Environ. Sci. Proc., 2023, ECAS 2023

This study performs a sensitivity analysis of strong cyclone track deflection over isolated topography, exploring the impacts of vortex impinging direction and strength. A dynamic model investigates track adjustments of cyclonic vortices on a β-plane. The study derives a meridional adjustment velocity (MAV) for vortex motion and examines variations in track patterns under different flow conditions. Results reveal an S-shaped pattern in most tracks and significant deflections when the vortex passes over high-rise terrain. Larger direction angles of the vortex result in more pronounced deflections attributed to the terrain loop effect induced by the strong topographic β effect. Adjacent vortex paths impinging from the south converge on the leeward side, improving prediction accuracy, while vortices crossing from the north diverge, reducing prediction accuracy. This study offers valuable insights into uncertainties associated with path prediction. Full article

Tropospheric ducts are an abnormal condition of the atmosphere that affects the propagation of electromagnetic waves, which has a direct impact on the performance of various radio systems, including mobile telephony, which is especially sensitive to these interferences in communications. In Cuba, there is only one investigation to date focused on the formation of tropospheric ducts. Therefore, studying this topic and its relationship with atmospheric weather is novel. Knowing what meteorological situations lead to the formation of these communications interference events allows us to alert the relevant authorities and take appropriate measures in time. In this study, we investigated the use of numerical model outputs for the detection of the occurrence of tropospheric ducts. Based on an ERA5 reanalysis (which was feasible for the development of the research) we determined the characteristic atmospheric parameters enabling the formation of the tropospheric ducts, as well as the conditions of synoptic scale that favor their appearance. The first result revealed that the mean thickest ducts (between 75 m and 80 m) are seen more frequently in the March–May quarter, while in September and October these values are reduced by half, oscillating between 40 m and 45 m. In another analysis, we determined that the presence of stable atmospheric conditions in combination with a humid layer at low levels favors the appearance of this phenomenon. Therefore, days with a predominance of subtropical high pressures in combination with the passage of tropical waves through the seas south of the island of Cuba, or with the arrival of migratory anticyclones, guarantee this stability in addition to surface relative humidity values close to 80%. Full article

Recent studies have suggested that there is a dynamic connection between the Atlantic Meridional Overturning Circulation (AMOC) and the North Atlantic subpolar gyre (SPG). This modeling study uses a fully coupled atmosphere–ocean–sea ice Earth system model to investigate the SPG dynamics throughout the past twenty-two thousand years. We found that the variations in the SPG and AMOC strength are synchronized. Consequently, during cold events in the Northern Hemisphere, the SPG strength declined simultaneously with the AMOC strength and with shallower mixed layer depths, which reduced the northward meridional heat transport and increased Atlantic sea ice coverage. Full article

The Mediterranean is recognized as one of the most sensitive regions regarding climate change. The northern sector winds are a dominant feature of summer low-tropospheric circulation over the Aegean basin in the eastern Mediterranean (EMed). This study is an updated assessment that uses state-of-the-art tools in order to investigate the projected changes in the meridional wind speed and Etesian regime during summer period (June-July-August) over the 21st century. The analysis is based on 17 Global Climate Models simulations (GCMs) available from Coupled Model Intercomparison Project Phase 6 (CMIP6) covering the historical period (from 1971 to 2014) and the future period (from 2015 to 2100) under two Shared Socioeconomic Pathways (SSPs), an intermediate-, and a very high-emission scenario (SSP2-4.5 and SSP5-8.5). Additionally, the results from GCMs analysis are compared to ERA5 reanalysis for the historical period from 1971 to 2000. Our findings suggest that the majority of GCMs reproduce the spatial pattern of Etesians but underestimate the meridional wind speed by about 0.5 to 1.0 m/s, as compared to ERA5. During the future period, the meridional wind speed is projected to be increased over the Aegean basin, mainly during the last period of 21st century. Findings show that the majority of GCM simulations (12 out of 17) show an increase in meridional wind speed of about 0.2 to 1.4 m/s for SSP5-8.5 and 0.2 to 0.6 m/s for SSP2-4.5, as compared to historical period from 1971 to 2000. Full article

Temperature, as one of the most important factors in meteorological data analysis, is a variable parameter with severe changes in different periods. The trend of temperature changes over time is also particularly important to investigating climate change. In this research, using the data from the TRY Project, which includes meteorological data with an accuracy of 1 km grid and a time accuracy of 1 hour, the temperature parameter of the city of Berlin is selected and the average temperature of the urban area of Berlin was calculated at different temporal scales. In addition to finding the linear regression trend of average annual temperature increase, Fourier transforms analysis and the least squared error fitting method was used to investigate harmonic temperature fluctuations to find the main sinusoidal period. Further, with the statistical analysis of data in daily averages and 1 h intervals by considering medians of data as the benchmark for classification, months from April to October were determined as the hot months of the year, and hours from 9 to 19 were determined as daytime. Based on the mentioned classification, it was found that while the median difference between hot and cold months is more than 12 °C, the median difference between days and nights for the hot and cold months’ data is 5.2 °C and 2.1 °C, respectively. With this classification, the probability distribution of temperature was studied for each group, and the degree of similarity of this distribution with probability distribution functions such as normal, beta, gamma, and cosine, were investigated. The separate analysis of the data categorized by this method had the highest degree of similarity with beta and normal functions. Full article

