Editor’s Choice Articles

Energetic electron precipitation (EEP) is associated with solar activity and space weather and plays an important role in the Earth’s polar atmosphere. Energetic electrons from the radiation belt precipitate into the atmosphere during geomagnetic disturbances and cause additional ionization rates in the polar middle atmosphere. These induced atmospheric ionization rates lead to the formation of radicals in ion-molecular reactions at the heights of the mesosphere and upper stratosphere with the formation of reactive compounds of odd nitrogen NOy and odd hydrogen HOx groups. These compounds are involved in catalytic reactions that destroy the ozone. In this paper, we present the calculation of atmospheric ionization rates during geomagnetic disturbances using reconstructed spectra of electron precipitation from balloon observations; estimation of ozone destruction during precipitation events using one-dimensional photochemical radiation-convective models, taking into account both parameterization and ion chemistry; as well as provide an estimation of electron density during these periods. Full article

Wildfires are relevant sources of PM emissions and can have an important impact on air pollution and human health. In this study, we examine the impact of wildfire PM emissions on the Piemonte (Italy) air quality regional monitoring network using a Generalized Additive Mixed Model. The model is implemented with daily PM₁₀ and PM_2.5 concentrations sampled for 8 consecutive years at each monitoring site as the response variable. Meteorological data retrieved from the ERA5 dataset and the observed burned area data stored in the Carabinieri Forest Service national database are used in the model as explanatory variables. Spline functions for predictive variables and smooths for multiple meteorological variables’ interactions improved the model performance and reduced uncertainty levels. The model estimates are in good agreement with the observed PM data: adjusted R² range was 0.63–0.80. GAMMs showed rather satisfactory results in order to capture the wildfires contribution: some severe PM pollution episodes in the study area due to wildfire air emissions caused peak daily levels up to 87.3 µg/m³ at the Vercelli PM₁₀ site (IT1533A) and up to 67.7 µg/m³ at the Settimo Torinese PM_2.5 site (IT1130A). Full article

We present the first report of global ionospheric disturbances due to the most powerful Gamma Ray Burst GRB221009A occurred on 9 October 2022. Very Low Frequency (VLF) and Low Frequency (LF) sub-ionospheric radio signals are used to diagnose the effect of the GRB on the lower ionosphere. Both daytime and nighttime effects are analyzed in VLF and LF bands. The magnitude of VLF signal perturbations varied with the propagation condition (day/night), path length, and frequency of the signal. The recovery times for the VLF/LF signals to get back to their pre-GRB levels varied from 2–60 min. Radio signals reflected from the E-region ionosphere for nighttime VLF signals and daytime LF signals showed greater effects compared to the daytime VLF signals reflected from the lower parts of the D-region. Full article

The ease of travel allowed by contemporary means of long-range transportation has brought increasingly higher numbers of visitors to remote and relatively undisturbed insular territories. In a framework of environmental conservation of the natural patrimony, sustainably accommodating touristic flooding and the associated polluting footprint poses a demanding challenge. Over the past decade, Ponta Delgada, the largest city of the mid-Atlantic Azores archipelago, has become a hotspot for transatlantic cruise ship (CS) lines in spring and autumn. CSs are substantial contributors to the emissions of greenhouse gases (GHG), as well as hazardous sulphur (SO_x) and nitrogen (NO_x) oxides. It is hereby retrospectively investigated whether the background levels of air pollutants were raised following the CS influx at Ponta Delgada, which conventionally displays great air quality. The daily CS traffic at the local harbor was associated with the daily concentrations of air pollutants (SO₂, O₃, NO₂, NO_x, PM₁₀ and PM_2.5), monitored by the local urban background monitoring station (~1.3 km northwards). Exceedances above daily legislated limits from 2013 until 2020 only occurred sporadically for PM₁₀ and PM_2.5, often during episodes of natural dust storms. No major correlation was found between CS parameters with the recorded values of pollutants, although a noticeable signal of NO_X increase of southern origin is observed during spring days with CS presence. Daily data suggest CS influx has not strongly influenced background air quality. A near-source, real-time monitoring network should be implemented in the city to provide the necessary spatial and temporal resolution for tracking short-term fluctuations in air pollutants during CS arrivals and departures. Full article

Mist spraying is a technique for locally lowering air temperature by spraying fine mist into the air and using the latent heat of evaporation immediately after spraying. This study focuses on the conditions under which mist spraying contributes to the increase in sensible heat release from the human body, using the ratio of air temperature decrease and humidity increase in the space where mist is sprayed. From the measurement results in front of the air-conditioning condenser unit, humidity increased by about 10 g/kg(DA), while air temperature decreased by about 10 °C. From the measurement results in an open space in a park, air temperature decreased by about 0.5 to 1 °C within 2 m of the mist spray and humidity increased by about 0.5 to 1 g/kg(DA) at the height of the mist spray, regardless of the distance from the mist spray. From the measurement results at semi-open bus stops, air temperature decreased slightly to 1 °C and humidity increased slightly to 1 g/kg(DA) under low-wind conditions. Unfortunately, the measured results of air temperature decrease in relation to humidity increase, which the human body perceives as cooler, were not available. Full article

Heat waves (HWs) with high humidity are dangerous to human health. However, existing studies on different types of HWs considering the effect of humidity are still limited. This study defines three types of wet summer HWs (that is, wet independent daytime and nighttime HWs and wet daytime-nighttime compound HWs) and investigates their spatial-temporal changes across China during 1961–2020. Results show significant upward trends of wet nighttime and compound HWs in terms of frequency, occurring days, duration, intensity and spatial extent, while changes for wet daytime HWs are weak and insignificant in nearly all sub-regions of China except for southwest and eastern northwest China. Compared with wet compound and daytime HWs, wet nighttime HWs accompanied by more elevated relative humidity exhibit larger growth rates in frequency, occurring days, duration and affected areas. Additionally, most wet nighttime and compound HWs with the longest duration and/or the maximum intensity are found to occur after the mid-1990s, compared to fewer than half for wet daytime HWs. Our findings emphasize the prominent intensifying trends in wet nighttime HWs across China for the last 60 years, and suggest more efforts on exploring humid HWs. Full article

This study is based on 5.5 years of continuous observation of sprites from Sagamihara, Japan. Up to February 2022, we detected 537 sprites and found that the most significant number of sprites were observed during the winter (303 sprites); on the other hand, there were only 46 sprites in summer. The hourly distribution of the number of observed sprites peaked at midnight JST (15:00 and 16:00 UTC). To understand the seasonal and the hourly distribution of sprites, we estimate the number of sprites considering the energy and the polarity of lightning, the temporal changes of surrounding environments of sprites, and the conditions for generating sprites. We found that the energy of lightning, the monthly ratio of a positive cloud-to-ground discharge, and the hourly change in the electron number density are essential factors to match the observed sprite distributions. Full article

We report effects in the upper high-latitude atmosphere related to the interaction of fast magnetosheath plasma streams, so-called jets, with the dayside magnetopause. The jets were observed by THEMIS mission in the dayside magnetosphere during a quiet day on 12 July 2009. It was found that the jet interaction was accompanied by strong localized compression and penetration of suprathermal magnetosheath plasma inside the dayside magnetosphere. The compression caused prominent magnetic variations with amplitudes up to 100 nT observed by ground-based magnetic networks SuperMAG and CARISMA. The magnetic variations were also visible in the geomagnetic Dst and AE indices. The jets also resulted in intense precipitation of the suprathermal ions with energies < 10 keV and energetic electrons with energies > 30 keV observed by low-altitude NOAA/POES satellites in a wide longitudinal range. The precipitations produced enhancements of ionization with an amplitude of ~1 TECU (~30% in relative units) and intensification of the ionospheric E and F1 layers as observed in the FORMOSAT-3/COSMIC misson. The enhanced ionization in the upper atmosphere might affect radio communication and navigation in the high-latitude regions. These results also provide new insight into the contribution of magnetospheric forcing to day-to-day ionospheric variability. Full article

