Black carbon (BC) is a component of fine particulate matter (PM_2.5) that is a key contributor to adverse human health effects and climate forcing. To date, BC mass concentrations and possible sources in Kazakhstan have not been studied. Thus, understanding the temporal variations of BC for a large developing region with a complex climate is useful. In this study, measurements of fine particulate BC mass concentrations in Astana were made from June 2020 to October 2021 by measuring light absorption of PM_2.5 on filters. The mean BC concentration was 2.56 ± 1.29 μg m^-3 with maximum and minimum monthly mean BC concentrations being 4.56 ± 2.03 μg m^-3 and 1.12 ± 0.42 μg m^-3 in January 2021 and June 2020, respectively. Temporal analyses of BC, SO₂, PM₁₀, NO_x, CO, meteorological and atmospheric stability parameters were performed. Aggregated pollutant 'episodic loadings' during the heating and non-heating periods were identified. Their relationships with blocking anticyclones and cyclones were investigated by examining the reversal of meridional gradients at 500 hPa geopotential height (GPH) maps and identifying Omega (Ω) and Rex blocking types. Astana has some of the highest BC concentrations of cities worldwide. Seasonal BC source location identification using Conditional Bivariate Probability Function (CBPF) analysis implicated combined heat and power (CHP) plant emissions as the major BC source in Astana. Significant increases in BC concentrations were observed during the cold season due to numerous sources, generally poorer atmospheric dispersion and blocking events. The Concentration Weighted Trajectory (CWT) analysis results showed that the distribution of the 75th percentile of BC during episodic periods actively controlled by blockings exceeding than the entire measurement period, which may reflect cross-border transport and adjacent countries.

Atmospheric fine particulate matter (PM2.5), a complex mixture of various chemical species, has emerged as a significant air quality issue in urban areas. PM2.5 is a key factor in harmful health effects, significantly contributes to the disease burden, plays a significant role in atmospheric visibility and climate change. These tiny particles can scatter and absorb sunlight, leading to haze and reduced visibility, especially in urban areas. Additionally, some components of PM2.5, like Black Carbon (BC), can contribute to global warming by absorbing heat in the atmosphere.Central Asia is home to several republics that have been striving for independent development over the past 25 years. Kazakhstan is probably the most advanced of these countries as well as the largest in area. It is rich in mineral resources, particularly fossil fuels and thus, has relied primarily on coal for its heating, electricity generation, and industrial base operations. Its air quality is not well characterized to the rest of the world since governmental monitoring data are not publicly available and few prior studies of the amounts or sources of particulate matter have been published.Currently, the capital Astana has become one of the most polluted cities. Thus, this work that provides almost two years of compositional data and source contributions provides an initial assessment of particulate air quality in Astana. This initial study thoroughly investigates the chemical compositions and source apportionment of PM2.5 based on elements, ions, BC, and estimated UMM, due to the lack of organic carbon data from the samples. Source apportionment was obtained by the U.S. EPA’s Positive Matrix Factorization (PMF) (v5.0) receptor model and Conditional Bivariate Probability Function (CBPF) analyses. Identified source types and average contribution to PM2.5 were ‘Spark Ignition’, ‘Coal Flyash’, ‘Secondary Nitrate’, ‘Primary Sulfate-Fuel Combustion’, ‘Secondary Sulfate-Coal Combustion’, ‘Soil/Road Dust’, ‘Diesel’, and ‘Local Power Plant(s)’. Carbonaceous matter, sulfates, and nitrates account for a significant PM2.5 fraction since power plants burn high-ash coal and fuel oil year-round in Astana city. The major contributions are heating power plants (CHPP-1 and CHPP-2), private residential chimney heating systems, autonomous boilers, vehicles, and local construction activities.Kazakhstan recently declared its intent to decarbonize by 2030 and achieve carbon neutrality by 2060 that should substantially improve air quality. This study will thus provide baseline data against which future apportionment studies can be compared.

