Aerosol monitoring for radioactivity is a mature and proven technology. However, by improving key specifications of aerosol monitoring equipment, more samples per day can be collected and analyzed with the same minimum detectable concentrations as current systems. This work models hypothetical releases of Ba and I over a range of magnitudes corresponding to the inventory produced from the fission of about 100 g to 1 kiloton TNT-equivalent of U. The releases occur over an entire year to incorporate the natural variability in atmospheric transport. Sampling equipment located at the 79 locations for radionuclide stations identified in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) for the International Monitoring System are used to determine the detections of the individual releases. Alternative collection schemes in next generation equipment that collect 2, 3, or 4 samples per day, rather than the current 1 sample per day, would result in detections in many more samples at more stations with detections for a given release level. The authors posit that next generation equipment will result in increased network resilience to outages and improved source-location capability for lower yield source releases. The application of dual-detector and coincidence measurements to these systems would significantly boost sensitivity for some isotopes and would further enhance the monitoring capability.
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http://dx.doi.org/10.1016/j.jenvrad.2022.107088 | DOI Listing |
Ann Agric Environ Med
December 2024
School of Biomedical Engineering and Imaging, Hubei University of Science and Technology, Hubei, China.
PLoS One
December 2024
Group of Atmospheric Optics (GOA-UVa), Universidad de Valladolid, Valladolid, Spain.
This work introduces CAECENET, a new system capable of automatically retrieving columnar and vertically-resolved aerosol properties running the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm using sun-sky photometer (aerosol optical depth, AOD; and sky radiance measurements) and ceilometer (range corrected signal; RCS) data as input. This method, so called GRASPpac, is implemented in CAECENET, which assimilates sun-sky photometers data from CÆLIS database and ceilometer data from ICENET database (Iberian Ceilometer Network). CAECENET allows for continuous and near-real-time monitoring of both vertical and columnar aerosol properties.
View Article and Find Full Text PDFEnviron Sci Technol
December 2024
State Ecology and Environment Scientific Observation and Research Station for the Yangtze River Delta at Dianshan Lake, Shanghai Environmental Monitoring Center, Shanghai 200030, China.
Biomass burning is an important source of brown carbon (BrC) aerosols, which influence climate by affecting the Earth's radiative balance. However, the transformation pathways of BrC chromophores, especially in the presence of photochemically active species, such as nitrate, are not well understood. In this study, the nitrate-mediated aqueous-phase photooxidation of three typical BrC chromophores from biomass burning was investigated, including 4-nitrocatechol, 3-nitrosalicylic acid, and 3,4-dinitrophenol.
View Article and Find Full Text PDFBiotechnol Lett
December 2024
Key Laboratory of Environmental Chemistry and Ecotoxicology of Organic Pollutants of Chongqing, Ecological and Environment Monitoring Center of Chongqing, 252 Qishan Road, Chongqing, 401132, China.
Rapid diagnostic tools for Porphyromonas gingivalis (Pg), the primary microorganism responsible for the development of periodontitis, particularly those designed for chair-side applications, could provide substantial health benefits to patients. To address this issue, we developed a CRISPR/Cas12a-based rapid Pg detection method. Dual-gRNA and hairpin reporter strategies were employed to enhance CRISPR/Cas12a reaction efficiency.
View Article and Find Full Text PDFSci Total Environ
December 2024
Department of Civil and Environmental Engineering, Universidad del Norte, Barranquilla, Colombia. Electronic address:
This study assessed the prevalence and spatial distribution of viable ultrafine and fine antibiotic-resistant bacteria aerosols (ARB) in the Metropolitan Area of Barranquilla, Colombia, pre- and post-lockdown (September 2019 to December 2020). Samples were systematically collected from urban, suburban, and rural sites using a six-stage viable cascade impactor. We employed logistic regression and Bayesian Neural Network Classifiers to analyze meteorological variables' influence on antibiotic resistance persistence.
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