Front. Earth Sci. 2012, 6(3): 324–330 DOI 10.1007/s11707-012-0326-y
RESEARCH ARTICLE
Characterization of polycyclic aromatic hydrocarbons in PM2.5 and PM10 in Tanggu District, Tianjin Binhai New Area, China Dan YANG1,2, Shihua QI (✉)1,2, Ningombam Linthoingambi DEVI1,2,4, Fang TIAN1,2, Ziping HUO3, Qingyuan ZHU3, Jing WANG3 1 State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan 430074, China 2 School of Environmental Studies, China University of Geosciences, Wuhan 430074, China 3 Tianrenhe Researching and Developing Center of Environmental Protection Techniques, Tanggu, Tianjin 300450, China 4 Transport Planning and Environment, Central Road Research Institute, New Delhi 110025, India
© Higher Education Press and Springer-Verlag Berlin Heidelberg 2012
Abstract Particulate matter (PM10 and PM2.5) concentrations were monitored during the November 2008 by using the filter samples collected day and night from three sites in Tanggu District at Tianjin Binhai New Area, China. The mean concentrations of PM2.5 and PM10 rank in the order of urban (150 μg/m3 for PM2.5 and 197 μg/m3 for PM10) > industrial (32 μg/m3 for PM2.5 and 170 μg/m3 for PM10) > suburb area (27 μg/m3 for PM2.5 and 59 μg/m3 for PM10). Sixteen polycyclic aromatic hydrocarbons (PAHs) were analyzed in PM10 and PM2.5 samples. Concentrations of total PAHs in PM2.5 and PM10 are in the range of 8.47– 113.94 ng/m3 with average of 62.88 ng/m3 and 21.07– 118.23 ng/m3 with average of 73.42 ng/m3, respectively. The light ring PAHs (2–4 rings) are dominant in both PM2.5 and PM10 during sampling time compares with the heavy ring (5–6 rings) PAHs. The relationship of PAHs and PM2.5 (r = 0.689, p < 0.05) is stronger than PAHs and PM10 (r = 0.570, p < 0.05), illustrating PAHs tend to adsorb in PM2.5. In addition, principal component analysis was applied to find the source of PAHs. Three principal factors representing three types of PAHs sources in Tanggu District are extracted, which were coke production, pyrogenic sources and vehicular source. Keywords PM2.5, PM10, polycyclic aromatic hydrocarbons (PAHs), Tanggu District, Tianjin Binhai New Area
Received March 15, 2012; accepted May 25, 2012 E-mail:
[email protected]
1
Introduction
Particulate matter (PM) has been related to a wide range of adverse health effects (Dutton et al., 2010). PM10 and PM2.5, with aerodynamic diameters less than 10 μm and 2.5 μm, respectively, can be inhaled into the respiratory tract leading to critical health problems. One of an important organic groups in PM in terms of health risk is polycyclic aromatic hydrocarbons (PAHs), which have attracted much attention in studies on air pollution recently because some of them are highly carcinogenic or mutagenic (Villalobos-Pietrini et al., 2007). Tianjin Binhai New Area (TBNA), located in the eastern coast of Tianjin, comprises three administrative regions of Tanggu District, Hangu District and Dagang District. The three functional zones are considered to be the Tianjin Economic-Technological Development Area. The economic development is thought to have direct and indirect influence on the atmosphere condition. Tianjin has suffered from heavy pollution problems in the atmosphere (Wu et al., 2004), and even PM2.5 in Tianjin was suspected to affect Beijing’s atmosphere (Sun et al., 2010). The levels of PAHs in suspended particulate matter, soil, sediment, and water in Tianjin are high in comparison with values reported from other city or river and marine systems (Shi et al., 2005; He et al., 2009). Emissions of PAHs are mainly from industrial and domestic utilization, such as combustion of fossil fuels. But in rural and suburban areas, PAHs are mainly from numerous low-efficiency boilers, stoves, and open-air biomass burning (Wu et al., 2005). In consideration of the limited research about PAHs concentrations in both PM2.5 and PM10 in Tanggu District, TBNA, the present work attempts to obtain quality
Dan YANG et al. Characterization of PAHs in PM2.5 and PM10 in Tanggu District, Tianjin
325
information on the atmosphere in urban, industrial and suburban regions in Tanggu District, including comparing the distribution of PM10 and PM2.5 during day and night time, and investigating the concentrations of PM bound PAHs and the correlation between the PAHs and PM. Moreover, the source of PAHs is estimated using principal component analysis (PCA), as well as the characteristic ratios of PAHs.