Karaganda, one of the most heavily polluted industrial cities worldwide, experiences severe air quality challenges due to emissions from coal mining, metallurgical industry and coal-fired power plants. This study investigates the influence of meteorological parameters on PM₂.₅ concentrations and associated air pollution episodes in Karaganda, Central Kazakhstan, using a monthly dataset spanning 2017–2024. The meteorological parameters including temperature (°C), relative humidity (%), atmospheric pressure (hPa), wind speed (m/s) and pollutant concentrations including suspended particulate matter (dust, mg/m³), PM₂.₅ (mg/m³), PM₁₀ (mg/m³), sulfur dioxide (SO₂, mg/m³), carbon monoxide (CO, mg/m³), nitrogen dioxide (NO₂, mg/m³), ozone (O₃, mg/m³), ammonia (NH₃, mg/m³), and formaldehyde (HCHO, mg/m³) were analyzed to explore meteorology-driven variability in air pollution. Time series analyses and correlation assessments were conducted, and three complementary regression approaches, Multiple Linear Regression (MLR), Random Forest Regression, and Gradient Boosting via LightGBM were applied to robustly characterize the relationships between meteorological conditions and PM₂.₅ levels. Results indicate persistently high pollution levels, with exceedances of daily average concentrations observed for PM₂.₅, PM₁₀, dust, phenol, formaldehyde, and ozone, with PM₂.₅ showing the most pronounced exceedances. Air pollution episodes were particularly severe during the cold season, driven by emissions from thermal power plants and residential heating. Multi-year trends revealed increasing occurrences of high-concentration events, primarily due to PM₂.₅, PM₁₀, SO₂, and CO, highlighting the significant contribution of industrial and energy-related emissions to the urban atmosphere. Meteorological conditions, particularly calm or low-wind periods (0–3 m/s), further exacerbated pollutant accumulation during episode periods, with 106 such days recorded in 2024 alone. These findings underscore the critical role of both emission sources and weather conditions in shaping air quality in Karaganda and provide a basis for targeted mitigation strategies. Key words: Karaganda, PM₂.₅, meteorological parameters, air pollution episodes

Over the past three decades, noise pollution has become a noticeable phenomenon in cities. Noise is an environmental stressor that adversely affects interpersonal communication, diminishes quality of life, impairs attention and cognitive function, and triggers emotional responses, resulting in noise-related discomfort. According to WHO (World Health Organization) guidelines, any noise above a threshold value of 55 dB is considered to be harmful to human health. Excessive noise can cause stress, sleep disturbances, hearing loss, and other health problems, impacting both psychological and physical well-being. Astana, the capital of Kazakhstan, experiences varying noise levels influenced by urban development, traffic, construction, and industrial activity. In central areas and along major roads, noise levels often exceed recommended limits, especially during peak traffic hours. This study provides quantitative evaluation of geospatial distributions of noise levels in the rapidly growing city of Astana, Kazakhstan. Over the entire measurement period, from October 22 to November 22, 2024 the average noise level in Astana was recorded at 73 dB. In this study 840 noise pollution measurements were conducted at 20 different noise measurement stations (NM1-NM20) in Astana. Data were collected at various times of day—morning (8:00–9:30), midday (13:00–14:30), and evening (17:30–19:00)—using the Sound Level Meter (SLM) UT352 and SLM NIOSH mobile app. The average discrepancy between measurements taken with the NIOSH SLM mobile app and the UT 352 SLM device ranges from 0.13 to 6.86 dB, depending on location. Noise measurements were taken in different geographic locations, including central business districts with heavy traffic, as well as residential neighborhoods where background noise is primarily influenced by vehicle traffic and the activities of residents in Astana. In essence, the city’s rapid urbanization is complicated by air and noise pollution, while its extreme climate exacerbates the environmental challenges. The objective of the study is to evaluate noise effects and analyze the characteristics of background noise in the urban environment, with the aim of developing strategies to enhance the urban environmental conditions in Astana city, Kazakhstan.