Recent studies have widely implicated that the strength of the North Atlantic subpolar gyre (SPG) is dynamically linked with the North Atlantic thermohaline circulation, affecting the subpolar marine environment. Therefore, it is crucial to understand the past changes in the SPG strength with changes in arctic sea ice and Atlantic meridional overturning circulation (AMOC). This climate modeling study employs a fully coupled atmosphere-ocean-sea ice Earth system model to explore the dynamics in the North Atlantic subpolar for the past 20ka (ka is thousand years before the present). This study highlights a close relationship between the strength of the SPG, Atlantic sea ice coverage, and AMOC circulation in the centennial timescale resolution for the past 20ka. The simulation shows that the changes in SPG and AMOC are in phase. However, the Atlantic sea ice coverage varied inversely to SPG and AMOC strength. Particularly during the Heinrich 1 (≈19ka–14.6ka) and Younger Dryas (≈12.9ka–11.7ka) events, the SPG strength decreased in unison with AMOC strength which reduced the northward meridional heat transport and resulted in the increase in the Atlantic sea ice coverage. However, the dynamic linkage between Atlantic sea ice coverage and ocean circulation does not follow during the prescribed unnatural freshwater supply during the meltwater pulse 1A (mwp-1A) event at about 14.1ka, which caused the Allerød warm period (≈14ka–12.9ka). This finding demonstrates that an abrupt change in freshwater discharge into the North Atlantic subpolar may destabilize the polar ocean-sea ice dynamics.

Air pollution is a major environmental concern with far-reaching consequences for human health, ecosystems, and sustainable development. Air pollution resulting from biomass combustion is a significant environmental issue in Mozambique. This study provides an overview of the impact of biomass burning on air quality in the country, focusing on the sources of pollution, emitted pollutants, and the associated health and environmental implications. Mozambique heavily depends on biomass for cooking, heating, and energy production, leading to elevated levels of air pollution caused by burning biomass fuels like wood, agricultural residues, and charcoal. Particulate matter (PM), carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), and hazardous air pollutants (HAPs) are all emitted into the atmosphere when biomass is burned. These contaminants harm human health, leading to respiratory and cardiovascular disorders. Furthermore, biomass combustion emits greenhouse gases, including carbon dioxide (CO2) and methane (CH4), contributing to climate change and global warming. Reducing air pollution caused by biomass in Mozambique is crucial for safeguarding public health and the environment. Initiatives promoting cleaner cooking technologies, such as improved cookstoves and biogas systems, aim to reduce dependence on traditional biomass burning. Additionally, raising awareness about the health risks associated with biomass combustion and ensuring access to alternative energy sources are essential steps in addressing this problem. However, challenges like limited access to clean energy options, financial constraints, and the need for sustainable biomass management techniques persist. To tackle biomass-related air pollution in Mozambique, comprehensive solutions require collaborative efforts involving the government, non-governmental organisations, and international partners. This paper offers an overview of biomass-related air pollution in Mozambique, concentrating on the sources, impacts, and potential solutions. 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.

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 Indo-Gangetic plain (IGP). For this study, high-resolution 1°x1° UVA and UVB data was 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), anthropogenic aerosols dominant (AAD), black carbon dominant (BCD), and organic carbon dominant (OCD). OCD and AAD showed the highest concentration at Kanpur and Lahore respectively whereas BCD showed lowest contribution at Karachi and Jaipur. The UVA and UVB fluxes were found to be highly influenced by DT at Jaipur, OCD at Kanpur, BCD and OCD at Karachi and DT at Lahore. As the UVA and UVB flux are affected by solar zenith angle and ozone column concentration, the effects of the same has also been studied on UVA and UVB for different aerosol types.

