Chemical Composition and Source Apportionment of Wintertime Airborne PM_2.5 in Changchun, Northeastern China

• Main Authors: Shichun Zhang, Daniel Q. Tong, Mo Dan, Xiaobing Pang, Weiwei Chen, Xuelei Zhang, Hongmei Zhao, Yiyong Wang, Bingnan Shang
• Format: Article
• Language: English
• Published: MDPI AG 2021-04-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: aerosol; PM_2.5; measurement; Northeast China; source apportionment
• Online Access: https://www.mdpi.com/1660-4601/18/8/4354
• ISSN: 1661-7827; 1660-4601

This study presents field observations and laboratory analyses of wintertime airborne particulate matter (PM_2.5) and its chemical components in the Changchun metropolitan area, the geographical center of northeastern China. Twenty-four hour PM_2.5 filter samples were collected from 23 December 2011 to 31 January 2012 at four sites in the types of traffic, residential, campus, and a near-city rural village, respectively. Daily PM_2.5 concentrations ranged from 49 to 466 µg m⁻³, with an arithmetic average of 143 µg m⁻³. Laboratory analyses showed that among all measured chemical species, mineral dust contributed the largest proportion (20.7%) to the total PM_2.5 mass, followed by secondary inorganic aerosols (SIA, including SO₄²⁻, NO₃⁻ and NH₄⁺), which constituted 18.8% of PM_2.5 mass. Another notable feature of PM_2.5 chemical composition was high halogen (Cl⁻ and F⁻) loadings at all sites, which was likely due to emissions from coal combustion, plastic manufacturing, and glass melting. Among the four sampling sites, the suburban site exhibited the highest PM_2.5 levels and extremely high Cl⁻ and F⁻ loadings due to residential wood burning and nearby industrial facilities lacking effective emission controls. Our results report one of the earliest observations of PM_2.5 composition in this region, providing a baseline of aerosol profiles of aerosol before PM_2.5 was routinely measured by environmental protection agencies in China, which could be useful for assessing long-term trends of air quality and effectiveness of mitigation measures.