Editor’s Choice Articles

Machine learning has experienced great success in many applications. Precipitation is a hard meteorological variable to predict, but it has a strong impact on society. Here, a machine-learning technique—a formulation of gradient-boosted trees—is applied to climate seasonal precipitation prediction over South America. The Optuna framework, based on Bayesian optimization, was employed to determine the optimal hyperparameters for the gradient-boosting scheme. A comparison between seasonal precipitation forecasting among the numerical atmospheric models used by the National Institute for Space Research (INPE, Brazil) as an operational procedure for weather/climate forecasting, gradient boosting, and deep-learning techniques is made regarding observation, with some showing better performance for the boosting scheme. Full article

While climate change has global causations and impacts, there is growing consensus on addressing the 2 °C challenge through local actions. However, at the local level, there is disintegrated knowledge on the following: (a) short-, mid- and long-term climate vulnerability, (b) economy and GHG structures and their future pathways, and (c) useful mitigation and adaptation undertaken elsewhere. We evaluate these gaps through a comprehensive review of scientific literature and policy approaches of urban-climate studies in the Asia-Pacific Region. Based on the research findings, we develop a collaborative research framework of an integrated climate action planning (ICLAP) model for evidence-based decision-making tool. It adopts an innovative methodology integrating knowledge and data from diverse analytics, as follows: (a) spatial: downscaling global/regional climate scenarios to forecast local climate variability (50 km × 50 km) for 2030 (SDG target) and 2050; (b) statistical: a meta-analysis of 49 five-million-plus cities to forecast economic, energy and GHG scenarios; (c) bibliometric: a systematic review of global urban climate interventions from Google Scholar that collectively aid cities on policy inputs for mid-term climate variability, GHG profiles and available solutions at their disposal. We conclude with a discussion on scientific and policy relevance of such a tool in fostering overall urban, regional and global sustainability. Full article

Seasonal anomalies of surface air temperature were analyzed for the North Eurasian regions in mid-latitudes using long-term data from the end of the 19th century with an assessment of El Niño Southern Oscillation (ENSO) effects. In particular, temperature anomalies in the spring–summer months for the European (ER) and Asian (AR) Russian regions for different phase transitions of the ENSO phenomena were estimated using the Niño3, Niño3.4 and Niño4 indices. The largest frequency of the extremely high-temperature and drought conditions in spring–summer months in ER was detected for years starting in the El Niño phase with the transition to the La Niña phase at the end of the year. Such conditions were realized in ER in summer 2010 (“Russian heatwave”). The corresponding largest frequency of high temperature in AR was obtained for conditions with the continuation of the El Niño phase during the whole year. Such conditions in AR were noted, in particular, in the summer of 2015, with an extremely high temperature and extremely low precipitation in the Lake Baikal basin. Full article

Black carbon (BC), a component of carbonaceous material, has an important role in the environment, and it is considered a short-lived climate forcer that plays a vital role in the global climate system. BC concentrations were analyzed during 2017 in two sites in Mexico, Juriquilla and Altzomoni, which have different emission sources and atmospheric dynamics. The annual average BC concentrations in 2017 were 0.84 ± 0.70 and 0.58 ± 0.37 µg m⁻³ for Juriquilla and Altzomoni, respectively. The principal contributors for the highest BC concentration in Juriquilla were anthropogenic sources, while pollutants transport from nearby cities was more important for Altzomoni. Comparison between this analysis and previous reports from 2015 for both sampling sites demonstrated an increase in BC concentration. Results of this study could contribute to a better understanding of BC effects under different emission conditions and provide a scientific reference for developing BC reduction strategies over Mexico. Full article

One of the greatest environmental health problems to arise in recent years is air pollution. Inorganic and organic particles are important components of air aerosol. The potential of air microbiota as an indicator of air quality is gaining increasing research interest. The aim of the present study was to determine the relationship between the level of fungal contamination and the levels of bacteria and smog particles in outdoor air in recreational areas during the heating season. A quantitative and qualitative mycological evaluation and quantitative bacteriological evaluation of air quality in 10 selected parks were performed. The numbers of microorganisms in the air were correlated with smog levels. The mean prevalence of fungi was 18.96 ± 15.43–23.30 ± 26.70 CFU/m³ of air and the mean bacterial count was 74.06 ± 130.89–268.04 ± 126.10 CFU/m³. Among the isolated fungi, clinically significant species were identified: four species belonged to Risk Group 2, and 17 to Risk Group 1. The predominant genera were Aspergillus, Penicillium and Alternaria. The total number of bacteria demonstrated a positive correlation with the size of the park, air temperature and ozone level during sampling, and a negative correlation with humidity, pressure and smog parameters (CO, NO, NO₂ and NO_x). The qualitative and quantitative composition of bioaerosols can be used as a bioindicator for environmental monitoring. There is a need for more efficient monitoring of airborne pollutants and microorganisms to learn about the structure of the air biota, the mechanisms regulating their occurrence, and to identify potential threats to human health. Full article

People spend up to 90% of their time indoors where they continuously interact with the indoor environment. Indoor Environmental Quality (IEQ), and in particular thermal comfort, Indoor Air Quality (IAQ), and acoustic and visual comfort, have proven to be significant factors that influence the occupants’ health, comfort, productivity and general well-being. The ongoing COVID-19 pandemic has also highlighted the need for real-life experimental data acquired through field measurement studies to help us understand and potentially control the impact of IEQ on the occupants’ health. In this context, there was a significant increase over the past two decades of field measurement studies conducted all over the world that analyse the IEQ in various indoor environments. In this study, an overview of the most important factors that influence the IAQ, thermal comfort, and the risk of virus transmission is first presented, followed by a comprehensive review of selected field measurement studies from the last 20 years. The main objective is to provide a broad overview of the current status of field measurement studies, to identify key characteristics, common outcomes, correlations, insights, as well as gaps, and to serve as the starting point for conducting future field measurement studies. Full article

In this work, the relative yields of aqueous secondary organic aerosols (aqSOAs) at the air–liquid (a–l) interface are investigated between photochemical and dark aging using in situ time-of-flight secondary ion mass spectrometry (ToF-SIMS). Our results show that dark aging is an important source of aqSOAs despite a lack of photochemical drivers. Photochemical reactions of glyoxal and hydroxyl radicals (•OH) produce oligomers and cluster ions at the aqueous surface. Interestingly, different oligomers and cluster ions form intensely in the dark at the a–l interface, contrary to the notion that oligomer formation mainly depends on light irradiation. Furthermore, cluster ions form readily during dark aging and have a higher water molecule adsorption ability. This finding is supported by the observation of more frequent organic water cluster ion formation. The relative yields of water clusters in the form of protonated and hydroxide ions are presented using van Krevelen diagrams to explore the underlying formation mechanisms of aqSOAs. Large protonated and hydroxide water clusters (e.g., (H₂O)nH⁺, 17 < n ≤ 44) have reasonable yields during UV aging. In contrast, small protonated and hydroxide water clusters (e.g., (H₂O)nH⁺, 1 ≤ n ≤ 17) form after several hours of dark aging. Moreover, cluster ions have higher yields in dark aging, indicating the overlooked influence of dark aging interfacial products on aerosol optical properties. Molecular dynamic simulation shows that cluster ions form stably in UV and dark aging. AqSOAs molecules produced from dark and photochemical aging can enhance UV absorption of the aqueous surface, promote cloud condensation nuclei (CCN) activities, and affect radiative forcing. Full article