The samples were collected for 3 days in the urban area from Nov.12th to 14th, 1 day in the suburb on Nov.15th, and 2 days in the industrial area sites on Nov.16th and 17th in 2008. Every day had day time sampling (8:00 am–8:00 pm) and night time sampling (8:00 pm–8:00 am the next day). In this study, 48 filters samples were collected, in which 24 held PM10 and 24 held PM2.5. All the filters were stored at – 20°C and analyzed within 8 days from collection.
2
Experiment
2.2
2.1
Sampling
The filter papers were weighed and injected with 1000 ng mixture of PAH surrogate standard, then Soxhlet-extracted with dichloromethane (DCM) for 24 h. Elemental sulfur was removed by adding activated copper granules to the collection flasks. The sample extract was concentrated and solvent-exchanged to hexane and further reduced to 2–3 mL by a rotary evaporator (Heidolph4000, Germany). A 1∶2 (v/v) alumina/silica gel column (48 h extraction with DCM, then 180°C and 240°C muffle drying for 12 h, both 3% deactivated with H2O before using) was used to clean up the extract and PAHs were eluted with 30 mL of DCM/ hexane (2∶3). The eluate was then concentrated to 0.2 mL under a gentle nitrogen stream. A known quantity (1000 ng) of hexamethylbenzene was added as an internal standard for analysis of PAHs prior to gas chromatography mass (Agilent 6890/5978 N) analysis.
Particulate matter samples were collected from suburban, industrial and urban areas in Tanggu District in TBNA, China, during November of 2008 (Fig. 1).
2.3
Fig. 1
Location map of the sampling stations in Tanggu District
The urban site was at the Environmental Protection Agency of Tanggu District, which is located in the center of the city with an intensive residential population; the industrial area site was in the Tanggu Lingang Industrial Area, where most factories and enterprises were under construction and not in operation yet. The suburban site is located in the southern suburbs of Tanggu District with less human activity and is considered as a background point. PM2.5 and PM10 were collected in the three sampling sites by using an atmospheric particulate monitoring instrument (Four Chamber PM10, PM2.5 Speciation Model TH-16A) to collect simultaneous samplings of PM10 and PM2.5. It has a stack to collect the particulates from the atmosphere and the capacity to pump up the particulate matter inside the four cylindrical chambers with velocity of 16.7 L/min to collect PM2.5 and PM10 on the quartz fiber filter with 47 mm diameter, each two chamber worked different functions.
Analytical procedure
Quality control and quality assurance
Method blanks (solvent), spiked blanks (internal standard compounds spiked into solvent), and field blanks were analyzed to check interference and cross-contamination. Correlation coefficients for the calibration curves of PAHs were higher than 0.9. Surrogate standards were added to each of the samples to monitor procedural performance and matrix effects. The limits of detection (LOD, ng) of PAHs were defined as the mean blank values plus 3 standard deviations. The average recoveries of PAHs were 77%–110%.
