Abstract
ABSTRACT We collected ambient PM10 and PM2.5 samples from six sites in Tian’jin, China, from February to March 2016 and then analyzed their chemical compositions and identified the emission sources using the positive matrix factorization model. The mean concentrations of the PM10 and PM2.5 were 98 and 71 µg m–3, respectively, with a mean PM2.5/PM10 ratio of 0.67. The average concentrations of the combined SO42–, NO3–, and NH4+ were 19.9–23.4 µg m–3, accounting for 72.4–77.1% of the total measured ions. The concentrations and percentages were significantly higher for NO3– and OC than for other species. The SO42–/NO3– ratio showed a decreasing tendency as the PM10 and PM2.5 concentrations increased, implying a strong influence from mobile sources. The mean OC/EC ratios for PM10 and PM2.5 were 3.1 and 3.2, respectively, with small spatial differences. The most abundant elements were crustal, accounting for 73.2–84.2% of the total detected elemental mass, and mainly enriched in the PM10. The optimal number of factors for PM2.5 and PM10 was selected via PMF analysis: the decrease in the Q/Qexcept values of these two fractions lessened when choosing six instead of five factors, indicating that five factors may be optimal. All the factors were mapped in bootstrap (BS) for 100% of the runs, and no swaps occurred with the displacement of factor elements (DISP) for five factors. Secondary inorganic aerosol, coal combustion, crustal dust, vehicle exhaust, and biomass burning contributed 28–30%, 20–21%, 18–21%, 17–20%, and 4%, respectively. Secondary inorganic aerosol displayed less spatial heterogeneity than the other sources in its contributions. Backward trajectory and PSCF analysis showed that air masses affecting Tian’jin mainly originated in the northwest during the heating period, and northeastern He’nan, southwestern Shan’dong, Bei’jing, and Tian’jin itself were major potential source areas.
Highlights
Particulate matter (PM) is mainly composed of inorganic, carbonaceous, and elemental matter (Zhang et al, 2013, 2014; Liu et al, 2016a)
PM2.5 ranged between 37–262 μg m–3 and between 17– 214 μg m–3, respectively (Fig. 2); the mean PM2.5/PM10 ratio was 0.67
Lower PM10 (94 μg m–3) and higher PM2.5 (78 μg m–3) concentrations were observed at QJ along with a higher PM2.5/PM10 ratio (0.78), likely indicating important contributions of fine-particle emission sources such as vehicles and secondary inorganic aerosol, as QJ was characterized by traffic and residential areas where the influence of vehicle emissions would be relatively high (Table S1)
Summary
Particulate matter (PM) is mainly composed of inorganic, carbonaceous, and elemental matter (Zhang et al, 2013, 2014; Liu et al, 2016a). Understanding PM chemical composition and source is critical to assessing impacts on air quality, climate change and human health, as well as to controlling pollution (Zhang et al, 2014; Li et al, 2016; Peng et al, 2017; Liu et al, 2018). Aerosol and Air Quality Research, 20: 1–13, 2020 by error estimation (EE) methods; the uncertainty of each factor’s identifying species is shown to be a useful gauge for evaluating multiple solutions, e.g., with a different number of factors (Brown et al, 2015). The EE methods can play an important guiding role in choosing an optimal factor solution. The related research on source apportionments using the PMF model with EE methods is still limited
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