Several works have shown that lightning jumps are precursors of severe weather in deep-convective thunderstorms. Since 2017, the Meteorological Service of Catalonia has operationally run an algorithm that identifies lightning jumps (LJs) in real time. It has resulted in being an effective tool for nowcasting severe weather with a lead time between 15 min and 120 min in advance. This time can be of high value for managing emergencies caused by severe phenomena or heavy rains. The present research focused on the events’ analysis in which more than one lightning jump occurred, searching for those elements that differentiate single warning cases. Thunderstorms producing LJs were divided into two main categories, depending on the number of jumps triggered during the life cycle. Besides, both classes were split into two main sub-types, based on the level of the LJ that occurred. Multiple LJ thunderstorms produce more Level 2—related to severe weather—jumps than Level 1—small hail or intense precipitation—while in the case of a single LJ, the opposite behaviour occurs. In general, multiple LJ thunderstorms with at least one Level 2 jump are the more intense and have a higher vertical development. Finally, lineal and well-organised thunderstorms are the more common modes in those intenser cases. Full article

The planetary boundary layer height (PBLH) is one of the key factors in influencing the dispersion of the air pollutants in the troposphere and, hence, the air pollutant concentration on ground level. For this reason, accurate air pollutant concentration depends on the performance of PBLH prediction. Recently, ceilometers, a lidar instrument to measure cloud base height, have been used by atmospheric scientists and air pollution control authorities to determine the mixing level height (MLH) in improving forecasting and understanding the evolution of aerosol layers above ground at a site. In this study, ceilometer data at an urban (Lidcombe) and a rural (Merriwa) location in New South Wales, Australia, were used to investigate the relationship of air pollutant surface concentrations and surface meteorological variables with MLH, to validate the PBLH prediction from two air quality models (CCAM-CTM and WRF-CMAQ), as well as to understand the aerosol transport from sources to the receptor point at Merriwa for the three case studies where high PM₁₀ concentration was detected in each of the three days. The results showed that surface ozone and temperature had a positive correlation with MLH, while relative humidity had negative correlation. For other pollutants (PM₁₀, PM_2.5, NO₂), no clear results were obtained, and the correlation depended on the site and regional emission characteristics. The results also showed that the PBLH prediction by the two air quality models corresponded reasonably well with the observed ceilometer data and the cause and source of high PM₁₀ concentration at Merriwa can be found by using ceilometer MLH data to corroborate back trajectory analysis of the transport of aerosols to the receptor point at Merriwa. Of the three case studies, one had aerosol sources from the north and north west of Merriwa in remote NSW, where windblown dust is the main source, and the other two had sources from the south and south east of Merriwa, where anthropogenic sources dominate. Full article

Among the China Seas, the Yellow Sea has the highest occurrence frequency of sea fog that can be categorized into widespread sea fog and coastal sea fog. In this paper, we study a typical coastal sea fog along the Shandong Peninsula that is accompanied by sea-land breezes. Based on a series of numerical experiments conducted by the Weather Research and Forecasting model with high spatial resolution, the impacts of the sea–land breezes on the formation and development of sea fog are investigated in detail. The land breeze can act as an accelerator that enhances humidification and cooling near the coast which promotes sea fog formation during the nighttime, resulting from nearshore vapor convergence and offshore cool-air transportation jointly by the descending branch and low-level breeze of the land breeze circulation. During the daytime, the sea breeze acts as a reducer that inhibits sea fog development, including the contraction of fog area caused by onshore advection of the sea breeze on cloud liquid water, and the restraint of fog vertical growth due to warming and drying by the descending branch of the sea breeze circulation. Full article

This paper explores extreme storms with marine flooding events in historical times. It focuses on the challenges associated with detecting these events with a degree of certainty in a changing environment. The paleoenvironmental changes which turned the Gulf of Pictons into the Belle Henriette lagoon have required the reconstruction of events to be based on cored sediments. This study aims to establish how sedimentological washovers can be detected in a depositional environment that has changed profoundly over recent centuries. The Belle Henriette lagoon site is unique. Despite the profound environmental changes that have taken place, the impact of storms was well preserved in the five cores extracted. Eighteen historical extreme storms with marine floods were detected in the sediment. By cross-referencing with historical archives, thirteen storms were estimated in 1990, 1940, 1896, 1876, 1859, 1838, 1820, 1811, 1751, 1711, 1645, 1469, and 1351. Five older storms dating back to 1090, 1036, 941, 809, and 581 will also be discussed. By conducting a thorough historical review, we can conclude that these extreme storms caused significant damage and had a profound impact on the socioeconomic coastal communities. Full article

A minor Antarctic sudden stratospheric warming (SSW) with the strongest circulation changes since the first major SSW over the Antarctic was recorded in 2002 occurred in early September 2019. The diagnosis demonstrates two possible causes of this SSW. First, the tropical central Pacific warming is identified, which enhanced the amplitude of tropospheric planetary wavenumber 1 (W1) in the extratropics on the seasonal time scale. Second, the impact of intraseasonal convection anomalies similar to previous studies is also suggested here. The enhanced deep convection over the South Pacific Convergence Zone (SPCZ) in late August–early September excited a Rossby wave train to deepen an anomalous ridge, which significantly and persistently strengthened the tropospheric W1. The central Pacific warming and intraseasonal convection anomalies jointly provided the conditions for the occurrence of the Antarctic SSW in 2019 on different time scales. On the other hand, the difference of the stratospheric state between the Antarctic SSWs in 2019 and 2002 may be an important reason why the 2019 event did not meet the major SSW criteria. The stratospheric state before the 2019 SSW event is somewhat not as ideal as that of the 2002 event. Vertical planetary waves are, hence, more difficult to enter into the polar stratosphere, making it more difficult to trigger major events. Full article

The atmosphere over Lake Baikal covers a vast area (31,500 square meters) and has more significant differences in the composition and variability of gaseous and aerosol components in atmospheric air than in coastal continental areas and is still a poorly studied object. In recent years, the anthropogenic impact on the ecosystem of Lake Baikal has been increasing due to the development of industry in the region, the expansion of tourist infrastructure and recreational areas of the coastal zone of the lake. In addition, one of the significant sources of atmospheric pollution in the Baikal region is the emissions of smoke aerosol and trace gases from forest fires, the number of which is increasing in the region. This article presents the results of experimental studies of the dispersed composition of aerosols and gas impurities, such as ozone, sulfur dioxide, and nitrogen oxides during route ship measurements in the water area of Lake Baikal in the summer of 2020. Full article

Thirty-year periods are treated in climatology as spans with relatively representative and stable climatic patterns, which can be used for calculating climate normals. Annual and seasonal series of circulation types were used to compare two 30-year sub-periods, 1961–1990 and 1991–2020, the second one being strongly influenced by recent global warming. This analysis was conducted according to the objective classification of circulation types and the climatic characteristics of sunshine duration, temperature, humidity, precipitation, and wind speed as calculated for the territory of the Czech Republic during the 1961–2020 period. For both sub-periods, their statistical characteristics were calculated, and the statistical significance of differences between them was evaluated. There was a statistically significant increase in the annual frequencies of anticyclonic circulation types and a significant decrease in cyclonic circulation types during 1991–2020 compared with 1961–1990. Generally, in both 30-year periods, significant differences in means, variability, characteristics of distribution, density functions, and linear trends appear for all climatic variables analysed except precipitation. This indicates that the recent 30-year “normal” period of 1991–2020, known to be influenced more by recent climate change, is by its climatic characteristics unrepresentative of the stable climatic patterns of previous 30-year periods. Full article