3
Results and discussion
3.1
Variation of PM concentration
The mass concentrations of daily PM2.5 and PM10 in urban, industrial and suburban areas are given in Table 1. The monitoring showed the mean concentration of PM2.5 and PM10 both in the order of urban > industrial > suburban area. The daily mean concentrations of PM10 in urban (197 μg/m3) and industrial (170 μg/m3) areas were higher than the daily average emission of the national secondary standard (150 μg/m3) of China Environmental Quality Standard (GB3095-1996), the US standard (150 μg/m3),
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Table 1 PM PM10
PM2.5
Front. Earth Sci. 2012, 6(3): 324–330
Concentrations and target values of PM2.5 and PM10 Value
Concentration/(μg/m3) Urban
Industrial
Target values Suburb
CHN
US
EU
150
150
50
–
35
40
Max
289
254
110
Min
114
91
8
Mean
197
170
59
Max
237
50
45
Min
79
17
8
Mean
150
32
27
and more than 3 times of the EU standard (50 μg/m3), which was even exceeded by the mean content of PM10 in the suburb (59 μg/m3). PM10 concentration in Tanggu (59– 197 μg/m3) district was lower than Beijing (252 μg/m3) (Sun et al., 2004), Nanjing (318 μg/m3) (Wang et al., 2003) and Lucknow City, India (204.026.7 μg/m3) (Pandey et al., 2012), but much higher than Guilin (79.228.6 μg/m3) (Guo et al., 2009), Hong Kong (73.927.9 μg/m3) , China (Cao et al., 2003), and Seoul, Republic of Korea (108 μg/m3) (Kim and Kim, 2003). The daily mean concentrations of PM2.5 (150 μg/m3) in the urban area was two times more than the second draft version of the Chinese Environmental Quality Standard for PM2.5 (75 μg/m3) in present, which will be fully implemented in 2016. Except in the urban area, the daily mean concentrations of PM2.5 were lower than the daily average emission of the United States (US) (35 μg/m3) and European Union (EU) (40 μg/m3) standards. Compared with the research in other cities in China, the PM2.5 mean content in the Tanggu urban area was at the same level as Tianjin (140.7 μg/m3) (Lin et al., 2005), Beijing (99.5 μg/ m3) (Wang et al., 2006a), and Guangzhou (102.7– 129.9 μg/m3) (Duan et al., 2007), much lower than Chongqing (216.9 μg/m3) (Pan et al., 2004), and the heavy industry city Taiyuan (193.4102.3 μg/m3) (Meng et al., 2007), but higher than some economically developed cities in the South, such as Shenzhen (60.818.0 μg/m3), Zhuhai (59.323.7 μg/m3) (Cao et al., 2003) and Hong Kong (49.9–56.4 μg/m3) (Duan et al., 2007). PM10 and PM2.5 contents had a positive correlation (r = 0.69, p < 0.05) but not very significant in this study, for each site had different sources and formation mechanisms of PM. Whereas in the urban site (r = 0.84, p < 0.05), this correlation was much higher than the other two sites, probably because the urban site is located within the city center with relatively stable sources of PM from human activities. The ratio (ρ) of PM2.5/PM10 was used to identify PM2.5 and PM2.5 – 10 contents in PM10. The ρ value under three sites was ranked in the order of urban area (0.78) > suburb (0.45) > industrial area (0.19). The concentrations of PM2.5 contribute the majority of the PM10 fraction in the urban area, probably because domestic pollution, car
exhaust, and especially winter heating played more important roles in enhancing the PM2.5 content in the urban area than in other areas. In the industrial area, the ρ value was lower than in the suburb as a result of building construction. More PM2.5 – 10 from the dust caused by construction made the PM10 in industrial area (170 μg/m3) 3 times that of the suburb (59 μg/m3), but the disparity in PM2.5 content was only 1.2 times larger than in the suburb. A higher ρ value found in the Tanggu suburb, compared with the other two sites, was consistent with other studies regarding high ρ values in the suburbs of Wuhan (0.64), Lanzhou (0.59), Chongqing (0.62), and Guangzhou (0.72) (Hao et al., 2006). These results are probably because fine particles are able to stay or move in the atmosphere for a longer time and distance than coarse particles, hence the PM2.5 from the urban and industrial area of Tanggu District could influence the suburban air condition. Figure 2 shows the variations of PM2.5 and PM10 mass concentrations from Nov.12th to 17th, 2008. Overall, the concentrations of PM2.5 and PM10 during the day were higher than at night, probably due to day work of the industry and construction, intense traffic and human activity, and the influence of meteorological parameters (Ho et al., 2003; Wang et al., 2004, 2005, 2006b). The concentration of PM2.5 in day time was higher in the
Fig. 2 Concentration of PM2.5 and PM10 in day and night in three sites (U = Urban area, I = Industrial area, S = Suburb, 2.5 = PM2.5, 10 = PM10.)
