## 3 Results and Discussion  
Prior to the comparison study, it is worthwhile to verify how long both devices operate with fully charged battery status at the setting of the sampling time = 1 min and the sampling flow rate = 0.1 lpm. Battery consumption test was repeated more than 3 times and both devices lasted approximately 17 to 22 h. The battery of Inst_2 lasted for 1332 min (around 22 h) and that of Inst_1 did for 1070 min (around 17.8 h) in average. The battery time was shorter than 24 h given by the manufacturer's specification, meaning that those devices are not new but are more than 4 years old, as mentioned earlier. Thus, it is natural that the battery lasts for a shorter time than a new device. The battery consumption rate will vary depending on the sampling interval and the sampling flow rate. The reason why battery of the old one (Inst_2) lasted longer than the new one (Inst_1) is that the new one (Inst_1) has been used more frequently than the old one (Inst_2) because of its stable acquisition of data. Thus, the battery performance of the new one degraded faster than the old one. We confirmed that the spot area of the filter is 7.07 mm\({}^{2}\) and the mass attenuation cross section is 12.5 m\({}^{2}\)/g by calculating the BC concentration using Equation (3) with the aforementioned spot area and mass attenuation cross section. The ratio of BC concentration to ATN remains constant during the measurement (not shown), which also verifies that microAeth\({}^{\circledR}\) AE51 does not apply any corrections for filter loading and scattering effect. Figure 2 shows a typical BC concentration collected from two devices for indoor BC. The Inst_1 intermittently exhibits spike noises while the Inst_2 does not. The occurrence of intermittent spikes, however, was not reproducible. Sometimes, the Inst_2 exhibited more severe spike noises than Inst_1 does, implying that the noise was not device-dependent. Changes in ATN values for two devices are also shown in Figure 2 as a function of time. Both devices show gradual increase in ATN values, meaning that the filter has been darkened by indoor aerosols. It is interesting to note that the initial ATN value is different from device to device. Even negative ATN value was reported in some cases for the initially installed clean filter though the initial negative ATN value does not affect the calculation of BC concentration [1]. As can be seen in Figure 3a, two devices show excellent agreement for the data shown in Figure 2. The slope of the linear fitting curve for Inst_2 versus Inst_1 is 0.972. The coefficient of determination (R\({}^{2}\)) is 0.976. However, Figure 3b shows that the relative error between both devices becomes larger when the battery status of Inst_1 is lower than 0.8 (The battery status indicates 1.0 at full charge). Not only is the slope deviated from 1, but the coefficient of determination is also lower than the case where the battery status was higher than 0.8. The y-intersect is also higher than the case where battery status was over 0.8. Nominally, the error is expected to be larger than 10% at low battery status. Note that a similar test is needed with respect to Inst_2 to completely understand the effect of battery status on the performance of devices. Data collected at low battery status may need to be double-checked for assurance. The process of obtaining BC concentration is as follows; (i) measurement of reference signal and sensing signal as inputs; (ii) calculation of ATN at time t using Equation (1); (iii) calculation of ATN at time \(t+\Delta t\); (iv) calculation of \(\Delta\)ATN using Equation (2); and (v) conversion of \(\Delta\)ATN into BC concentration using Equation (3). As an attempt to reduce noise, we took a numerical derivative of ATN. We observed that the time series of the numerical derivative of ATN showed very nice similarity to BC concentrations, as can be seen in Figure 4. Furthermore, the intensity of intermittent spikes decreased for both Inst_1 and Inst_2.