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Size-segregated chemical characteristics of aerosol during haze in an urban area of the Pearl River Delta region, China
Urban Climate 4 (2013) 74–84
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Size-segregated chemical characteristics of aerosol during haze in an urban area of the Pearl River Delta region, China Guohua Zhang a,b, Xinhui Bi a,⇑, Lo Yin Chan a, Xinming Wang a, Guoying Sheng a, Jiamo Fu a,c a State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, PR China b Graduate University of Chinese Academy of Sciences, Beijing 100049, PR China c School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, PR China
a r t i c l e
i n f o
Article history: Received 30 September 2012 Revised 5 April 2013 Accepted 6 May 2013
Keywords: Haze Size distribution Particle Chemical composition Light extinction PRD
a b s t r a c t This study focuses on the chemical characteristics of size-segregated aerosols and the size distribution of submicron aerosol in an urban area of Pearl River Delta (PRD) region, China during 23th October 2010 and 10th January 2011. Light dry haze, with mean PM3 concentration at 130.2 ± 25.4 lg m3, approximately 1.6 times that for clear days, was frequently observed throughout this period. A particle mass build-up period from 27th October to 06th November 2010 was obtained corresponding to the enhanced light extinction. The results show that organic matter (OM), SO2 4 , þ NO 3 and NH4 increased remarkably on the hazy days, and the major enhancement of these species was found in the size range of 0.49–1.5 lm. Higher fraction of SO2 4 and NO3 in the size range of 0.95–1.5 lm on hazy days increased the water uptake and also the mass concentration. The yield of secondary organics in the size range <0.49 lm showed strong dependent on the aerosol acidity on the hazy days. Light extinction coefficients of different chemical components were also estimated by IMPROVE protocol. Sulfate and OM played an important role in visibility impairment, followed by nitrate (being more important on hazy days) and elemental carbon (EC). The results would help us to better understand the physical and chemical properties of atmospheric aerosols and their influence on the formation of haze in the PRD region. Ó 2013 Elsevier Ltd. All rights reserved.
⇑ Corresponding author. Tel.: +86 20 85290195; fax: +86 20 85290288. E-mail address: [email protected] (X. Bi). 2212-0955/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.uclim.2013.05.002
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1. Introduction Pearl River Delta (PRD) region, especially its urban areas, has been subjected to substantial air pollution under a rapid industrialization (Chan and Yao, 2008; Streets et al., 2008). Haze occurred frequently (approximately 150 days year1) for the years between 1980 and 2006 (Huang et al., 2008; Deng et al., 2008), and causes a deep concern due to its strong impact on various aspects of our living environment, such as health related problems, visibility impairment and regional climate change (Ma et al., 2010; Quan et al., 2011). Schichtel et al. (2001) demonstrated the correlation between a declination of haze over the United States and the reduction of PM2.5 and sulfur emission. Variations of chemical compositions in the atmospheric aerosols can strongly impact the optical properties of particles and lead to the formation of haze under certain meteorological conditions (Kim Oanh and Leelasakultum, 2011; Wu et al., 2005). Several studies on the chemical and physical characteristics of atmospheric aerosols have revealed high levels of water soluble inorganic ions þ (WSII) (e.g., SO2 4 , NO3 , NH4 ) and secondary organic aerosol (SOA) during haze episodes in the PRD region (Tan et al., 2009). Combination of ambient observations and theoretical calculation, Cheng et al. (2008) and Yu et al. (2010) suggested the important role of elemental carbon (EC), organic matter (OM), ammonium sulfate and ammonium nitrate on the atmospheric light extinction in the PRD region. Cheng et al. (2008) also indicated that increase of aerosol water content ([H2O]) on hazy days may substantially contribute to the enhanced light extinction. Knowledge on the size-resolved chemical composition is a necessary prerequisite to understand the physical and chemical atmospheric processes affecting aerosol properties during hazy episodes (Cheng et al., 2011; Huang and Yu, 2008). In this study, chemical characteristics of size-segregated aerosols, coupled with size distribution of submicron particles, was investigated in an urban area of PRD region. The concentrations of chemical compositions were further applied to calculate the aerosol acidity and their contribution to light extinction. The aim is to improve