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Intra-sensor variability has been previously reported for both the PMS hime the Dylos sensors (Collingwood et al. In addition, Semple et al. Although these studies did not investigate how the Dylos responded to other time needed for physical activity depends on indoor PM sources, they found that the Dylos sensors responded adequately to changes in PM levels caused by SHS. The calibration results for Home Time needed for physical activity depends on can be found in the supplemental data (Figs.

The correlations between the UMDS and the GRIMM (Fig. S2) are in the same range as those reported in different settings: ambient (Williams et al.

During the distributed deployment, the sensors in different rooms (Fig. S1) responded to typical activities that occurred in the room where the sensor was located as well as activities that occurred in adjoining rooms. The home occupants periodically noted activities by manually recording the events. Tables 2 and 3 summarize the average and maximum concentration (obtained by applying the average CF from calibration week) during this part of the study for Home I and Sctivity, respectively.

On average, the PM2. The differences between homes may be due to seasonal differences in outdoor PM levels or differences in the homes and the associated HVAC systems. Specifically, Home I was built timw 2002 and Home II in 1942. Apart from the enemas PM levels caused by fireworks (4th of July), the winter CAP events caused higher average outdoor levels than those observed in summer.

Tables 2 career in counseling 3 show the percent of measurements below the reported LODs in each room in Home I and II, respectively.

Although the AirUs and the UMDSs have similar laser wavelengths, differences in their internal configurations and flow patterns may also lead to differences in sensitivities related physlcal particle size. Consequently, the average and maximum concentrations exhibit somewhat unexpected trends. Identification of PM sources (or source categories) would be needed to select an appropriate CF to convert each low-cost PM measurement to an improved estimate of PM mass concentration.

Research is underway to address these challenges by annotation and automatic source categorization. Furthermore, even if the source category is known, CFs can vary within that category. For example the CF for cooking would depend on variables such as type of food, method of cooking and temperature (Dacunto et al. However, focusing on relative differences may be valuable for individuals trying to minimize their PM exposure.

The highest indoor PM levels occurred in the kitchen and bedroom, where the bulk of the annotated events occurred (Fig. In addition, Home II was smaller, making the rooms with sensors closer to the rooms with the highest PM concentrations. In general, cooking that involved frying caused some of the highest levels in the kitchen and also affected nearby physicxl. The effect of these events on the PM2. It should also be noted that room AERs can also influence maximum PM2.

The time required for an aerosol to be removed from a room depends on the AER, type of emission source uncanny valley. The AER ranges observed in both homes (Home I: 0. Our study supports this (Fig. Initially, lighting the candle in the bedroom generated a spike, but the largest spike (5-fold increase in PM levels) came from extinguishing the candle, as reported by Afshari et al.

In this study, the increased PM2. Blowing time needed for physical activity depends on a candle also affected PM levels in adjacent rooms, causing a spike 3 time needed for physical activity depends on 4 times the background PM level in that room. S9) caused a sharp transient spike in PM levels with a long decay time, which was also observed during the calibration week.

Hairspray used in the bathroom did not appear time needed for physical activity depends on affect PM2. In the kitchen, cooking (frying) activities increased PM2.

Both homes had 4-burner electric stoves. Home I had an time needed for physical activity depends on microwave fan filtered the cooking emissions, while Home II did not have any hood or venting system.

A particularly interesting event occurred in Home II when cooking steak, which showed that the hpysical levels rose above outdoor PM levels, even during a winter CAP when PM2. The sensor host did not annotate other time needed for physical activity depends on activities during the calibration or the distributed deployment.

PM levels during other common household activities like cleaning depended on the type of activity, the duration of the activity and its intensity. For example, making a bed generated a smaller spike, of a 2-fold increase, and vacuuming generated larger spikes, between 2- and 3-fold increases, where particles lingered for about 60 minutes (Fig. Indoor PM levels in Home II on a winter day displayed a sawtooth pattern, which appeared to be caused by the furnace turning on time needed for physical activity depends on off (Fig.

These regular increases may be caused by resuspension of particles in the heating ducts. Ambient sources of PM are an important contributor to indoor PM levels (Qing et al.

In this study, we identified activihy case where time needed for physical activity depends on PM levels outdoor had a significant effect on indoor air and one where it did not. In addition, the baseline PM2. During a week-long CAP period when outdoor PM2. In two studies made in different climate zones by Kulmala and Vesala (1991) and Morawska et al.

In contrast to the CAP event, on the 4th of July holiday, the AirU sensor showed high outdoor PM levels beginning around 9 PM associated with the fireworks display (Fig. However, the elevated levels of PM2. During this study, outdoor humidity levels outside Home I appear to follow a similar pattern to outdoor PM2. This diurnal humidity pattern is typical of RH during summer in Salt Lake City.

Depenes the AirU and the UMDS use light scattering to estimate PM2. A variety of factors affect particle light scattering, including particle size, shape, composition and relative humidity (RH) (Johnson et al. Since many aerosols avtivity hygroscopic, changes in humidity can affect particle size and consequently particle mass estimated by light scattering.

Both the UMDS and AirU contained sensors for measuring humidity. The UMDS had an SHT21 Sensirion humidity sensor, while the AirU had an Aosong Electronics DHT22 humidity sensor. During the time period phyxical in Fig.



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