Borneo Squall Line (BSL) is a disaster risk associated with intense rain and wind gust that affect the activities and residence near the northern coast of Borneo. Using 3-hourly rainfall from Tropical Rainfall Measuring Mission (TRMM) 3B42V7 during southwest monsoon season (May–September) from 1998–2018, a total of 629 squall days were identified. Their monthly and annual average was 6 and 30 days, respectively, with July representing the month with the highest number of squall line days. BSL is frequently initiated during midnight/predawn and terminated in the morning. Composite analyses of BSL days using the daily winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim revealed that lower tropospheric wind convergence is a crucial controlling factor for BSL formation. The position of the monsoon trough closer to the equatorial South China Sea (SCS), and strong westerly and south-westerly winds played an important role in creating this wind convergence region. Analyses of tropical cyclone (TC) data from the Regional Specialized Meteorological Centre (RSMC), Tokyo showed that nearly 72% of BSL occurred with the presence of TC. Spectral analysis exhibited prominent frequencies mainly in the 3–4- and 6-year time scale, which likely reflected the influence of interannual modulation of El-Niño Southern Oscillation (ENSO). Correlation coefficient between squall days and Sea Surface Temperature (SST) anomalies indicated that BSL increased after La-Niña events. This study is expected to have implications for real-time squall line forecasting in Malaysia and contributes toward a better understanding of BSL. Full article

Radon is a natural and radioactive gas that can accumulate in indoor environments. Indoor radon concentration (IRC) is influenced, among other factors, by meteorology, which is the subject of this paper. Weather parameters impact indoor radon levels and have already been investigated, but rarely in Switzerland. Moreover, there is a strong need for a better understanding of the radon behaviour inside buildings in Switzerland for public health concerns as Switzerland is a radon prone area. Based on long-term, continuous, and hourly radon measurements, radon distributions classified according to different weather event definitions were investigated and then compared at three different study sites in Western Switzerland. Outdoor temperature influences the most indoor radon, and it is globally anti-correlated. Wind influences indoor radon, but it strongly depends on intensity, direction, and building characteristics. Precipitation influences periodically indoor radon levels relatively to their intensity. Atmospheric pressure and relative humidity do not seem to be huge determinants on IRC. Our results are in line with previous findings and provide a vivid example in Western Switzerland. This paper underlines the different influence complexities of radon, and the need to communicate about it within the broader public and with construction professionals, to raise awareness. Full article

In this paper, we investigated the impact of solar flares on the horizontal (H), eastward (Y) and vertical (Z) components of the geomagnetic field during solar cycles 23 and 24 (SC23/24) using data of magnetometer measurements on the sunlit side of the Earth. We examined the relation between sunspot number and solar flare occurrence of various classes during both cycles. During SC23/24, we obtained correlation coefficient of 0.93/0.97, 0.96/0.96 and 0.60/0.56 for C-class, M-class and X-class flare, respectively. The three components of the geomagnetic field reached a peak a few minutes after the solar flare occurrence. Generally, the magnetic crochet of the H component was negative between the mid-latitudes and Low-latitudes in both hemispheres and positive at low latitudes. By contrast, the analysis of the latitudinal variation of the Y and Z components showed that unlike the H component, their patterns of variations were not coherent in latitude. The peak amplitude of solar flare effect (sfe) on the various geomagnetic components depended on many factors including the local time at the observing station, the solar zenith angle, the position of the station with respect to the magnetic equator, the position of solar flare on the sun and the intensity of the flare. Thus, these peaks were stronger for the stations around the magnetic equator and very low when the geomagnetic field components were close to their nighttime values. Both cycles presented similar monthly variations with the highest sfe value (ΔH_sfe = 48.82 nT for cycle 23 and ΔH_sfe = 24.68 nT for cycle 24) registered in September and lowest in June for cycle 23 (ΔH_sfe = 8.69 nT) and July for cycle 24 (ΔH_sfe = 10.69 nT). Furthermore, the sfe was generally higher in cycle 23 than in cycle 24. Full article

Ground-level ozone is a pollutant that is harmful to urban populations, particularly in developing countries where it is present in significant quantities. It greatly increases the risk of heart and lung diseases and harms agricultural crops. This study hypothesized that, as a secondary pollutant, ground-level ozone is amenable to 24 h forecasting based on measurements of weather conditions and primary pollutants such as nitrogen oxides and volatile organic compounds. We developed software to analyze hourly records of 12 air pollutants and 5 weather variables over the course of one year in Delhi, India. To determine the best predictive model, eight machine learning algorithms were tuned, trained, tested, and compared using cross-validation with hourly data for a full year. The algorithms, ranked by R² values, were XGBoost (0.61), Random Forest (0.61), K-Nearest Neighbor Regression (0.55), Support Vector Regression (0.48), Decision Trees (0.43), AdaBoost (0.39), and linear regression (0.39). When trained by separate seasons across five years, the predictive capabilities of all models increased, with a maximum R² of 0.75 during winter. Bidirectional Long Short-Term Memory was the least accurate model for annual training, but had some of the best predictions for seasonal training. Out of five air quality index categories, the XGBoost model was able to predict the correct category 24 h in advance 90% of the time when trained with full-year data. Separated by season, winter is considerably more predictable (97.3%), followed by post-monsoon (92.8%), monsoon (90.3%), and summer (88.9%). These results show the importance of training machine learning methods with season-specific data sets and comparing a large number of methods for specific applications. Full article

The Earth’s ionosphere presents long-term trends that have been of interest since a pioneering study in 1989 suggesting that greenhouse gases increasing due to anthropogenic activity will produce not only a troposphere global warming, but a cooling in the upper atmosphere as well. Since then, long-term changes in the upper atmosphere, and particularly in the ionosphere, have become a significant topic in global change studies with many results already published. There are also other ionospheric long-term change forcings of natural origin, such as the Earth’s magnetic field secular variation with very special characteristics at equatorial and low latitudes. The ionosphere, as a part of the space weather environment, plays a crucial role to the point that it could certainly be said that space weather cannot be understood without reference to it. In this work, theoretical and experimental results on equatorial and low-latitude ionospheric trends linked to the geomagnetic field secular variation are reviewed and analyzed. Controversies and gaps in existing knowledge are identified together with important areas for future study. These trends, although weak when compared to other ionospheric variations, are steady and may become significant in the future and important even now for long-term space weather forecasts. Full article

Mechanical ventilation consumes a huge amount of global energy. Natural ventilation is a crucial solution for reducing energy consumption and enhancing the capacity of atmospheric self-purification. This paper evaluates the impacts of indoor-outdoor temperature differences on building ventilation and indoor-outdoor air pollutant dispersion in urban areas. The Computational Fluid Dynamics (CFD) method is employed to simulate the flow fields in the street canyon and indoor environment. Ventilation conditions of single-side ventilation mode and cross-ventilation mode are investigated. Air change rate, normalized concentration of traffic-related air pollutant (CO), intake fraction and exposure concentration are calculated to for ventilation efficiency investigation and exposure assessment. The results show that cross ventilation increases the air change rate for residential buildings under isothermal conditions. With the indoor-outdoor temperature difference, heating could increase the air change rate of the single-side ventilation mode but restrain the capability of the cross-ventilation mode in part of the floors. Heavier polluted areas appear in the upstream areas of single-side ventilation modes, and the pollutant can diffuse to middle-upper floors in cross-ventilation modes. Cross ventilation mitigates the environmental health stress for the indoor environment when indoor-outdoor temperature difference exits and the personal intake fraction is decreased by about 66% compared to the single-side ventilation. Moreover, the existence of indoor-outdoor temperature differences can clearly decrease the risk of indoor personal exposure under both two natural ventilation modes. The study numerically investigates the building ventilation and pollutant dispersion in the urban community with natural ventilation. The method and the results are helpful references for optimizing the building ventilation plan and improving indoor air quality. Full article