the understanding on the difference in physical and chemical properties of atmospheric aerosols between the clear and hazy days. 2. Material and methods 2.1. Ambient sampling Particulate matter smaller than 10 lm was collected on Whatman quartz fiber filter using an Andersen model SA235 sampler, equipped with a size-selective inlet high volume cascade impactor (Andersen Instruments Inc.). The sampler, with air flow rate at 1.13 m3 min1, was set up on the rooftop of a 15 m-high building in Guangzhou Institute of Geochemistry, Chinese Academy of Sciences. The sampling site is surrounded by heavily trafficked roads and dense residential areas, representing a typical urban location. The sampling lasted for 24 h or 48 h, generally starting at 8:00 a.m. Before sampling, filters were pre-heated at 600 °C for 4 h. The filters were also conditioned before and after sampling in an electronic hygrothermostat for 24 h, at 25 °C and 50% relative humidity (RH). The filters were stored in a refrigerator at 40 °C to prevent the evaporation of semi-volatile components before an analysis. Particle concentration of each sample set, named by time sequence (set 1, set 2, set 3, . . ., set 22), and the corresponding sampling periods are listed in Table S1 of the Supplementary material. A total of 22 set size-segregated aerosol filter samples were collected during the 23th October 2010 to 10th January 2011. Due to the sampling period overlapping with the Asian Game held in Guangzhou (between 1st November and 20th December 2010), the air quality guarantee program and the traffic restriction were enforced, the number of vehicles on the roads during the Asian Games were about half that of normal. Other dominant emission sources such as power plants and substandard factories were also restricted under this program. Each sample set consisted of six stages, representing the following size ranges: <0.49, 0.49–0.95, 0.95–1.5, 1.5–3.0, 3.0–7.2, and 7.2–10.0 lm. The cut size of 3.0 lm was used to divide PM10 into fine and coarse particles since the cut size of 2.5 lm was not available with the cascade impactor in this study. A hazy day can be defined when daily mean visibility is below 10 km with the absence of other factors (e.g., extremely high RH, precipitation or dust
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storm) (Wu et al., 2007). Under the criteria, there were seven sample sets (sets 2, 3, 4, 8, 10, 19, 20) and 15 sample sets for clear and hazy days, respectively. The meteorological parameters, such as temperature, RH, wind speed, and visibility during the sampling period were available from http:// www.wunderground.com. 2.2. Analysis of OC, EC and WSII The concentrations of organic carbon (OC) and EC were analyzed by the thermal/optical carbon analyzer (Sunset laboratory, OR, USA) and the analysis protocol followed the NIOSH Method 5040 (Birch and Cary, 1996). Four temperature steps (325, 500, 620, and 870 °C) were applied in the first stage of analysis with the presence of pure helium. After cooling down to 550 °C, another program started with four temperature steps (625, 700, 775, and 850 °C) in a mixture of 2% O2/98% He. Charring correction using optical transmittance is only applied to the filter at backup stage (<0.49 lm) of uniform deposition, since it is not appropriate to determine the OC and EC split point for other filters of non-uniform deposition in cascade impactor (Huang and Yu, 2008). The OC and EC split point for other filters was set as the same value of that for the backup filter. Duplicate measurements for each sample showed good analytical precision, with the average relative standard deviation lower than 6% for both OC and EC. This application should be acceptable for the determination of OC and EC split point, although there is still some limitation (Huang and Yu, 2008). In the thermal/optical method, OC evolves in the inert atmosphere and produces pyrolyzed organic carbon (POC), which is expected to be dependent on chemical composition of aerosols and vary among aerosols within different size bins. POC may have the similar light attenuation coefficient with native EC, and evolves before the native EC in the oxidizing atmosphere (2% O2/98% He) (Han et al., 2010). The artifacts may be inevitable in this study. The limits of detection for EC and OC were 0.2 and 0.5 lg m3, respectively. A factor of 1.4 was applied in order to convert OC to OM (Turpin and Lim, 2001; Russell, 2003). Differences among different size ranges were not taken into account because of insufficient knowledge on accurate chemical compositions of OM. The concentrations of WSII were analyzed according to the procedure given by Peltier et al. (2008). Aliquot of filter was extracted with 10 mL ultrapure water (Milli-Q Grandient, Millipore Company, USA) in an ultrasonic bath for 30 min. The extract was filtered using a 0.45 lm Teflon filter, and subsequently analyzed by ion chromatography (Metrohm, Houston, TX). The limits of detection were 3 2 + 0.022, 0.032, 0.136, 0.018, 0.010, 0.014, 0.046, 0.017 and 0.041 lg m3 for Cl, NO 3 , PO4 , SO4 , Na , þ + 2+ 2+ NH4 , K , Mg and Ca , respectively. The reproducibility tests showed that the relative standard deviation of each ion was generally lower than 5%. 