Fengwen
Wang
a,
Tian
Lin
b,
Jialiang
Feng
c,
Huaiyu
Fu
a and
Zhigang
Guo
*a
aShanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China. E-mail: guozgg@fudan.edu.cn; Fax: +86 21 65643117; Tel: +86 21 65643117
bState Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550002, China
cInstitute of Environmental Pollution and Health, Shanghai University, Shanghai 200444, China
First published on 10th December 2014
Providing quantitative information on the sources of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) in urban regions is vital to establish effective abatement strategies for air pollution in a megacity. In this study, based on a year data set from October 2011 to August 2012, the sources of PM2.5-bound 16 USEPA priority PAHs (16 PAHs) in Shanghai, a megacity in China, were apportioned by positive matrix factorization (PMF) modeling. The average concentrations (in ng m−3) of 16 PAHs in PM2.5 in the fall, winter, spring and summer were 20.5 ± 18.2, 27.2 ± 24.0, 13.7 ± 7.7 and 6.4 ± 8.1, respectively, with an annual average of 16.9 ± 9.0. The source apportionment by PMF indicated that coal burning (30.5%) and gasoline engine emission (29.0%) were the two major sources of PAHs in the PM2.5 in Shanghai, followed by diesel engine emission (17.5%), air-surface exchange (11.9%) and biomass burning (11.1%). The highest source contributor for PAHs in the fall and winter was gasoline engine emission (36.7%) and coal burning (41.9%), respectively; while in the spring and summer, it was diesel engine emission that contributed the most (52.1% and 43.5%, respectively). It was suggested that there was a higher contribution of PAHs from engine emissions in 2011–2012 compared with those in 2002–2003. The major sources apportioned by PMF complemented well with this of using diagnostic ratios, suggesting a convincing identification of sources for the PM2.5-bound 16 PAHs in a megacity.
Environmental impactThis is the first study that quantitatively apportioned the sources of PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) in Shanghai using positive matrix factorization (PMF) modeling. Five distinct source categories, namely, gasoline engine emission, diesel engine emission, coal burning, biomass burning, and air-surface exchange were identified. The major sources apportioned by PMF complemented well with that of using diagnostic ratios, suggesting a convincing identification of sources for the PM2.5-bound 16 PAHs in a megacity. This work, we believe, can provide insight into the identification of organic contamination in the megacity in China, and perhaps in the world. |
In recent years, air quality research has focused on fine particles (i.e., PM2.5, aerodynamic diameter less than 2.5 μm) due to their strong effects on atmospheric visibility, human health and global climate. Shanghai, the largest city in China by population (i.e., ∼24 million in 2013), is one of the global financial centers and a transport hub with the world's busiest container port. According to the monitored data, the PM2.5 pollution in Shanghai deteriorated in the recent decade, and its significant role in the air quality of Shanghai has been a source of great concern for researchers. For example, Hou et al. (2011) reported the carbonaceous pollutants in PM2.5 in Shanghai in 2006–2007, and assessed their implication on heavy haze formation.5 Huang et al. (2012) observed three typically episodic hazes associated with 2009 PM2.5 in Shanghai, and found that the chemical composition of PM2.5 played a key role in air quality.6 Furthermore, there have been studies emphasizing specific components, such as PAHs, in the PM2.5 of Shanghai. Feng et al. (2006) measured the composition and sources of organic matter in PM2.5, and found that engine exhausts made a prominent contribution to PAHs in urban areas.7 Gu et al. (2010) presented the occurrence and compositions of PAHs based on over two years of PM2.5 samples, and revealed the sources of petroleum and coal/biomass combustion for PAHs.8 These studies provided qualitative information on PAH sources, and implied that PAHs played a significant role in the air quality of Shanghai. It should be noted that, although the air quality of Shanghai has been ameliorated since the mid-1990s, fine particles (i.e., PM2.5) and the associated organic fraction still remain priority pollutants in the atmosphere.9 Therefore, in order to more effectively abate the organic contamination and especially the PAH fraction in the PM2.5 in Shanghai, it is necessary to quantitatively apportion the sources of these pollutants. However, to the best of our knowledge, no work has been published on the quantitative apportionment of PAH sources in the atmosphere of Shanghai. In this study, 72 PM2.5 samples from October 2011 to August 2012 were collected at an urban site in Shanghai. The objectives of this work are to examine the seasonal variation of PAH occurrence and composition, and to apportion the sources of the PAHs using positive matrix factorization (PMF) modeling.
