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Low-cost monitors make it possible now for the first time to collect long-term (months to years) measurements of potential indoor exposure to fine particles. Indoor exposure is due to two sources: particles infiltrating from outdoors and those generated by indoor activities. Calculating the relative contribution of each source requires identifying an infiltration factor. We develop a method of identifying periods when the infiltration factor is not constant and searching for periods when it is relatively constant. From an initial regression of indoor on outdoor particle concentrations, a Forbidden Zone can be defined with an upper boundary below which no observations should appear. If many observations appear in the Forbidden Zone, they falsify the assumption of a single constant infiltration factor. This is a useful quality assurance feature, since investigators may then search for subsets of the data in which few observations appear in the Forbidden Zone. The usefulness of this approach is illustrated using examples drawn from the PurpleAir network of optical particle monitors. An improved algorithm is applied with reduced bias, improved precision, and a lower limit of detection than either of the two proprietary algorithms offered by the manufacturer of the sensors used in PurpleAir monitors. [ABSTRACT FROM AUTHOR]

This paper reports on the design, and implementation of piezoelectric-on-silicon MEMS resonators installed within a portable experimental setup for sensing nanoparticles in a laboratory environment. MEMS oscillators with a center frequency of approximately 5.999 MHz are employed for sensing 50 nm size-selected silver nanoparticles generated in the laboratory. The same experimental setup is then assembled to sense indoor particles that are present in the laboratory environment. The challenges associated with particle deposition as a result of assembling the portable experimental setup is highlighted. Furthermore, the MEMS oscillators demonstrate that the total mass of silver nanoparticles deposited onto the MEMS resonator surface using the inertial impaction technique-based experimental setup is approximately 7.993 nanograms. The total indoor particle mass accumulated on the MEMS resonator surface is estimated to be approximately 1.732 nanograms and 26.9 picograms for two different runs. The frequency resolution of the MEMS oscillator is estimated to be approximately 32 ppb and, consequently, the minimum detectable particle mass is approximately 60 femtograms for a 9.2 s integration time. [ABSTRACT FROM AUTHOR]

Elevated exposure to airborne particulate matter is linked to deleterious health and well-being outcomes. Exposure assessment can be improved through enhanced understanding of source-receptor relationships, for example as expressed in the inhalation intake fraction metric. This study provides new knowledge about how inhalation intake of airborne particles varies with spatially varying indoor emissions. In a controlled environmental chamber with low background particle levels, we monitored the time- and size-resolved particle concentrations at multiple locations including the subject's breathing zone. We investigated two types of particle emissions: (i) controlled releases from several specific indoor locations; and (ii) natural release from skin and clothing for a range of simulated occupant activities. Findings show that particles released proximate to the human envelope caused a total inhalation intake fraction of 7–10 per thousand, which was 1.5–16 × higher than the intake fraction for other indoor release locations. These outcomes reflect the influence of emissions-receptor proximity combined with the efficient transport of particles by means of the thermal plume to the breathing zone. The results show that the well-mixed representation of an indoor environment could underestimate the inhalation intake by 40–90% for various localized indoor emissions, and by up to 3 × for particles emitted from the human envelope. The post-release exposure period contributed substantially to total inhalation intake. For particles released naturally from the human envelope, inhalation intake fractions varied with activity type and were higher for a subject when seated rather than walking.

Elevated exposure to airborne particulate matter is linked to deleterious health and well-being outcomes. Exposure assessment can be improved through enhanced understanding of source-receptor relationships, for example as expressed in the inhalation intake fraction metric. This study provides new knowledge about how inhalation intake of airborne particles varies with spatially varying indoor emissions. In a controlled environmental chamber with low background particle levels, we monitored the time- and size-resolved particle concentrations at multiple locations including the subject's breathing zone. We investigated two types of particle emissions: (i) controlled releases from several specific indoor locations; and (ii) natural release from skin and clothing for a range of simulated occupant activities. Findings show that particles released proximate to the human envelope caused a total inhalation intake fraction of 7–10 per thousand, which was 1.5–16 × higher than the intake fraction for other indoor release locations. These outcomes reflect the influence of emissions-receptor proximity combined with the efficient transport of particles by means of the thermal plume to the breathing zone. The results show that the well-mixed representation of an indoor environment could underestimate the inhalation intake by 40–90% for various localized indoor emissions, and by up to 3 × for particles emitted from the human envelope. The post-release exposure period contributed substantially to total inhalation intake. For particles released naturally from the human envelope, inhalation intake fractions varied with activity type and were higher for a subject when seated rather than walking.

