The present study aimed to evaluate the concentration of odor substances and fine dust in areas where livestock farms are densely located, and to perform a correlation analysis of these concentrations to characterize the composition of fine dust. The mass concentration of fine dust in the areas tested was 33.6~46.68 μ/m3 for particulate matter with a diameter ≤ 10 μm (PM<sub>10</sub>) and 16.85~32.82 μ/m3 for particulate matter with a diameter ≤ 2.5 μm (PM<sub>2.5</sub>). These concentrations were higher than those in most of the neighboring areas. Ammonia concentration was measured in the range of 2.82~11.42 μ/m3. The concentrations of the volatile organic compounds (VOCs), methyl ethyl ketone and toluene, were 0.24~11.82 μ/m3, and 3.08~30.61 μ/m3, respectively. Composition analysis showed that fine dust was composed of 8.2~10.2% carbon, 0.3~1.7% sulfur, and 0.1~0.9% nitrogen. Anions were detected at a higher concentration than cations, and SO<sub>4</sub>2- was measured at the highest concentration. Of the four most prevalent metals detected (i.e., Al, B, Cu, and Zn), Al showed the highest concentration in both PM<sub>10</sub> and PM<sub>2.5</sub>, and accounted for the majority of the total metal component (84.7% and 82.2%, respectively). A correlation analysis of find dust with ammonia and VOC (methyl ethyl ketone and toluene) concentrations showed that ammonia generated from livestock facilities affected the formation of fine dust in nearby areas. VOCs emitted from nearby industrial facilities were also considered to contribute to the constituents of fine dust.
A great deal of study for loss reduction of photovoltaic system is conducted currently. It is hard to distinct the fault of photovoltaic system with the naked eye. For that reason, it is essential to repair and maintain the PV system by monitoring the system. The fault of individual modules can cause the huge loss of the entire system because of the mismatch. Therefore, the method of diagnosing the PV array is necessary by measuring the multi-channel arrays simultaneously. In this paper, it is presented the method of measuring I-V curve of multi-channel arrays simultaneously by using the charge and discharge characteristics of capacitor. Generated DC power at PV arrays is charged and discharged at the capacitors in a moment. By measuring the charged voltage and current, it is possible to diagnose of performance of PV arrays.
This paper proposes the PV module fault diagnosis sensor which is applied to Zigbee wireless network, and monitoring system using the developed sensor. It is designed with embedded sensor in junction box. The diagnosis elements for algorithm were voltage and temperature. For that reason, It is able to reduce the price and separate the fault of bypass diode from shading differently from other monitoring systems. This fault diagnosis algorithm verified through the Field-installed operations of PV module.
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