Rainfed agriculture in Senegal is heavily affected by weather-related risks, particularly timing of start/end of the rainy season. For climate services in agriculture, the National Meteorological Agency (ANACIM) of Senegal has defined an onset of rainy season based on the rainfall. In the field, however, farmers do not necessarily follow the ANACIM’s onset definition. To close the gap between the parallel efforts by a climate information producer (i.e., ANACIM) and its actual users in agriculture (e.g., farmers), it is desirable to understand how the currently available onset definitions are linked to the yield of specific crops. In this study, we evaluated multiple onset definitions, including rainfall-based and soil-moisture-based ones, in terms of their utility in sorghum production using the DSSAT–Sorghum model. The results show that rainfall-based definitions are highly variable year to year, and their delayed onset estimation could cause missed opportunities for higher yields with earlier planting. Overall, soil-moisture-based onset dates determined by a crop simulation model produced yield distributions closer to the ones by semi-optimal planting dates than the other definitions, except in a relatively wet southern location. The simulated yields, particularly based on the ANACIM’s onset definition, showed statistically significant differences from the semi-optimal yields for a range of percentiles (25th, 50th, 75th, and 90th) and the means of the yield distributions in three locations. The results emphasize that having a good definition and skillful forecasts of onset is critical to improving the management of risks of crop production in Senegal. Full article

This study aims to evaluate and compare the indoor air velocities and thermal environment inside different generations of public residential buildings developed by the Housing and Development Board (HDB) of Singapore and analyze the impact of façade design on the indoor thermal environment. To achieve this goal, several case studies were carried out, namely, five typical HDB blocks built in different generations from the 1970s to recent years. Firstly, these five blocks with different façade design features were simulated to obtain the indoor air temperatures for both window-closed and window-open scenarios by using the EnergyPlus V22.2.0 (U.S. Department of Energy) and Design-Builder v6 software(DesignBuilder Software Ltd, Stroud, Gloucs, UK). Meanwhile, the computational fluid dynamics (CFD) simulations were conducted to obtain the area-weighted wind velocities in the corresponding zones to evaluate the indoor thermal comfort. Accordingly, the effects of façade design on indoor air temperatures under both the window-closed and window-open conditions were compared and analyzed. Positive correlations between the facades’ window-to-wall ratio (WWR) and the residential envelope transmittance value (RETV) and T_a were confirmed with statistical significance at a 0.05 level. Furthermore, the indoor thermal comfort based on the wind open scenarios was also investigated. The results indicate that the thermal environment can be greatly improved by implementing proper façade design strategies as well as opening the windows, which could result in an average 3.2 °C reduction in T_a. Finally, some principles were proposed for the façade design of residential buildings in tropical regions with similar climate conditions. Full article

Statistical GNSS-RO measurements of phase and amplitude scintillation are analyzed at the mid-latitudes in the local summer for a 100 km altitude. These conditions are known to contain frequent sporadic-E, and the S${}_4$-${\sigma }_{\varphi }$ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S${}_4$-${\sigma }_{\varphi }$ histograms are presented, showing roughly linear trends until the S${}_4$ saturates near 0.8. To interpret the measurements and understand the sporadic-E contributions, 10,000 simulations of RO signals perturbed by sporadic-E layers are performed using length, intensity, and vertical thickness distributions from previous studies, with the assumption that the sporadic-E layer acts as a Gaussian lens. Many of the key trends observed in the measurement histograms are present in the simulations, providing a key for understanding the complex mapping between layer characteristics and impacts on the GNSS-RO signals. Additionally, the inclusion of Kolmogorov turbulence and a diffusion-limited threshold on the lens strength/(vertical thickness)${}^2$ ratio helps to make the layers more physically realistic and improves agreement with the observations. Full article

This research is concerned with understanding the degree of human thermal (dis)comfort in connection with the various microclimates present in the vicinity of bike trails in Balneário Camboriú/SC, Brazil, throughout the summer. Local Climate Zones were determined using the Sky View Factor and were identified along research routes and schedules at 9:00 a.m. and 4:00 p.m. on a subtropical summer day (14 January 2022). Data were collected with weather devices attached to the bicycle, measuring air temperature, relative humidity, and globe temperature, from which the mean radiant temperature was calculated. The PET and UTCI indices were used to assess outdoor thermal comfort in the summer. The findings revealed that at 9:00 a.m., the eastern half of the city had a higher tendency for thermal discomfort; however, at 4:00 p.m., this same location had thermal comfort for users along bike routes. At 4:00 p.m., the PET index indicated that 24% of the bike paths were pleasant, and the UTCI index indicated that 100% of them were in thermal comfort. At 9:00 a.m., the majority of the city was under discomfort conditions. The index values reflect the morning time, and the study shows that there is now a negative correlation between the SVF and the indexes, which means that the greater the SVF computations, the lower the values are. The PET and UTCI indices revealed a positive association in the afternoon period: The greater the SVF values, the higher the PET and UTCI indices. Further research should be conducted in the future because many parameters, such as construction, position, and urban (im)permeability, as well as sea breeze and solar radiation, can have a significant impact on outdoor human thermal comfort in Balneário Camboriú, and when combined with the type of LCZ and the SVF, it is possible to understand how all of these active systems interact and form microclimates that are beneficial to bike path users. Full article

We studied the correlations between the migrating and non-migrating tides and solar cycle in the mesosphere and lower thermosphere (MLT) regions between 60$°$S and 60$°$N, which are in LAT-LON Earth coordinates, by analyzing the simulation datasets from the thermosphere and ionosphere extension of the Whole Atmosphere Community Climate Model (WACCM-X). A least squares fitting method was utilized to obtain the daily mean migrating tides and non-migrating tides. The Pearson linear correlation coefficient was used to analyze the correlations between tides and solar activity. Our analysis shows that the negative correlations between tides and solar activity are mostly impacted by the first symmetrical structure of the tidal modes for both migrating and non-migrating components. The coefficient of molecular thermal conductivity for the first symmetrical structure is small at low solar flux, so the tides dissipate more slowly when the F10.7 cm radio flux level is low. Thus, the amplitudes of tidal variations under a solar minimum condition are larger than those under a solar maximum condition. The correlation between tides and solar activity could also be influenced by some other factors, such as geomagnetic activity and the density of carbon dioxide $\left({\mathrm{CO}}_2\right)$ on Earth. The tidal variations can be influenced by westward background wind, which grows stronger as geomagnetic activity rises. Further, dissipation of the tides decreases because the heat conduction and molecular viscosity are weakened in the cooling thermosphere caused by increasing ${\mathrm{CO}}_2$, which results in larger tidal amplitudes under the solar maximum condition. It is found that the correlations between tides and solar cycle vary at different altitudes and latitudes. The negative correlations are most possibly influenced by the first symmetrical structure of tidal variations and may also be impacted by geomagnetic activity. The positive correlations are impacted by the density of ${\mathrm{CO}}_2$. Full article

The World Health Organization has pointed out that airborne transmission via aerosol particles can be a strong vector for the spread of SARS-CoV-2. Protecting occupants from infectious diseases or harmful particulate matter (PM) in general can be challenging. While experimentally outlining the detailed flow of PM in rooms may require complex setups, computational fluid dynamics (CFD) simulations can provide insights into improving the safety of the built environment and the most effective positioning of air-purifying devices. While previous studies have typically leveraged Reynolds-averaged Navier–Stokes (RANS) approaches for predicting particle propagation, the turbulence length scales accurately captured in these simulations may not be sufficient to provide a realistic spread and the mixing of particles under the effects of forced convection. In this paper, we experimentally validate a Lattice Boltzmann very large eddy simulation (VLES) approach including particle modeling. We also demonstrate how this simulation approach can be used to improve the effectiveness of air filtration devices in realistic office environments. Full article