Low-cost monitors make it possible now for the first time to collect long-term (months to years) measurements of potential indoor exposure to fine particles. Indoor exposure is due to two sources: particles infiltrating from outdoors and those generated by indoor activities. Calculating the relative contribution of each source requires identifying an infiltration factor. We develop a method of identifying periods when the infiltration factor is not constant and searching for periods when it is relatively constant. From an initial regression of indoor on outdoor particle concentrations, a Forbidden Zone can be defined with an upper boundary below which no observations should appear. If many observations appear in the Forbidden Zone, they falsify the assumption of a single constant infiltration factor. This is a useful quality assurance feature, since investigators may then search for subsets of the data in which few observations appear in the Forbidden Zone. The usefulness of this approach is illustrated using examples drawn from the PurpleAir network of optical particle monitors. An improved algorithm is applied with reduced bias, improved precision, and a lower limit of detection than either of the two proprietary algorithms offered by the manufacturer of the sensors used in PurpleAir monitors.

Airborne particle transport in indoor environments plays an important role in occupant exposure to aerosols and public health problems. Several studies have examined indoor airflow and particle transport using computational fluid dynamics models. For the Lagrangian particle tracking model, the minimum particle concentration necessary for accurate prediction may vary with the airflow regime and sampling volume. Nonetheless, only a few studies have systematically quantified suitable particle numbers and sampling volumes, according to indoor airflow and ventilation conditions. This study addresses this gap by exploring quality control strategies for a Lagrangian particle tracking model to reliably predict indoor particle transport. Based on transient simulations, we analyzed the spatiotemporal distributions of indoor particle trajectories while varying the number of particles, sampling volume, and ventilation strategy. The results indicate that in general a sampling volume of 5 L can predict the normalized mean concentrations better than a 1 L sampling volume, particularly when dealing with a smaller number of particles. Furthermore, the required particle number concentrations vary significantly depending on the chosen ventilation strategy. For instance, under the conditions of a 5 L sampling volume and an air exchange rate of 2.7 h−1, the minimum particle number concentrations for achieving reliable modeling predictions were observed to be 0.0075 cm−3 for displacement ventilation and 0.015 cm−3 for mixing ventilation. These results highlight the crucial role of the number of simulated particle trajectories in Lagrangian particle tracking models in determining prediction quality. The study findings suggest that quality control measures should acknowledge the significant variability in required particle numbers, which can often differ by an order of magnitude, contingent upon the specific combination of ventilation strategy and sampling volume. • Quality control strategies for Lagrangian simulation were evaluated. • At a ventilation rate of 2.7 h−1, minimum concentration ranged 0.0075–0.015 cm−3. • A 5 L sampling volume improves prediction reliability compared to 0.5 L and 1 L. • Minimum particle concentrations varied with ventilation strategy over 10 times. [ABSTRACT FROM AUTHOR]

In modern society, ventilation is an important method for removing indoor particles. This study applies the parameter of attenuation index to analyse the effect of the removal of indoor particles in the two typical ventilation modes called ceiling exhaust and slit exhaust. Experiment was conducted in a chamber and riboflavin particles were used as the indoor particles source, instantaneous microbial detection (IMD) used to measure the particulate concentration. The results showed there was obvious concentration difference in the vertical distribution for the slit exhaust when indoor particles tended stable, and the smaller the particle size was, the more obvious the difference was. Air exchange rate (ACH) is an important factor affecting the indoor particle concentration distribution. In the process of indoor free settling (air exchange rate is 0 ACH), the sedimentation rate were 0.086 h −1 , 0.122 h −1 and 0.173 h −1 for the particles of 0.5–1.0 μm, 1.0–3.0 μm and 3.0–5.0 μm. When the air exchange rate increased to 2.5 ACH, the differences in the attenuation index is significant. There was also a significant linear relationship between air exchange rate and attenuation index. Furthermore, the effect of the slit exhaust mode on the removal of coarse particles is more remarkable as the increasing air exchange rate. [ABSTRACT FROM AUTHOR]

Two dynamical models, the traditional method of moments coupled model (MCM) and Taylor-series expansion method of moments coupled model (TECM) for particle dispersion distribution and gravitation deposition are developed in three-dimensional ventilated environments. The turbulent airflow field is modeled with the renormalization group (RNG) k – ε turbulence model. The particle number concentration distribution in a ventilated room is obtained by solving the population balance equation coupled with the airflow field. The coupled dynamical models are validated using experimental data. A good agreement between the numerical and experimental results can be achieved. Both models have a similar characteristic for the spatial distribution of particle concentration. Relative to the MCM model, the TECM model presents a more close result to the experimental data. The vortex structure existed in the air flow makes a relative large concentration difference at the center region and results in a spatial non-uniformity of concentration field. With larger inlet velocity, the mixing level of particles in the room is more uniform. In general, the new dynamical models coupled with computational fluid dynamics (CFD) in the current study provide a reasonable and accurate method for the temporal and spatial evolution of particles effected by the deposition and dispersion behaviors. In addition, two ventilation modes with different inlet velocities are proceeded to study the effect on the particle evolution. The results show that with the ceiling ventilation mode (CVM), the particles can be better mixed and the concentration level is also higher. On the contrast, with the side ceiling ventilation mode (SVM), the particle concentration has an obvious stratified distribution with a relative lower level and it makes a much better environment condition to the human exposure. [ABSTRACT FROM AUTHOR]