We present the mapping at fine spatial scale of aerosol optical properties using a mobile laboratory equipped with LIDAR (Light Detection And Ranging), sun photometer and in situ instruments for performing on-road measurements. The mobile campaign was conducted from 9 May to 19 May 2017 and had the main objective of mapping the distribution of pollutants in the Beijing and North China Plain (NCP) region. The highest AOD (Aerosol Optical Depth) at 440 nm of 1.34 and 1.9 were recorded during two heavy pollution episodes on 18 May and 19 May 2017, respectively. The lowest Planetary Boundary Layer (PBL) heights (0.5–1.5 km) were recorded during the heavy pollution events, correlating with the highest AOD and southern winds. The transport of desert dust from the Gobi Desert was captured during the mobile measurements, impacting Beijing during 9–13 May 2017. Exploring the NCP outside Beijing provided datasets for regions with scarce ground measurements and allowed the mapping of high aerosol concentrations when passing polluted cities in the NCP (Baoding, Tianjin and Tangshan) and along the Binhai New Area. For the first time, we provide mass concentration profiles from the synergy of LIDAR, sun photometer and in situ measurements. The case study along the Binhai New Area revealed mean extinction coefficients of 0.14 ± 0.10 km⁻¹ at 532 nm and a mass concentration of 80 ± 62 μg/m³ in the PBL (<2 km). The highest extinction (0.56 km⁻¹) and mass concentrations (404 μg/m³) were found in the industrial Binhai New Area. The PM₁₀ and PM_2.5 fractions of the total mass concentration profiles were separated using the columnar size distribution, derived from the sun photometer measurements. This study offers unique mobile datasets of the aerosol optical properties in the NCP for future applications, such as satellite validation and air quality studies. Full article

We investigated the role of the passive volcanic plume of Mount Etna (Italy) in the formation of new particles in the size range of 2.5–10 nm through the gas-to-particle nucleation of sulfuric acid (H₂SO₄) precursors, formed from the oxidation of SO₂, and their evolution to particles with diameters larger than 100 nm. Two simulations were performed using the Weather Research and Forecasting Model coupled with chemistry (WRF-Chem) under the same configuration, except for the nucleation parameterization implemented in the model: the activation nucleation parameterization (J_S1 = 2.0 × 10⁻⁶ × (H₂SO₄)) in the first simulation (S1) and a new parameterization for nucleation (NPN) (J_S2 = 1.844 × 10⁻⁸ × (H₂SO₄)^1.12) in the second simulation (S2). The comparison of the numerical results with the observations shows that, on average, NPN improves the performance of the model in the prediction of the H₂SO₄ concentrations, newly-formed particles (~2.5–10 nm), and their growth into larger particles (10–100 nm) by decreasing the rates of H₂SO₄ consumption and nucleation relative to S1. In addition, particles formed in the plume do not grow into cloud condensation nuclei (CCN) sizes (100–215 nm) within a few hours of the vent (tens of km). However, tracking the size evolution of simulated particles along the passive plume indicates the downwind formation of particles larger than 100 nm more than 100 km far from the vent with relatively high concentrations relative to the background (more than 1500 cm⁻³) in S2. These particles, originating in the volcanic source, could affect the chemical and microphysical properties of clouds and exert regional climatic effects over time. Full article

The COVID-19 outbreak has significantly affected global industrial and transportation markets. Airlines, rails, and cars’ industries and their supporting energy sectors have been substantially disrupted by the pandemic. This has resulted in undermined energy demand around the world during 2019 and 2020. The organization of the Petroleum Exporting Countries (OPEC) led by Saudi Arabia failed to persuade Russia to cutback oil supplies to deal with the loss of demand from the COVID-19 pandemic. On 8 March 2020, Saudi Arabia announced a raise in its oil production and offered a large discount on its crude oil sales. By April 2020, Saudi Arabia increased its oil production to about 12 million-oil barrels/day. This rise in oil production has not only resulted in the biggest fall in oil prices since the 1991 Gulf War but also increased methane emissions over the Gulf Cooperation Council (GCC) regions. Here, we report 2019 and 2020 data set of average seasonal methane-mixing ratio retrieved from TROPOspheric Monitoring Instrument (TROPOMI) on board of S5P spacecraft over 19 refineries and oil fields in Saudi Arabia, Kuwait, Oman, United Arab Emirates, Qatar, and Bahrain. Low methane emissions were recorded over western and central Saudi Arabia compared to the eastern side of the country. In general, high methane emissions were observed in 2020 compared to 2019 around oil refineries and fields in western, central, and eastern regions of Saudi Arabia as well as over other GCC countries. This could be attributed to the oil high production associated with the oil prices fluctuation during 2020. Full article

The Space and Terrestrial Weather (Weather Complex) impact on ischemia cases in Saint Petersburg is investigated. The results show the main feature of the Weather Complex when it was related to the days of the different ischemia situations in the different ischemia people gender groups. The data treatment was done with some elements of the Folder Epochs Method, Cluster Analysis and the Mann–Whitney hypothesis test criterion. Full article

Multi-source meteorological data can reflect the development process of single meteorological elements from different angles. Making full use of multi-source meteorological data is an effective method to improve the performance of weather nowcasting. For precipitation nowcasting, this paper proposes a novel multi-input multi-output recurrent neural network model based on multimodal fusion and spatiotemporal prediction, named MFSP-Net. It uses precipitation grid data, radar echo data, and reanalysis data as input data and simultaneously realizes 0–4 h precipitation amount nowcasting and precipitation intensity nowcasting. MFSP-Net can perform the spatiotemporal-scale fusion of the three sources of input data while retaining the spatiotemporal information flow of them. The multi-task learning strategy is used to train the network. We conduct experiments on the dataset of Southeast China, and the results show that MFSP-Net comprehensively improves the performance of the nowcasting of precipitation amounts. For precipitation intensity nowcasting, MFSP-Net has obvious advantages in heavy precipitation nowcasting and the middle and late stages of nowcasting. Full article

The Quasi-Biennal Oscillation (QBO) and the El Niño-Southern Oscillation (ENSO) largely modulate the zonal wind in the tropics. Previous studies showed that QBO phases produce changes in deep convection through an increase/decrease in the tropopause height over the tropics and subtropics. This study investigates the combined effects of QBO and ENSO on tropical cyclone activity by modulating tropopause height. We found that tropopause height increases over the Gulf of Mexico, the Caribbean region, and the Western North Atlantic Ocean during La Niña + QBOW, allowing deeper tropical convection to develop over those regions. As a consequence, TC activity over those regions is not only increased in number but also enhanced in intensity. Conversely, during El Niño + QBOE, most deep tropical convection is inhibited over those same regions due to the decrease in tropopause height over the subtropics. We conclude that QBO effects on TCs and deep convection should be studied in combination with ENSO. Additional comparative studies using long record data at high vertical resolution are needed to fully understand to what extent QBO interacts with ENSO in the lower tropical stratosphere and upper tropical troposphere. Full article