We present joint analysis of the UV (365 nm) images captured by the cameras on board ESA’s Venus Express and JAXA’s Akatsuki spacecraft. These observations enabled almost continuous characterization of the cloud top circulation over the longest period of time so far (2006–2021). More than 46,000 wind vectors were derived from tracking the UV cloud features and revealed changes in the atmospheric circulation with the period of 12.5 ± 0.5 years. The zonal wind component is characterized by an annual mean of −98.6 ± 1.3 m/s and an amplitude of 10.0 ± 1.6 m/s. The mean meridional wind velocity is −2.3 ± 0.2 m/s and has an amplitude of 3.4 ± 0.3 m/s. Plausible physical explanations of the periodicity include both internal processes and external forcing. Both missions observed periodical changes in the UV albedo correlated with the circulation variability. This could result in acceleration or deceleration of the winds due to modulation of the deposition of the radiative energy in the clouds. The circulation can be also affected by the solar cycle that has a period of approximately 11 years with a large degree of deviation from the mean. The solar cycle correlated with the wind observations can probably influence both the radiative balance and chemistry of the mesosphere. The discovered periodicity in the cloud top circulation of Venus, and especially its similarity with the solar cycle, is strongly relevant to the study of exoplanets in systems with variable “suns”. Full article

Warnings of severe weather with a lead time longer that two hours require the use of skillful numerical weather prediction (NWP) models. In this study, we test the performance of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Conformal Cubic Atmospheric Model (CCAM) in simulating six high-impact weather events, with a focus on rainfall predictions in South Africa. The selected events are tropical cyclone Dineo (16 February 2017), the Cape storm (7 June 2017), the 2017 Kwa-Zulu Natal (KZN) floods (10 October 2017), the 2019 KZN floods (22 April 2019), the 2019 KZN tornadoes (12 November 2019) and the 2020 Johannesburg floods (5 October 2020). Three configurations of CCAM were compared: a 9 km grid length (MN9km) over southern Africa nudged within the Global Forecast System (GFS) simulations, and a 3 km grid length over South Africa (MN3km) nudged within the 9 km CCAM simulations. The last configuration is CCAM running with a grid length of 3 km over South Africa, which is nudged within the GFS (SN3km). The GFS is available with a grid length of $0.25$°, and therefore, the configurations allow us to test if there is benefit in the intermediate nudging at 9 km as well as the effects of resolution on rainfall simulations. The South African Weather Service (SAWS) station rainfall dataset is used for verification purposes. All three configurations of CCAM are generally able to capture the spatial pattern of rainfall associated with each of the events. However, the maximum rainfall associated with two of the heaviest rainfall events is underestimated by CCAM with more than 100 mm. CCAM simulations also have some shortcomings with capturing the location of heavy rainfall inland and along the northeast coast of the country. Similar shortcomings were found with other NWP models used in southern Africa for operational forecasting purposes by previous studies. CCAM generally simulates a larger rainfall area than observed, resulting in more stations reporting rainfall. Regarding the different configurations, they are more similar to one another than observations, however, with some suggestion that MN3km outperforms other configurations, in particular with capturing the most extreme events. The performance of CCAM in the convective scales is encouraging, and further studies will be conducted to identify areas of possible improvement. Full article

To select plant species for particulate matter (PM) removal from urban environments, it is important to consider the plant species’ ecosystem (dis)services and environmental suitability in addition to their effectiveness in PM removal. In this study, 61 plant species were ranked for PM removal using three separate models: (i) leaf traits, (ii) leaf saturation isothermal remanent magnetization (SIRM), and (iii) ecosystem services and disservices. The plant species’ effectiveness in PM accumulation and the effective leaf traits were identified using leaf SIRM. In each model, plant species were assigned scores and weights for each criterion. The weighted average or the product (Π)-value was calculated for each plant species. The weighted average of each plant species was multiplied by the scores of leaf longevity and leaf area index (LAI) to scale up to a yearly basis and per unit of ground surface area. The preference ranking organization method for enrichment of evaluations (PROMETHEE) method was employed for the services and disservices model because of the lack of precise weights for the included criteria in the model. A scenario analysis was performed to determine a change in the ranking of plant species when the weights of the criteria were modified in the services and disservices model. The plant species with increased ecosystem services and reduced ecosystem disservices were Tilia cordata (Mill.), Tilia platyphyllos (Scop.), Alnus incana (L.), Acer campestre (L.), and Picea abies (L.). The findings of this study can be relevant to urban planners for recommending suitable choices of plant species for the development of urban green spaces. Full article

In the last few decades, excessive greenhouse gas emissions into the atmosphere have led to significant climate change. Many approaches to reducing carbon dioxide (CO₂) emissions into the atmosphere have been developed, with carbon capture and sequestration (CCS) techniques being identified as promising. Flue gas emissions that produce CO₂ are currently being captured, sequestered, and used on a global scale. These techniques offer a viable way to encourage sustainability for the benefit of future generations. Finding ways to utilize flue gas emissions has received less attention from researchers in the past than CO₂ capture and storage. Several problems also need to be resolved in the field of carbon capture and sequestration (CCS) technology, including those relating to cost, storage capacity, and reservoir durability. Also covered in this research is the current carbon capture and sequestration technology. This study proposes a sustainable approach combining CCS and methane production with CO₂ as a feedstock, making CCS technology more practicable. By generating renewable energy, this approach provides several benefits, including the reduction of CO₂ emissions and increased energy security. The conversion of CO₂ into methane is a recommended practice because of the many benefits of methane, which make it potentially useful for reducing pollution and promoting sustainability. Full article

The prediction of the total electron content (TEC) in the ionosphere is of great significance for satellite communication, navigation and positioning. This paper presents a multiple-attention mechanism-based LSTM (multiple-attention Long Short-Term Memory, MA-LSTM) TEC prediction model. The main achievements of this paper are as follows: (1) adding an L1 constraint to the LSTM-based TEC prediction model—an L1 constraint prevents excessive attention to the input sequence during modelling and prevents overfitting; (2) adding multiple-attention mechanism modules to the TEC prediction model. By adding three parallel attention modules, respectively, we calculated the attention value of the output vector from the LSTM layer, and calculated its attention distribution through the softmax function. Then, the vector output by each LSTM layer was weighted and summed with the corresponding attention distribution so as to highlight and focus on important features. To verify our model’s performance, eight regions located in China were selected in the European Orbit Determination Center (CODE) TEC grid dataset. In these selected areas, comparative experiments were carried out with LSTM, GRU and Att-BiGRU. The results show that our proposed MA-LSTM model is obviously superior to the comparison models. This paper also discusses the prediction effect of the model in different months. The results show that the prediction effect of the model is best in July, August and September, with the R-square reaching above 0.99. In March, April and May, the R-square is slightly low, but even at the worst time, the fitting degree between the predicted value and the real value still reaches 0.965. We also discussed the influence of a magnetic quiet period and a magnetic storm period on the prediction performance. The results show that in the magnetic quiet period, our model fit very well. In the magnetic storm period, the R-square is lower than that of the magnetic quiet period, but it can also reach 0.989. The research in this paper provides a reliable method for the short-term prediction of ionospheric TEC. Full article

