4.7 Article

Online monitoring of carbonaceous aerosols in a northern Chinese city: Temporal variations, main drivers, and health risks

Journal

ATMOSPHERIC ENVIRONMENT
Volume 316, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2023.120169

Keywords

Carbonaceous aerosols; Organic carbon; Black carbon; Health risk

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This study examined the variability and source of carbonaceous aerosols in a typical northern Chinese city, finding differences in concentration based on season and time of day, and analyzed the influence of meteorological conditions on carbonaceous aerosols. The results contribute to a deeper understanding and comprehensive management of carbonaceous aerosol pollution.
This study examined the variability and source of carbonaceous aerosols, encompassing total carbon (TC), organic carbon (OC), and secondary organic carbon (SOC) for the years 2019-2020, as well as equivalent black carbon (eBC) and equivalent ultraviolet BC (eUVBC) data spanning 2019-2022, in the context of a typical northern Chinese city: Yanzhou. Averaged concentrations of TC, OC, SOC, eBC, eUVBC, and the ratio (OC/ elemental carbon (EC)) reached 11.1 +/- 6.7, 8.9 +/- 5.1, 3.9 +/- 2.0, 3.1 +/- 1.3, and 4.3 +/- 2.4 mu g/m3, and 5.0 +/- 2.2, respectively. The concentrations of TC, OC, eBC, and eUVBC were higher in winter, followed by spring and autumn, and summer, while SOC presented the opposite seasonal patterns. The diurnal variations of TC, OC, eBC, and eUVBC exhibited a bimodal pattern with peaks in the early morning (08:00-09:00 LT) and late evening (00:00-01:00 LT) and a trough in the afternoon (14:00-16:00 LT), pointing to vehicular emission and meteo-rological dispersion as major drivers of the hourly variability. The results obtained from the EC tracer method and minimum R squared (MRS) revealed that r(SOC/OC) were highest in summer (60%) and lowest in winter (26%), showing a fast summer photochemical oxidation of volatile organic compounds (VOCs) that generate SOC. In this study, the influence of meteorological conditions on the weighting of diverse carbonaceous aerosols was quantified using a machine learning method. Results showed that the main drivers of carbonaceous aerosols were height of the planetary boundary layer (HPBL), ambient temperature (AT), relative humidity (RH), and atmospheric pressure (AP) in all seasons. Additionally, the potential health risks of eBC based on the equivalent passive smoking of cigarettes (PSC) suggested that there was a certain level of human health risk in this city. The obtained results will provide more in-depth and comprehensive understanding of carbonaceous aerosol pollution and management strategies.

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