The high-resolution long-term hydrometeorological “COSMO-CLM Russian Arctic hindcast” based on nonhydrostatic regional atmospheric model COSMO-CLM v.5.06 for the 1980–2016 period covering the North Atlantic, Barents, and Kara and Laptev Seas with ~12 km grid size was utilized to estimate climatological trends of extreme wind speed. In this study, we used the 10 m wind speed data from 95 Russian weather stations inside the hindcast domain. Trends in mean, maximal, 0.90, 0.95, 0.99 quantiles wind speed values, and occurrences of wind speed above 20, 25, 30, and 33 m/s were calculated for all stations and corresponding nearest model grids for yearly data and data from four months of the calendar year (January, April, July, and October). Yearly mean wind speed and quantiles values were observed to increase over the northern Kara Sea, while decreases were observed over the western Barents Sea and northern Atlantic. Extreme wind speeds were observed to increase in January in the eastern Evenkia and northern Yakutia, while declining was observed over north-eastern European Russia. The 0.99 quantile values increased in July near the Gyda peninsula coastline, but decreased over polar regions, the Pechora Sea, and the White Sea coastline. Maximal wind speed declined in October over north-western European Russia, eastern Taymyr, and the Norway Sea, but grew over the Eastern Siberian Sea. Full article

In recent years, by expanding cities, air pollution has become one of the most important problems caused by humans. Tehran, as the capital of Iran, is expanding gradually and its population is rising day by day. Therefore, the increase in human activities causes many problems, such as air pollution, in this area. In this study, data from Sentinel-5 for Tehran city are used from the last month of 2018 to present and collected from the Google Earth Engine. Three main parameters of air pollution are studied, including aerosol, ozone and CO. Different statistics of each parameter are calculated. Then, temporal evolutions are analyzed using Statgraphics. From the analysis, the calculated aerosol median is −0.555 mol ${\mathrm{m}}^{-2}$ and the interquartile range is 1.248 mol ${\mathrm{m}}^{-2}$. For the ozone parameter, the median is calculated to be 0.131 mol ${\mathrm{m}}^{-2}$ and the interquartile range is 0.015 mol ${\mathrm{m}}^{-2}$. Also, for the CO parameter, the median is 0.037 mol ${\mathrm{m}}^{-2}$ and the interquartile range is 0.011 mol ${\mathrm{m}}^{-2}$. The total trend of aerosol is increasing, especially during the summer months, when aerosol amounts are higher than in the winter months. Our statistics show a decreasing trend for the ozone parameter, but in the winter months, ozone is higher than in the summer months. The trends for aerosol and ozone are statistically significant at the 95% confidence level. The trend of CO is totally stable but a little higher at the end of fall and during the first days of winter. Full article

The scope of this study is an attempt to develop an automated visualization module to monitor rainfall and hail estimations in real-time, highlighting areas with potential risk from extreme weather phenomena. The rainfall/hail products are provided by a known satellite-based algorithm that uses exclusively Meteosat multispectral images. The application is fully automated, written in the Python programming environment using open-source libraries, and provides colored graphs about the spatial variation of the examined parameters with the same temporal resolution as the Meteosat imagery. Additional functions of this application include warnings for extreme situations each time predefined threshold values are exceeded, as well as geographical areas that are vulnerable to heavy rainfall and/or hail occurrences. This application is a pilot operating over the Greek periphery. Also, there is a capability to create small video animations for the spatiotemporal evolution of the rainfall and hail estimations up to 6 h before the latest available satellite images. Full article

In recent years, computational fluid dynamics (CFD) has become a method widely used by the scientific community to study the dispersion of air pollutants in urban areas. This article analyzes the effectiveness of computational fluid dynamics models and their validation methods used to estimate pedestrian exposure to traffic-related air pollutants. This work proposes an exploratory methodology based on a literary review. A total of 28 articles were selected and analyzed from 455 articles published in the Scopus database in 2018–2023. The results show the effects of meteorological variables, such as wind speed and wind direction, on the dispersion of pollutants, especially the effects demonstrating that, at higher wind speeds, they tend to disperse more quickly, which reduces the concentration of these pollutants at the level of the pedestrian respiratory zone. Computational fluid dynamics is an advantageous tool; however, it is necessary to complement it with other models that consider the physical activity of people and thus more precisely evaluate the effect of inhaled pollutants on the entire respiratory system of pedestrians. Full article