Air pollution is still one of the biggest environmental threats to human health on a global scale. In urban environments, exposure to air pollution is largely influenced by the activity patterns of the population as well as by the high spatial and temporal variability in air pollutant concentrations. Over the last years, several studies have attempted to better characterize the spatial variations in air pollutant concentrations within a city by deploying dense, fixed as well as mobile, low-cost sensor networks and more recently opportunistic sampling and by improving the spatial resolution of air quality models up to a few meters. The purpose of this work has been to investigate the use of properly designed mobile monitoring campaigns along the streets of an urban neighborhood to assess the capability of an operational air dispersion model as SIRANE at the district scale to capture the local variability of pollutant concentrations. To this end, an IoT ecosystem—MONICA (an Italian acronym for Cooperative Air Quality Monitoring), developed by ENEA, has been used for mobile measurements of CO and NO₂ concentration in the urban area of the City of Portici (Naples, Southern Italy). By comparing the mean concentrations of CO and NO₂ pollutants measured by MONICA devices and those simulated by SIRANE along the urban streets, the former appeared to exceed the simulated ones by a factor of 3 and 2 for CO and NO₂, respectively. Furthermore, for each pollutant, this factor is higher within the street canyons than in open roads. However, the mobile and simulated mean concentration profiles largely adapt, although the simulated profiles appear smoother than the mobile ones. These results can be explained by the uncertainty in the estimation of vehicle emissions in SIRANE as well as the different temporal resolution of measurements of MONICA able to capture local high concentrations. Full article

As a result of rising environmental awareness, vehicle-related emissions such as particulate matter are subject to increasing criticism. The air pollution in urban areas is especially linked to health risks. The connection between vehicle-related particle emissions and ambient air quality is highly complex. Therefore, a methodology is presented to evaluate the influence of different vehicle-related sources such as exhaust particles, brake wear and tire and road wear particles (TRWP) on ambient particulate matter (PM). In a first step, particle measurements were conducted based on field trials with an instrumented vehicle to determine the main influence parameters for each emission source. Afterwards, a simplified approach for a qualitative prediction of vehicle-related particle emissions is derived. In a next step, a virtual inner-city scenario is set up. This includes a vehicle simulation environment for predicting the local emission hot spots as well as a computational fluid dynamics model (CFD) to account for particle dispersion in the environment. This methodology allows for the investigation of emissions pathways from the point of generation up to the point of their emission potential. Full article

The Indo Gangetic Plain (IGP) is a food basket of South Asia and is considered a hotspot for air pollution due to persistently high emissions of anthropogenic aerosols. High levels of aerosols in the IGP not only affect the health of people but also the health of the natural system and the climate of the region. Aerosol effects on crop production in the IGP is an emerging area of interest for policymakers and the scientific community due to their possible effect on the food security and livelihood of millions of people in the region. To investigate the effect of anthropogenic aerosols on wheat production in the eastern IGP, we used a calibrated and validated Agricultural Production System Simulator (APSIM) model at nodes in Bangladesh, India and Nepal, 2015–2017. The effects of anthropogenic aerosols on wheat production were examined by running the APSIM model under three conditions: firstly, the condition with anthropogenic aerosols, using the observed meteorological data; secondly, the condition without anthropogenic aerosols, considering only the radiative effect of anthropogenic aerosols (adding the reduced radiation due to anthropogenic aerosols on the observed data); thirdly, the condition without anthropogenic aerosols, considering the radiation as well as temperature effects (by adding the reduced solar radiation and temperature due to anthropogenic aerosols on the observed data). The study revealed that, on average, anthropogenic aerosols reduced the wheat grain yield, biomass yield, and crop evapotranspiration by 11.2–13.5%, 21.2–22%, and 13.5–15%, respectively, when considering the 2015–2017 seasons at the target sites of eastern IGP. The study also showed an average reduction of more than 3.2 kg per capita per annum of wheat production in the eastern IGP due to anthropogenic aerosols, which has a substantial effect on food security in the region. Moreover, the loss of wheat grain yield due to anthropogenic aerosols in the eastern IGP is estimated to be more than 300 million USD per annum during the study period, which indicates a significant effect of anthropogenic aerosols on wheat production in the eastern IGP. Full article

The dynamic evolution of particle size distributions (PSDs) during coagulation is of great importance in many atmospheric and engineering applications. To date, various numerical methods have been developed for solving the general dynamic equation under different scenarios. In this study, a radial basis function (RBF) method was proposed to solve particle coagulation evolution. This method uses a Gaussian function as the basis function to approximate the size distribution function. The original governing equation was then converted to ordinary differential equations (ODEs), along with numerical quadratures. The RBF method was compared with the analytical solutions and sectional method to validate its accuracy. The comparison results showed that the RBF method provided almost accurate predictions of the PSDs for different coagulation kernels. This method was also verified to be reliable in predicting the self-preserving distributions reached over long periods and for describing the temporal evolution of moments. For multimodal coagulation, the RBF method also accurately predicted the temporal evolution of a bimodal distribution owing to scavenging effects. Moreover, the computational times of the RBF method for these cases were usually of the order of seconds. Thus, the RBF method is verified as a reliable and efficient tool for predicting PSD evolution during coagulation. Full article

In the past, the Lorenz 1963 and 1969 models have been applied for revealing the chaotic nature of weather and climate and for estimating the atmospheric predictability limit. Recently, an in-depth analysis of classical Lorenz 1963 models and newly developed, generalized Lorenz models suggested a revised view that “the entirety of weather possesses a dual nature of chaos and order with distinct predictability”, in contrast to the conventional view of “weather is chaotic”. The distinct predictability associated with attractor coexistence suggests limited predictability for chaotic solutions and unlimited predictability (or up to their lifetime) for non-chaotic solutions. Such a view is also supported by a recent analysis of the Lorenz 1969 model that is capable of producing both unstable and stable solutions. While the alternative appearance of two kinds of attractor coexistence was previously illustrated, in this study, multistability (for attractor coexistence) and monostability (for single type solutions) are further discussed using kayaking and skiing as an analogy. Using a slowly varying, periodic heating parameter, we additionally emphasize the predictable nature of recurrence for slowly varying solutions and a less predictable (or unpredictable) nature for the onset for emerging solutions (defined as the exact timing for the transition from a chaotic solution to a non-chaotic limit cycle type solution). As a result, we refined the revised view outlined above to: “The atmosphere possesses chaos and order; it includes, as examples, emerging organized systems (such as tornadoes) and time varying forcing from recurrent seasons”. In addition to diurnal and annual cycles, examples of non-chaotic weather systems, as previously documented, are provided to support the revised view. Full article

The modern coal chemical industry is a typical high carbon emission industry, which has formed a large-scale development in China. In the context of carbon neutrality, it is considered to be an ideal combination mode that captures high-concentration CO₂ emitted by the modern coal chemical plants and transports it to oilfields through pipelines, which can both realize the low-carbon development goals of the modern coal chemical industry and reduce the cost of the whole process of Carbon Capture and Storage (CCS), as well as promote the development of CCS in China. Based on the data from modern coal chemical projects and depleted oil basins across China, a model of a pipeline network with optimal layout design was constructed, aiming to achieve specific emission reduction targets. Meanwhile, its economic effects will be analyzed. It turns out that this layout can help achieve an annual emission reduction of 280 million tons of CO₂, with an average annual net income of USD 2.20 billion, and a unit net income of USD 7.85 per ton of CO₂. A total of 166 pipelines up to 15,783 km in total length need to be built across China. Suitable storage sites can be found within an average radius of 94 km for emission sources. A total of 11,115 km of pipelines needs to be built in the “Three North” areas, accounting for 70.4% of the total pipeline length. Full article

We analyzed the C-structures in the mesospheric metal layers. We used two datasets: one from a narrow band Sodium (Na) Density and Temperature LIDAR and the other from a high-resolution dual band Na and Potassium (K) LIDAR, both operated at São José dos Campos, Brazil (23° S, 46° W). We also investigated the Es layer occurrence and wind shear influences forming these structures. We found three C-type events over 82 analyzed nights in the first data set. They all showed lower temperatures inside C-structures compared to the borders. The squared Brunt-Väissälä frequency analyses showed positive values in the region of C-structures. In two out of three cases, dynamical instability was present (Ri < 0.25). We compared these results with the nine simultaneous C-type events identified in the 185 nights from the second data set. They showed height and time simultaneity correspondence as observed in the Na and K layers. Our results showed a low correlation between Es occurrence and C-structures. Additionally, strong wind shears in the altitude and time where C-structures appeared were always present. The advection of a metal cloud to the LIDAR station and a wind distortion seems to be the plausible mechanism that can explain all the observations. Full article

