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Typhoon Noru (2022) was a historic storm that caused significant damage to the central region of Vietnam. Typhoon Noru has caused strong winds and torrential rainfall in Da Nang, Quang Nam, and Quang Ngai. Quang Nam Province saw many trees and power lines fall, and many areas were flooded. The Da Nang government has reported the typhoon toppled many trees, blew the rooftops of three houses, damaged the walls of several schools, and caused a power outage at some 3200 substations. It resulted in widespread flooding in coastal areas and downstream from the Vu Gia-Thu Bon River river basin. This study evaluates the impact of Typhoon Noru. The results show that: (1) The numerical simulation was applied to re-analyze the offshore meteorological field with the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model as an input for 2D wave propagation and hydraulic models; (2) The study couples the 1D and 2D models in MIKE FLOOD to simulate the flood and inundation caused by Typhoon Noru in the study area. The calibration and validation results of the 1D hydraulic model, the 2D wave propagation model, and the 2D hydrodynamic model were reasonably good, with a Nash coefficient ranging from 0.84 to 0.96 and a percent bias (BIAS) of −0.9% to 7.5%. The results of the simulation showed that the flood and inundation caused by Typhoon Noru resulted in significant damage in two districts: Thang Binh in Quang Nam province and Hoa Vang in Da Nang province. The practical significance of these results is that they provide valuable support for warning systems and troubleshooting efforts related to the impact of typhoons.

The subject and purpose of the work - the COVID-19 pandemic - has so far affected almost all countries of the world and sharply reminded of the need for further research on many aspects of viruses. An attempt to use classical approaches to describe the mechanisms of transmission and spread of this infection and the related methods of carrying out sanitary and preventive measures turned out to be ineffective. Nowadays, the creation of models of new viral infection has acquired particular relevance, allowing one to explain the features of its course observed in practice and to propose a mathematical description of the mechanism of its spread. Methods and methodology of work. The theory of probability and mathematical statistics, numerical modeling tools for solving systems of ordinary differential equations describing the spread of a viral infection are used. Results of work. A lego model for describing the structure of a compound viral infection is proposed, which makes it possible to explain the possibility of recurrent disease and the presence of several waves of it. Estimates of the probability of disease and mortality from the number of fragments of lego infection were obtained. The need to comply with special sanitary and hygienic measures to reduce the likelihood of severe disease and mortality is indicated. Using compartment models, a system of equations has been proposed to describe the dynamics of the spread of a new coronavirus infection COVID-19, which takes into account the presence of the latent period of infection, as well as the possibility of additional infection in a medical institution. Предмет і мета роботи – пандемія COVID-19 наразі торкнулася майже всіх країн світу та гостро нагадала про необхідність подальших досліджень багатьох аспектів вірусів. Спроба використання класичних підходів для опису механізмів передачі та поширення цієї інфекції та пов’язаних з ними методів проведення санітарно-профілактичних заходів виявилася неефективною. У наш час особливої актуальності набуло створення моделей нової вірусної інфекції, що дозволяє пояснити особливості її перебігу, що спостерігаються на практиці, і запропонувати математичний опис механізму її поширення. Методи та методика роботи: в роботі використовуються теорія ймовірності та математична статистика, засоби чисельного моделювання для розв’язування систем звичайних диференціальних рівнянь, що описують поширення вірусної інфекції. Результати роботи: Запропоновано лего модель для опису структури складної вірусної інфекції, яка дає змогу пояснити можливість рецидиву захворювання та наявність кількох його хвиль. Отримано оцінки ймовірності захворюваності та смертності від кількості фрагментів лего зараження. Вказується на необхідність дотримання спеціальних санітарно-гігієнічних заходів для зниження ймовірності тяжкого перебігу захворювання та смертності. За допомогою компартментних моделей запропоновано систему рівнянь для опису динаміки поширення нової коронавірусної інфекції COVID-19, яка враховує наявність латентного періоду інфекції, а також можливість додаткового зараження в лікувальному закладі.