Dan YANG et al. Characterization of PAHs in PM2.5 and PM10 in Tanggu District, Tianjin
suburb than in the industrial area, probably due to the long range transport (LRT) of PM2.5 from other areas. 3.2
PAHs in PM
Sixteen PAHs, Naphthalene (NaP), Acenaphthylene (Acy), Acenaphthene (Ace), Fluorene (Flu), Phenanthrene (Phe), Anthracene (Ant), Fluoranthene (Fluo), Pyrene (Pyr), Benzo[a]anthracene (BaA), Chrysene (Chr), Benzo[b] fluoranthene (BbF), Benzo[k]fluoranthene (BkF), Benzo [a]pyrene (BaP), Indeno[1,2,3-cd]pyrene (Ind), Dibenzo [a,h]anthracene (Dib) and Benzo[ghi]perylene (BghiP), were detected in PM10, and PM2.5 except Ind, Dib and BghiP. Concentrations of total PAHs in PM2.5 and PM10 were 8.47–113.94 ng/m3 with an average of 62.88 ng/m3 and 21.07–118.23 ng/m3 with an average of 73.42 ng/m3, respectively. Content of PAHs in PM2.5 and PM10 were found highest in the urban site and lowest in the suburban site, and PAHs concentration in daytime was higher than at night (Fig. 3). Among the PAHs, concentration of Acy was lower and Ant was higher than other compounds in PM2.5 and PM10. Detection rate of BaP was 70.8%, and all of them exceeded the air criteria of World Health Organization (1 ng/m3), indicating the air pollution of PAHs in Tanggu District was serious. In comparison to previous research, PAHs contents in PM2.5 in Tanggu District were lower than the heaviest traffic road in Qingdao (263 ng/m3), China (Guo, et al., 2009) and much higher than downtown Atlanta (3.16–3.40 ng/m3), US (Li et al., 2009), whereas in PM10, concentration of PAHs was significantly higher than Algiers (15.8–29.3 ng/m3), Algeria (Ladji et al., 2009) and the Greater Area of Athens, Greece (7.9 ng/m3) (Mantis et al., 2005) in winter. We found significant differences in concentrations among different PAHs, due to the adsorption effect of molecular weight. We divided the PAHs into four groups according to number of benzene rings including groups
Fig. 3 night)
Variation of PAHs in PM in day and night (d = day, n =
327
with 2 rings (NaP, Acy, Ace and Flu), 3 rings (Phe, Ant and Fluo), 4 rings (Pyr, BaA, Chr, BbF and BkF), and 5–6 rings (BaP, Ind, Dib and BghiP). As shown in Fig. 4, the light ring PAHs (2–4 rings) were dominant in both PM2.5 and PM10 in all day measurements, which is inconsistent with the results of Atlanta (Li et al., 2009) and Brazil (Bourotte et al., 2005), which found the main contribution of 5–6 rings. As the heavy ring PAHs (5–6 rings) have low vapor pressure and low volatility, they were expected to exist primarily in the PM rather than light rings ones. But with the high volatility, light ring PAHs transport better in the atmosphere than heavy ones, which lead to erratic distribution. In addition, it’s interesting to find that the percentage of 5–6 rings PAHs in PM10 was higher than in PM2.5. As we know, higher-molecular weight PAHs are expected to require more time than lower-molecular weight species to partition to coarse particles, thus tend to remain in fine particles (Chrysikou et al., 2009). Moreover, it should be mentioned that fine particles might coagulate into coarse particles (Venkataraman et al., 1999). And the relatively stable 5–6 ring PAHs with fine particles probably contributed to the coagulation of the coarse particles to make the high percentage in PM10. From the above discussion, concentration of total PAHs and PM showed similar variation in the study. Therefore, it is necessary to investigate the relationships between PM and PAHs. Figure 5 shows the positive correlation between the PAHs and PM. The relationship of PAHs and PM2.5(r = 0.689, p < 0.05) was higher than PAHs and PM10 (r = 0.570, p < 0.05), illustrated PAHs tend to adsorb in the PM2.5, probably attributed to the smaller PM having a larger specific surface area to adsorb organic chemicals. 3.3
Sources estimation