Studies conducted in the early COVID-19 pandemic stages showed positive associations between chronic exposure to ambient air pollution and COVID-19 morbidity. Here, we examined the associations between populations’ chronic exposure to air pollutants (NO₂, CO, PM₁₀, PM_2.5, and SO₂), demographics, and vaccination rates, to COVID-19 morbidity rates in 280 Israeli municipalities during the Delta-variant-dominated morbidity wave of summer 2021. We found that COVID-19 morbidity was positively associated with chronic exposure to air pollutants, the municipality’s population density, total population size, and the rate of elderly people. Multivariate linear regression models showed similar trends: positive associations between COVID-19 rates and density, ratio of elderly people, and most air pollutants, and a non-significant link to COVID-19 vaccine second dose ratio. Our results emphasized the effects of chronic air pollution exposure on the spread of the pandemic and strengthen the urgent need for uncompromising policy for a dramatic reduction in air pollution. They also highlighted the vulnerable populations (elderly, densely populated municipalities) during the Delta morbidity wave. These findings could assist policy makers to better inform the public and manage health policies in future COVID-19 waves, hopefully leading to a reduced impact on health. Full article

This paper presents the Intertropical Convergence Zone (ITCZ) as the possible source mechanism of the medium-scale traveling ionospheric disturbances (MSTIDs) propagating to the southeast direction over the South American region. Using the data collected by the GNSS dual-frequency receivers network from January 2014 to December 2019, detrended TEC maps were generated to identify and characterize 144 MSTIDs propagating southeastward over the South American low-latitude and equatorial region. We also used images from the Geostationary Operational Environmental Satellite (GOES) 13 and 16 in the infrared (IR) and water vapor (WV) channel, and reanalisys data from the National Centers for Environmental Prediction (NCEP) of the National Oceanic and Atmospheric Administration (NOAA) to study the daily features and seasonal migration of ITCZ. In the winter, when ITCZ migrates to the northern hemisphere around 10–15° N, 20 MSTIDs propagated southeastward. During summer, when the ITCZ lies within the continent, around 0–5° S 80 MSTIDs were observed to propagate southeastward; in the equinoxes (spring and fall), 44 MSTIDs were observed. Again, the MSTIDs propagating southeastward showed a clear seasonality of their local time dependence; in summer, the MSTIDs occurred frequently in the evening hours, whereas those in winter occurred during the daytime. We also found for the first time that the day-to-day observation of ITCZ position and MSTIDs propagation directions were consistent. With regard to these new findings, we report that the MSTIDs propagating southeastward over the South American region are possibly induced by the atmospheric gravity waves, which are proposed as being generated by the ITCZ in the troposphere. The mean distribution of the horizontal wavelength, period, and phase velocity are 698 ± 124 km, 38 ± 8 min, and 299 ± 89 m s⁻¹, respectively. For the first time, we were able to use MSTID propagation directions as a proxy to study the source region. Full article

Automobile emissions in urban cities, such as Peru, are significant; however, there are no published studies of the effects of these emissions on PM_2.5 (fine particulate matter) formation. This study aims to analyze the contributions of vehicle aerosol emissions to the surface mass concentration of PM_2.5 in the Metropolitan Area of Lima and Callao (MALC), one of the most polluted cities in Latin America and the Caribbean (LAC) known to have high concentrations of PM_2.5. In February 2018, we performed two numerical simulations (control and sensitivity) using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). We considered both trace gasses and aerosol emissions from on-road traffic for the baseline simulation (hereinafter referred to as “control”); gasses without particulate emissions from vehicles were considered for the sensitivity simulation (hereinafter referred to as WithoutAerosol). For control, the model’s performance was evaluated using in situ on-ground PM_2.5 observations. The results of the predicted PM_2.5 concentration, temperature, and relative humidity at 2 m, with wind velocity at 10 m, indicated the accuracy of the model for the control scenario. The results for the WithoutAerosol scenario indicated that the contributions of vehicular trace gasses to secondary aerosols PM_2.5 concentrations was 12.7%; aerosol emissions from road traffic contributed to the direct emissions of fine aerosol (31.7 ± 22.6 µg/m³). Full article

There is a global trend toward intensive livestock breeding, which tends to increase the microbial load in the environment as well as the presence of volatile compounds and dust that can cause health issues. Cattle is the major producer of Escherichiacoli (E. coli), a group of foodborne bacteria associated with severe human diseases, and Neuquén province in Argentina has one of the highest rates of uremic hemolytic syndrome incidence in the world. This paper presents the results of two sampling events of E. coli bacteria at 39 sites in La Paisana ranch (LPR), in Añelo (Neuquén), considering locations inside the pens, upwind, and downwind of the feedlot with different time steps, using a Microflow α equipment. The ranch has approximately 600 heads and clean and controlled installations. The field experiment included sampling airborne aerosol deposition and concentration using passive and active methods. Concentrations were also estimated using an atmospheric dispersion model. During the field experiment, counts of up to 2970 CFU/m³ were obtained in the cattle stockyards and up to 111 CFU/m³ at a distance of 100 m. Full article

Based on the multi-data of the global ionospheric map (GIM), ionospheric total electron content (TEC) inversed from GPS observations, the critical frequency of the F2 layer (f_OF₂) from the ionosonde, electron density (Ne), electron temperature (Te), and He⁺ and O⁺ densities detected by the China Seismo-Electromagnetic Satellite (CSES), the temporal and spatial characteristics of ionospheric multi-parameter perturbations were analyzed around the Maerkang Ms6.0 earthquake swarm on 9 June 2022. The results showed that the seismo-ionospheric disturbances were observed during 2–4 June around the epicenter under quiet solar-geomagnetic conditions. All parameters we studied were characterized by synchronous changes and negative anomalies, with a better consistency between ionospheric ground-based and satellite observations. The negative ionospheric anomalies for all parameters appeared 5–7 days before the Maerkang Ms6.0 earthquake swarm can be considered as significant signals of upcoming main shock. The seismo-ionospheric coupling mechanism may be a combination of two coupling channels: an overlapped DC electric field and an acoustic gravity wave, as described by the lithosphere–atmosphere–ionosphere coupling (LAIC). In addition, in order to make the investigations still more convincing, we completed a statistical analysis for the ionospheric anomalies of earthquakes over Ms6.0 in the study area (20°~40° N, 92°~112° E) from 1 January 2019 to 1 July 2022. The nine seismic events reveal that most strong earthquakes are preceded by obvious synchronous anomalies from ground-based and satellite ionospheric observations. The anomalous disturbances generally appear 1–15 days before the earthquakes, and the continuity and reliability of ground-based ionospheric anomaly detection are relatively high. Based on the integrated ionospheric satellite–ground observations, a cross-validation analysis can effectively improve the confidence level of anomaly identification and reduce the frequency of false anomalies. Full article

A high-resolution (∼500 m) numerical model was used to study the reef and atoll wakes in the Xisha Archipelago (XA) during 2009. Statistical analyses of simulation data indicated strong cyclonic dominance in the mixing layer (above ∼35 m) and weak anticyclonic dominance in the subsurface layer (35∼160 m) for both eddies and filaments in the XA. The intrinsic dynamical properties of the flow, such as the vertical stratification and velocity magnitude, and the terrain of reefs and atolls had a significant effect on the asymmetry. Without considering the existence of reefs and atolls, the “background cyclonic dominance” generated under local planetary rotation ($f\approx 4.1\times {10}^{-5}$ s⁻¹) and vertical stratification (with mean Brunt–Väisälä frequency N = 0.02 s⁻¹ at 75 m) was stronger for filaments than eddies in the upper layer from 0∼200 m, and the larger vorticity amplitude in the cyclonic filaments could greatly enhance the cyclonic wake eddies. Furthermore, inertial–centrifugal instability induced selective destabilization of anticyclonic wake eddies in different water layers. As the Rossby number (Ro) and core vorticity (Burger number, Bu) decreased (increased) with the water depth, a more stable state was achieved for the anticyclonic wake eddies in the deeper layer. The stratification and slipping reefs and atolls also led to vertical decoupled shedding, which intensified the asymmetry. Full article