In this study, the WRF (Weather Research and Forecasting) model was used to simulate and investigate diurnal and annual variations of wind speed and wind power density over Southern Vietnam at 2‐km horizontal resolution for two years (2016 and 2017). The model initial and boundary conditions are from the National Centers for Environmental Prediction (NCEP) Final Analyses (FNL). Observation data for two years at 20 m height at Bac Lieu station were used for model bias correction and investigating diurnal and annual variation of wind speeds. The results show that the WRF model overestimates wind speeds. After bias correction, the model reasonably well simulates wind speeds over the research area. Wind speed and wind power density show much higher values at levels of 50–200 m above ground levels than near ground (20 m) level and significantly higher near the coastal regions than inland. Wind speed has significant annual and diurnal cycles. Both annual and diurnal cycles of wind speeds were well simulated by the model. Wind speed is much stronger during daytime than at nighttime. Low-level wind speed reaches the maximum at about 14 LT to 15 LT when the vertical momentum mixing is highly active. Wind speeds over the eastern coastal region of Southern Vietnam are much stronger in winter than in summer due to two main reasons, including (1) stronger large-scale wind speed in winter than in summer and (2) funnel effect creating a local maximum wind speed over the nearshore ocean which then transports high-momentum air inland in winter.

We investigated concentrations of organic carbon (OC), elemental carbon (EC), and a wide range of particle-bound organic compounds in daily sampled PM2.5 at the remote Pha Din (PDI) – Global Atmosphere Watch (GAW) monitoring station in northwestern Vietnam during an intense 3-week sampling campaign from 23 March to 12 April 2015. The site is known to receive trans-regional air masses during large-scale biomass burning (BB) episodes. BB is a globally widespread phenomenon and BB emission characterization is of high scientific and societal relevance. Emissions composition is influenced by multiple factors (e.g., fuel and thereby vegetation type, fuel moisture, fire temperature, available oxygen). Due to regional variations in these parameters, studies in different world regions are needed. OC composition provides valuable information regarding the health- and climate-relevant properties of PM2.5. Yet, OC composition studies from PDI are missing in the scientific literature to date. Therefore, we quantified 51 organic compounds simultaneously by in situ derivatization thermal desorption gas chromatography and time-of-flight mass spectrometry (IDTD-GC-TOFMS). Anhydrosugars, methoxyphenols, n-alkanes, fatty acids, polycyclic aromatic hydrocarbons, oxygenated polycyclic aromatic hydrocarbons, nitrophenols, and OC were used in a hierarchical cluster analysis highlighting distinctive patterns for periods under low, medium, and high BB influence. The highest particle phase concentration of the typical primary organic aerosol (POA) and possible secondary organic aerosol (SOA) constituents, especially nitrophenols, were found on 5 and 6 April. We linked the trace gas mixing ratios of methane (CH4), carbon dioxide (CO2), carbon monoxide (CO), and ozone (O3) to the statistical classification of BB events based on OA composition and found increased CO and O3 levels during medium and high BB influence. Likewise, a backward trajectory analysis indicates different source regions for the identified periods based on the OA clusters, with cleaner air masses arriving from the northeast, i.e., mainland China and the Yellow Sea. The more polluted periods are characterized by trajectories from the southwest, with more continental recirculation of the medium cluster and more westerly advection for the high cluster. These findings highlight that BB activities in northern Southeast Asia significantly enhance the regional organic aerosol loading and also affect the carbonaceous PM2.5 constituents and the trace gases in northwestern Vietnam. The presented analysis adds valuable data on the carbonaceous and chemical composition of PM2.5, in particular of OC, in a region of scarce data availability, and thus offers a reference dataset from Southeast Asian large-scale BB for future studies. Such a reference dataset may be useful for the evaluation of atmospheric transport simulation models, or for comparison with other world regions and BB types, such as Australian bush fires, African savannah fires, or tropical peatland fires.

The financial support by the European Union's Horizon 2020 research and innovation program (ACTRIS-2, grant agreement no. 654109) is gratefully acknowledged. The investigation was supported by the Belarusian Republican Foundation for Fundamental, Research Agreement No. F18EA-011, by the Russian Foundation for Basic Research (grant No. 18-55-81001), and also by Vietnam Academy of Science and Technology (project code QTRU05.01/18-20). The Portuguese team acknowledges the support from the Portuguese Science Foundation, in the frame of the European Regional Development Fund -COMPETE 2020, under the projects UID/GEO/04683/2013 (POCI-01-0145-FEDER-007690), The paper presents the preliminary results of the lidar&radiometer measurement campaign (LRMC2017), estimation of statistical relations between aerosol mode concentrations retrieved from CALIOP and ground-based lidar stations and case study of fire smoke events in the Eurasian regions using combined ground-based and space lidar and radiometer observations., European Union's Horizon 2020 research and innovation program (ACTRIS-2) 654109, Belarusian Republican Foundation for Fundamental, Research F18EA-011, Russian Foundation for Basic Research (RFBR) 18-55-81001, Vietnam Academy of Science and Technology QTRU05.01/18-20, Portuguese Science Foundation, in the frame of the European Regional Development Fund -COMPETE 2020 UID/GEO/04683/2013 (POCI-01-0145-FEDER-007690)

