Chemical characterization and source apportionment of atmospheric fine particulate matter (PM2.5) at an urban site in Astana, Kazakhstan
Ormanova G. Hopke P.K. Dhammapala R. Ozturk F. Shah D. Torkmahalleh M.A.
January 2025Elsevier B.V.
Atmospheric Pollution Research
2025#16Issue 1
PM2.5 is a significant air quality concern in urban areas globally. PM2.5 in Astana exceeded the US EPA standard for annual mean PM2.5 EPA with an average PM2.5 mass concentration of 23.43 ± 11.50 μg/m3 and a maximum daily value of 63.8 μg/m3 in January (heating season). The lowest 3.7 μg/m3 was observed in September (non-heating season). However, source apportionment in Kazakhstan has not been done because of a lack of PM2.5 composition measurements. This study presents the first analysis of chemical composition of PM2.5 and source apportionments in Kazakhstan. It comprehensively examined Astanas PM2.5 chemical characteristics and source apportionment over ∼ two years (November 2019 to August 2021). Using elements, water-soluble inorganic ions, black carbon (BC), and estimated unmeasured mass (UMM), source apportionment was obtained using Positive Matrix Factorization (PMF) supported by conditional bivariate probability function (CBPF) analyses. Average PM2.5 contributions of the eight sources were ‘Spark Ignition’ (30.3%), ‘Coal Flyash’ (17.1%), ‘Secondary Nitrate’ (15.1%), ‘Primary Sulfate-Fuel Combustion’ (9.9%), ‘Secondary Sulfate-Coal Combustion’ (8.5%), ‘Soil/Road Dust’ (7.9%), ‘Diesel’ (7.1%), and ‘Local Power Plant(s)’ (4.2%). Local power plants burn high-ash coal and fuel oil year-round. The major contributions of heating/power plants, private residential heating systems, autonomous boilers, vehicles, asphalt pavement mixing facilities, and local construction activities. This studys source apportionment analysis provides critical insights for developing targeted air quality management strategies in Kazakhstan. Findings highlight the need for improved controls on vehicular emissions and heat/power generation sources and for the implementation of measures by local governments to effectively reduce PM2.5.
Air pollution , Astana , Conditional bivariate probability function (CBPF) , Kazakhstan , PM2.5 , Positive matrix factorization (PMF) , Source apportionment
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Department of Civil and Environmental Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, 010000, Kazakhstan
Institute for a Sustainable Environment, Clarkson University, Potsdam, 13699, NY, United States
Department of Public Health Sciences, University of Rochester Medical Center, 265 Crittenden Boulevard CU420644, Rochester, 14642, NY, United States
South Coast Air Quality Management District, Diamond Bar, CA, United States
Environmental Engineering Department, Faculty of Engineering, Bolu Abant İzzet Baysal University (BAIBU), Bolu, 14030, Turkey
Department of Chemical and Materials Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, 010000, Kazakhstan
Department of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago, Chicago, 60612, IL, United States
Department of Civil and Environmental Engineering
Institute for a Sustainable Environment
Department of Public Health Sciences
South Coast Air Quality Management District
Environmental Engineering Department
Department of Chemical and Materials Engineering
Department of Environmental and Occupational Health Sciences
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