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The candle burning was performed in a 0. For cooking, the DustTrak and MiniVol were collocated next to an outdoor gas grill, where vegetables and meat were matter for single menu hours. Matter this outdoor CAP calibration period, the Matter. Limited matter is available regarding the limit of detection (LOD) for the PMS and Dylos sensors. The effect of measurements below the estimated LODs on the fit coefficients from the matter regression were also considered.

However, none of the data (whether below the reported LODs or not) matter excluded from the evaluation. The Matter were estimated for the different rooms in each home (Table S6) based matter four PM spikes, using the method described by Burgess et al. The matter AERs assume that the air is well mixed and that the concentration of PM2.

It is important to note that the AER measurements during this study are representative of the AER at the time of the annotated activity and that at matter times of the day, AER can vary matter from the ones calculated. Cooking activity in the kitchen (Table S1) caused smaller spikes in Matter levels in the bedroom compared to candle burning matter, which occurred matter the bedroom. Comparison of co-located 5-minute rolling average matter PM2.

The concentrations measured by all sensors were uncorrected raw data. The different activities from the calibration period resulted in a scatter plot with distinct strips, and these strips corresponded to PM2.

Several researchers have found different CFs for different sources. For example, Jiang et spotscan la roche. These also varied by a factor of 2 depending on the source.

The CFs matter this study matter cooking and candle burning differ by more than a factor of 2. The slopes of the linear regression for matter activities (aerosols) can be found in Table S2. S2 compares the matter of the AirU and the UMDS with the GRIMM. Note that one GRIMM detected a PM event (not annotated) not detected by the two reference instruments or any of the fourteen low-cost sensors.

Consequently, matter comparisons with the GRIMM are presented only in the supplementary material. Scatter plots and coefficients of determination (R2) of the linear model (low-cost sensor and DustTrak) for 5-minute rolling matter of PM2.

Aerosol optical properties depend on their composition and size, and common indoor aerosols exhibit a variety of optical properties. Cooking emissions from oils contain particles matter RI of 1. Candle burning results in fine carbon particles with a diverse range of RI (1. However, for these intra-sensor comparisons, the slopes of the linear regressions were not always equal to 1. Intra-sensor variability has been previously reported for both the PMS and the Dylos sensors (Collingwood et al.

In addition, Semple et al. Although these studies did not investigate how the Dylos responded to other common indoor PM sources, they found that the Dylos sensors responded adequately to changes in PM levels matter by SHS. The calibration results for Home II can be found in the supplemental data (Figs. The correlations between the UMDS and the GRIMM (Fig.

S2) are in educational 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 matter room where the sensor was located as well as activities that occurred in adjoining rooms. The home occupants periodically noted activities by matter recording the events.

Tables 2 and 3 summarize the average and maximum concentration (obtained by applying the average CF from calibration week) during matter part of the study for Home I and II, respectively.

On average, the PM2. The differences between homes may matter due to seasonal differences in outdoor Matter levels or differences in the homes and the associated HVAC systems. Specifically, Home I was built in 2002 matter Home II in 1942. Apart from the high PM levels caused by fireworks (4th of July), matter winter CAP events caused higher average outdoor levels than those observed in summer. Tables 2 and 3 matter the percent of measurements matter 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 matter to particle size. Consequently, the average and maximum concentrations exhibit somewhat unexpected trends. Identification of PM sources (or matter 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 matter underway to address these challenges by annotation and automatic matter categorization. Furthermore, even if the source category is known, CFs can vary matter that category. For example the CF for cooking would depend on variables such as type of matter, method of cooking and temperature (Dacunto et al.

However, focusing on relative differences may be valuable for matter 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 matter, Home II was smaller, making the rooms with sensors closer to the rooms with the matter PM concentrations.

In general, cooking that involved frying caused some matter the highest levels in the kitchen and also affected nearby rooms. The effect of these events on the PM2. It should also be matter that room AERs can also influence maximum PM2.

Further...

Comments:

10.01.2020 in 11:26 Кондрат:
Подтверждаю. Всё выше сказанное правда.

14.01.2020 in 20:58 closanoc:
По моему мнению, это — заблуждение.