Globally consistent measurements of airborne metal concentrations in fine particulate matter (PM2.5) are important for understanding potential health impacts, prioritizing air pollution mitigation strategies, and enabling global chemical transport model development. PM2.5 filter samples (N ~ 800 from 19 locations) collected from a globally distributed surface particulate matter sampling network (SPARTAN) between January 2013 and April 2019 were analyzed for particulate mass and trace metals content. Metal concentrations exhibited pronounced spatial variation, primarily driven by anthropogenic activities. PM2.5 levels of lead, arsenic, chromium, and zinc were significantly enriched at some locations by factors of 100–3000 compared to crustal concentrations. Levels of metals in PM2.5 and PM10 exceeded health guidelines at multiple sites. For example, Dhaka and Kanpur sites exceeded the US National Ambient Air 3-month Quality Standard for lead (150 ng m−3). Kanpur, Hanoi, Beijing and Dhaka sites had annual mean arsenic concentrations that approached or exceeded the World Health Organization’s risk level for arsenic (6.6 ng m−3). The high concentrations of several potentially harmful metals in densely populated cites worldwide motivates expanded measurements and analyses.

Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short-and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency. Fil: Snider, G.. Dalhousie University Halifax; Canadá Fil: Weagle, C. L.. Dalhousie University Halifax; Canadá Fil: Martin, R. V.. Dalhousie University Halifax; Canadá. University of Cambridge; Reino Unido Fil: van Donkelaar, A.. Dalhousie University Halifax; Canadá Fil: Conrad, K.. Dalhousie University Halifax; Canadá Fil: Cunningham, D.. Dalhousie University Halifax; Canadá Fil: Gordon, C.. Dalhousie University Halifax; Canadá Fil: Zwicker, M.. Dalhousie University Halifax; Canadá Fil: Akoshile, C.. University of Ilorin; Nigeria Fil: Artaxo, P.. Governo Do Estado de Sao Paulo; Brasil Fil: Anh, N. X.. Vietnam Academy of Science and Technology. Institute of Geophysics; Vietnam Fil: Brook, J.. University of Toronto; Canadá Fil: Dong, J.. Tsinghua University; China Fil: Garland, R. M.. North-West University; Sudáfrica Fil: Greenwald, R.. Rollins School of Public Health; Estados Unidos Fil: Griffith, D.. Council for Scientific and Industrial Research; Sudáfrica Fil: He, K.. Tsinghua University; China Fil: Holben, B. N.. NASA Goddard Space Flight Center; Estados Unidos Fil: Kahn, R.. NASA Goddard Space Flight Center; Estados Unidos Fil: Koren, I.. Weizmann Institute Of Science Israel; Israel Fil: Lagrosas, N.. Manila Observatory, Ateneo de Manila University campus; Filipinas Fil: Lestari, P.. Institut Teknologi Bandung; Indonesia Fil: Ma, Z.. Rollins School of Public Health; Estados Unidos Fil: Vanderlei Martins, J.. University of Maryland; Estados Unidos Fil: Quel, Eduardo Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Rudich, Y.. Weizmann Institute Of Science Israel; Israel Fil: Salam, A.. University Of Dhaka; Bangladesh Fil: Tripathi, S. N.. Indian Institute Of Technology, Kanpur; India Fil: Yu, C.. Rollins School of Public Health; Estados Unidos Fil: Zhang, Q.. Tsinghua University; China Fil: Zhang, Y.. Tsinghua University; China Fil: Brauer, M.. University of British Columbia; Canadá Fil: Cohen, A.. Health Effects Institute; Estados Unidos Fil: Gibson, M. D.. Dalhousie University Halifax; Canadá Fil: Liu, Y.. Rollins School of Public Health; Estados Unidos

This paper describes a research work whose objective is to help students to learn algebra with a computer. Firstly, we summarise the theoretical foundations and we describe a prototype devoted to the factoring problem. With this prototype, the student solves problems without making the calculations. The student can also observe the system solving a problem and providing explanations. Secondly, we summarise several experiments we carried out with students and we describe the results we got. Last, we present our new objective that consists of making a product that will be available for all students and teachers.