The PM2.5 samples were collected by an aerosol sampler (Guangzhou Mingye Huanbao Technology Company) with quartz filters (20 × 25 cm2, 2500 QAT, PALL, USA) at a flow rate of 18 m3 h−1. The sampler began to collect samples at 9:00 am on day one and stopped at 8:30 am the following day, ensuring the duration time for a sample was about 23.5 h. A total of 72 PM2.5 samples were taken during 24 Oct. to 16 Nov. 2011 (fall, n = 20), 24 Dec. 2011–11 Jan. 2012 (winter, n = 18), 29 Mar.–28 Apr. 2012 (spring, n = 19) and 24 Jul.–12 Aug. 2012 (summer, n = 15). Each paired sampling campaign consisted of a 23.5 h sampling, starting at 9:00 am on the first day to 8:30 am the following day. There were at least two parallel operational sampling blanks in each season. Sample media were prepared as follows: the filters were wrapped in aluminum foil and baked together at 450 °C for 4 h to remove residual organic contaminants; they were then sealed in marked valve bags and stored in the laboratory prior to sample collection. All post-sampling filters were stored at −20 °C for later analysis.
Site | Period | Size | PAHs | References |
---|---|---|---|---|
Shanghai | 2011, 10 to 2012, 08 | PM2.5 | 16.9 | This work |
Beijing | 2002, 07 to 2003, 01 | PM2.5 | 112.7 | 15 |
Harbin | 2008, 08 to 2009, 07 | TSP | 45.0 | 16 |
Qingdao | 2001, 06 to 2002, 05 | TSP | 87.5 | 17 |
Guangzhou | 2001, 04 to 2002, 03 | TSP | 23.7 | 18 |
Xiamen | 2008, 10 to 2009, 09 | TSP | 11.9 | 19 |
Los Angeles | 2001, 05 to 2002, 07 | PM2.5 | 0.8 | 20 |
London | 1995, 09 to 1996, 06 | TSP | 5.8 | 21 |
According to the properties and sources of the 16 PAHs, they can be classified into 2–3-ring (Nap, Ac, Ace, Fl, Phe, Ant), 4-ring (Flu, Pyr, BaA, Chr), and 5–6-ring PAHs (BbF, BkF, BaP, IP, DBA, BghiP). The seasonal composition patterns for the 16 PAHs are shown in Fig. 2. It can be seen that BbF (7.9–20.4%), BkF (5.2–15.6%), BaP (8.7–12.8%) and BghiP (11.6–14.3%) were the main components. A similar composition pattern over the four seasons can be observed, with the highest contribution from the 5–6-ring (56.4%), followed by the 4-ring (30.6%) and the 2–3-ring PAHs (9.4%). According to Dachs et al. (2002), 2–3-ring PAHs can be formed in the pyrolysis of unburned fossil fuel.22 4-ring PAHs were abundant in coal combustion1 and biomass burning.23 5–6-ring PAHs mainly originate from high-temperature combustion processes such as vehicular exhaust.24 In this study, the combustion-derived PAHs represented 56.4% of the total PAHs, indicating a prominent contribution from the combusted origins of PAHs. These kinds of composition characteristics for the 16 PAHs in PM2.5 could be caused by various factors, such as meteorological conditions, emission sources and transport paths.8,25 In this study, we mainly focused on the possible influence of emission sources on the PAH characteristics in PM2.5. This will be further discussed below.
Fig. 3 Seasonal correlations between 16 PAHs with EC and OC in PM2.5 in Shanghai (the extremely high concentration represented by “dark rectangle” in the summer of 2012 was excluded). |
The correlations between 16 PAHs and OC are shown in Fig. 3b. As shown, the strongest correlations were in the winter (R2 = 0.87, n = 20, Fig. 3b-1), followed by the fall (R2 = 0.69, n = 18, Fig. 3b-2) and spring (R2 = 0.22, n = 19, Fig. 3b-3). The correlation index in the summer was only 0.02 (n = 15, Fig. 3b-4), much poorer than in the other three seasons. This kind of seasonal difference between PAHs and OC could be attributed to emission sources as well as influence from prevailing meteorological conditions. As suggested by Feng et al. (2009), the OC fractions in PM2.5 of Shanghai, based on four seasonal data sets, were mostly from fossil combustion sources, such as vehicular exhaust and/or coal combustion.9 Therefore, the good correlations in the winter and fall indicate that the PAHs were partly associated with vehicular emissions and coal burning. According to Turpin et al. (1995),27 OC can be divided into primary organic carbon and secondary organic carbon (SOC), and a more prominent SOC percentage was revealed in warm seasons than in cold seasons.26,28 Meteorological conditions in warm seasons, such as a higher frequency of sunny days and more intense solar radiation, could result in a higher photochemical activity.28 In this study, the SOC formation through chemical reactions, such as photolytic oxidation, is a likely cause for the weak correlations between PAHs and OC in the spring and summer. In the summer, higher temperatures and more intense solar radiation could provide more favorable conditions for photochemical activity and SOC production,26 leading to a relatively high availability of gaseous VOC precursors in the atmosphere. Therefore, SOC formation in the summer could be much more prominent than that in the spring, resulting in a rather poor correlation between PAHs and OC.
