficiency, most of them are still not equipped with ad-hoc ventilation systems [2].

Airborne particles are among the main pollutants that negatively impact IAQ. Their presence is due to combustion phenomena (e.g., cooking activities) predominantly responsible for the emission of sub-micrometric particles (measured as particle number concentration, PNC) rather than super-micrometric ones (i.e., particles measured as particle mass concentration, e.g., PM₁₀ and PM_2.5). Nowadays, the limited diffusion of real-time airborne particles monitoring devices for IAQ is mainly due to high costs and the lack of an easy-to-use approach, in addition to the absence of specific regulation. In this respect, EN 16798-1:2019 suggests admitted limits for indoor and outdoor air pollutants in agreement with the World Health Organization (WHO) requirements [3], leading to several practical criticalities. In fact, the limits for airborne particles are set only for outdoor environments, omitting PNC, despite being considered the most impactful metric in indoor environments. Hence, effective monitoring of IAQ requires accurate measurement of airborne particles, particularly sub-micrometric ones.

The measurement of airborne particle concentration in terms of mass (e.g., PM₁₀ and PM_2.5) and number (i.e., PNC) can be carried out through different methods, as described in Table 1. The reference measurement method for PM₁₀ and PM_2.5 concentrations is the gravimetric method in which a size-selective inlet is used to convey the ambient air at a known constant flow rate, thus allowing the relevant particle fraction to be collected on a filter. The mass of particulate matter is determined by weighing the filter under pre-established and constant conditions before and after the particulate deposition. Thus, the gravimetric measurement can be defined as a direct method since the concentration is obtained as the ratio between the mass of particulate matter collected on the filter and the air volume measured at constant flow-rate in a fixed sampling duration. The expected accuracy of the gravimetric method is typically within 10% and it is mainly due to the metrological characteristics of the balance used (it is also worth noting that the weighing uncertainty shall be computed twice because the method requires a measurement by difference), the sampling flow-rate and duration. Consequently, this method is quite complex and does not allow continuous and automated measurements. Along with this method, continuous and automated measurement systems, based on microbalance, radiometric and optical methods, were developed. The two main measurement methods based on microbalance are the Tapered Element Oscillation Microbalance (TEOM) and the Quartz Crystal Microbalance (QCM). TEOM measures PM mass based on the alteration of the resonance frequency of a tapered quartz wand, due to the accumulation of particles on a sampling filter, which is connected to the wand tip. On the other hand, the piezoelectric quartz crystal sensor of a QCM changes its resonance frequency when even a small variation of the mass on its surface occurs. Radiometric method uses a radiometric source to emit beta particles and to measure the degree of their attenuation which is proportional to the collected mass. Both microbalance and radiometric methods present a good accuracy (even <10%), indeed, the EU Air Quality Directive 2008/50/EC allows the use of such systems if the equivalence with the gravimetric reference method is demonstrated, according the Data Quality Objectives for continuous measurements [4]. Finally, optical instruments, which rely on light scattering, present a lower accuracy (within 20-30%), but they can be employed also as portable devices.

For PNC measurements, the light scattering airborne particle counters (LSAPCs) are the most accurate devices (i.e., accuracy within 10%), as they determine the particle concentration by counting discrete occurrences of light scattered by particles passing through a fixed inspection volume. LSAPCs can be considered the reference method for measuring PNC when they are calibrated according to ISO 21501-4:2018 by using the aerosol electrometer (AE) as a reference. Another method to measure PNC is based on the electrical charging of the aerosols through the diffusion chargers (DCs), with which air ions are generated in a corona discharge and mixed with the aerosol. The charged particles are then detected by electrometers and counted by measuring the charges carried by the particles. The DCs specifications are more relaxed compared to the laboratory-grade systems (accuracy within 20-30%), but their compact size also makes them ideal for personal monitoring.

Table 1. Metrological characteristics for airborne particle measurements.

