Temporal Source Apportionment of PM_2.5 Over the Pearl River Delta Region in Southern China

Abstract

The key problems in addressing air pollution include determining the source of the pollutants and developing a means to control them. In addition to the source area and source category of pollutants, the contributions of pollutants emitted during various periods is an important factor that must be better understood for effective and efficient policymaking. A temporal source apportionment module in the Comprehensive Air Quality Model with Extensions was developed and applied to analyze the temporal contributions of emissions to the concentration of atmospheric particulate matter with a diameter ≤2.5 μm (PM2.5) in the Pearl River Delta (PRD) region. The results showed that in addition to cross‐boundary transport, the PM2.5 concentration in the PRD region was generally influenced by emissions on the current day and previous day. Local emissions from 06:00–17:59 on the current day accounted for approximately 30% of the PM2.5 concentration, whereas regional sources (cross‐city transport) had greater contributions during earlier emission periods. During the periods of episodic pollution, a weak wind situation hindered the transportation and diffusion of pollutants; thus, pollutants from 2 days earlier were trapped within the PRD region. When only the emissions from the PRD region were considered, particulate nitrate was more affected by regional emissions from the previous day, whereas the main contributors of other major components of PM2.5 were emissions from the current day. Our results suggest that emission control measures should be implemented 2 days in advance when adverse meteorological conditions are predicted.

Toward the Origins of Quadruple Sulfur Isotope Anomalies in Modern Sulfate: A Multitracer Approach and Implications for Paleo- and Planetary Atmospheres

“…Sulfate concentrations in this study range from 4.9 to 14.7 μg m –3 , with an average (and ±1 standard deviation) of 8.2 ± 3.1 μg m –3 . These values generally match recent observations (∼8 μg m –3 ) and model (∼6 μg m –3 ) results in this region . They are significantly lower than those in the same city during 2007–2011 (23–14 μg m –3 ), when a series of air pollution control measures in China just started to implement.…”

“…We note that our Δ 33 S and Δ 36 S values are identical to prescribed values within errors (9.54 ± 0.09 and −0.14 ± 0.25‰, respectively), but our δ 34 S value is lower than the prescribed value of 10.25 ± 0.22‰. Given that the difference of ∼1‰ in δ 34 S is more than twice that of our experimental error for δ 34 S (0.40‰), an analytical artifact is statistically unlikely. We note that an outlier of the measured S-MIF-1 δ 34 S value (9.4‰) was found by the stable isotope laboratory at the Institut de Physique du Globe de Paris (IPGP).…”

“…These values generally match recent observations (∼8 μg m −3 ) and model (∼6 μg m −3 ) results in this region. 34 They are significantly lower than those in the same city during 2007−2011 (23−14 μg m −3 ), 30 when a series of air pollution control measures in China just started to implement. The δ 34 S values of sulfate aerosols collected at Guangzhou range from −0.1 to 5.3‰, with an average of 2.7 ± 1.8‰ (Table 2).…”

“…Mass-dependent processes may lead to small nonzero Δ 33 S and Δ 36 S values. First, mixing of two sulfur reservoirs with a significant difference in δ 34 S may lead to nonzero Δ 33 S and Δ 36 S values in the mixing product, even though the Δ 33 S and Δ 36 S values of these two sulfur reservoirs are 0‰. Based on two extreme δ 34 S values of modern sulfate aerosols (−10 and 20‰, respectively) and the assumption that they are isotopically normal (i.e., Δ 33 S = Δ 36 S = 0‰), we calculate the largest Δ 33 S and Δ 36 S anomalies due to mixing to be −0.028 and 0.19‰, respectively (Figure 3A,B), with a Δ 36 S/Δ 33 S slope of −6.9 (Figure 3C).…”

“…The external errors (one standard deviation; n = 6) of δ 34 S, Δ 33 S, and Δ 36 S in the full procedure are quantified to be less than 0.40, 0.030, and 0.12‰, respectively (Table 1). All samples were corrected to these IAEA-S1 measurements (subject to the full procedure) and reported against the VCDT (Vienna-Canyon Diablo Troilite) scale by assuming δ 34 The accuracy and precision of our measurements were further tested by analysis of other international reference materials IAEA-S2 and S-MIF-1. The obtained δ 34 S, Δ 33 S, and Δ 36 S values for the international Ag 2 S reference material IAEA-S2 are 22.02 ± 0.25, 0.016 ± 0.064, and −0.47 ± 0.20‰, respectively (n = 3), consistent with those measured in other laboratories 25−28 (Table 1).…”