The air quality of the Himalayan region of India is deteriorating due to the increasing load of particulate matter that is emitted from various local and regional sources, as well as to the transit of dust-related pollutants from the Indo-Gangetic Plain (IGP) and surrounding areas. In this study, the mineralogical characteristics of coarse mode particulate matter (PM₁₀) was analyzed using the X-ray diffraction (XRD) technique from January to December 2019 over Nainital (29.39° N, 79.45° E; altitude: 1958 m above mean sea level), a central Himalayan region of India. XRD analysis of PM₁₀ samples showed the presence of clay minerals, crystalline silicate minerals, carbonate minerals, and asbestiform minerals. It was shown that quartz minerals with significant levels of crystallinity were present in all the samples. Other minerals that are contributing to the soil dust were also observed in the analysis (CaFe₂O₄, CaCO₃, CaMg(CO₃)₂, calcium ammonium silicate hydrate (C-A-S-H), gypsum, kaolinite, illite, augite, and montmorillonite). The minerals ammonium sulphate, hematite, and magnetite were also found in the samples and are suggested to be from biogenic and anthropogenic activities, including biomass burning, fuel combustion, vehicle exhaust, construction activities, etc. This study indicated that the majority of the minerals in PM₁₀ that were present in this Himalayan region are from soil/crustal dust. Full article

On the basis of a long-term analysis (2013–2021), we report the inter-annual and seasonal concentrations and possible sources of trace elements (TEs) in PM_2.5 over Delhi, India. In all the PM_2.5 samples, 19 major and trace elements were extracted: Na, Al, Fe, Ti, Mg, Cu, Zn, Cr, Mn, Ni, As, Mo, Cl, P, S, Ca, K, Pb, and Br. The total annual mean concentration (∑El in PM_2.5) of major and trace elements was 17.4 ± 3.1 µg m⁻³, accounting for 13.9% of PM_2.5. The enrichment factor (EF) and IMPROVE model analysis indicate the seasonal abundance of mineral/soil dust (Fe, Al, Ti, Na, Ca, and Mg) at the sampling location of Delhi. During the sampling period, the highest loading of trace elements was recorded in 2015 (19% of PM_2.5) and the lowest in 2020 (9% of PM_2.5), possibly due to limited activity during COVID-19 lockdown/unlock times. The major sources of elements (in PM_2.5) were extracted by a principal component analysis (PCA) as crustal/soil/road dust, vehicular traffic/industrial emissions, combustion (solid + fossil fuels), and sodium magnesium salts in Delhi. Full article

Wave phase difference is a fundamental property that characterises the relative behaviour of transmitted signals. It has significant roles in signal wave analysis and in interpreting various propagation phenomena, which are crucial when designing wireless links and various applications in signal processing techniques, optics, and acoustics. This study investigated the concept of phase difference significance based on high frequencies (i.e., 1.0, 2.4, 10.0, and 20.0 GHz). Several phase difference models and their shortcomings were reviewed to emphasise the need for greater accuracy and precision in quantifying phase differences. The outcomes revealed that 1 GHz contributed to the lowest phase difference among the other frequencies. A constructive signal may be deployed to provide a better link build-up. Overall, determining the importance of phase difference in GHz and identifying the signal attitude substantially contribute to the advancement of wave analysis, while simultaneously encouraging further exploration in this domain. Full article

The increased concentration of pollutants is a challenge to the health of the population. This work aims to investigate the health risk that is related to the pollutants’ level in the center of Rhodes city. Rhodes Island is a desirable tourist destination with important economic activity over the southeastern Aegean Sea. This analysis covers the (summer) July–August months and the (winter) December month of 2022. Hourly recordings of the concentrations of PM_2.5, NO₂ and O₃ from a mobile air quality monitoring system (AQMS) are analyzed. In order to investigate the effects of pollution level on people’s health, the Air Quality Health Index (AQHI) is calculated. Results show that summer shows an increased health danger compared to winter period, possibly due to increased traffic emissions, tourist density and the different meteorological conditions. In the summer period, the AQHI is classified between the middle and upper-medium health risk class. During the winter month, AQHI is mainly classified in the low-medium health risk class. The summer shows increased health risk despite the AQHI diurnal variability being lower when compared to December. Additionally, the diurnal differences between the two periods show an increased health risk in the summer period for the majority of the hours. Finally, this analysis shows that traffic activities possibly affect the health risk and also highlights that the authorities should adopt green policies to protect human health and the environment. Full article

We examine several different features of DSDs based on data and observations from two mid-latitude coastal locations: (a) the Delmarva peninsula, USA, and (b) Incheon, South Korea. In each case, the full DSD spectra were obtained from two collocated disdrometers. Two events from location (a) and one event from location (b) are presented. For (a), observations and retrievals from NASA’s S-band polarimetric radar are included in the analyses as well as retrieved DSD parameters from the dual-wavelength precipitation radar onboard the Global Precipitation Measurement satellite. For (b), the disdrometer-based DSD data are compared with measurements from another sensor. Our main aim is to examine the underlying shape of the DSDs and their representation by the generalized gamma model. Full article

