采样(信号处理)
微流控
环境科学
仿形(计算机编程)
计算机科学
空气污染
遥感
微粒
实时计算
追踪
纳米技术
地理
电信
化学
操作系统
探测器
有机化学
材料科学
作者
Jia Yuan,Wenyu Wu,J. P. Zheng,Zhonghua Ni,Hao Sun
出处
期刊:Biomicrofluidics
[American Institute of Physics]
日期:2019-09-01
卷期号:13 (5)
被引量:5
摘要
Accurate and quantitative profiling of air particulate matter (PM) compositions is essential for assessing local pollution information. The method combining mobile aerial sampling using unmanned aerial vehicles (UAVs) and prompt analysis excels in this regard as it allows spatiotemporal mapping of air pollution, especially in the vertical direction. However, applications of the method are still scarce as it is limited by a lack of sampling reliability due to insufficient aerial sampling time and a lack of accurate, portable quantification techniques. In this work, by integrating mobile aerial sampling with in-flight tethered charging and smartphone-based colorimetric analysis in a cost-effective paper microfluidic device, we present a method for quantitative, reliable profiling of spatiotemporal variation in air PM compositions. The method extends aerial sampling time to 12-15 flight hours per deployment, thereby significantly improving sampling reliability while maintaining the maneuverability of the UAVs. Also, smartphone-based colorimetric analysis combined with paper-based microfluidics enables portable, economically efficient analysis and is well-suited for using in low-resource settings. We demonstrated the utility of the method by carrying out a spatiotemporal variation study of air PM trace metal components (Fe, Ni, and Mn) at 4 geographical locations in Fuzhou, China, for a period of 21 days, and the results were in good agreement with results obtained from using a commercial instrument. Beside air PM composition study, this method is universally applicable and holds great potential to be extended to multipollutant analysis, such as prompt detection of airborne viruses, bacteria, and others.
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