Many studies have been carried out on the environmental impact of the research stations on the Antarctic continent. However, the assessment of indoor air quality in these confined environments has been neglected. The main objectives of this study are to investigate the granulometric distribution of the indoor particles in the different compartments of the Brazilian Antarctic Station, to examine the number and mass concentration of the indoor particles, to conduct chemical and morphological analyses of the indoor PM2.5, and to identify the possible sources of the PM. The results showed that Na, K, Cl, Fe, Zn, S and Si were the main elements detected. High levels of black carbon were recorded in the workshop, which may be associated with the use of diesel vehicles. To identify the human activities related to the indoor particle emission in the station, the size distribution of the particles in the living room was monitored for seven consecutive days, during normal station operation. It was possible to identify the influence of individual processes, such as incineration, cooking and the movement of people, upon the particle size number concentration. The indoor/outdoor (I/O) ratio for the total suspended particles (TSP), PM10, PM2.5 and PM1 measured was significantly larger than those reported for urban buildings. In general, the I/O ratio distribution for all the compartments shows peak values between 2.5 and 10 μm, which is often related to human activity, such as cleaning, personnel circulation or clothing surfaces. The maximum I/O ratio at this range varied from 12 to 60. In addition, the compartments affected by combustion processes tend to present a significant number of submicron particles. [ABSTRACT FROM AUTHOR]

To determine the composition of particulate matter (PM) in the indoor environments of four different types of archives (three naturally ventilated and one filtered), intensive size-resolved sampling was performed for four seasons of the year. For reconstituting indoor PM, nine aerosol components were considered. Organic matter was the dominant component of both fine and coarse fractions and represented approximately 50–80% of the PM. In the fine fraction, the next most abundant components were elemental carbon and sulphate, and in the coarse fraction the next most abundant were crustal matter, sulphate and nitrate. The resulting mass closure explained 95(±13)% and 115(±38)% of the gravimetric indoor PM in the fine and coarse size fractions, respectively. The results revealed that all the particles found indoors can be considered to be potentially threatening to the stored materials. The results also showed that the most important source of indoor PM in the naturally ventilated archives was penetration from the outdoor air, whereas in the filtered archive, the concentrations of particles were strongly reduced. In naturally ventilated archives the influence of domestic heating, road traffic and local sources (industrial pollution, camp fires) was observed. Furthermore, activities of the staff were identified as an indoor source of coarse particles in all archives. [ABSTRACT FROM AUTHOR]

Abstract: A new drift–flux model for particle distribution and deposition in indoor environments is developed. Gravitational settling and deposition are examined thoroughly and the model is applied to simulate particle distribution and deposition in a ventilated model room. The turbulent airflow field is modeled with the renormalization group (RNG) k–ε turbulence model. For the particulate phase, the concentration field is divided into two regions, the core region and the concentration boundary layer. The concentration distribution in the core region is obtained by solving a three-dimensional particle transport equation. Deposition flux towards the wall is determined with a semi-empirical particle deposition model. With the feasibility of the proposed Eulerian model, the influences of the other deposition mechanisms can be captured easily into the model. The model is validated experimentally and a good agreement between numerical and experimental results is found. Inferring from the result, it shows that the well-mixed assumption cannot hold for coarse particles. The model presented in the current work provides an efficient and reliable tool for investigation of spatial and temporal particle concentration in enclosures and the result will be very useful for improving our current understanding of human exposure assessment. [Copyright &y& Elsevier]

Diurnal variation of indoor submicrometer (0.007–0.808 μm) particle number and particle mass (approximation of PM2.5) concentrations was investigated in 15 houses in a residential suburb of Brisbane during winter in 1999. Continuous monitoring for more than 48 h was conducted using a condensation particle counter (CPC) and a photometer (DustTrak) in the kitchen of each house, and the residents kept diaries of the activities conducted. In addition, data from a central monitoring station was used to investigate indoor/outdoor relationships. The results show that there were clear diurnal variations in both particle number and approximation of PM2.5 concentrations, for all the investigated houses. The pattern of diurnal variations varied from house to house, however, there was always a close relationship between the concentration and human indoor activities. The average number and mass concentrations during indoor activities were (18.2±3.9)×103 particles cm−3 and (15.5±7.9) μg m−3, respectively, and under non-activity conditions, (12.4±2.7)×103 particles cm−3 (11.1±2.6)±μg m−3, respectively. In general, there was a poor correlation between mass and number concentrations and the correlation coefficients were highly variable from day to day and from house to house. This implies that conclusions cannot be drawn about either one of the number or mass concentration characteristics of indoor particles, based on measurement of the other. The study also showed that it is unlikely that particle concentrations indoors could be represented by measurements conducted at a fixed monitoring station due to the large impact of indoor and local sources. [Copyright &y& Elsevier]