In this work, the single-walled carbon nanotubes (SWCNTs) were filled with cobaltocene. The growth properties of individual chirality nanotubes were studied with Raman spectroscopy. It was shown that the larger nanotubes grow slower. The growth of inner nanotubes becomes faster with increasing annealing temperature. These results are of high importance as they stimulate research on carbon nanotubes, and bring ideas from laboratories into factories. Full article

Delhi is one of the most densely populated megacities in the world, and it is experiencing deteriorating air quality due to rapid industrialization and excessive use of transportation. The limited emission control measures in Delhi have led to worsening air quality problems, which have become a serious threat to human health and the environment. In the present study, we investigate the long-term (2011–2021) interrelationship between air pollutants and the vegetation index using satellite datasets. Air pollutant data viz. nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) were obtained from NASA’s Aura satellite called the Ozone Monitoring Instrument (OMI)Additionally, the data for carbon monoxide (CO) and particulate matter 2.5 (PM_2.5) were obtained from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) model. The vegetation indices, i.e., the normalized difference vegetation index (NDVI) and the enhanced vegetation oxide (EVI), were collected from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. The analysis of both datasets revealed higher concentrations of air pollutants in the summer months when the NDVI and EVI were minimal. Furthermore, a higher pollution load was observed in the months of October–January when the NDVI and EVI were lower. Furthermore, we also investigated the spatial patterns of PM_2.5 and other gaseous pollutants (viz. CO, SO₂, and NO₂) and observed that their levels were lower in the vegetated region in comparison to the sparsely vegetated area of Delhi. The present study indicates that vegetation could ameliorate various air pollutants; however, it needs to be validated with ground observed data. Full article

Volcanoes are not traditionally considered to be significant sources of black carbon particles for the stratosphere. The main reason for this well-established view is the absence of appreciable traces of black carbon in volcanic emissions. Recently, a new hypothesis of the formation and injection of nanodisperse carbon into the stratosphere during explosive volcanic eruptions due to the transformation of carbon-containing volcanic gases into black carbon particles was proposed. Critical analysis of this hypothesis and new observational data have shown that it does not contradict the existing ideas about the principal possibility of the process but can and should be substantially supplemented and corrected. The data on the detection of carbon particles in the stratosphere and in volcanic ash confirm the possibility of the formation of the predicted particles and their identity with particles formed by known technological processes and found after powerful volcanic eruptions in Kamchatka (Russia). The main limiting factors determining both the possibility and the lower boundary of the conditions for the formation of particles of different types of black carbon have been identified: temperature and concentration of carbon-bearing gases in the volcanic column. For Plinian-type eruptions, these parameters appear to be insufficient for the formation of black carbon particles in appreciable amounts and their accumulation in the stratosphere, which contradicts the previously mentioned hypothesis. Virtually, all of the black carbon produced must remain in volcanic ash and volcanic sediments. Full article

The layer of the Earth’s atmosphere known as the ionosphere presents a significant obstacle to global satellite navigation systems (GNSS) due to its ability to introduce errors. To address this challenge, various navigation systems have introduced new signals designed to minimize the errors caused by the ionosphere. These signals not only aid in error reduction but also facilitate the examination of electron content behavior. This study focuses on the analysis of vTEC plots obtained from RINEX data collected at the INEG station in Aguascalientes, Mexico, from 2011 to 2018, with a particular emphasis on highly intense geomagnetic storms characterized by values below −100 nT. Our analysis of these plots employed the Probability Density Function (PDF), which allows for the graphical representation of data distribution. This distribution is then examined in conjunction with the station’s Total Electron Content (TEC) values and the Dst index during the corresponding geomagnetic storm events. The findings establish the correlation between each of these parameters during such events. Full article

Air pollution caused by biomass burning is the main environmental concern in Mozambique. This paper investigates the effect of biomass combustion on air quality, focusing on the sources of pollution, pollutants released, and health and environmental consequences. The substantial reliance on biomass for cooking, heating, and energy generation causes high levels of air pollution from the combustion of wood, agricultural residues, and charcoal. During biomass burning, particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NO_x), volatile organic compounds (VOCs), and hazardous air pollutants (HAPs) are emitted, resulting in health hazards and contributing to climate change. Mozambique can considerably improve air quality, safeguard public health, and contribute to sustainable development by using cleaner cooking technology, supporting sustainable biomass management practices, and raising awareness. Full article

