Abstract
An intensive sampling of PM2.5 was conducted at a rural site (Gucheng) in the North China Plain from 22 October to 23 November 2016. A total of 25 elements (Al, Na, Cl, Mg, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Sr, Cd, Ba, Pb, and Sb) from PM2.5 filter samples collected daily were measured using a wavelength dispersive X-ray fluorescence spectrometer. Cl, S, and K were the most abundant elements, with average concentrations of 2077.66 ng m−3 (range 118.88–4638.96 ng m−3), 1748.78 ng m−3 (range 276.67–4335.59 ng m−3), and 1287.07 ng m−3 (range 254.90–2748.63 ng m−3), respectively. Among noncrustal trace metal elements, the concentration of Zn was the highest, with an average of 397.74 ng m−3 (range 36.45–1602.96 ng m−3), followed by Sb and Pb, on average, of 299.20 ng m−3 and 184.52 ng m−3, respectively. The morphologies of PM2.5 samples were observed using scanning electron microscopy. The shape of the particles was predominantly spherical, chain-like, and irregular. Positive matrix factorization analysis revealed that soil dust, following by industry, secondary formation, vehicle emissions, biomass and waste burning, and coal combustion, were the main sources of PM2.5. The results of cluster, potential source contribution function, and concentration weighted trajectory analyses suggested that local emissions from Hebei Province, as well as regional transport from Beijing, Tianjin, Shandong, and Shanxi Province, and long-range transport from Inner Mongolia, were the main contributors to PM2.5 pollution.
Highlights
In the past few decades, China has experienced rapid economic growth, urbanization, industrialization, and population expansion
The positive matrix factorization (PMF) model developed by the Environmental Protection Agency (EPA) of USA is an advanced factor analysis technique, which employs a flexible modeling method to effectively use information in data and to identify the possible source contributions without the source profiles
Compared with the results obtained at various sites in China, Mongolia, and Europe from previous studies (Table 2), this concentration was higher than that measured in Beijing (95.47 μg m−3 ) [25], Ulaanbaatar (Mongolia, 92.8 μg m−3 ) [26], Košetice (Czech, 13.6 μg m−3 ) [27], Terviso (Italy, 44 μg m−3 ) [28], and Athens (Greece, 14.2 μg m−3 ) [29], but lower than that recorded in Baoding (192 μg m−3 ) [30]
Summary
In the past few decades, China has experienced rapid economic growth, urbanization, industrialization, and population expansion. The positive matrix factorization (PMF) model developed by the Environmental Protection Agency (EPA) of USA is an advanced factor analysis technique, which employs a flexible modeling method to effectively use information in data and to identify the possible source contributions without the source profiles. The characterization and source identification of trace elements in PM2.5 play an important role in the prevention and control of air pollution. Such approaches can improve air quality and reduce negative effects on human health, attracting extensive attention among researchers. Clusters of air mass back trajectories, the potential source contribution function (PSCF), and the concentration weighted trajectory (CWT) were utilized to explore the transport pathways and likely source regions
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