3.1. Concentrations and metal compositions of PM2.5
The mean mass concentration of PM2.5 during the entire period of sampling was 69.3 ± 35.8 µg m–3 which exceeded the Mongolian NAAQS for PM2.5 (50 µg m–3) and was seven times higher than World Health Organization (WHO) guideline (5 µg m–3) (*** reference is needed). Table 4 shows the descriptive statistics of the PM2.5 during the sampling period. The concentrations of PM2.5 were highest in winter 2021 (2022) with an average of 94.7 ± 45.5 (99.6 ± 35.0) µg m–3, respectively. The lower PM2.5 concentration occurred through the summer with the average of 13.6 ± 4.2 µg m–3. High coal consumption and low boundary layer height (BLH) reveal high PM2.5 concentrations in winter (Tseren-Ochir Soyol-Erdene, 2021). While, in summer, less coal and biomass burning, more particle dispersion, and better deposition conditions through rainout could contribute to the lower PM2.5 concentrations (Nishikawa et al., 2016). Comparison of the concentrations of PM2.5 for different seasons is shown in Fig. 2.
The wind speed and direction greatly influence the degree of PM2.5 pollution in UB (DUGERJAV et al., 2018; Wang et al., 2017). On the other hand, low temperatures and inversion in winter limit the dispersion of air pollutants in UB. The weather conditions in winter generally enhance PM2.5 pollution from the ger districts to travel to UB downtown area (Ganbat & Baik, 2016). To understand the distribution of PM2.5, the contour polar plots of relations between wind speed, wind direction and PM2.5 concentration during study periods are illustrated in Fig. 3. Significant seasonal variations were observed in the relationship of wind speed and wind direction with PM2.5 concentration. In winter, the main pollution episodes usually occurred when the wind speed was 1 m s− 1 or less and wind blew south or southeast (Fig. 3). A clean episode (PM2.5 concentration not exceeding the NAAQS) occurred when the wind direction blew north or northwest and the wind speed was higher than 2 m s− 1. In summer, wind speed impacted pollution levels, but wind direction had little significance. Low PM2.5 pollution episodes usually occurred due to high wind speeds in summer.
The PM2.5 concentrations of fourteen elements (Al, Ca, Mg, Fe, Ti, As, Co, Sb, Ni, Ba, Cr, Cu, K, Mn, Pb) are summarized in Table 5 and Fig. 4. Among the elements, Ca was the most abundant one in PM2.5 in both winter (741 ng m− 3 in2021 and 1240 ng m− 3 in 2022) and summer (105 ng m− 3). Arsenic (As), lead (Pb), and chromium (Cr) were much higher in winter than that in summer with the concentration ratios of winter to summer (W:S) of 1222, 1358, and 1307, respectively. The concentration ratios (W:S) followed by Sb (83), Ni (71), and Ba (60) and other elements were between the range of 12 (Mg) and 34 (P). In summer, Cu, Ba, and Mn showed higher concentrations than other elements. The concentrations of metals were ordered as follows: Pb > Cr > Mn > Cu > As > Ni in winter and Cu > Mn > Ni > Cr ≈ Pb > As.
To compare with the studies in other countries, the mean concentrations of some heavy metals in PM2.5 are summarized in Table 6. The mean value of metal concentrations in UB were higher than other cities in Asia by the factors of 1.6–7.6 for Pb, 1.2–3.4 for Cu, 10–2.7 for Ni, 2.3–22 for As, 3.4–1.5 for Mn, respectively. Metal concentrations in UB were extremely higher than those in European countries for most elements with the factors of 59.8, 4.34, 5.9, 309, 7.7 for Pb, Cu, Ni, As, Mn, respectively. Most heavy metals are usually generated by combustion of fossil fuels and other industrial processing as well as by natural sources. In highly populated cities, particles from motor vehicles (from diesel exhaust, brake wear., etc ) and roads are important sources of PM2.5 mass (Maciejczyk et al., 2021).