A comprehensive study was executed within the urban vicinity of Kenitra city, covering the period from 2020 to 2021. During this study, 60 effective PM_2.5 samples were collected in a period of 24 h using a dichotomous sampler and Nuclepore track-etched polycarbonate filters with a diameter of 37 mm. Ion chromatography was employed to identify the composition of our samples, including Cl⁻, SO₄²⁻, F⁻, NO₃⁻, NH₄⁺, Na⁺, Ca²⁺, and K⁺. The results showed that the average mass concentration (± standard deviation) of the seven ions in PM_2.5 was 3.2 ± 1.3 µg/m³, constituting approximately 18% of the total mass concentration. Among the ions, the concentrations followed the order of Na⁺ > SO₄²⁻> Cl⁻ > NO₃⁻> K⁺ > NH₄⁺ > F⁻. The predominant constituents of water-soluble ions in PM_2.5 were detected to be secondary inorganic species (NH₄⁺, SO₄²⁻, and NO₃⁻), contributing an average of 44% to the total PM_2.5 ions. Throughout the four seasons, the concentrations of these three ions exhibited variability, with the greatest levels observed in spring, followed by summer, fall, and winter. The ratio of [NO₃⁻]/[SO₄²⁻] was found to be almost equal to unity, indicating that the primary sources of nitrogen and sulfur in the Kenitra atmosphere were prioritized from stationary sources (typically associated with power plants, industrial and commercial activities, and other large-scale facilities). Full article

Exposure to chemicals in many occupational and environmental settings has the capacity to significantly disturb the commensal microbiota that symbiotically reside in humans. However, much more is known about gut microbiota (GM) than lung microbiota (LM) due to the challenges of collecting LM samples. The advent of culture-independent methodologies has revealed the complex and dynamic community of microbes harbored by the respiratory tract. It is now being recognized that LM can directly impact immunity in a manner that can result in disease. Significant differences in community composition and diversity have been shown between the LM of diseased lungs and those of healthy subjects. Studies have linked LM dysbiosis with human diseases such as idiopathic pulmonary fibrosis, lung inflammation, chronic obstructive pulmonary disease (COPD), asthma, and lung cancer. However, it is not known whether LM dysbiosis initiates/promotes disease pathogenesis or is merely a biomarker of disease. Many chronic lung diseases often occur together with chronic GIT diseases in what is termed as the gut–lung axis. The LM also affects the CNS, in the bidirectional lung–brain axis, through a number of potential mechanisms that include the direct translocation of micro-organisms. Chemically induced LM dysbiosis appears to play a significant part in human diseases as has been shown to arise due to air pollution, cigarette smoking, and the use of chemical antibiotics. Full article

The fashion industry is one of the world’s largest and third most polluting industries. It produces a carbon footprint of around 10% annually, which is much higher than the footprint produced by flights and shipping. Nowadays, there is an increase in demand for different and new products for people of all ages due to which fast-changing fashion is becoming a trend. But there is a hidden cost in the manufacturing of each material, which is ignored by people and which costs the environment and eventually the health of people. It not only pollutes the air due to the emission of greenhouse gases but also consumes plenty of water along with an increase in plastic and some other waste that pollutes our environment. The solution to the problem is to avoid and move away from this fast fashion trend and subsequently buy a few items of clothing that are good in quality and do not pose a threat to the environment. But this will lower the sales as well as the revenue of the fashion industry, which will eventually affect our economy. The purpose of this study is to construct a novel fractional mathematical programming model that caters to both objectives, i.e., minimizing environmental pollution and maximizing the revenue of the fashion industry with respect to the constraints based on the industry and environment. Full article

Air pollution is a serious issue in most parts of Bihar, especially in its capital city, Patna. The air quality in Patna has significantly worsened due to factors like rapid urbanization, increased traffic, and various natural and human-related causes. This decline in air quality has led to several negative health effects. In light of this, the aim of this study was to examine how air pollution affects the long-term health of Patna’s residents, taking into account age and exposure time as important factors. We gathered data from one busy intersection in Patna, specifically Danapur. Health effects from air pollution were collected from the residents via a formatted questionnaire. To analyze the relationship between age, exposure time, and the health effects reported by the participants, we used a statistical test called the chi square test of independence. The findings of the study revealed a clear link between age, exposure time, and the health status of the participants. We concluded that older individuals and those with longer exposure times faced a higher risk associated with the increasing air pollution levels. This study provides a foundation for raising awareness among both authorities and the general public of the adverse health impacts associated with declining air quality, emphasizing the urgency in taking appropriate measures to counter this challenge. Full article

The occurrence of earthquakes, which can strike suddenly without any warning, has always posed a potential threat to humanity. However, researchers worldwide have been diligently studying the mechanisms and patterns of these events in order to develop warning systems and improve detection methods. One of the most reliable indicators for predicting large earthquakes has been the examination of electron availability in the ionosphere. This study focuses on analyzing the behavior of the Total Electron Content (TEC) in the ionosphere during the 30-day period leading up to the three most devastating earthquakes of the past decade. Specifically, the data were examined from the cGPS stations closest to the epicenters: MERS for the Turkey earthquake with 7.8 Mw on 6 February 2023, CHLM for the Nepal earthquake with 7.8 Mw on 25 April 2015, and MIZU for the Japan earthquake with 9.1 Mw on 11 March 2011. Notable positive and negative anomalies were observed for each earthquake, and the vertical Total Electron Content (vTEC) for each PRN (pseudo-random number) was plotted to determine the specific time of the TEC anomaly. The spatial distribution of vTEC for the anomalous specific time revealed that the anomalies were in close proximity to the earthquake epicenters, particularly within denser fault zones. Full article

