Résumé
The tenth international symposium on "Large TPCs for low-energy rare event detection” was held in Paris from 15th to 17th of December 2021 at the Institute of Astroparticle physics of the University of Paris. The 2020 issue of this conference series was cancelled due to the Covid pandemic. The symposium was organized in a hybrid mode, which allowed about 40 people to attend in-person among a total of 131 registered participants. Very strict sanitary measures were taken to keep the meeting safe.As in previous events the program included neutrino physics, dark matter and axion searches, related detector R&D and theoretical aspects.To celebrate the tenth edition of the symposium the conference was held on three full days. Special speakers were invited to give a historical overview related to our field. David Nygren shared his memories of the invention and development of the Time Projection Chamber. François Vannucci revealed to us the invisible world of neutrinos. Ioannis Giomataris pointed out various innovative ideas that emerged during presentations and discussions in the last two decades. Jean Iliopoulos retraced the concept and development of the Standard Model and shared his personal vision on the future of particle physics.We wish to thank the many people who contributed to the success of the conference and especially the conveners of the sessions, who allowed for a smooth running of the meeting. We particularly acknowledge the APC management for providing the nice Buffon auditorium and infrastructure. We also thank DSM-Irfu, the University of Zaragoza, the European Research Council and ACAV Ile de France for their valuable support.The organizersList of Organizing Committee is available in this Pdf.
Résumé
The present work aimed to assess the ambient levels of air pollution with particulate matter for both mass concentrations and number of particles for various fractions in Ploiesti city during the lockdown period determined by the COVID-19 pandemic (March–June 2020). The PM10 continuously monitored data was retrieved from four air quality automatic stations that are connected to the Romanian National Network for Monitoring Air Quality and located in the city. Because no other information was available for other more dangerous fractions, we used monitoring campaigns employing the Lighthouse 3016 IAQ particle counter near the locations of monitoring stations assessing size-segregated mass fraction concentrations (PM0.5, PM1, PM2.5, PM5, PM10, and TPM) and particle number concentration (differential Δ) range between 0.3 and 10 microns during the specified timeline between 8.00 and 11.00 a.m., which were considered the morning rush hours interval. Interpolation maps estimating the spatial distribution of the mass concentrations of various PM fractions and particle number concentration were drawn using the IDW algorithm in ArcGIS 10.8.2. Regarding the particle count of 0.5 microns during the lockdown, the smallest number was recorded when the restriction of citizens' movement was declared (24 March 2020), which was 5.8-times lower (17,301.3 particles/cm3) compared to a common day outside the lockdown period (100,047.3 particles/cm3). Similar results were observed for other particle sizes. Regarding the spatial distribution of the mass concentrations, the smaller fractions were higher in the middle of the city and west (PM0.5, PM1, and PM2.5) while the PM10 was more concentrated in the west. These are strongly related to traffic patterns. The analysis is useful to establish the impact of PM and the assessment of urban exposure and better air quality planning. Long-term exposure to PM in conjunction with other dangerous air pollutants in urban aerosols of Ploiesti can lead to potential adverse effects on the population, especially for residents located in the most impacted areas.
Résumé
Biological agents used in biological warfare or bioterrorism are also present in bioaerosols. Prompt identification of a biological weapon and its characteristics is necessary. Herein, we optimized an environmentally adaptive detection algorithm that can better reflect changes in the complex South Korean environment than the current models. The algorithm distinguished between normal and biological particles using a laser-induced fluorescence-based biological particle detector capable of real-time measurements and size classification. We ensured that the algorithm operated with minimal false alarms in any environment by training based on experimental data acquired from an area where rainfall, snow, fog and mist, Asian dust, and water waves on the beach occur. To prevent time and money wastage due to false alarms, the detection performance for each level of sensitivity was examined to enable the selection of multiple sensitivities according to the background, and the appropriate level of sensitivity for the climate was determined. The basic sensitivity was set more conservatively than before, with a 3% alarm rate at 20 agent-containing particles per liter of air (ACPLA) and a 100% alarm rate at 63 ACPLA. The reliability was increased by optimizing five variables. False alarms did not occur in situations where no alarm was unnecessary.