Time | Seasons | Phe/Phe + Ant | Flu/Flu + Pyr | BaA/BaA + Chr | IP/IP + BghiP |
---|---|---|---|---|---|
2011–2012 (This study) | Fall | 0.84–0.91(0.88) | 0.50–0.58(0.55) | 0.27–0.51(0.39) | 0.44–0.50(0.47) |
Winter | 0.88–0.94(0.91) | 0.51–0.58(0.56) | 0.29–0.46(0.37) | 0.44–0.48(0.45) | |
Spring | 0.89–0.95(0.92) | 0.11–0.59(0.53) | 0.24–0.79(0.33) | 0.42–0.48(0.44) | |
Summer | 0.81–0.91(0.89) | 0.51–0.56(0.53) | 0.34–0.47(0.38) | 0.40–0.51(0.43) | |
2002–2003 (ref. 7) | Winter | 0.88–0.95(0.92) | 0.49–0.54(0.52) | 0.26–0.35(0.30) | 0.43–0.48(0.46) |
Summer | 0.89–0.94(0.91) | 0.45–0.52(0.49) | 0.28–0.38(0.31) | 0.44–0.47(0.45) | |
Diagnostic ratios | 0.5 gasoline | <0.4 unburned petroleum | <0.2 petrogenic sources | <0.5 engine fuel combustion | |
0.65 diesel | 0.4–0.5 liquid fossil fuel | 0.2–0.35 petrogenic and combustion | |||
0.76 coal | >0.5 wood, coal combustion | >0.35 pyrolytic sources | >0.5 coal/biomass burning | ||
References | 30 | 30 | 3 | 30 |
Fig. 4 5-factor loadings by PMF analysis from 16 PAH data of 72 PM2.5 samples collected in Shanghai over four seasons. |
Factor 1 accounted for 29.0% of the sum of the measured 16 PAHs. It has a high loading of 5–6 ring PAHs, including BbF, BaP, IP and BghiP, and moderate contributions from BkF, BaA and Chr. This kind of profile is considered to be associated with gasoline engine emission.31,32 In recent decades, gasoline has been used primarily as a fuel in internal combustion engines of automobiles. As a world megacity, Shanghai has been experiencing a rapid increase in vehicles, especially those for private use. According to ChinaIRN (http://www.chinairn.com/), Shanghai had 1.01 × 106 private vehicles in 2011, a certainly significant use of gasoline by any measure. Therefore, factor 1 is defined as gasoline engine emission sources.
Factor 2 contributed 17.5% of all the measured 16 PAHs. High loadings of BkF, BaP and BghiP and moderate loadings of Flu, Pyr, BaA, and Chr were observed. A similar profile of high loadings of BaP and BghiP was also observed in aerosols in the Hudson River Estuary.33 By visually comparing with the factor 1, assigned as gasoline engine emission, the profile of factor 2 exhibited more 3–4-ring PAH characteristics. It has been revealed that the diesel emissions are enriched in Flu, Pyr32 and BkF33 relative to gasoline emissions. Accordingly, factor 2 is characterized as a diesel engine emission source. Diesel fuel has been widely used in trucks and sport utility vehicles (SUVs), since they are more powerful and fuel-efficient than similar-volume gasoline engines.
Factor 3 explained 30.5% of the sum of the measured 16 PAHs. This is dominated by Flu and Pyr, with moderate loadings of BaA, Chr, BbF, and BkF. Flu and Pyr have been considered to be tracers of coal burning.1 According to NBSC (http://www.stats.gov.cn/english/), coal consumption in China accounted for more than 70% of the total energy used in 2011. As the largest industrial and commercial city in China, Shanghai consumes a large amount of coal. Hence, factor 3 is assigned as coal burning sources.