Earthquake-induced liquefaction is one of the main causes of levee breaches that can threaten human life and property. Conventionally, liquefaction hazard has been assessed in terms of the factor of safety $FoS$ against liquefaction which ignores the potential variability of groundwater table (GWT) due to precipitation events. A probabilistic methodology, taking into account these GWT variations over time, is therefore presented in this study to assess the liquefaction hazard of an earthen flood protection levee. A frequency analysis based on the Annual Maxima/Generalised Extreme Value (AM/GEV) approach is first used to characterize the distribution of GWT extreme values. The CPT-based method is then applied with the provided GWT scenarios to predict liquefaction and display the hazard curves. Assuming a single constant GWT estimate during an earthquake revealed a certain liquefaction hazard within a sandy layer. Considering GWT variations during earthquakes showed, however, that liquefaction is unlikely to occur with an $FoS$ threshold set at 1.0. These findings highlight: (1) the conservatism of the conventional approach that overestimates the liquefaction hazard, (2) the importance of the proposed probabilistic approach as a complementary tool for more reliable decision-making, and (3) the dependency of liquefaction hazard predictions on the degree of uncertainty in GWT estimates and $FoS$ threshold. Full article

On 21 May 2021 (UT), Yangbi Ms6.4 and Maduo Ms7.4 earthquakes occurred in mainland China. This paper analyzed the ionospheric perturbations possibly related to the earthquake, based on global positioning system (GPS) total electron content (TEC) and global ionosphere map (GIM) TEC data. We identified GPS TEC anomalies by the sliding quartile, based on statistical analysis. After eliminating the days with high solar activity levels and strong geomagnetic disturbances, the time series analysis of GPS TEC data showed that there were significant TEC anomalies from 5 to 10 May. TEC anomalies were mainly positive anomalies. We obtained the spatial and temporal distributions of TEC anomalies using natural neighbor interpolation (NNI). The results showed that the TEC anomalies were distributed in the seismogenic zone and surrounded the epicenters of the Maduo and Yangbi earthquakes, indicating that they may be related to the earthquakes. From the GIM TEC difference map, we found the TEC enhancement in the seismogenic zone and its magnetic conjugate area of the Maduo and Yangbi earthquakes at 10:00–12:00 (UT) on the 5 and 6 May. We discussed our results according to the lithosphere-atmosphere-ionosphere coupling mechanism. Finally, based our results, we suggested that the Yangbi and Maduo earthquakes may affect the ionosphere through seismogenic electric field and thermal anomalies generated during the process of lithosphere-atmosphere-ionosphere coupling. Full article

In recent years, ozone (O₃) concentration has shown a decreasing trend in the Beijing–Tianjin–Hebei (BTH) region in China. However, O₃ pollution remains a prominent problem. Accurate estimation of O₃ exposure levels can provide support for epidemiological studies. A total of 13 variables were combined to estimate short- and long-term O₃ exposure levels using the geographically weighted regression (GWR) model in the BTH region with a spatial resolution of 1 × 1 km from 2017 to 2020. Five variables were left in the GWR model. O₃ concentration was positively correlated with temperature, wind speed, and SO₂, whereas is was negatively correlated with precipitation and NO₂. Results showed that the model performed well. Leave-one-out cross-validation (LOOCV) R² for short- and long-term simulation results were 0.91 and 0.71, and the values for RMSE were 11.14 and 3.49 μg/m³, respectively. The annual maximum 8 h average O₃ concentration was the highest in 2018 and the lowest in 2020. Decreasing concentrations of major precursors of O₃ due to the regional joint prevention and control may be the reason. O₃ concentration was high in the southeast of the BTH region, including in Hengshui, Handan, Xingtai and Cangzhou. Full article

The purpose of space weather is the systemic study of the Sun–Earth system, in order to determine the impact of solar events on the electromagnetic environment of the Earth. This article proposes a new transdisciplinary approach of the Sun–Earth system based on the universal physical process of the dynamo. The dynamo process is based on two important parameters of the different plasmas of the Sun–Earth system, the motion and the magnetic field. There are four permanent dynamos in the Sun–Earth system: the solar dynamo, the Earth dynamo, the solar wind-magnetosphere dynamo, and the ionospheric dynamo. These four permanent dynamos are part of different scientific disciplines. This transdisciplinary approach links all of these dynamos in order to understand the variations in the Earth’s magnetic field. During a magnetic disturbed period, other dynamos exist. We focused on the ionospheric disturbed dynamo generated by Joule energy dissipated in the high latitude ionosphere during magnetic storms. Joule heating disrupts the circulation of thermospheric winds and in turn generates disturbances in the Earth’s magnetic field. This systemic approach makes it possible to understand magnetic disturbances previously not well understood. Full article

Understanding the water cycle change under a warming climate is essential, particularly the ocean to land moisture transport, which affects the precipitation over land areas and influences society and the ecosystem. Using ERA5 data from 1988 to 2020, the time series of moisture transport and the trend across the boundary of each continent, including Eurasia, Africa, North America, South America, Antarctic, Australia, and Greenland, have been investigated. The inflow and outflow sections of the moisture have been identified for each continent. The trends of moisture convergence over Eurasia, Africa, North America, and Antarctic are all positive, with the values of 2.59 ± 3.12, 2.60 ± 3.17, 12.98 ± 2.28, and 0.32 ± 0.47 (in 10⁶ kg/s/decade), respectively, but only the trend over North America is statistically significant at a 0.1 significance level. The moisture convergence trend of −0.59 ± 3.63 (in 10⁶ kg/s/decade) over South America is negative but insignificant. The positive trend of 0.10 ± 0.35 (in 10⁶ kg/s/decade) over Greenland is very weak. The precipitation, evaporation, and moisture convergence are well balanced at middle and low latitudes, but the combination of moisture convergence and evaporation is systematically lower than the precipitation over Antarctic and Greenland. Contributions of evaporation and moisture convergence (or transport) to the continental precipitation vary with the continent, but the moisture convergence dominates the precipitation variability over all continents, and the significant correlation coefficients between the anomaly time series of continental mean moisture convergence and precipitation are higher than 0.8 in all continents. Full article

To investigate the spatiotemporal patterns of fine particulate matter (PM_2.5) under years of control measures in China, a comprehensive analysis including statistical analysis, geographical analysis, and health impact assessment was conducted on millions of hourly PM_2.5 concentrations data during the period of 2017–2020 in six typical major urban agglomerations. During the period of 2017–2020, PM_2.5 concentrations in the Beijing–Tianjin–Hebei urban agglomeration (BTH-UA), Central Plains urban agglomeration (CP-UA), Yangtze River Delta urban agglomeration (YRD-UA), Triangle of Central China urban agglomeration (TC-UA), Chengdu–Chongqing urban agglomeration (CY-UA), and Pearl River Delta urban agglomeration (PRD-UA) decreased at a rate of 6.69, 5.57, 5.45, 3.85, 4.66, and 4.1 µg/m³/year, respectively. PM_2.5 concentration in BTH-UA decreased by 30.5% over four years, with an annual average of 44.6 µg/m³ in 2020. CP-UA showed the lowest reduction ratio (22.1%) among the six regions, making it the most polluted urban agglomeration. In southern BTH-UA, northeastern CP-UA, and northwestern TC-UA, PM_2.5 concentrations with high levels formed a high–high agglomeration, indicating pollution caused by source emission in these areas was high and hard to control. Atmospheric temperature, pressure, and wind speed have important influences on PM_2.5 concentrations. RH has a positive correlation with PM_2.5 concentration in north China but a negative correlation in south China. We estimated that meteorological conditions can explain 16.7–63.9% of the PM_2.5 changes in 129 cities, with an average of 33.4%, indicating other factors including anthropogenic emissions dominated the PM_2.5 changes. Among the six urban agglomerations, PM_2.5 concentrations in the CP-UA were most influenced by the meteorological change. Benefiting from the reduction in PM_2.5 concentration, the total respiratory premature mortalities in six regions decreased by 73.1%, from 2017 to 2020. The CP-UA had the highest respiratory premature mortality in six urban agglomerations. We suggested that the CP-UA needs more attention and stricter pollution control measures. Full article