We present a Bayesian inversion method for estimating volcanic ash emissions using satellite retrievals of ash column load and an atmospheric dispersion model. An a priori description of the emissions is used based on observations of the rise height of the volcanic plume and a stochastic model of the possible emissions. Satellite data are processed to give column loads where ash is detected and to give information on where we have high confidence that there is negligible ash. An atmospheric dispersion model is used to relate emissions and column loads. Gaussian distributions are assumed for the a priori emissions and for the errors in the satellite retrievals. The optimal emissions estimate is obtained by finding the peak of the a posteriori probability density under the constraint that the emissions are non-negative. We apply this inversion method within a framework designed for use during an eruption with the emission estimates (for any given emission time) being revised over time as more information becomes available. We demonstrate the approach for the 2010 Eyjafjallajökull and 2011 Grímsvötn eruptions. We apply the approach in two ways, using only the ash retrievals and using both the ash and clear sky retrievals. For Eyjafjallajökull we have compared with an independent dataset not used in the inversion and have found that the inversion-derived emissions lead to improved predictions. Full article

In recent years, cases of unexplained, elevated levels of radioactive particles have demonstrated an increasing need for efficient and robust source localization methods. In this study, a Bayesian method for source localization is developed and applied to two cases. First, the method is validated against the European tracer experiment (ETEX) and then applied to the still unaccounted for release of Ru-106 in the fall of 2017. The ETEX dataset, however, differs significantly from the Ru-106 dataset with regard to time resolution and the distance from the release site to the nearest measurements. Therefore, sensitivity analyses are conducted in order to test the method’s sensitivity to these parameters. The analyses show that the resulting source localization depends on both the observed temporal resolution and the existence of sampling stations close to the source. However, the method is robust, in the sense that reducing the amount of information in the dataset merely reduces the accuracy, and hence, none of the results are contradictory. When applied to the Ru-106 case, the results indicate that the Southern Ural region is the most plausible release area, and, as hypothesized by other studies, that the Mayak nuclear facility is the most likely release location. Full article

In Korea, sudden cold weather in spring occurs repeatedly every year and causes severe damage to field crops and fruit trees. Detailed forecasting of the daily minimum or suddenly decreasing temperature, closely related to the local topography, has been required in the farmer community. High-resolution temperature models based on empirical formulas or statistical downscaling have fundamental limitations, making it difficult to perform biophysical application and mechanism explanation on small-scale complex terrains. Weather Research and Forecasting–Large Eddy Simulation (WRF–LES) can provide a dynamically and physically scientific tool to be easily applied for farm-scale numerical weather predictions. However, it has been applied mainly for urban areas and in convective boundary layer studies until now. In this study, 20 m resolution WRF–LES simulation of nighttime near-surface temperature and wind was performed for two cold spring weather events that induced significant crop damages in the apple production area and the results were verified with automatic weather station observation data. The study showed that the maximum mean bias of temperature was −1.75 °C and the minimum was −0.68 °C in the spring, while the root mean square error varied between 2.13 and 3.00 °C. The minimum temperature and its duration significantly affected the crop damage, and the WRF–LES could accurately simulate both features. This implies that the application of WRF–LES, with proper nest-domain configuration and harmonized physical options, to the prediction of nighttime frost in rural areas has promising feasibility for orchard- or farm-scale frost prevention and low-temperature management. Full article

We present the first box model simulation results aimed at identification of possible effects of the atmospheric photochemical evolution of the organic component of biomass burning (BB) aerosol on the aerosol radiative forcing (ARF) and its efficiency (ARFE). The simulations of the dynamics of the optical characteristics of the organic aerosol (OA) were performed using a simple parameterization developed within the volatility basis set framework and adapted to simulate the multiday BB aerosol evolution in idealized isolated smoke plumes from Siberian fires (without dilution). Our results indicate that the aerosol optical depth can be used as a good proxy for studying the effect of the OA evolution on the ARF, but variations in the scattering and absorbing properties of BB aerosol can also affect its radiative effects, as evidenced by variations in the ARFE. Changes in the single scattering albedo (SSA) and asymmetry factor, which occur as a result of the BB OA photochemical evolution, may either reduce or enhance the ARFE as a result of their competing effects, depending on the initial concentration OA, the ratio of black carbon to OA mass concentrations and the aerosol photochemical age in a complex way. Our simulation results also reveal that (1) the ARFE at the top of the atmosphere is not significantly affected by the OA oxidation processes compared to the ARFE at the bottom of the atmosphere, and (2) the dependence of ARFE in the atmospheric column and on the BB aerosol photochemical ages almost mirrors the corresponding dependence of SSA. Full article

Background: Hokkaido was the first Japanese prefecture to be affected by COVID-19. Since the beginning of the pandemic, the Japanese government has been publishing the information of each individual who was tested positive for the virus. Method: The current study analyzed the 1269 SARS-CoV-2 cases confirmed in Hokkaido in order to examine sex-based differences in symptomology and infectiveness, as well as the status of reinfections and the viral transmission networks. Results: The majority of asymptomatic patients were females and older. Females were 1.3-fold more likely to be asymptomatic (p < 0.001) while a decade of difference in age increased the likelihood of being asymptomatic by 1% (p < 0.001). The data contained information up to quaternary viral transmission. The transmission network revealed that, although asymptomatic patients are more likely to transmit the virus, the individuals infected by asymptomatic cases are likely to be asymptomatic (p < 0.001). Four distinct co-occurrences of symptoms were observed, including (i) fever/fatigue, (ii) pharyngitis/rhinitis, (iii) ageusia/anosmia, and (iv) nausea/vomiting/diarrhea. The presences of diarrhea (p = 0.05) as well as nausea/vomiting (p < 0.001) were predictive of developing dyspnea, i.e., severe disease. About 1% of the patients experienced reinfection. Conclusions: Sex and symptomatology appear to play important roles in determining the levels of viral transmission as well as disease severity. Full article

Many modern ionospheric studies rely on incoherent scatter radars (ISR) since this kind of radar is able to detect various ionospheric parameters over very long ranges. The performance of ISR significantly depends on its coding system. In recent decades, a new type of coding system, which is the so-called composite coding, was presented. It used to be constructed by using a certain code to modulate alternating code to achieve better detection resolution and anti-noise performance for ISRs. In the present study, a new composite coding system was presented, which is constructed based on complementary codes and alternating codes. In this paper, the performance of the new composite code will be compared with that of several traditional codes to show that the new composite code can help to improve the detection performance of the ISR. According to the analysis based on the ambiguity function, the present composite coding system helps to improve the range resolution and detection range for ISR detections. In addition, numerical tests on anti-noise performance show that the complementary composite coding system has a good anti-noise performance and helps to reduce the necessary times of incoherent integration. As a result, the composite coding system can improve the time resolution. Full article