Delhi is one of the most densely populated megacities of the world and 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 vegetation index using satellite datasets. Air pollutant data viz. nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) obtained from NASA’S Aura satellite called Ozone Monitoring Instrument (OMI), and carbon monoxide (CO) and particulate matter 2.5 (PM_2.5) from Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) model. The vegetation indices i.e. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Oxide (EVI) collected from the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. The analysis of both data revealed higher concentrations of air pollutants in the summer months when NDVI & EVI was minimum. Further, a higher pollution load was observed in October – January months when NDVI and EVI were lower. Furthermore, we also investigated the spatial patterns of PM_2.5 and other gaseous pollutants (viz. CO, SO_2, and NO₂) and observed that they were less in the vegetated region in comparison to the sparsely vegetated area of Delhi. The present study indicates vegetation could ameliorate various air pollutants, however, it needs to validate with ground observed data.

During last few decades a prominent example of extreme weather event in Indian Ocean region is Cyclonic Storm. In this paper annual variation of different categories of tropical Cyclonic Storms like Tropical over Bay Of Bengal (BOB) and Arabian Sea (ARS) have been analyzed .The analysis revels that the total number of cyclone (TNC) has increased with high rate (gradient being +1.67 per year) and although C.S. is more over BOB than that over ARS. The rate of increase of C.S. over Arabian Sea is more than that over Bay of Bengal. Furthermore, two interesting features have been noted: (i) Monsoon tends to prohibit the formation of C.S (ii) Cyclonic Storm(C.S.) increases with the increase of Global Sea Surface Temperature (GSST) during said period. An attempt has also been made to find out the influence of solar activity on these extreme weather events. Keeping in mind that the Sun Spot Number (SSN) is an indicator of the strength of solar effects, it has been found that in most of the times the high value of SSN is associated with small number of total cyclone (C.S.). High SSN (> 90) and number of cyclones shows high Correlation coefficient (0.78) .Significance at 99.99% level while Correlation Coefficient (C.C.) of cyclones with time is 0.53 and with SSN < 60 it is0.095 . Thus it appears that although C.S. frequency is increasing with time, Sun’s Spot’s influence is such that it basically opposes the formation of cyclone provided SSN exceeds certain critical value (roughly 90).

The wave phase difference is a fundamental property that characterizes the relative behavior of transmitted waves. It plays a crucial role in wave analysis and understanding various wave phenomena which could accommodate when designing the wireless link as well as a variety of applications in signal processing, optics, and acoustics. This study explores the concept of phase difference significance using high frequencies such as 1, 2.4, 10, and 20 GHz to offer a willingness to the upcoming era. We review existing phase difference models and their shortcomings, emphasizing the need for greater accuracy and precision in quantifying phase differences. The result shows that 1 GHz is the lowest phase difference among others. However, the constructive signal could be accommodated and provide a better link build-up. Overall, Addressing the importance of phase difference in GHz and identifying the signal attitude would offer contributes to the advancement of wave analysis and encourages further exploration in this domain.

One of the primary contributors to the ambient air pollution in Ulaanbaatar is the combustion of raw coal and briquettes in ger areas. The pollution caused by the combustion process also significantly impacts indoor air quality, resulting in severe implications for people’s health. This study, designed and implemented by the nonprofit organization Breathe Mongolia – Clean Air Coalition, aimed to assess indoor air pollution in gers that had installed Cooking, Heating and Insulation Packages (CHIPs)—an initiative that provides electrical heating and cooking and insulation material at a subsidized rate. 28 gers participated in the study—25 with CHIPs and three without for comparison. We used low-cost technology to measure carbon monoxide (Binary System monitors) in all 28 gers and fine particulate matter (AirVisual monitors) in 14 gers. The data acquisition took place during the winter season of 2022-2023. The highest PM_2.5 concentration was 279.09 μg/m³ in the evening and the highest weekday level was 248.70 μg/m³ on Fridays. The highest carbon monoxide concentration was 20.62 ppm in the evening and 16.08 ppm Thursdays. For a comprehensive assessment of indoor air quality in gers and to gauge the effectiveness of interventions like CHIPs in reducing indoor air pollution, Breathe Mongolia will continue its monitoring efforts in ger areas. Through such efforts, we hope to address data scarcity and help evaluate what interventions are needed to improve indoor air quality.

