Modelling the Black Carbon Variability and Dynamics in Almaty, Kazakhstan, During Winter and Summer Seasons

Meteorological Applications
ABSTRACT
Large cities with poor air quality can affect surrounding areas through pollutant transport and advection, especially in remote regions with complex mountain environments. One such example is the city of Almaty (Kazakhstan), which frequently experiences severe air pollution episodes and is located at the foothills of the Ile Alatau (part of the northern Tien Shan mountains). In this work, the impact of locally emitted black carbon (BC) from Almaty on the surrounding mountain areas was investigated. The WRF-CHIMERE regional chemical transport model (CTM) was employed with three nested domains up to 1 km resolution for January and July 2023. Simulation results indicated that during winter, BC concentrations remained trapped over the Almaty basin, at the lower elevations north of the city, and along the main valleys. In contrast, in summer, despite lower anthropogenic emissions arising from the city, BC was found to reach the mountain tops more effectively, likely due to increased vertical mixing and enhanced mountain-valley circulation. Additionally, model runs with and without online exchange between meteorology and chemistry were conducted to quantify the effect of BC concentrations on the radiative fluxes. The direct radiative effect of BC at the bottom of the atmosphere (BC DREBOA) due to Almaty emissions was estimated to be −1.20 (January) and −0.41 (July) W m−2, while within the atmosphere (BC DREATM) was +1.33 (January) and +0.45 (July) W m−2. Analysis of the potential temperature gradients in both months indicated, on average, no significant effect of BC concentrations on vertical atmospheric mixing, due to the presence of strong temperature inversions over the region. This research provides new insights into BC dynamics in the Central Asian region and highlights the need to extend the analysis to transitional periods (spring, autumn) when the temperature inversions are weaker or absent.

year: 2026

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