2.3. Determination of submicron particle size distributions A cylindrical scanning differential mobility analyzer, collocated with a butanol-based condensation particle counter (SMPS + C 5.401, GRIMM Aerosol Technik GmbH & Co. KG) was operated to measure the particle size distribution from 23th October to 06th November 2010. An operating cycle took approximate 7 min to complete a logarithmic scan from a mobility diameter of 11.1 nm to 1083.3 nm with 44 channels. The sheath and excess flow of 3.0 L min1 were used, with a 10:1 flow rate ratio of sheath-to-aerosol. A conversion of mobility diameter to aerodynamic diameter was performed using the method described by DeCarlo et al. (2004), assuming the particles were spherical with mass density of 1.7 g cm3 (Cheng et al., 2006). Therefore, the converted aerodynamic diameter covered the size range between 19 and 1000 nm (mobility diameter between 11.1–595 nm) and only this fraction was involved in the discussion. Overall, more than 2300 valid size distributions were obtained. 3. Results and discussion 3.1. Particle mass and number concentrations The detected PM3 varied in a wide range between 47.0 and 186.1 lg m3, and its average concentration was 114.4 ± 33.4 lg m3. The ratio of PM3/PM10 ranged from 0.70 to 0.90 with an
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average of 0.80, indicating severe fine aerosol pollution in the PRD region. Compared to clear days, hazy days were typically characterized by lower visibility (7.8 ± 1.9 km) and wind speed (2.5 ± 1.2 m/s), and higher RH (52.6 ± 6.7%) and pollution level. The average PM3 concentration on hazy days was 130.2 ± 25.4 lg m3, about 1.6 times that on clear days. Information on the variations of PM3 concentrations and meteorological parameters (visibility, wind speed, RH and temperature) throughout the sampling can be found in Fig. S1. It is noted that RH at this level, 52.6 ± 6.7% was much lower than those reported on the typical hazy days (71.8 ± 7.4%) (Tan et al., 2009), and it reflected dry haze. As shown in Fig. 1, aerosol size distributions exhibited bimodal pattern with a fine mode (<0.49 lm) and a coarse mode (3.0–7.2 lm) on both clear and hazy days. Particles in the size range <0.49 lm were the most abundant compared to the other sizes, accounting for almost half of PM10. However, the particles in the size range of 0.49–0.95 lm and 0.95–1.5 lm were mainly enhanced on hazy days. This phenomenon reflects the favorable growth of particles through the formation of secondary species such as sulfate and nitrate during hazy period, and also regional transport (Yue et al., 2010). During the SMPS + C observation period (23th October–06th November 2010), number concentration of submicron particles (19–1000 nm) varied between 2.3 103 and 5.6 104 cm3. The relative occurrence frequency for total particle number concentration was distributed around the mean value of 1.1 104 cm3 with the highest frequency at (6480–8720) cm3 on clear days, and around a mean value of 1.8 104 cm3 with the highest frequency at (8720–10,960) cm3 on hazy days (Fig. S2), suggesting that the concentration of particles increased and the distribution shifted toward larger particles during the haze. A continuous built up of particle mass from 27th October to 06th November 2010 was observed. Fig. 2 illustrates the hourly averaged derived mass concentration from SMPS + C measurements and derived light extinction coefficient bext (according to Koschmieder relationship: bext = 3.912/Vis, where Vis is the mean visibility in a defined period), and a significant correlation (r = 0.75, p < 0.001) between them. The trend suggests that mass concentration of atmospheric aerosols experienced a boost, starting between 27th and 28th October, and reached the peak concentration in the morning of 06th November 2010. The highest bext (2000 Mm1) observed in the morning of the same day was consistent with the observation of SMPS + C (hourly average derived mass concentration of submicron particles: 300 lg m3). The trend of averaged derived mass concentration in 48 h from SMPS + C measurements was consistent with that of PM1.5 from filter samples (r = 0.97,
Figure 1. The mass size distribution, size-resolved mass fraction of PM10 on clear and hazy days, and the enhancement ratio of size-resolved particle mass from clear to hazy days.