Detailed long-term hydrometeorological hindcast for Russian Arctic based on regional nonhydrostatic atmospheric model COSMO-CLM ver. 5.05 for 1980–2016 with ~12 km grid size used to estimate climatological trends of extreme wind speed. This hindcast shared online partially on the figshare service [1] and includes about a hundred hydrometeorological variables at both surface and 50 model levels with 1 hour output step covering the North Atlantic and Russian Arctic [2].

In this study, we used the 145 weather stations 10 m wind speed data covering Russian Arctic, Scandinavia and Arctic islands inside the hindcast domain. Trends in mean, 0.95, 0.99, 0.999 quantiles wind speed values, and occurrence of wind speed above 20, 25 and 33 m/s were calculated for all stations and corresponding nearest model grids. Statistical significance of all trends was estimated according to the Student’s t-test on 95% level.

Mean wind speed have shown most significant positive trends over northern parts of Barents and Kara seas corresponding to areas with the largest rate of ice-freeing during the last decades. At the same time, rest part of the Barents Sea and Atlantic sector shown generally negative trends. Wind speed over continents do not show any large areas of significant trends except for decrease in Taymyr peninsula.

Extreme wind speed trends according to its occurrence over 20 m/s indicated significant changes: increase over northern Barents and Kara Sea, southern Barents Sea, western Kara Sea, eastern Svalbard, White Sea Throat and subpolar region; decrease over Northern Atlantic, northern island of Novaya Zemlya, Severnaya Zemlya, Tiksi coastline and Taymyr peninsula.

References:

1. Data from the COSMO-CLM Russian Arctic Hindcast archive, figshare repository https://figshare.com/collections/Arctic_COSMO-CLM_reanalysis_all_years/5186714; https://doi.org/10.6084/m9.figshare.c.5186714

2. Platonov V., Varentsov M. Introducing a New Detailed Long-Term COSMO-CLM Hindcast for the Russian Arctic and the First Results of Its Evaluation. 2021 Atmos. 12(3) 350 http://dx.doi.org/10.3390/atmos12030350

Trace elements contribute a small fraction to fine-mode aerosols as compared to the other chemical species (organic & inorganic) and affect the ambient air quality and human health. In this paper, we report the inter-annual and seasonal concentrations, and sources of trace elements in PM_2.5 over Delhi, India based on long-term analysis (2013–2021). In all the PM_2.5 samples 19 trace elements were extracted: Na, Mg, Ca, Mn, Al, Fe, Ti, Cu, Zn, Cr, Ni, As, Mo, Cl, P, S, K, Pb, and Br. The total annual mean concentration (∑El in PM_2.5) of trace elements was 17.49±3.13 µg m^-3 which is accounted for 13.9% of PM_2.5 mass concentration. 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 site of Delhi, India. 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) due to restricted activities during covid-19 lockdown/unlock periods. Four major sources of trace elements (in PM_2.5) were extracted by principal component analysis as crustal/soil dust, vehicular traffic/industrial emissions, combustion (solid+fossil fuels), and sodium magnesium salts in Delhi. This long-term study on the elemental composition of PM_2.5 will be useful for policymakers in mitigating ambient air quality and improving human health.

The increased concentration of pollutants is a challenge for the population health. This work aims to investigate the health risk that is related to pollutants’ level in the center of Rhodes city. Rhodes Island is a desirable tourist destination with important economic activity over the southeastern Aegean Sea. The analysis covers the (summer) July-August months and the (winter) December month of 2022. Hourly recordings of the concentrations of PM2.5, 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 compared to winter period shows increased health danger possibly due to the increased traffic emissions, tourist density as well as the different meteorological conditions. In summer period, the AQHI is classified between the upper Low to Medium health risk class and during winter month, AQHI is classified in Low health risk class, respectively. The AQHI diurnal variability is higher during July-August compared to December. Additionally, the diurnal differences between two periods show increased health risk for summer months mainly between the hours from early evening to early morning. Finally, the analysis shows that the traffic activities affect the health risk and highlight that the authorities should adopt green policies to protect human’s health.