Climate

The Russian Far East is one of the regions of the country with the least investigated processes affecting the air quality and related climate changes of the region. In the current study 3D numerical modeling (WRF-Chem) together with the ground- and satellite-based observation data of the particular atmospheric pollutants (NO₂, CO, SO₂, O₃, aerosols) were applied to demonstrate how wildfires and transboundary pollution from China could influence air quality in the Far East of Russia (with focus on the Amur region) in July 2015 and January 2023. The WRF-Chem modeling system represents a near-surface air temperature with bias (compared to observations) of 0.5–2 °C and standard deviation, or STD, of 2–5 °C. In general the model overestimates near-surface wind speed—the bias varies in the range 0.8–1.9 m/s with STD of ~2 m/s. This fact should affect the model performance of near-surface gaseous and aerosol composition. Robust Pearson correlation coefficient (from ~0.5) in both periods was found only between modeled and observed near-surface NO₂ and CO. Significant correlation for O₃ (0.73) was found only in January. By using WRF-Chem regional modeling it was demonstrated that seasonal wildfires in the northern Amur region, Zabaykalsky Krai, and the Republic of Yakutia (July 2015) and transboundary pollution from northeastern China (January 2023) could cause the degradation of air quality in the Amur region. Additionally, the possible effect on air quality from the domestic anthropogenic emissions of the Amur region was found in January 2023. According to the modeling, in July 2015 monthly mean NO₂ concentration higher than state standards was found in the territory of the Amur region. The highest monthly mean near-surface NO₂ concentrations exceeding state standards were modeled in northeastern China (~0.05 ppm). The modeled concentrations of other pollutants in the Russian Far East fit the state norms in both periods. The effect of wildfires and transboundary pollution episodes on air quality in the Russian Far East can be considered for the evaluation in the future state air quality reports.

The aim of this study is to quantify the impact of increased surface solar radiation on climate warming in Central Europe from 1915 to 2024 and to examine the relationship between CO₂ air concentrations and emissions on a global scale with an empirical approach. A statistical model with proxies for short-wave and long-wave radiation (sunshine duration SSD and CO₂ concentration) as independent variables and surface air temperature as the dependent variable was tested for validity and significance, and the results were presented for six long-term measuring stations in Central Europe. The statistical model fulfilled all tests (error probability, normal distribution of the residuals, autocorrelation, statistical power, multicollinearity) and showed that the increase in SSD in the entire year accounts for around 20% of the warming over the last 100 years; in the summer half-year (April–September) and summer (June–August) it is around 30%. The increase in CO₂ concentration accounts for the remainder portion of warming of 70–80%. Studies and models neglecting the influence of the increase in surface solar radiation are overestimating the influence of GHG on warming. A lifetime concept for CO₂ was evaluated empirically for the last 130 years: the development of CO₂ air concentration from industrialization until today can be mapped very well with a lifetime of 58 years. With this lifetime, reducing annual CO₂ emissions by around half would stabilize CO₂ concentrations. The contrasting concept of cumulative CO₂ emissions, according to which stabilization can only be achieved with ‘zero emissions’, is discussed in this context.

The year 2024 has been recorded as the warmest year on record, with global temperatures temporarily exceeding the 1.5 °C threshold owing to rising anthropogenic greenhouse gas emissions. This has intensified global attention on heatwaves, which are a major public health threat linked to increased morbidity and mortality rates. This study conducted a bibliometric analysis of 901 Web of Science-indexed journal articles (2004–2024) using the term “heat wave health.” The findings revealed a significant increase in global temperatures, with an increasing frequency, intensity, and duration of extreme heat events. Heatwaves have been linked to higher rates of injuries, mental health disorders, and mortality, particularly in urban areas, due to ozone pollution, atmospheric contaminants, and the urban heat island effect, leading to increased emergency hospitalisation. Rural populations, especially outdoor labourers, face occupational heat stress and a higher risk of fatality. Adaptation measures, including early warning systems, heat indices, air conditioning, white and green roofs, and urban cooling strategies, offer some mitigation but are inadequate in the long term. Significant knowledge gaps persist regarding regional vulnerabilities, adaptation effectiveness, and socio-economic disparities, underscoring the urgent need for interdisciplinary research to inform heat-resilient public health policies and climate adaptation strategies. This study highlights the urgent need for further interdisciplinary research and targeted policy interventions to enhance heatwave resilience, particularly in under-researched and highly vulnerable regions of the world.