This paper investigates the influence of tropical cyclones on water vapor concentrations in the upper atmosphere above these storms. We use independent data sets of tropical storm intensity, water vapor and lightning activity to investigate this relationship. Water vapor in the upper troposphere is a key greenhouse gas, with direct impacts on surface temperatures. Both the amount and altitude of water vapor impact the radiative balance and the greenhouse effect of the atmosphere. The water vapor enters the upper troposphere through deep convective storms, often associated with lightning activity. The intensity of the lightning activity represents the intensity of the convection in these storms, and hence the amount of water vapor transported aloft. In this paper, we investigate the role of tropical cyclones on the contribution of water vapor to the upper atmosphere moistening. Tropical cyclones are the largest most intense storms on Earth and can last for up to two weeks at a time. There is also evidence that the intensity of tropical cyclones is increasing, and will continue to increase, due to global warming. In this study we find that the maximum moistening of the upper atmosphere occurs at the 200 hPa level (~12 km altitude), with a lag of 1–2 days after the maximum sustained winds in the tropical cyclone. While the water vapor peaks after the maximum of the storm intensity, the lightning activity peaks before the maximum intensity of the storms, as shown previously. We show here that the absolute amount of water vapor in the upper troposphere above tropical storms increases linearly with the intensity of the storms. For every 10 hPa decrease in the minimum pressure of tropical storms, the specific humidity increases around 0.2 g/kg at the 200 hPa level. Full article

In this study, 24 h quantitative precipitation forecasts (QPFs) by a cloud-resolving model (with a grid spacing of 2.5 km) on days 1–3 for 29 typhoons in six seasons of 2010–2015 in Taiwan were examined using categorical scores and rain gauge data. The study represents an update from a previous study for 2010–2012, in order to produce more stable and robust statistics toward the high thresholds (typically with fewer sample points), which is our main focus of interest. This is important to better understand the model’s ability to predict such high-impact typhoon rainfall events. The overall threat scores (TS, defined as the fraction among all verification points that are correctly predicted to reach a given threshold to all points that are either observed or predicted to reach that threshold, or both) were 0.28 and 0.18 on day 1 (0–24 h) QPFs, 0.25 and 0.16 on day 2 (24–48 h) QPFs, and 0.15 and 0.08 on day 3 (48–72 h) QPFs at 350 mm and 500 mm, respectively, showing improvements over 5 km models. Moreover, as found previously, a strong dependence of higher TSs for larger rainfall events also existed, and the corresponding TSs at 350 and 500 mm for the top 5% of events were 0.39 and 0.25 on day 1, 0.38 and 0.21 on day 2, and 0.25 and 0.12 on day 3. Thus, for the top typhoon rainfall events that have the highest potential for hazards, the model exhibits an even higher ability for QPFs based on categorical scores. Furthermore, it is shown that the model has little tendency to overpredict or underpredict rainfall for all groups of events with different rainfall magnitude across all thresholds, except for some tendency to under-forecast for the largest event group on day 3. Some issues associated with categorical statistics to be aware of are also demonstrated and discussed. Full article

The drag coefficient is essential for calculating the aerodynamic friction between air and sea. In this study, we regress a set of relationships between the drag coefficient and the wind speed for different wind ranges using an observational dataset that consists of 5941 estimates of the mean flow and fluxes from 11 aircraft turbulent measurements over the sea surface. Results show that: (1) the drag coefficient is a power function of wind speed over smooth sea surface when it is no greater than 4.5 ms⁻¹, and the drag coefficient decreases with the increase of wind speed; and (2) for rough sea surface, when the wind speed is greater than 4.5 ms⁻¹ and less than or equal to 10.5 ms⁻¹, the drag coefficient increases linearly with the increase of horizontal wind speed; when the wind speed is greater than 10.5 ms⁻¹ and less than or equal to 33.5 ms⁻¹, the drag coefficient changes parabolically with the increase of wind speed; when the wind speed is greater than 33.5 ms⁻¹, the drag coefficient is constant. Additionally, regressed from drag coefficient, the saturated wind speed threshold is 23 ms⁻¹. Parameterizations of turbulent heat transfer coefficient ($C_h$) and water vapor transfer coefficient ($C_e$) are also investigated. Full article

Atmospheric radio refractivity has an obvious influence on the signal transmission path and communication group delay effect. The uncertainty of water vapor distribution is the main reason for the large error of tropospheric refractive index modeling. According to the distribution and characteristics of water vapor pressure, temperature, and pressure, which are the basic components of the refractive index, a method for retrieving atmospheric refractivity profile based on GNSS (Global Navigation Satellite System) and meteorological sensor measurement is introduced and investigated in this study. The variation of the correlation between zenith wet delay and water vapor pressure is investigated and analyzed in detail. The partial pressure profiles of water vapor are retrieved with relevance vector machine method based on tropospheric zenith wet delay calculated by single ground-based GPS (Global Positioning System) receiver. The atmospheric temperature and pressure is calculated with the least square method, which is used to fit the coefficients of the polynomial model based on a large number of historical meteorological radiosonde data of local stations. By combining the water vapor pressure profile retrieving from single ground-based GPS and temperature and pressure profile from reference model, the refractivity profile can be obtained, which is compared to radiosonde measurements. The comparison results show that results of the proposed method are consistent with the results of radiosonde. By using over ten years’ (through 2008 to 2017) historical radiosonde meteorological data of different months at China Big-Triangle Points, i.e., Qingdao, Sanya, Kashi, and Jiamusi radiosonde stations, tropospheric radio refractivity profiles are retrieved and modeled. The comparison results present that the accuracies of refractivity profile of the proposed method at Qingdao, Sanya, Kashi, and Jiamusi are about 5.48, 5.63, 3.58, and 3.78 N-unit, respectively, and the annual average relative RMSE of refractivity at these stations are about 1.66, 1.53, 1.49, and 1.23%, respectively. Full article

The formation of precipitation in clouds is initiated by inorganic and organic/biological ice nuclei. Certain species of bacteria and fungi are known to act as efficient biological ice nuclei at temperatures between −10 and 0 °C. Biological ice nuclei have been found and characterized in precipitation samples (snow, rain, and hail). We investigated the presence of warm temperature biological ice nuclei in 17 fresh snow samples from Greece and isolated and partially characterized ice nucleation active bacteria from these. All snow samples contained particles or other material active as ice nuclei at −9 °C in concentrations ranging from 3 to 943 nuclei/L. The numbers of this class of ice nuclei were reduced or eliminated after incubating snowmelt concentrates at 100 °C for 15 min and by treatment with lysozyme, a bacterial cell wall-degrading enzyme. These findings indicate the presence of microbial ice nuclei in snow samples from Greece. We also isolated ice nucleation active bacteria from some of the samples. These bacteria belong to genus Pseudomonas and are common on plants and soil. This is the first report on biological ice nuclei in precipitation samples from Greece. Full article

Environmentally persistent free radicals (EPFRs) were previously considered an unrecognized composition of air pollutants and might help explain the long-standing medical mystery of why non-smokers develop tobacco-related diseases such as lung cancer. However, there is no investigated on EPFRs in Xuanwei rural areas, especially in high prevalence of lung cancer areas. In this study, we selected six types of coal and three types of biomass in Xuanwei, then conducted simulated combustion, and six group of atmospheric particulate matters (APMs) to explore the content and particle size distribution pattern of EPFRs and a new health risk assessment method to evaluate the risk of EPFRs in PM for adults and children. Our results show that the contribution of EPFRs for biomass combustion, coal combustion and APMs were mainly distributed in the size range of <1.1 μm, which accounted for 76.15 ± 4.14%, 74.85 ± 10.76%, and 75.23 ± 8.18% of PM3.3. The mean g factors and ΔHp-p indicated that the EPFRs were mainly oxygen-centered radicals in PM in Xuanwei. The results suggest that the health risk of EPFRs is significantly increased when the particle size distribution of EPFRs is taken into account, and coal combustion particulate matter (174.70 ± 37.86 cigarettes for an adult, 66.39 ± 14.39 cigarettes per person per year for a child) is more hazardous to humans than biomass combustion particulate matter (69.41 ± 4.83 cigarettes for an adult, 26.37 ± 1.84 cigarettes per person per year for), followed by APMs (102.88 ± 39.99 cigarettes for an adult, 39.10 ±15.20 cigarettes per person per year for) in PM_3.3. Our results provides a new perspective and evidence for revealing the reason for the high incidence of lung cancer in Xuanwei, China. Full article