Factor 4 accounted for 11.1% of all measured 16 PAHs. It was highly loaded with Phe, Ant, Flu, and Pyr, and moderately with BaA, Chr, and BbF. This source profile of PAHs in PM2.5 has been reported in the literature to be mainly from biomass burning.14,23 In China, including rural areas in the YRD, agricultural refuse, such as straws, stalks, and deadwood, are mostly used for cooking. They are usually burned in primitive stoves without forced blasting, emitting ample organic pollutants, including PAHs.
Factor 5 accounted for 11.9% of all the measured 16 PAHs. This profile contains more volatile PAHs (i.e., 2–3-rings, such as Nap, Ace, Phe) and is readily found in the warm seasons (i.e., fall and summer), as expected for a temperature-driven process. The PAH profiles (% of the factor total) of this factor were similar with those investigated by Wang et al. (2014) (red dot in Fig. 4), which was assigned as an air-surface exchange.12 In previous studies, Nap has been used as a tracer of the fugitive loss of petroleum products.34 Ace, Fl and Phe are abundant in natural mineral dust transport.23 Moreover, the low molecular weight (LMW) PAHs are favored in air-surface exchange.33 Gaseous PAH concentrations have been observed to have an exponential relationship with temperature, due to evaporation from contaminated ground during the warmer weather.35 Dimashki et al. (2001) also recognized this process and suggested that a process of volatilization of these compounds from surfaces might be appreciable for Phe, Fl and Flu.36 In addition, it has been suggested that the soil could also be a potential source of PAHs in the atmosphere, driven by higher temperatures.37 Accordingly, factor 5 could be attributed to air-surface exchange. The “exchange” here indicates a possible re-emission of aged PAHs from “contaminated soil” or volatilization of PAHs directly from the ground into the atmosphere, to be absorbed later by the particles.
The seasonal contributions of each source to the 16 PAHs are shown in Fig. 5. A strong seasonal variation of PAH sources can be seen. Gasoline engine emission and coal burning were the two major sources, both in the fall (36.7% and 27.9, respectively) and in the winter (34.6% and 41.9%, respectively); while diesel engine emission contributed the most in the spring (52.1%) and in the summer (43.5%). In the fall and winter, the prevailing winds in Shanghai are northwesterly. Therefore, aside from the local emission sources, the influence of pollutants transported not only from the YRD but also from northern China on the PAH sources should be taken into account. The intense manufacturing activities of the YRD and northern China demand a large amount of energy, provided mostly by coal-fired power plants, and the large vehicular fleet is a rapidly growing source of emissions. Moreover, the contributions from biomass and coal burning in the winter (57.0%) almost doubled that of the fall (38.3%). Space heating is technically not allowed in the south in winter, while in northern China, centralized heating via coal is provided. For example, in Beijing and Qingdao, the coal and biomass burned in the winter contributed more PAHs in PM2.5 than vehicular emissions,14 possibly due to the space heating policy in northern China.17,38 In the spring and summer, the prevailing winds in Shanghai are southeasterly, mostly from the relatively “clean” East China Sea. The prevailing “southeasterly winds” could be further evidenced by the HYSPLIT air mass back trajectory model from the National Oceanic and Atmospheric Administration (http://ready.arl.noaa.gov/hysplit-bin/trajasrc.pl). As a marginal sea off eastern China, the East China Sea has two typical busy ports located adjacent to Shanghai. The Port of Shanghai, the world's busiest container port, set a historic record by handling over 32 million twenty-foot equivalent units (TEUs) in 2012 (http://www.shanghai.gov.cn/). Yangshan Port, a deepwater port for container ships in Hangzhou Bay south of Shanghai, was on track to move 12.3 million TEUs in mid-2011 (http://www.marine-news-china.com). These two ports are used for domestic ferry rides, and also handle cargos for national or international trade. It should be noted that, due to the larger demands of these cargos transported nationwide in China, the number of trucks in Shanghai increased accordingly. In 2011, there were already 3.0 × 104 trucks registered in the Port of Shanghai. Diesel is commonly used instead of gasoline to power the ferry, cargo ships and trucks like this. Considering the wide usage of diesel fuel, as stated above, and the southeasterly winds in the spring and summer off Shanghai, it is reasonable to suggest that the diesel engine emission from maritime activity could be a crucial source of the 16 PAHs in the PM2.5.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c4em00570h |
This journal is © The Royal Society of Chemistry 2015 |