There are multiple extreme events underway in the Arctic that are beyond previous records: rain in Greenland, Alaska weather variability, and ecosystem reorganizations in the Barents and the northern Bering Sea associated with climate change and sea-ice loss. Such unique extreme events represent a philosophical challenge for interpretation, i.e., a lack of statistical basis, as well as important information for regional adaptation to climate change. These changes are affecting regional food security, human/wildlife health, cultural activities, and marine wildlife conservation. Twenty years ago, the Arctic was more resilient to climate change than now, as sea ice had a broader extent and was three times thicker than today. These new states cannot be assigned probabilities because one cannot a priori conceive of these states. They often have no historical analogues. A way forward for adaptation to future extremes is through scenario/narrative approaches; a recent development in climate change policy is through decision making under deep uncertainty (DMDU). Full article

Air pollution is a global problem, which needs to be understood and controlled to ensure a healthy environment and inform sustainable development. Urban areas have been established as one of the main contributors to air pollution, and, as such, urban air quality is the subject of an increasing volume of research. One of the principal means of studying air pollution dispersion is to use computational fluid dynamics (CFD) models. Subject to careful verification and validation, these models allow for analysts to predict air flow and pollution concentration for various urban morphologies under different environmental conditions. This article presents a detailed review of the use of CFD to model air pollution dispersion in an urban environment over the last decade. The review extracts and summarises information from nearly 90 pieces of published research, categorising it according to over 190 modelling features, which are thematically systemised into 7 groups. The findings from across the field are critically compared to available urban air pollution modelling guidelines and standards. Among the various quantitative trends and statistics from the review, two key findings stand out. The first is that, despite the existence of best practice guidelines for pollution dispersion modelling, anywhere between 12% and 34% of the papers do not specify one or more aspects of the utilised models, which are required to reproduce the study. The second is that none of the articles perform verification and validation according to accepted standards. The results of this review can, therefore, be used by practitioners in the field of pollution dispersion modelling to understand the general trends in current research and to identify open problems to be addressed in the future. Full article

The coupling effects of sandstorm and dust from coal bases themselves can have a major impact on the atmospheric environment as well as on human health. The typical coal resource city of Wuhai in Inner Mongolia was selected in order to study these impacts during a severe sandstorm event in March 2021. Particulate matter (PM₁, PM_2.5 and PM₁₀) and total suspended particulate matter (TSP) samples were collected during the sandstorm event of 15–19 March 2021 and non-sandstorm weather (11–13 March 2021) and analyzed for their chemical composition. The concentrations of PM₁, PM_2.5, PM₁₀ and TSP in Wuhai city during the sandstorm were 2.2, 2.6, 4.8 and 6.0 times higher than during non-sandstorm days, respectively. Trace metals concentrations in particles of different sizes generally increased during the sandstorm, while water-soluble ions decreased. Positive matrix fraction (PMF) results showed that the main sources of particles during both sandstorm and non-sandstorm days were industrial emissions, traffic emissions, combustion sources and dust. The proportion of industrial emissions and combustion sources increased compared with non-sandstorm days, while traffic emissions and dust decreased. The backward trajectory analysis results showed that airflows were mainly transported over short distances during non-sandstorm days, and high concentration contribution source areas were from southern Ningxia, southeast Gansu and western Shaanxi. The airflow was mainly transported over long distances during the sandstorm event, and high concentration contribution source areas were from northwestern Inner Mongolia, southern Russia, northern and southwestern Mongolia, and northern Xinjiang. A health risk analysis showed that the risk to human health during sandstorm days related to the chemical composition of particles was generally 1.2–13.1 times higher than during non-sandstorm days. Children were more susceptible to health risks, about 2–6.3 times more vulnerable than adults to the risks from heavy metals in the particles under both weather conditions. Full article

Under the influence of space weather, abnormal disturbances in the ionosphere will distort the ionosphere model seriously and affect the global navigation satellite system negatively. This study analyzes the ionospheric activity characteristics and the ionospheric model performance in low latitude during a strong geomagnetic storm from 7 to 9 September 2017. The research goals are to determine the abnormal behavior of the ionosphere during the geomagnetic storm and to refine the ionosphere model in the low latitude. In the experiment, the vertical total electron content (VTEC) peak value at low latitudes caused by this geomagnetic storm was significantly higher than that on the geomagnetic quiet day, and the VTEC peak value increased by approximately 75%. In the main phase of the geomagnetic storm, the degree of VTEC variation with longitude is significantly higher than that of the geomagnetic quiet day. The VTEC variation trend in the northern hemisphere is more severe than that in the southern hemisphere. In the region where VTEC decreases with longitude, the VTEC in the northern hemisphere is higher than that in the southern hemisphere on the same longitude at low latitudes, and this phenomenon is not significantly affected by the geomagnetic disturbance of the recovery phase. During the geomagnetic storm, the daily minimum value of VTEC at different latitudes was basically the same, approximately 5 TECU, indicating that the nighttime VTEC of the ionosphere in low latitudes was weakly affected by latitude and geomagnetic storms. Geomagnetic disturbances during geomagnetic storms will lead to anomalous features of the “Fountain effect” in the ionosphere at low latitudes. In addition, this geomagnetic storm event caused the accuracy of spherical harmonics (SH), polynomial, and ICE models to decrease by 7.12%, 27.87%, and 48.56%, respectively, and caused serious distortion, which is negative VTEC values fitted by the polynomial model. Full article

Atmospheric methane (CH₄) is an important greenhouse gas that can reflect variations of CH₄ emissions and sinks. This study aimed to detect spatial and temporal variations of atmospheric CH₄ concentrations in China during 2003–2021 based on CH₄ column-averaged dry-air mole fraction (XCH₄) products from three satellites, namely, Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), Greenhouse Gases Observing Satellite (GOSAT), and Copernicus Sentinel-5 Precursor (S5P). The results revealed that XCH₄ observed from three satellites showed high agreement in spatiotemporal variations and demonstrated good consistency with ground station measurements. The correlation coefficients (r) between the three satellites were 0.72 and 0.73, and the correlation coefficients for the ground stations were 0.79, 0.66, 0.03, 0.21, 0.70, and 0.80. The spatial distribution of XCH₄ in China was generally high in the east and low in the west and close to that of CH₄ emissions, indicating that CH₄ emission sources dominated the spatial variations of atmospheric XCH₄. From 2003 to 2006, XCH₄ remained stable with an annual growth rate of 0.51 ppb·yr⁻¹ and then abruptly increased with an overall growth rate of 6.96 ppb·yr⁻¹. There were obvious seasonal changes in XCH₄, with peaks in autumn and summer and nadir in winter and spring. These seasonal variations of XCH₄ were related to CH₄ emissions from rice planting. Rice cultivation areas generally had high XCH₄ concentrations, and the growth cycle of rice plants significantly contributed to seasonal variations of XCH₄ in the main rice planting areas. These results provide scientific data that could encourage decision-makers to enact policies and processes to reduce methane emissions. Full article