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Figure 2. Hourly averaged derived mass concentration from SMPS + C measurements and derived light extinction (bext) from visibility.
p < 0.001) in Fig. S3. The discrepancy is attributed to the missing data of SMPS + C measurements and the assumption of effective density for the conversion between mobility and aerodynamic diameter.
3.2. Concentration level of chemical components The most abundant chemical species found in PM10 samples were carbonaceous species (OM and þ EC) and WSII dominated by SO2 4 , NO3 , and NH4 . Mean concentrations for OM and EC (39.3 and 3 5.3 lg m ) in PM10 on hazy days were much higher than those (24.8 and 3.2 lg m3) on clear days, despite of their similar contribution to PM10 (Table S2). Similarly, mean concentrations for SO2 4 , NO3 , þ 3 NH4 in PM10 on hazy days were 34.8, 20.9, and 10.7 lg m , respectively, and they were much higher than those on clear days (22.1, 8.2 and 6.1 lg m3). It was interesting that NO 3 represented 15% and 25% of WSII for clear and hazy days, respectively, indicating that meteorological condition might facilitate the formation of NO 3 on hazy days (Sun et al., 2006; Wang et al., 2006a). Similarly, a very 2 þ high enhancement of NO 3 than SO4 and NH4 on hazy days has also been observed in Beijing and Guangzhou, which might be an outcome of a higher conversion rate of NOx to NO 3 on hazy days (Tan et al., 2009; Wang et al., 2006b).
3.3. Size distribution of chemical components 3.3.1. Water soluble inorganic ions (WSII) þ Average mass size distribution, size-segregated mass fraction of SO2 4 , NO3 and NH4 , and their mass enhancement ratio from clear to hazy days within different size ranges are displayed in Fig. 3. It shows þ that SO2 4 , NO3 and NH4 mainly existed in the size range <0.49 lm on both clear and hazy days. The major difference between their size distributions on clear and hazy days is the appearance of second ary peaks of SO2 4 and NO3 in the size range of 0.95–1.5 lm on hazy days, however, it did not occur for þ þ NH4 . The enhancement ratio of SO2 4 , NO3 and NH4 in this size range was 3.2, 4.4, and 1.8, respectively, which is seemingly inconsistent with the total mass enhancement ratio (1.8) provided in Fig. 1. The inconsistency is mainly due to the chemically undetermined mass interpreted as water, dust and the other water insoluble components (Matta et al., 2003; Temesi et al., 2001). The undetermined mass accounted for 35% of particulate mass for clear days, while it only represented less than þ 7% for hazy days in this size range. On the contrary, SO2 4 , NO3 and NH4 together accounted for 34% and 63% of particulate mass in the size range of 0.95–1.5 lm for clear and hazy days, respectively. Therefore, the decrease of these undetermined components on hazy days should offset part of the enhancement of the major chemical constituents (i.e., sulfate, nitrate and ammonium).
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þ Figure 3. Mass size distributions of SO2 4 , NO3 and NH4 , with size-segregated enhancement ratio from clear to hazy days (left), and their mass fraction in each size range (stack bar at the right side) for clear and hazy days.