Principal components analysis (PCA) with varimax rotation was performed on the 48 data sets at 3 sites to apportion the source of 16 PAHs in Tanggu District. The loading of three principal factors accounted for 82.9% of the total variability. As showed in Fig. 6, Factor 1, accounted 43.4% of the total variability, was heavily loaded with Acy, Ace, Flu, Phe, and Ant, which are typical markers for coke production (Simcik et al., 1999). It appears that both biomass (mainly straw) burning and coke production in Tianjin is important source of PAHs (Zuo et al., 2007). Factor 2 mainly with Pyr, BaA, Chr, BbF, BkF accounted for 22.1% of the total variance. These PAHs are identified as typical markers for pyrogenic sources (coal and petroleum combustion) (Simcik et al., 1999; Larsen and Baker, 2003). It appears that heating in winter is an important energy as well as PAHs source in Tianjin. Factor 3 explained 17.4% of the total variance, including Ind, Dib, and BghiP, which indicate a vehicular source (Simcik et al., 1999; Larsen and Baker, 2003). On the other hand, the characteristic ratios of PAHs can give the information to distinguish different resources in
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Fig. 4 Percentage of different rings of PAHs in PM
Fig. 5 Correlation of PAHs concentration in PM
ambient air of suburban, industrial and urban areas. In comparison to the target value (Table 2), the ratio of Pyr/ BaP is lower than 2 in urban areas, which indicates that combustion of coal is the major source of PAHs. In the industrial region, the ratio of Pyr/BaP is between 2 and 6, the ratio of Flu/Pyr is lower than 1, and the ratio of Fluor/ (Pyr + Flu) is larger than 0.5 suggest traffic releasing, petroleum, and wood burning are predominant sources of PAHs in this region. In the suburban area, the ratio of Flu/ Pyr and Fluor/(Pyr + Flu) are the same as the ratios in industrial the region, and the ratio of Pyr/BaP is lower than 2 indicating possible mixture of emission from wood, coal, and petroleum combustion was the main source of PAHs in the suburb. The suburb is considered to be a relatively clean area in Tanggu District; the complex sources of PAHs in the suburb indicated the possible transportation from urban and industrial areas or other polluted regions.
Fig. 6
Loading of three principal factors for PAHs in PM
Dan YANG et al. Characterization of PAHs in PM2.5 and PM10 in Tanggu District, Tianjin
Table 2
Characteristic ratios of PAHs in study sites and reference targets Pyr/BaP
Flu/Pyr
Fluor/(Pyr + Flu)
Urban site
1.43
1.16
0.63
Industrial site
2.11
0.9
0.68
Suburb site
1.41
0.97
0.79
suburban area. The concentrations of PM2.5 and PM10 during the day were higher than at night, probably due to day work of the industry and construction, intense traffic, and human activity. The significant discrepancy of PM in day and night was found in the suburb, illustrated LRT of PM from urban and industrial areas were the main sources affecting PM contents in the suburb. Sixteen PAHs were analyzed in PM10 and PM2.5. Concentrations of total PAHs in PM2.5 and PM10 were 8.47–113.94 ng/m3 with average of 62.88 ng/m3 and 21.07–118.23 ng/m3 with average of 73.42 ng/ m3, respectively. Significant differences were found in concentrations among different PAHs, for the molecular weight affected concentration of PAHs adsorbed on the particles, and the result illustrated PAHs with 2–4 benzene rings were dominant in both PM2.5 and PM10 in daytime measurements. The higher correlation coefficient of PAHs and PM2.5 showed PAHs tend to adsorb in the PM2.5 rather than in the PM10. Three principal factors representing three sources of PAHs in Tanggu District, which were coke production, pyrogenic sources, and vehicular source, were extracted by principal component analysis. Combustion of coal was the major source of PAHs in the urban area. In the industrial region, traffic releasing and petroleum and wood burning were the predominant sources of PAHs. For the suburban area, the possible sources of PAHs were not only from the combustion of coal, wood, and petroleum, also influenced from LRT from urban and industrial areas or other polluted regions. Acknowledgements We are grateful for the assistance of our group members in the State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences and Tanggu Environmental Department for their support during the study.
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