Global Navigation Satellite System (GNSS) radio occultation (RO) provides plentiful sounding profiles over regions lacking conventional observations. The Gridpoint Statistical Interpolation (GSI) hybrid system for assimilating RO data is integrated in this study with the Model for Prediction Across Scales–Atmosphere (MPAS) to improve tropical cyclone forecasts. After the MPAS-GSI assimilation cycles, dynamical vortex initialization (DVI) that may effectively spin up the initial inner typhoon vortex through cycled model integration is implemented to improve the initial analysis fit to the best track position as well as maximum wind or pressure intensity for Typhoon Nepartak (2016) that moved northwestward toward southern Taiwan. During the cycling assimilation, assimilation with RO data improves the temperature and moisture analysis, and largely reduces the forecast errors compared to those without RO data assimilation. The two RO operators that assimilate local bending angle or refractivity produce similar analyses, but the temperature and moisture increments from bending angle assimilation are slightly larger than those from refractivity assimilation. The MPAS forecasts at 60-15 km resolution show that the typhoon track prediction is improved with RO data, especially using bending angle data. The reduction in track deviations is explained by the wavenumber-one potential vorticity budget for several forecasts associated with the track deflection near southern Taiwan. Assimilation of RO data has fewer impacts on the typhoon intensity forecast compared to the DVI that largely improves the initial and thus forecasted intensity of the typhoon but at the cost of a slightly degraded track. Use of the enhanced 3 km resolution in the typhoon path also further improved the forecasts with and without the DVI. The feasible performance of the MPAS-GSI system with the RO data impact is also illustrated for Typhoon Mitag (2019), that passed around northern Taiwan. Full article

This article presented a brief review of studies of the Earth’s ionosphere at the heights of the mesosphere and lower thermosphere by a method based on the creation of artificial periodic inhomogeneities (APIs) of the ionospheric plasma by high-frequency radiation from powerful thermal installations. APIs are created by a standing wave due to the interference between upward-propagating radio waves and those reflected from the ionosphere. API studies of the ionosphere were based on Bragg scattering of probing impulse signals from an artificial periodic structure. The method makes it possible to measure the parameters of the neutral and ionized components of the Earth’s atmosphere. Note that, despite the fact that the API method assumes an artificial perturbation of the ionospheric plasma, the parameters of the mesosphere and lower thermosphere are determined at the stage of inhomogeneity relaxation and characterize the undisturbed medium. To date, periodic inhomogeneities have been observed at the heating points of Zimenki and Sura ionospheric heating facility (SURA, Vasilsursk, Russia), Gissar (Tajikistan), Arecibo (Puerto Rico, USA), High Power Auroral Stimulation Observatory (HIPAS) and High Frequency Active Auroral Research Program (HAARP, Gakona, AK, USA), and European Incoherent Scatter (EISCAT, Tromso, Norway). Most of the API studies of the ionosphere were carried out at the SURA mid-latitude heating facility (56.1° N; 46.1° E). The review presented the main results of determining the parameters of the ionosphere and neutral atmosphere at altitudes of 60–120 km and studies of the atmosphere during sunrise and sunset events and solar eclipses. In fact, the review is far from a complete illustration of the possibilities of using the API method to study the mesosphere and lower thermosphere. Full article

Snow avalanches are one of the most devastating natural hazards in the highlands that often cause human casualties and economic losses. The complex process of modeling terrain susceptibility requires the application of modern methods and software. The prediction of avalanches in this study is based on the use of geographic information systems (GIS), remote sensing, and multicriteria analysis—analytic hierarchy process (AHP) on the territory of the Šar Mountains (Serbia). Five indicators (lithological, geomorphological, hydrological, vegetation, and climatic) were processed, where 14 criteria were analyzed. The results showed that approximately 20% of the investigated area is highly susceptible to avalanches and that 24% of the area has a medium susceptibility. Based on the results, settlements where avalanche protection measures should be applied have been singled out. The obtained data can will help local self-governments, emergency management services, and mountaineering services to mitigate human and material losses from the snow avalanches. This is the first research in the Republic of Serbia that deals with GIS-AHP spatial modeling of snow avalanches, and methodology and criteria used in this study can be tested in other high mountainous regions. Full article

The stratosphere contains haze rich in sulfuric acid, which plays a significant role in stratospheric chemistry and in global climate. Commercial aircraft deposit significant amounts of incomplete combustion products into the lower stratosphere. We have studied the stability of these incomplete combustion products to reaction with sulfuric acid, using a predictive model based on experimental reaction kinetics. We demonstrate that sulfuric acid chemistry is likely to be a significant component of the chemistry of organics in the stratosphere. We find that at least 25 of the 40 known incomplete combustion products from aviation fuel have lifetimes to reaction with aerosol sulfuric acid of at least months. We estimate that ~10⁹ kg of long-lived products could be deposited per year in the lower stratosphere. We suggest that the high molecular weight organic compounds formed as incomplete combustion products of commercial long-haul aviation could play a significant role in the stratosphere. Full article

Heat islands and warming temperatures are a growing global public health concern. Although cities are implementing cooling interventions, little is known about their efficacy. We conducted a literature review of field studies measuring the impact of urban cooling interventions, focusing on cooling centers, misting stations, cool pavements, and cool or green roofs. A total of 23 articles met the inclusion criteria. Studies of cooling centers measured the potential impact, based on evaluations of population proximity and heat-vulnerable populations. Reductions in temperature were reported for misting stations and cool pavements across a range of metrics. Misting station use was evaluated with temperature changes and user questionnaires. The benefits and disadvantages of each intervention are presented, and metrics for evaluating cooling interventions are compared. Gaps in the literature include a lack of measured impacts on personal thermal comfort, limited documentation on intervention costs, the need to standardize temperature metrics, and evaluation criteria. Full article

One of the greatest issues nowadays is that of the urban heat island effect on the thermal conditions inside cities. The air temperature inside the city core is warmer than that in suburbs, thus deteriorating the quality of life for citizens and making outdoor spaces uncomfortable in terms of thermal comfort. This phenomenon is usually assessed in large scale cities worldwide and less often in medium-sized towns. The current study aimed to investigate the urban heat island effect and, therefore, to assess the outdoor thermal comfort conditions in a medium-sized city. More specifically, the methodology of the current study includes: (i) the combination of different monitoring techniques to quantify the urban heat island effect in a medium-sized Mediterranean city. Both in situ measurements and remote sensing techniques were applied to assess the urban heat island effect in terms of both the canopy layer (CUHI) and the surface (SUHI); (ii) the identification of the parameters that affect thermal comfort and the identification of the most appropriate bioclimatic indices that determine outdoor thermal comfort in the city of interest. Both questionnaire survey and in situ measurements took place on a sidewalk in the city of Xanthi, Northern Greece, during the summer. The CUHI effect was obvious, especially in the morning and afternoon. Downscaled MODIS satellite images also showed that the intensity of SUHI was higher in the morning and afternoon. Apart from air temperature, important differences in the values of most microclimatic parameters were recorded between the meteorological station placed inside the urban area and those gathered from a nearby meteorological station. The narrow roads, the thermal properties of construction materials, and the absence of greenery characterized the area of interest and may be the key factors creating these differences in climate. Concerning the thermal comfort assessment, the most significant parameters were the air temperature and solar radiation, although, both empirical and direct indices were found to describe the comfort values well. According to the results, downscaling techniques are also important for the SUHI effect to be investigating in detail in medium-sized urban environments. Full article

The detection and prediction of sea clutter power is the basis of inversing atmospheric duct. At present, the technology of atmospheric duct within radar detection range is relatively perfect, but the long-distance inversion of atmospheric duct is limited by radar detection range, and the prediction of the echo power of the measured sea clutter is the basis of long-distance inversion of atmospheric duct. Based on the theory of weighted Markov model and grey Markov model, a weighted grey Markov model is constructed, and the sliding method is introduced to establish the sliding weighted grey Markov model. The relative error between the measured sea clutter power and predicted values of the above four models is calculated and analyzed using the experimental data collected. The results show that the sliding weighted grey Markov model has better accuracy not only in short-range prediction but also in long-distance prediction, which could provide data support for inversing atmospheric duct. Full article