Despite the instrument's metrological performances, for both PM and PNC measurement, the effectiveness of the sampling procedure is crucial in view of lowering the measurement uncertainties in indoor monitoring. In particular, the distances of the sampling point with respect to ground, walls, ventilation systems and pollutant sources should be preliminarily evaluated to define a sampling point representative of the indoor environment. Moreover, all the thermo-hygrometric parameters, i.e., relative humidity, ventilation speed, air exchange rate and temperature, must be m2easured and recorded aiming at demonstrating the metrological robustness of the data sets.

Experimental campaign and measurement setup

The limited availability of IAQ monitoring devices has prompted an investigation into whether airborne particle concentrations can be predicted using low-cost sensors that measure parameters like CO₂. While CO₂ sensors are reliable for indoor use, PM₁₀ sensors face challenges with calibration, accuracy, and stability [5] and affordable PNC sensors are hardly available yet. This study aimed to evaluate the correlation between airborne particle metrics and CO₂ concentrations through a three-day experimental analysis in 10 homes. The analysis measured reductions in airborne particles and CO₂ following a campaign promoting mitigation strategies, such as opening windows or using kitchen hoods during cooking activities.

Measurements included indoor and outdoor PNCs, PM₁₀, and CO₂ concentrations, taken with two DCs particle counters (Testo DiSCmini), two DustTrak™ DRX Aerosol Monitors (PM₁₀), and a Testo CO₂ probe. Indoor measurements were taken during cooking activities, and outdoor samples were collected from balconies or terraces. Data were post-processed as 1-minute averages.

To ensure data quality, DustTrak photometers were calibrated against the gravimetric method, and DiSCminis were compared to a TSI 3068B AE using NaCl particles. Portable instruments were zeroed using HEPA filters, and 10-minute parallel readings of indoor and outdoor instruments were conducted before each 3-day session. Since outdoor values influence indoor particle concentrations, indoor PM₁₀ and PNC were normalized to outdoor levels, while CO₂ data were left unadjusted due to the negligible effect of outdoor CO₂ variability.

Figure 1. PNC (part. cm-3), PM10 (µg m-3) and CO₂ (ppm) trends (both indoor and outdoor) measured for 24 h in one of the homes under investigation are reported. In the graph the cooking events, are also highlighted in grey bands.

In Figure 1the trends of PNC (part. cm-3), PM₁₀ (µg m-3), and CO₂ (ppm) indoors and outdoors over a 24-hour period in one home are shown, with cooking events marked by grey bands. The data reveal significant peaks during cooking, particularly in PNCs, which increased by 2-3 orders of magnitude compared to pre-event levels. After each peak, concentrations gradually decreased but remained higher than outdoor levels for hours. This decay depends on factors such as air exchange rate, particle deposition, and removal mechanisms (e.g., hoods, air purifiers). CO₂ peaks were also observed during cooking, but their impact was less pronounced due to the occupants' exhaled CO₂ contributing to indoor levels.

Figure 2. Relative reductions amongst median values measured during cooking activities performed within baseline and follow-up periods in the 10 homes as resulting from the quantitative analysis (adapted from [6]).

The analysis of all 10 homes before and after the information campaign revealed that exposure to airborne particles during cooking events was reduced after implementing mitigation strategies. Relative reductions of 28% (23%–39%) for CO₂, 47% (8%–70%) for PM₁₀, and 59% (49%–77%) for PNC were observed (Figure 2), largely due to more frequent and prolonged manual ventilation and hood use, as recorded in occupant diaries. However, reductions in CO₂ levels were poorly correlated with those of PNC and PM₁₀, indicating that airborne particle exposure cannot be accurately inferred from CO₂ levels measured by low-cost sensors.

Conclusions

Specific regulations are becoming increasingly necessary to protect health from the adverse effects of air pollutants, particularly airborne particles, in indoor residential buildings. The experimental campaign demonstrated that increases in PNC, PM₁₀, and CO₂ concentrations and their relative reductions are poorly correlated. It can be concluded that strategies aimed at reducing exposure to all airborne particle metrics (including sub-micrometric particles) cannot be effectively monitored by other pollutants (e.g., CO₂). For these reasons, a development of low-cost devices capable of monitoring airborne particles easily used by occupants in residential environments is necessary.

References

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