Source identification of PM 2.5 -bound heavy elements
Enrichment factor and principal component analysis were used to determine the sources of these heavy metals, and the method from the United States Environmental Protection Agency (EPA) were applied to assess both the carcinogenic and non-carcinogenic risks to adults and children (***need a reference). EF analysis was used for clarifying whether the elements in the ambient air PM2.5 were from anthropogenic or natural (crust) sources. Figure 5 illustrates enrichment factors of elements in three seasons (Winter 2021, Summer 2021, Winter 2022) in UB.
In both winter seasons, EF values for all elements were above 1 except for only Ba which was below 1 (0.26) in winter of 2021–2022 and all elements were contributed from anthropogenic sources. In winter sampling periods, the EFs of Ca, Mg, Co, Ba, K, Mn was below 10, signifying that these elements were influenced by both anthropogenic and crust sources, but predominantly by crust source. The EFs of Ni and P were between 10 and 100. Cu is closer to 100, indicating that Cu was influenced by both anthropogenic and crust sources, Ni is closer to 10 (31.5, 33.5 in winter 2021, 2022), indicating the main influence was from crust sources. Enrichment factors for As, Sb, Cr, and Pb were above 100. The EFs of Sb and Pb were closer to 100, signifying that Sb and Pb were more influenced from anthropogenic sources, while Co, Ba are closer to 10, signifying that these elements were more influenced from crust sources.
The principal component loading results for the metals are summarized in Table 7. In winter, three main factors were extracted explaining the total 89.9% variance. The first factor has an eigenvalue of 9.7 and can explain 69.0% of the total variance, with high loading of Ca, Mg, Fe, Ti, As, Co, Ni, Cr, Cu, K, Mn. The EF values of Ca, Mg, Fe, Co show that main source of these elements is crust derived from anthropogenic sources and As, Cu, Cr, Ni, are known as anthropogenic originated elements (Batbold et al., 2021). A previous study (Davy et al., 2011) showed that coal fly ash were main source Ca, Mg, Fe, Ti, Al in atmospheric PM. Therefore, it can be determined that the first factor is mixed sources of crustal and coal combustion emission.
The second factor in winter accounted for 12.7% of the total variance, with a 1.8 eigen value were comprised of high loadings of Ba and Pb. Barium mainly originates from traffic exhaust gases in urban environments, ( (Belis, 2019), and Pb can be related to road dust. In Mongolia, until the mid-2010’s, leaded gasoline has been used, and comparably high concentrations of lead were accumulated in road dust and roadside soil (Sh.Tserenpil, 2016).Therefore, the second factor can be related to traffic emissions.
The third principal component in winter can explain 8.2% of the total datasets with a 1.14 eigenvalue and high loadings of Sb. A study showed that antimony (Sb) in UB soil was significantly higher and originated from coal ash (Bilguun et al., 2019). PM2.5 with Sb also can originate from coal ash because in winter season, coal consumption is the main heating source in UB and consequently, coal ash is the main component of solid waste from the ger area residences. The ash is resuspended into the urban atmosphere before moving to the landfills(Enkhchimeg Battsengel, 2020) Thus, the third factor is related to coal ash.
For the summer season, two principal components accounted for 100.0% of the total variance of the dataset. The first principal component explained 71.9% of the total data, with 10.1 eigenvalue and loaded with the highest values for Fe and Mn among the metals. During the warm season, there is much lower emission from coal combustion (Gunchin et al., 2019; Nishikawa, 2019). Coal combustion source is not extracted in the PCA in summer. Most metals including Pb, Ni, and Mn had enrichment factors less than 10 in summer (see Fig. 5). Therefore, the first factor seems that dust resuspension due to dry weather and city construction work contribute to the crustal sources. The second principal component accounted for 28.2% of the total dataset, with an eigenvalue of 3.94 with high loadings of Sb, K and Pb. Antimony (Sb) that is used for brake lining and lubricant Pb can be the indicator of traffic related source (Shazia Nawaz, 2022). There were no such highly loaded crustal elements; thus, the third factor may be from traffic-related emissions.