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Removal of typical antibiotics from the symbiotic system of Microcystis aeruginosa and emergent plants

Pang Lidan, Zhou Haidong, Li Mengwei, Zhao Ziming, Xu Xinxuan, Ye Mixuan, Liu Xiaojiang

Environment Protection Engineering

2023

Vol. 49, nr 1

5--24

In a simulated urban river system, the conversion and distribution of six typical antibiotics were investigated under the following conditions: no plant, only Microcystis aeruginosa (algae) and algae combined with Juncus effusus, Cyperus alternifolius, and Acorus calamus. Through the calculation of the mass balance, the quantitative distribution of antibiotics in the water phase, sediment, Microcystis aeruginosa, and plant tissues, and the total elimination efficiency of the antibiotics were determined. The results showed that higher concentrations of sulfathiazole (STZ) and sulfamethoxazole (SMZ) were detected in the water phase of the non-plant group, which were 52.81% and 56.88%, respectively, and ciprofloxacin (CIP) and tetracycline (TCY) were detected higher in the sediment, up to 1562 ng/g and 1829 ng/g, respectively. The antibiotic removal rates have been greatly improved, and those in the system containing Microcystis aeruginosa were higher than that in the system without aquatic plants or algae. The calculation of the mass balance showed that the removal effect of algae combined with Juncus effusus was the best, and the removal rates (azithromycin (AZM) and clarithromycin (CLM)) were the highest, reaching 68.88% and 61.96%. It seems that algae and plants play an important role in the removal of antibiotics.

Automatic pavement macrotexture depth calculation using a statistical approach based on the tire/road noise signal by directional microphones

Liu Hao, Zhang Yiying, Xu Zhengwei, Liu Xiaojiang

Bulletin of the Polish Academy of Sciences. Technical Sciences

2022

Vol. 70, nr 3

art. no. e140519

This paper develops an automatic method to calculate the macrotexture depth of pavement roads, using the tire/road noise data collected by the two directional microphones mounted underneath a moving test vehicle. The directional microphones collect valid tire/road noise signal at the travel speed of 10–110 km/h, and the sampling frequency is 50 kHz. The tire/road noise signal carries significant amount of road surface information, such as macrotexture depth. Using bandpass filter, principal component analysis, speed effect elimination, Gaussian mixture model, and reversible jump Markov Chain Monte Carlo, the macrotexture depth of pavement roads can be calculated from the tire/road noise data, automatically and efficiently. Compared to the macrotexture depth results by the sand-patch method and laser profiler, the acoustic method has been successfully demonstrated in engineering applications for the accurate results of macrotexture depth with excellent repeatability, at the test vehicle’s travel speed of 10-110 km/h.