Small unmanned aerial vehicles (UAVs), also known as drones, have recently become promising tools in various fields. We investigated the feasibility of wind vector profile measurement using an ultrasonic anemometer installed on a 1-m-wide hexarotor UAV. Wind vectors measured by the UAV were compared to observations by a 55-m-high meteorological tower, over a wide range of wind speed conditions up to 11 m s−1, which is a higher wind speed range than those used in previous studies. The wind speeds and directions measured by the UAV and the tower were in good agreement, with a root-mean-square error of 0.6 m s−1 and 12° for wind speed and direction, respectively. The developed method was applied to field meteorological observations near a volcano, and the wind vector profiles, along with temperature and humidity, were measured by the UAV for up to an altitude of 1000 m, which is a higher altitude range than those used in previous studies. The wind vector profile measured by the UAV was compared with Doppler lidar measurements (collected several kilometers away from the UAV measurements) and was found to be qualitatively similar to that captured by the Doppler lidar, and it adequately represented the features of the atmospheric boundary layer. The feasibility of wind profile measurement up to 1000 m by a small rotor-based UAV was clarified over a wide range of wind speed conditions.
The first phase of the Urban air quality Model InterComparison Study in Japan (UMICS) has been conducted to find ways to improve model performance with regard to elemental carbon (EC). Common meteorology and emission datasets are used with eight different models. All the models underestimate the EC concentrations observed in Tokyo Metropolitan Area in the summer of 2007. Sensitivity analyses are conducted using these models to investigate the causes of this underestimation. The results of the analyses reveal that emissions and vertical diffusion are dominant factors that affect the simulated EC concentrations. A significant improvement in the accuracy of EC concentrations could be realized by applying appropriate scaling factors to EC emissions and boundary concentrations. Observation data from Lidar and radiosonde suggest the possible overestimation of planetary boundary layer height, which is a vital parameter representing vertical diffusion. The findings of this work can help to improve air quality models to that they can be used to develop more effective strategies for reducing PM 2.5 concentrations.
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