A Compact-Sized Fully Self-Powered Wireless Flowmeter Based on Triboelectric Discharge.

Flow sensing exhibits significant potential for monitoring, controlling, and optimizing processes in industries, resource management, and environmental protection. However, achieving wireless real-time and omnidirectional sensing of gas/liquid flow on a simple, self-contained device without external power support has remained a formidable challenge. In this study, a compact-sized, fully self-powered wireless sensing flowmeter (CSWF) is introduced with a small size diameter of down to less than 50 mm, which can transmit real-time and omnidirectional wireless signals, as driven by a rotating triboelectric nanogenerator (R-TENG). The R-TENG triggers the breakdown discharge of a gas discharge tube (GDT), which enables flow rate wireless sensing through emitted electromagnetic waves. Importantly, the performance of the CSWF is not affected by the R-TENG's varied output, while the transmission distance is greater than 10 m. Real-time wireless remote monitoring of wind speed and water flow rate is successfully demonstrated. This research introduces an approach to achieve a wireless, self-powered environmental monitoring system with a diverse range of potential applications, including prolonged meteorological observations, marine environment monitoring, early warning systems for natural disasters, and remote ecosystem monitoring.

Spatiotemporal relationship between Himawari-8 hourly columnar aerosol optical depth (AOD) and ground-level PM2.5 mass concentration in mainland China.

Himawari-8 aerosol products have been widely used to estimate the near-surface hourly PM2.5 concentrations due to the high temporal resolution. However, most studies focus on the evaluation model. As the foundation of the estimation, the relationship between near-surface PM2.5 and columnar aerosol optical depth (AOD) has not been comprehensively investigated. In this study, we investigate the relationship between PM2.5 and advanced Himawari imager (AHI) AOD for 2016-2018 across mainland China on different spatial and temporal scales and the factors affecting the association. We calculated the Pearson correlation coefficients and the PM2.5/AOD ratio as the analysis indicators in 345 cities and 14 urban agglomerations based on the collocations of PM2.5 and AHI AOD. From 9:00 to 17:00 local time, the PM2.5-AOD correlation become significantly stronger while The PM2.5/AOD ratio markedly decrease in Beijing-Tianjin-Hebei, Yangtze River Delta, and Chengyu regions. The strongest correlation is between 12:00 and 14:00 LT (at noon) and between 13:00 and 17:00 LT (afternoon), respectively. The ratio in a day shows an obvious unimodal mode, and the peak occurred at around 10:00 or 11:00 LT, especially in autumn and winter. There is a pronounced variation of the PM2.5-AOD relationship in a week during the winter. Moreover, there are the strongest correlation and the largest ratio for most urban agglomerations during the winter. We also find that PM2.5 and AOD are not always correlated under different meteorological conditions and precursor concentrations. Furthermore, for the scattering-dominated fine-mode aerosol, there is a high correlation and a low ratio between PM2.5 and AOD. The correlation between PM2.5 and AHI AOD significantly increases with increasing the number of AOD retrievals on a day. The findings will provide meaningful information and important implications for satellite retrieval of hourly PM2.5 concentration and its exposure estimation in China, especially in some urban agglomerations.