In Cuba, short-term predictions have been developed for wind speed in the Gibara wind farms. These predictions present an mean absolute error (MAE) that sometimes exceeds 3 m/s. This study aims to verify the wind forecast generated by SisPI using the Synoptic Situation Types Catalog (TSS), a form of wind speed observation data provided by the anemometers installed in the wind turbine. The study period spanned from May 2020 to April 2021. For the evaluation, the metrics root mean square error (RMSE) and MAE were used, and the analysis was made in the rainy and dry seasons via the methodology developed by Patiño (2023). The results indicate that subtype 3 (extended undisturbed anticyclonic flow) had the highest frequency of cases between very good and good in both seasonal periods. Subtype 19 (migratory anticyclone in an advanced state of transformation) was the system that produced the worst results in the dry season, with the largest number of cases of bad wind speed forecasts. The results of the statistical bias (BIAS) and Pearson’s Correlation Coefficient (R) were very favorable. Full article

Conducted by the nonprofit organization Breathe Mongolia—Clean Air Coalition, this study investigated ambient air pollution in Ulaanbaatar, focusing on the significant role of coal briquette combustion within ger areas. This combustion not only contributes to outdoor air pollution but also significantly degrades indoor air quality within these traditional dwellings, leading to substantial health concerns. To address this challenge, the study assessed indoor air pollution in gers—traditional Mongolian yurts—that had implemented Cooking, Heating, and Insulation Packages (CHIP), a program offering subsidized electrical heating, cooking, and insulation materials. The study encompassed 28 gers, among which 25 were equipped with CHIP while 3 were not, enabling a comparative analysis. Employing cost-effective technology, carbon monoxide levels were monitored across all 28 gers using Binary System monitors. Fine particulate matter concentrations were measured using AirVisual monitors in 14 of these gers. Data collection occurred during the winter of 2022–2023. To comprehensively assess indoor air quality within gers and ascertain the efficacy of interventions like CHIP in diminishing indoor air pollution, Breathe Mongolia intends to continue monitoring efforts within ger areas. These initiatives strive to address data gaps and inform strategies aimed at enhancing indoor air quality. Full article

The variability of the North Atlantic Subtropical High and its influence on the behavior of tropical cyclogenesis are characterized and analyzed. The database of the Center for Environmental Prediction and the Center for Atmospheric Research was consulted for the months of May to October between 1950 and 2019. The variables used were the central pressure to determine the position of the North Atlantic Subtropical High on the surface and the geopotential to obtain the position of the anticyclonic center at 850 hPa, as well as the geopotential at 500 and 200 hPa over the region of the anticyclone on the surface. This system weakens at the surface level and intensifies at other tropospheric levels. The relationship with tropical cyclone activity in the Atlantic basin was assured and updated. Low levels play an important role in tropical cyclogenesis; the position and extension of the anticyclonic ridge at this level are the parameters with the highest coincidence, and in the present century, the anticyclone parameters in the months of June and July have increased their significance. Full article

Urban regeneration is not only an opportunity for the city to adapt according to criteria of resilience to climate change, but also a significant opportunity to build a city based on an approach to health that places the human person at the center of the whole system. According to the World Health Organization, health is not only the absence of disease, but the broader well-being understood as a complex of socio-economic, biological, and environmental relationships. We want to present some results of applying this human-centered approach where the urban fabric’s shape, texture, and materials are essential to building the boundary conditions for developing a healthy city. Full article

Household air pollution was responsible for an estimated 3.2 million deaths per year in 2020, including over 237,000 deaths of children under the age of 5. A large number of these death cases was particularly recorded in developing countries where many people rely heavily on biomass for energy. Burning biomass emits carbon monoxide and other pollutants resulting in indoor air pollution, exacerbations of asthma, hospitalizations for heart attacks and respiratory illness, birth defects, neurological diseases, and even mortality, which are all brought on by indoor air pollution. Because women and children typically do most of the cooking, they are most affected by indoor air pollution. In this research, an active sampling technique was adopted in estimating the amount of three major criteria gaseous pollutants (CO, H₂S, and SO₂) in the air in rural household kitchens within the Jos metropolis. The Attair 5X gas detector was used. The power button was pressed and the equipment was allowed to initialize for few minutes while the readings were taken downwind in-situ at a distance of 1 m, 2 m, 3 m, 4 m, and 5 m respectively from the emission source at the expiration of one (1) minute for each distance to check the impact of emissions on the environment and people in such areas. The results obtained shows that CO, H₂S, and SO₂ were higher from firewood emission sources when compared with charcoal emission sources from the 14 different rural kitchens in the Bauchi ring road, Jos, Plateau State, Nigeria. Hence, this study serves as a ready reference for environmentalists to make target decisions on air pollution reduction. Full article