The Gobi Desert is a major source of Asian dust events, and the resulting health hazards have increased significantly in recent years. We reported that a variety of live bacteria were distributed in the Gobi Desert in relation to land use. Bacterial distribution was confirmed in the environment and on the land used by animals; however, bacterial saltation due to dust events has not been investigated in detail. In this study, to understand the distribution of surface bacteria in the atmosphere by dust saltation, live bacteria in four dust-generating areas in the Gobi area were monitored using an artificial dust generating device. The live bacteria were detected by experimental saltation at a wind speed of 6.5–8 m/s in all areas. A certain number of live bacteria are constantly saltated by dust events, and these bacteria depend on land use. Moreover, the bacterial saltation strain depended on land use and diversity, indicating that live bacteria are lifted into the environment by dust events. These findings indicate that dust events saltate environmental bacteria on the ground, suggest the risk of animal-derived bacterial saltation affected by land use, and present cross-border public health challenges to be considered in the future. Full article

The increase of the vertical scaling exponent of the horizontal wind Hv(s) with altitude from the surface of the Pacific Ocean to 13 km altitude, as observed by GPS dropsondes, is investigated. An explanation is offered in terms of the decrease of gravitational force and decrease of quenching efficiency of excited photofragments from ozone photodissociation with increasing altitude (decreasing pressure). Turbulent scaling is examined in both the vertical from dropsondes and horizontal from aircraft observations; the scaling exponents H for both wind speed and temperature in both coordinates are positively correlated with traditional measures of jet stream strength. Interpretation of the results indicates that persistence of molecular velocity after collision induces symmetry breaking emergence of hydrodynamic flow via the mechanism first modelled by Alder and Wainwright, enabled by the Gibbs free energy carried by the highest speed molecules. It is suggested that the combined effects have the potential to address the cold bias in numerical models of the global atmosphere. Full article

The number of cities, or parts of cities, where air quality has been computed using the PMSS 3D model now appears to be sufficient to allow assessment and understanding of performance. Two fields of application explain the growing number of sites: the first is the long-term air quality assessment required in urban areas for any building or road project. The geometric complexity found in such areas can justify the use of a 3D approach, as opposed to Gaussian ones. However, these studies have constraining rules that can make the modelling challenging: several scenarios are needed (current, future with project, future without project), the long-term impact implies a long physical time period to be computed, and the spatial extension of the domain can be large in order to cover the traffic impact zone of the project. The second type of application is dedicated to services and, essentially, to forecasting. As for impact assessments, the modelling can be challenging here because of the extension of the domain if the target area is a whole city. Forecast also adds the constraint of time, as results are requested early, and the constraint of robustness. The CPU amount needed to meet all these requirements is important. It is therefore crucial to optimize all possible parts of the modelling chain in order to limit cost and delay. The sites presented in the article have been modelled with PMSS for long periods. This allows feedback to be provided on different topics: (a) daily forecasts offer an opportunity to increase the robustness of the modelling chain; (b) quantitative validation at air quality measurement stations; (c) comparison of annual impact based on a whole year, and based on a sampling list of dates selected thanks to a classification process; (d) large calculation domains with widespread pollutant emissions offer a great opportunity to qualitatively check and improve model results on numerous geometrical configurations; (e) CPU time variations between different sites provide valuable information to select the best parametrizations, to predict the cost of the services, and to design the needed hardware for a new site. Full article

This paper analyzes the results of the automatic (in situ) recording of the regional transport of pollutants from the large regional coal-fired thermal power plants in the atmospheric boundary layer above the southern basin of Lake Baikal. Due to high stacks (about 200 m), emissions from large thermal power plants rise to the altitudes of several hundreds of meters and spread over long distances from their source by tens and hundreds of kilometers. The continuous automatic monitoring of the atmosphere in the southern basin of Lake Baikal on top of the coastal hill (200 m above the lake) revealed the transport of a large number of sulfur oxides and nitrogen oxides in the form of high-altitude plumes from thermal power plants of the large cities located 70 to 100 km to the northwest of the lake (Irkutsk and Angarsk). The consequence of such transport is the increased acidity of precipitation in the southern basin of Lake Baikal and the additional influx of biogenic nitrogen compounds to the lake ecosystem. The spatial scale and possible risks of such regional transport of air pollution for the lake ecosystem require further closer study. Full article

As a link for energy transfer between the land and atmosphere in the terrestrial ecosystem, karst vegetation plays an important role. Karst vegetation is not only affected by environmental factors but also by intense human activities. The nonlinear characteristics of vegetation growth are induced by the interaction mechanism of these factors. Previous studies of this relationship were not comprehensive, and it is necessary to further explore it using a suitable method. In this study, we selected climate, human activities, topography, and soil texture as the response factors; a nonlinear relationship model between the karst normalized difference vegetation index (NDVI) and these factors was established by applying a back propagation neural network (BPNN), a radial basis function neural network (RBFNN), the random forest (RF) algorithm, and support vector regression (SVR); and then, the karst NDVI was predicted. The coefficient of determination (R²), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE) of the obtained results were calculated, and the mean R² values of the BPNN, RBFNN, RF, and SVR models were determined to be 0.77, 0.86, 0.89, and 0.91, respectively. Compared with the BPNN, RBFNN, and RF models, the SVR model had the lowest errors, with mean MSE, RMSE, and MAPE values of 0.001, 0.02, and 2.77, respectively. The results show that the BPNN, RBFNN, RF, and SVR models are within acceptable ranges for karst NDVI prediction, but the overall performance of the SVR model is the best, and it is more suitable for karst vegetation prediction. Full article

The indoor air quality of healthcare and care facilities is poorly studied. The aim of this study was to qualitatively and quantitatively describe the chemical pollution and the microbiological contaminations of the indoor environment of these facilities. Methods: A wide range of chemical compounds (39 volatile and 13 semi-volatile organic compounds, carbon dioxide, fine particulate matter) and microorganisms (fungi and bacteria) were studied. Sampling campaigns were conducted in two French cities in summer 2018 and winter 2019 in six private healthcare facilities (general practitioner’s offices, dental offices, pharmacies) and four care facilities (nursing homes). Results: The highest median concentrations of chemical compounds (μg/m³) were measured for alcohols (ethanol: 378.9 and isopropanol: 23.6), ketones (acetone: 18.8), aldehydes (formaldehyde: 11.4 and acetaldehyde: 6.5) and terpenes (limonene: 4.3). The median concentration of PM_2.5 was 9.0 µg/m³. The main bacteria of these indoor environments were Staphylococcus, Micrococcus and Bacillus genera, with median bacterial concentrations in the indoor air of 14 cfu/m³. The two major fungal genera were Cladosporium and Penicillium, with median fungal concentrations of 7 cfu/m³. Conclusions: Indoor air in healthcare and care facilities contains a complex mixture of many pollutants found in higher concentrations compared to the indoor air in French hospitals in a previous study. Full article

