The annual and intraseasonal variability of near-ground daytime mixing ratios of gaseous pollutants ( O 3 , NO, NO 2 , CO, and benzene) and aerosols ( PM 10 and PM 2.5 ) measured at the A.M. Obukhov Institute of Atmospheric Physics of the Russian Academy of Sciences observation site in the center of Moscow in 2018–2023 is analyzed. The primary gas species ( NO, NO 2 , CO , and benzene) and PM 2.5 show a unimodal seasonal cycle with a maximum in winter and a minimum in summer months, reflecting a combined influence of extratropical tropospheric features and local meteorology. A distinct summertime ozone maximum provides evidence for the strong input from its photochemical source, which is presumably attributed to the upper part of the urban mixing layer. The relative contribution of Moscow emissions to the observed pollutant levels during the cold (warm) season is estimated to be approximately 56% (42%) for CO and 64% (67%) for NOx, 70% (59%) for PM 2.5 , and 78% (77%) for PM 10 , with the remaining part beingdue to advection of chemically aged air from upwind pollutant sources on a wide range of spatial scales. The number of synoptic-scale episodes ( N ) with the enhanced PM 2.5 and CO levels decreases exponentially with episode duration ( τ , days) as N(τ) ~ e –λ∙τ where the rate of decrease ( λ ) is 0.66 (0.83) for the cold (warm) season.
Mangrove ecosystems play a critical role in coastal resilience and long-term carbon storage, yet their spatiotemporal dynamics in small island systems remain poorly understood. This study analyzes mangrove land-cover change from 2000 to 2022 across four major islands in the Karimunjawa Archipelago (Karimunjawa, Kemujan, Parang, and Nyamuk) and projects future trends to 2042. Using multi-temporal satellite imagery and carbon stock–based estimates of CO₂ emissions resulting from mangrove land-cover change, the results reveal heterogeneous trajectories of degradation and recovery. Estimated CO₂ emissions were calculated by multiplying the change in carbon stock, the molecular weight conversion factor from carbon (12/44), and the area of mangrove land-cover change (ha). In 2015, Karimunjawa and Kemujan maintain the largest mangrove extents but are also associated with the highest estimated CO₂ emissions, reaching 273,899.30 t CO₂ ha-¹ as a consequence of land-use conversion, whereas Nyamuk exhibits relatively stable dynamics with localized carbon stock loss corresponding to estimated CO₂ emissions of up to 1,037.13 t CO₂ ha-¹, and Parang shows persistent decline with estimated CO₂ emissions of up to 587.97 t CO₂ ha-¹. Future projections indicate increasing carbon stock loss and associated estimated CO₂ emissions toward 2042, particularly on Kemujan, Nyamuk, and Parang, reaching 574,188.40, 2,551.95, and 1,953.84 t CO₂ ha-¹, respectively, highlighting growing risks to coastal ecosystem integrity and climate change mitigation efforts. These findings underscore the influence of geomorphology, anthropogenic pressure, and governance in shaping mangrove dynamics on small islands. Integrated, site-specific, and adaptive management strategies are therefore essential to conserve mangrove carbon stocks, minimize carbon losses associated with land-cover change, and strengthen coastal resilience in the Karimunjawa Archipelago.
This article analyzes greenhouse gas emission trends in Russian Federation regions from 2017 to 2023, calculated using the author’s methodology. The methodological approach combined a sectoral decomposition of regional changes (identifying the leading driver and assessing the concentration of changes in one or two sectors), measuring structural shifts in the sectoral structure of emissions (the Gatev index), and testing the dynamic factors using a logarithmic change model. The national emission trajectory over the study period was undulating. Emissions declined in 2017–2020 and recovered in 2020–2023, with fuel combustion representing the dominant driver at both stages. However, structural adjustments in most regions were limited, and notable structural shifts were driven by changes in non-fuel sectors, i.e., fugitive emissions from mining, industrial processes, and agriculture. This highlighted the importance of sectoral specialization and local intrasector factors in interpreting regional dynamics. The regression model for the full period 2017–2023 revealed a statistically significant relationship between emission dynamics and changes in economic activity and energy intensity, while for shorter subintervals, the robust relationships are weaker, reflecting the impact of shocks and high sectoral heterogeneity. The analysis also reveals differentiated decoupling patterns between economic growth and greenhouse gas emissions across Russian regions, with 29 regions (approximately 35%) demonstrating absolute decoupling effects. The results demonstrated that the analysis of subnational trajectories requires a combination of aggregated estimates and sectoral interpretation, taking into account differences in emission generation mechanisms when developing low-carbon development policies.
Peripheral natural areas in Russia are being increasingly incorporated into tourism without scientifically grounded methods for assessing their potential, which creates risks and leads to missed economic opportunities for regional development. This study was conducted on the Kolva River in Perm Krai, Russia. We developed and tested a methodology for the integrated assessment of river-based tourism potential in peripheral areas using a combination of expeditionary field methods and GIS tools for tourist route planning. The methodology integrates field hydrological measurements, UAV surveys, campsite assessment based on six criteria, and GIS mapping. Using this approach, we designed a 144-km river expedition route. Thirty-two potential campsites were assessed, and eight were selected, with an average spacing of 25 km. Orthophoto maps were produced for key sections of the route. Twenty rock outcrops were recorded along the river, corresponding to a density of 0.14 units/km. Flood risk at the campsites was assessed using long-term hydrological records from local gauging stations. Hydrochemical analyses of water samples confirmed good water quality, and eight springs had sufficient discharge to supply drinking water along the route. The Kolva River is at the pioneer stage of tourism development, with no infrastructure or signs of recreational impact. The proposed approach to tourist route planning in peripheral areas may be considered broadly applicable to similar settings elsewhere, and the results can support spatial development planning and tourism route design in peripheral regions.
Understanding the spatial determinants of long-term forest ecosystem sustainability is a prerequisite for designing effective climate adaptation strategies. Long-term provenance trials serve as invaluable in situ laboratories for assessing the adaptive capacity of keystone forest species under novel climatic regimes. This study capitalizes on a unique 66-year-old experiment involving 44 climatic ecotypes of Scots pine ( Pinus sylvestris L.) – a foundation species of the Eurasian boreal and temperate forests – in Belarus to quantify, for the first time, the relationship between geographical origin and a composite, multi-criteria ecosystem sustainability rank. A novel ranking system was developed, reinterpreting conventional mensurational metrics – stand survival, structural integrity, and biomass stock – as empirical proxies for adaptive capacity and functional resilience. The analysis revealed a pronounced, non-linear geographical gradient in sustainability. The Bryansk ecotype (Central Russian Upland) achieved the highest composite sustainability rank (1.4), significantly outperforming local populations. Northern and south-eastern ecotypes exhibited critically low adaptive capacity, with several provenances undergoing terminal stand collapse. The local Vitebsk ecotype, possessing the single highest radial growth rate, displayed only intermediate integral sustainability, demonstrating that current productivity and long-term resilience are decoupled. The findings provide direct, whole-life-cycle evidence that the geographical provenance of a foundation tree species is a primary determinant of ecosystem stability under a shifting climate. The generated geographical sustainability ranks offer a scalable, spatially explicit decision-support tool for selecting optimal seed sources and adaptive management trajectories to enhance the resilience of forest landscapes across the East European Plain.
