The use of the angular spectrum method (ASM) to simulate the reflection of airborne ultrasound beams from a thin membrane separating air from a mixture of air and another gas is examined. The main advantage of this method is its high computing speed and efficiency for practical design calculations, suitable for sensing applications. The implemented ASM code is validated against custom Rayleigh integral code in a pure propagation simulation. In addition, ultrasound beam reflection calculations using ASM with finite element numerical results and experimental measurements are compared, finding good agreement in both cases. Then, ASM is used to estimate the sensitivity of specular reflection signals to variations in the composition of the incidence medium as a function of the angle of incidence. Conditions for which a reflection signal using inexpensive commercial ultrasound emitter/receiver at 40 kHz, in a simple configuration, offer a high enough sensitivity suitable for monitoring air quality indoors are found.
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http://dx.doi.org/10.1121/10.0016580 | DOI Listing |
Nature
January 2025
Key Laboratory of Coastal Environment and Resources of Zhejiang Province, School of Engineering, Westlake University, Hangzhou, China.
The amount of methane released to the atmosphere from the Nord Stream subsea pipeline leaks remains uncertain, as reflected in a wide range of estimates. A lack of information regarding the temporal variation in atmospheric emissions has made it challenging to reconcile pipeline volumetric (bottom-up) estimates with measurement-based (top-down) estimates. Here we simulate pipeline rupture emission rates and integrate these with methane dissolution and sea-surface outgassing estimates to model the evolution of atmospheric emissions from the leaks.
View Article and Find Full Text PDFToxics
November 2024
Department of Ecology, University of Debrecen, Egyetem tér 1, 4032 Debrecen, Hungary.
Potentially toxic elements (PTEs) and microplastics (MPs) in the atmosphere raise widespread apprehension due to their association with the ecosystem and public health. The accumulation of airborne MPs and PTEs was analyzed in leaves, and the Pollution Index (PI) was calculated along an industrial, residential, and rural gradient in Bangladesh. Only polyethylene terephthalate (PET) was found in the highest concentration in industrial areas compared to other areas.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Geomorphology and Quaternary Geology, Faculty of Oceanography and Geography, University of Gdańsk, Bażyńskiego 4, 80-952, Gdańsk, Poland.
This study introduces a novel methodology for estimating and analysing coastal cliff degradation, using machine learning and remote sensing data. Degradation refers to both natural abrasive processes and damage to coastal reinforcement structures caused by natural events. We utilized orthophotos and LiDAR data in green and near-infrared wavelengths to identify zones impacted by storms and extreme weather events that initiated mass movement processes.
View Article and Find Full Text PDFEnviron Res
December 2024
Social Epidemiology and Health Policy, Department of Family Medicine and Population Health, University of Antwerp, Doornstraat 331, BE-2610, Wilrijk, Belgium; Institute for Environment and Sustainable Development (IMDO), Groenenborgerlaan 171, BE-2020, Antwerpen, Belgium; Laboratory of Applied Microbiology and Biotechnology (LAMB), Department of Bioscience Engineering, University of Antwerp, Groenenborgerlaan 171, BE-2020, Antwerpen, Belgium.
Introduction: Previous studies on prenatal green space exposure and early respiratory health show inconsistent results. This may reflect stage-specific in utero effects and pollen influence. We examine associations of surrounding greenness and pollen exposure during pregnancy (overall and by trimester) with preschool wheezing, and assess potential mediation by pollen.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
Department of Internal Medicine, Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, United States.
The COVID-19 pandemic and the recent increased interest in generative artificial intelligence (GenAI) highlight the need for interprofessional communities' collaboration to find solutions to complex problems. A personal narrative experience of one of the authors compels us to reflect on current approaches to learning and knowledge acquisition and use solutions to the challenges posed by GenAI through social learning contexts using connectivism. We recognize the need for constructivism and experiential learning for knowledge acquisition to establish foundational understanding.
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