In this study, a new approach for rainfall spatial interpolation in the Luxembourgian case study is introduced. The method used here is based on a Fuzzy C-Means (FCM) clustering method. In a typical FCM procedure, there are a lot of available data and each data point belongs to a cluster, with a membership degree [0 1]. On the other hand, in our methodology, the center of clusters is determined first and then random data are generated around cluster centers. Therefore, this approach is called inverse FCM (i-FCM). In order to calibrate and validate the new spatial interpolation method, seven rain gauges in Luxembourg, Germany and France (three for calibration and four for validation) with more than 10 years of measured data were used and consequently, the rainfall for ungauged locations was estimated. The results show that the i-FCM method can be applied with acceptable accuracy in validation rain gauges with values for R² and RMSE of (0.94–0.98) and (9–14 mm), respectively, on a monthly time scale and (0.86–0.89) and (1.67–2 mm) on a daily time scale. In the following, the maximum daily rainfall return periods (10, 25, 50 and 100 years) were calculated using a two-parameter Weibull distribution. Finally, the LISFLOOD FP flood model was used to generate flood hazard maps in Dudelange, Luxembourg with the aim to demonstrate a practical application of the estimated local rainfall return periods in an urban area. Full article

The High-Resolution Infrared Radiation Sounder (HIRS) on NOAA and MetOp A/B satellites has been observing the Earth continuously for over four decades, providing essential data for operational numerical weather prediction, retrieval of atmospheric vertical profile, and total column information on atmospheric temperature, moisture, water vapor, ozone, cloud climatology, and other geophysical parameters globally. Although the HIRS data meets the needs of the short-term weather forecast, there are inconsistencies when the long-term decadal time series is used for time series analysis. The discrepancies are caused by several factors, including spectral response differences between the HIRS models on the satellites and spectral response uncertainties and other calibration issues. Previous studies have demonstrated that significant improvements can be achieved by recalibrating some of the HIRS longwave CO₂ channels (Channels 4, 5, 6, and 7), which has helped make the time series more consistent. The current study aims to extend the previous study to the remaining longwave infrared sounding channels, including Channels 1, 2, 3, and 8, using a similar approach. Similar to previous findings, the spectral shift of the HIRS bands has helped improve the consistency in the time series from NOAA-06 to MetOp-A and B for these channels. We also found that HIRS channels on MetOp-B also have bias relative to Infrared Atmospheric Sounding Interferometer (IASI) on the same satellite, especially Channel 4, and a spectral shift significantly reduced the bias. To bridge the observation gap in time series in the mid-1980s between NOAA-07 and NOAA-09, the global mean method has been used since no transfer radiometers between them was available for this period, and the spectral response function corrections, therefore, can be applied to the earliest satellites (NOAA-06) for these channels. The recalibration parameters have been provided to other scientists at the University of Wisconsin for improving the time series in their long-term studies using historical HIRS data and are now made available to the science community. Full article

A prototype of a three-dimensional (3-D) radiation model is developed using the lattice Boltzmann method (LBM) and implemented on a graphical processing unit (GPU) to accelerate the model’s computational speed. This radiative transfer-lattice Boltzmann model (RT-LBM) results from a discretization of the radiative transfer equation in time, space, and solid angle. The collision and streaming computation algorithm, widely used in LBM for fluid flow modeling, is applied to speed up the RT-LBM computation on the GPU platform. The isotropic scattering is assumed in this study. The accuracy is evaluated using Monte Carlo method (MCM) simulations, showing RT-LBM is quite accurate when typical atmospheric coefficients of scattering and absorption are used. RT-LBM runs about 10 times faster than the MCM in a same CPU. When implemented on a NVidia Tesla V100 GPU in simulation with a large number of computation grid points, for example, RT-LBM runs ~120 times faster than running on a single CPU. The test results indicate RT-LBM is an accurate and fast model and is viable for simulating radiative transfer in the atmosphere with ranges for the isotropic atmosphere radiative parameters of albedo scattering (0.1~0.9) and optical depth (0.1~12). Full article

Shopping malls in Hong Kong are usually located near major roads. Indoor air quality (IAQ) in these buildings is subject to infiltration of outdoor traffic-related pollutants, such as PM10, PM2.5, CO, and NO₂. Furthermore, the existence of indoor sources and building geometry added to the complexity of variations in IAQ. To understand outdoor infiltration and spatial heterogeneity of these pollutants, we conducted fixed and cruise indoor sampling, together with simultaneous outdoor measurements, in a typical mall in Hong Kong. The cruise sampling was conducted indoors on a predesigned route and repeated 15 times. Outdoor infiltration was quantified based on regression analysis between indoor and outdoor sampling. Results showed that 75% of PM2.5, 53% of PM10, and 59% of NO₂ were infiltrated into the mall during opening hours. Elevated PM2.5 and CO were observed during the dinner period, suggesting an impact from cooking. Substantial spatial variations were observed for PM10, PM2.5, and NO₂, particularly at locations near entrances and restaurants. Measures are needed to reduce pollution intrusion from building openings and cooking-related sources to improve air quality in the selected mall. Fixed and cruise sampling methods used in this study provide insights on sensor deployment for future air quality monitoring in buildings. Full article

Black carbon (BC) aerosols have a considerable impact on humans because they not only cause environmental pollution and reduce visibility but also harm human health. During the heating season in northern China, a large amount of coal is burned for heating, producing a large amount of BC. There are few studies on BC properties during the heating season. In this paper, BC is measured optically, so it is referred to as equivalent black carbon (EBC). This paper investigated EBC properties in depth during the heating and nonheating seasons of a typical urban environment in China with two years of EBC measurements. The results show that: (1) EBC aerosol concentrations during the heating season were significantly higher than those during the nonheating season. (2) The main sources of EBC aerosols throughout the year are liquid sources. During the heating season, solid sources (coal and biomass combustion) are dominant. (3) The proportion of brown carbon (BrC) produced by biomass energy during the heating season is greater than that during the nonheating season. (4) The resulting backward trajectory indicates that a large portion of the high EBC aerosol concentration sources originate from northern and northwestern China. Our results reveal that the characteristics and sources of EBC in the urban environment of northern China vary widely, suggesting that different measures should be taken to reduce BC aerosol concentrations during heating and nonheating seasons. Full article

A computationally efficient source inversion algorithm was developed and applied with the Lagrangian atmospheric dispersion model DIPCOT. In the process of source location estimation by minimizing a correlation-based cost function, the algorithm uses only the values of the time-integrated concentrations at the monitoring stations instead of all of the individual measurements in the full concentration-time series, resulting in a significant reduction in the number of integrations of the backward transport equations. Following the source location estimation the release start time, duration and emission rate are assessed. The developed algorithm was verified for the conditions of the ETEX-I (European Tracer Experiment—1st release). Using time-integrated measurements from all available stations, the distance between the estimated and true source location was 108 km. The estimated start time of the release was only about 1 h different from the true value, within the possible accuracy of estimate of this parameter. The estimated release duration was 21 h (the true value was 12 h). The estimated release rate was 4.28 g/s (the true value was 7.95 g/s). The estimated released mass almost perfectly fitted the true released mass (323.6 vs. 343.4 kg). It thus could be concluded that the developed algorithm is suitable for further integration in real-time decision support systems. Full article