Wildfires threaten human lives and ecosystems and have a significant impact on the economy. Greece is one of the most vulnerable countries in the world with respect to wildfires. The purpose of this article is to assess the climate change impact of wildfires on the ecosystems of Greece and to determine areas where prevention measures should be utilized. To achieve this, the variability of the Fire Weather Index (FWI) is examined under the RCP4.5 and RCP8.5 scenarios from 2022 to 2098. Under both scenarios, a significant intensification of fire weather is observed, which increases the likelihood of severe wildfires occurring in various ecosystems in Greece. The worst affected areas are Southern and Eastern Greece, provided that they have sufficient fuel. The results are more pronounced for RCP8.5, especially after the mid-century. By the end of the century, most ecosystems will be prone to intense fire activity under RCP8.5. Even under the milder RCP4.5 scenario, high-intensity wildfires are projected to occur with increasing frequency in places where they are currently rare. This project highlights the necessity of climate change mitigation and the employment of more effective and widespread prevention and firefighting methods. The management of the current fire-prone areas should be emphasized, but the state must be prepared to face extreme fire incidents in a broader range of ecosystems, including mid-altitude and high-altitude forests. Full article

The optical and radiative properties of aerosols are governed by their types. In this paper, the optical and radiative properties of different aerosol types in Wuhan, China, have been inverted and investigated using the collected PM_2.5 samples. The results show that PM_2.5 (average mass concentration about 31.25 μg/m³) is mainly contributed by sulfate (SO₄) and organic carbon (OC) (22% and 52%, respectively), while aerosol optical depth (AOD, average about 0.28) is mainly contributed by SO₄ and black carbon (EC) (22% and 19%, respectively). SO4 and nitrate (NO₃) have a negative radiative forcing at the top of the atmosphere (TOA) and a cooling effect, while OC and EC have a positive radiative forcing and a heating effect. Moreover, EC has the most significant effect on the radiative forcing in Wuhan, contributing up to 61% and 73% at the bottom of the atmosphere (BOA) and atmosphere (ATM), respectively, while contributing up to 75% to the atmospheric heating rate (about 1~2 K/day). Full article

The objective of this study was to statistically analyze the concentration of pollution in the air by PM_2.5 particulate matter and vehicular traffic using a methodology based on quadrants, considering the periods of “working” and “holiday” activities in the downtown area from the port city of Tampico, Mexico. The vehicular traffic count was carried out in three hourly ranges per day for a week in each period. Moreover, an analysis of the correlation coefficient based on the Spearman method was carried out, both in the working and vacation periods, between the variables of PM_2.5 concentration and total vehicular traffic by the hourly range and by day in each quadrant. A strong to very strong correlation (0.828 ≥ r ≤ 0.960) was identified between pollutant concentration and vehicular traffic on several days and quadrants in the work period. On the other hand, in the holiday period, a weak to moderate correlation was observed on most of the days considered in this study. Full article

Atmospheric aerosols play a crucial role in the scattering and absorption of solar radiation, directly influencing the UV flux reaching the Earth’s surface. This study investigates the impact of different atmospheric aerosol types on the ultraviolet (UV) flux at four stations over the Indo-Gangetic plain (IGP). For this study, high-resolution 1° × 1° UVA and UVB data were obtained from Clouds and the Earth’s Radiant Energy System (CERES). Various aerosol types present in the atmosphere were categorized based upon their optical properties and their quantitative influence on UVA and UVB flux was examined. Ground-level aerosol products were obtained from the NASA-based Aerosol Robotic Network (AERONET) at four stations in the IGP. Based on the optical properties of aerosols (fine mode fraction, single scattering albedo, aerosol optical depth and angstrom exponent), four distinct atmospheric aerosol types were inferred, namely dust-dominant (DT), polluted-continental-dominant (PCD), black-carbon-dominant (BCD), and organic-carbon-dominant (OCD). It is observed that the AOD of different aerosol types when separated do not seem to have made significant effects on UVA/B radiation (except at Kanpur), possibly due to the statistically smaller data set. For the entire combined AOD, the effects on UVA/B became quite significant at all the stations, which shows that a unit rise in AOD leads to a reduction of 5–7 Wm⁻² in UVA and 0.14–0.23 Wm⁻² in UVB. Full article

Protected Areas can play an important role in climate change adaptation as nature-based solutions. With the huge adaptation deficit, which results in an average loss of RUB 60 billion from extreme weather events annually, the importance of protective ecosystem services is being underestimated. The conservation of intact vegetation enables the maintenance of the stability in a territory that is several times larger, than within a Protected Area. In mountainous regions, forests and grasslands prevent mudflows. In tundra and high mountains, vegetation slows down the fast degradation of permafrost in a warming climate. Forests work to increase the minimum river low flow during droughts and to decrease the magnitude and pace of floods. Protected Areas provide territory and natural resources to indigenous people; thus, they can maintain their traditional lifestyle. It is of utmost importance to emphasize the value of Protected Areas as nature-based solutions by estimating the costs of the ecosystem services they provide and the amount of damage they help to avoid. Full article

