Research Center for Environmental Changes, Academia Sinica, Taipei, 11529, Taiwan.
Research Center for Environmental Changes, Academia Sinica, Taipei, 11529, Taiwan.
Chemosphere. 2020 Sep;254:126867. doi: 10.1016/j.chemosphere.2020.126867. Epub 2020 Apr 28.
The unique maneuverability, ease of deployment, simplicity in logistics, and relatively low costs of multicopters render them effective vehicles for low atmospheric research. While many efforts have contributed to the fundamental success of atmospheric applications of multicopters in the past, several challenges remain, including limited measurable variables, possible response-delay in real-time observations, insufficient measurement accuracy, endurance of harsh conditions and tolerance towards interferences. To address these challenges and further fortify the applicability in diversified research disciplines, this study developed an optimized multicopter UAV sounding technique (MUST). The MUST serves as an integrated platform by combining self-developed algorithms, optimized working environments for sensors/monitors, and retrofitted sampling devices to probe a comprehensive set of atmospheric variables. These variables of interest include meteorological parameters (temperature, relative humidity, pressure, wind direction and speed), the chemical composition (speciated VOCs, CO, CO, CH, CO isotopologues, O, PM2.5, and black carbon), and the radiation flux, as well as visible and thermal images. The aim of this study is to achieve the following objectives: 1. to easily probe a comprehensive set of near-surface atmospheric variables; 2. to improve data quality by correcting for sensors' delay in real-time observations and minimizing environmental interferences; and 3. to enhance the versatility and applicability of aerial measurements by incorporating necessary hardware and software. Field launching cases from the surface to a maximum height of 1000 m were conducted to validate the robustness of the integrated MUST platform with sufficient speed, accuracy and resolution for the target variables.
多旋翼飞行器独特的机动性、易于部署、后勤保障简单,以及相对较低的成本,使其成为低空大气研究的有效工具。尽管过去许多努力为多旋翼飞行器在大气应用方面的基本成功做出了贡献,但仍存在一些挑战,包括可测量变量有限、实时观测中可能存在响应延迟、测量精度不足、恶劣条件下的耐久性以及对干扰的容忍度。为了应对这些挑战,并进一步加强在多样化研究领域的适用性,本研究开发了一种优化的多旋翼无人机探测技术(MUST)。MUST 通过结合自主开发的算法、优化的传感器/监测器工作环境以及改装的采样设备,构成一个集成平台,用于探测一系列全面的大气变量。这些感兴趣的变量包括气象参数(温度、相对湿度、压力、风向和风速)、化学成分(VOCs 成分、CO、CO2、CH、CO 同位素、O、PM2.5 和黑碳)以及辐射通量,以及可见和热图像。本研究的目的是实现以下目标:1. 轻松探测一系列近地表大气变量;2. 通过纠正实时观测中传感器的延迟并最小化环境干扰来提高数据质量;3. 通过整合必要的硬件和软件,提高空中测量的多功能性和适用性。从地面到 1000 米的最大高度进行现场发射案例,以验证集成的 MUST 平台的稳健性,该平台具有足够的速度、精度和分辨率来满足目标变量的要求。