## 3 Results and Discussion
### Zero Test Using Filtered Clean Air  
The zero test was performed to validate the noise levels at different sampling time settings. BC concentrations for filtered clean air are shown in Figure 9. Noise levels were acceptable to the measurement of BC at low concentrations except when the sampling time was 1 s. Note that the variation of BC concentrations at 1 s of sampling time is 10 times higher than those for 30, 60, and 300 s. For further analysis, standard deviations (error) of BC concentrations at each sampling time settings were plotted versus the sampling time, and a curve fitting between the standard deviations and the samplings time was performed using a power law relation. According to Equation (3), the noise levels increase as the sampling time gets shorter and it is not unreasonable to infer that the power would be \(-1\). However, the power in this present study turned out to be \(-0.72\), which means that there are other  
Figure 8: Difference of \(\Delta\)ATN (attenuation) between Inst_1 and Inst_2. Figure 7: Spectrum of Fast Fourier Transform (FFT) for the black carbon (BC) concentration collected by Inst_1 and Inst_2 every minute. sources of noise generation. Presumably, a drift in ATN exists similarly to the case of AE-31 which is an instrument for monitoring BC continuously and operates with a principle similar to AE51 [7]. Figure 10 presents BC concentrations and the variations of ATN for filter-cleaned air at different sampling time settings. Errors get bigger as the sampling time gets shorter. It is worthwhile to note that BC concentrations turned out to be near zero in average, though real-time negative values were present for all the different sampling time settings. One of the unexpected features in the present performance test is that the ATN values varied even though particle free air was introduced into the device. Figure 10 clearly shows that ATN nominally decreased for all the sampling time settings though ATN should be constant for particle free air. In order to further investigate the decreasing tendency in ATN as a function of time, the zero test was performed for 10 days under the condition where the sampling time was set to 60 s and the sampling flow rate was 0.1 lpm. These settings were the most stable among other setting values. As already investigated, the battery lasts only about 20 h. To test longer than 20 h, we used two auxiliary battery packs which are frequently used for charging smartphones and tablets. For the entire data collected for 10 days, the average concentration was \(-0.011\) ng/m\({}^{3}\) and the standard deviation was 46.9 ng/m\({}^{3}\). These values are similar to those obtained during the short term zero test performed for 6 h. Generally, microAeth(r) AE51 performs extremely well, as it should. The concentration overshot occasionally due to the sudden changes in ATN, which was probably caused by the battery status. As can be seen in Figure 11, an auxiliary battery charged the internal battery installed in a device from around 80% up to full charge status as soon as the auxiliary battery was connected to the device. Then the auxiliary battery was used as a power source as long as it drained until Apr. 22. As soon as the auxiliary battery ran short of its power, the fully-charged internal battery started to be used as a power source. ATN changed subsequently on the moment when the power source was switched from the auxiliary battery into the internal battery with the auxiliary battery being connected to the device. Sudden changes in flow rate might cause abrupt variation in BC concentration because one of the variables to determine BC concentration is the flow rate. Figure 11 shows that the flow rate varied within \(\pm 2\%\) of a setting value for 10 days. The flow rate was maintained nearly constant independent on the battery status and on the switching moment of power sources. Consequently, it was demonstrated that the ATN drastically changed when the power source was altered.