Dust storms are one of the most frequent weather phenomena in the Middle East and North Africa (MENA) region. Therefore, the daily forecast of dust events is vital for different sectors. Many regional models can be used to forecast atmospheric dust storms. Here, the ICTP regional climate model (RegCM4) was used to simulate atmospheric dust emission, transportation, and deposition, using the optical properties of dust particles, over the MENA region. In the current work, the dust optical depth (DOD) obtained using RegCM4 was compared with the aerosol optical depth (AOD) measured by AERONET at different stations and by MODIS. In the first experiment, two datasets (NCEP/GFS and ERA-Interim) for the meteorological initial and boundary conditions have been used, whereas in the second experiment, GFS with two dust emission schemes have been used. In the last experiment, GFS with two values of the erodibility factor (1 and 0.5) have been used. The RegCM4 forecast with GFS and the first dust emission scheme provided higher values of DOD than AERONET. However, when using the reanalysis data of ERA-Interim or the second dust emission scheme, there was no significant difference, but the erodibility factor decreases led to a reduction in the overestimated values. Full article

Wildfires emit large quantities of air pollutants into the atmosphere. As wildfires increase in frequency, intensity, duration, and coverage area, the emissions from these fires have become a significant control issue and health hazard for residential populations, especially vulnerable groups. A critical barrier to addressing the health impacts of air pollution caused by wildfires lies in our limited understanding of its true extent. This problem is expected to be exacerbated by additional factors such as the anticipated increase in wildfire intensity due to climate change, and the associated rise in fine particulate matter (PM_2.5) in wildfire smoke, which, according to recent toxicological studies, could be more harmful than typical ambient PM_2.5. The primary goal of our study is to develop a novel statistical framework that enables the forecasting of future emissions from active wildfires. This research aims to address the unquantified impacts of wildfire emissions and is a priority research area for many US federal agencies, e.g., NIEHS, US EPA, and NOAA. The framework integrates physicochemical models of emissions and satellite observations with forecasting models based on spatial statistics and machine learning models. Through the incorporation of these diverse datasets, we aim to improve the accuracy and reliability of our predictions regarding the spatio-temporal distribution of wildfire emissions. The potential human health impacts resulting from poor air quality during wildfires are also explored. By modeling the relationship between environmental exposures and disease risk, the burden of disease attributed to both short- and long-term impacts of exposure to wildfire events will be assessed. Full article

During the last few decades, a prominent example of extreme weather events in the Indian Ocean region has been cyclonic storms. In this paper, annual variations of different categories of tropical cyclonic storms over the Bay of Bengal (BOB) and Arabian Sea (ARS) are analyzed. The analysis reveals that the total number of cyclones (TNC) has increased at a high rate (the gradient being + 1.67 per year) and that there are more CSs over the BOB than over the ARS. The rate of increase in CSs over the Arabian Sea is more than that over the Bay of Bengal. Furthermore, two interesting features were noted: (i) monsoons tend to prohibit the formation of CSs; (ii) cyclonic storms (CSs) increased with the increase in Global Sea Surface Temperature (GSST) during said period. An attempt was also made to find out the influence of solar activity on these extreme weather events. Keeping in mind that the sunspot number (SSN) is an indicator of the strength of solar effects, it was found that, most of the time, a high SSN value was associated with a small number of total cyclones (CSs). A high SSN (>90) and number of cyclones showed ahigh correlation coefficient (0.78). The significance was at the 99.99% level, while the correlation coefficient (CC) of cyclones with time was 0.53, and with SSN < 60, it was 0.095. Thus, it appears that although CS frequency is increasing with time, the influence of sunspots is such that it basically opposes the formation of cyclones provided the SSN exceeds a certain critical value (roughly 90). Full article

The proposed climate monitoring system aims to address the substantial risks to human health, climate stability, and ecological balance posed by air pollution, utilizing Raspberry Pi as a central procession unit and integrating various sensors which also incorporate sensors to measure the concentrations of PM1, PM2.5, PM10, and black carbon. This method meets the need for effective and immediate air quality monitoring and offers useful information to communities, academics, and policy makers. Through IoT connectivity, the gathered data are sent to a cloud-based platform for analysis and visualization. The system offers a user-friendly interface that presents actionable insights for informed decision making. Its warning capabilities alert users when pollution levels exceed thresholds, and this system also contributes to a comprehensive understanding of air pollution. By measuring particulate matter and black carbon levels, it supports the development of effective air quality management strategies. The system helps to take proactive measures and create cleaner and healthier environments. In conclusion, the proposed climate monitoring system utilizing Raspberry Pi, sensors, IoT connectivity, and machine learning techniques offers an effective and real-time solution for monitoring air quality. The integration of IoT connectivity allows for remote access to air quality data, while machine learning algorithms analyze the data and initiate alerts. Full article