The droplet mode of SO2 4 and NO3 in the size range of 1.0–1.8 lm was similarly reported in prior studies (Anlauf et al., 2006; Guo et al., 2010; Liu et al., 2008). Since the droplet mode aerosol is dominantly produced from an aqueous mechanism such as cloud/fog processing, it is believed that particles in the size range of 0.49–1.5 lm might be influenced by the regional transport and follow-up growth. In the size range of 0.95–1.5 lm, water concentration [H2O] estimated by the Aerosol Inorganic Model (E-AIM, more details are provided in the Supplementary material) on hazy days was 5 times higher than on clear days (Table 1). Higher fraction of SO2 4 and NO3 in this size range probably increased the water uptake and thus the aerosol mass concentration (McFiggans et al., 2006). In addition, the higher [H2O] in wet aerosols might promote the production of NO 3 through enhanced hydrolysis of N2O5 (Pathak et al., 2011) and the condensation of semi-volatile nitrate (e.g., ammonium nitrate) (Hu et al., 2008), and the production of SO2 4 through aqueous-phase SO2 oxidation (Anlauf et al., 2006). Large amount of [H2O] on hazy days would further enhance the light extinction and deteriorate the visibility, supported by the moderate correlation between bext and RH in this study and it is consistent with previous results by Cheng et al. (2011). 2 þ The high occurrence of molar ratio NHþ 4 =SO4 < 2 suggested that NH4 could not completely neutralize SO2 . Consequently, acidic aerosol was presented with a reason of low concentration of other 4 cations compared to NHþ 4 . An influence of species pattern on the aerosol acidity was estimated by EAIM. The total [H+], average [H2O] and free [H+] in the fine fraction on clear and hazy days are listed in Table 1. The average total [H+] ranged from 36.9 to 171.7 nmol/m3 on hazy days and 11.9 to 117.1 nmol/m3 on clear days, respectively. The total [H+] was comparable to those observed in
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Table 1 The average total [H+] (lg/m3), aerosol water content [H2O] (lg/m3) and free [H+] (nmol/m3) estimated from E-AIM on clear and hazy days. Free [H+]
Total [H+]
Free [H+]/total [H+]
Size bins (lm)
[H2O] Hazy
Clear
Hazy
Clear
Hazy
Clear
Hazy
Clear
<0.49 0.49–0.95 0.95–1.5 1.5–3.0
11.8 7.3 10.6 2.7
5.8 4.5 1.9 0.9
22.9 56.7 89.3 25.7
14.5 30.4 14.3 7.4
171.7 107.6 141.7 36.9
117.1 58.9 30.5 12.0
0.13 0.53 0.63 0.70
0.12 0.52 0.47 0.62
Figure 4. Mass size distributions of OC and EC, and size-segregated OC/EC ratio for both clear and hazy days.
Guanghzou (70 nmol/m3), Lanzhou (65 nmol/m3), and Hong Kong (51–103 nmol/m3), but significantly lower than Jinan, Beijing and Shanghai (220–390 nmol/m3) (Cheng et al., 2011; Pathak et al., 2003, 2009). More acidic aerosol was observed on hazy days, with free [H+] 1.6–6.2 times those on clear days, consistent with the previous observation in Jinan (Cheng et al., 2011). Aerosol acidity might have implication on the formation of SOA as discussed in the following.
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3.3.2. OC and EC Average size distributions of OC and EC both showed bimodal characteristics with a fine mode in the size range <0.49 lm and a coarse mode in the size range of 3–7.2 lm on both clear and hazy days (Fig. 4). Generally, secondary organic carbon (SOC) is estimated according to the minimum ratio method (Castro et al., 1999; Turpin and Huntzicker, 1995), which is described in the following equation:
SOC ¼ OCtotal EC ðOC=ECÞmin where OCtotal refers to the total measured ambient OC, and (OC/EC)min is the corresponding minimum OC/EC ratio in each size range. The (OC/EC)min value was 2.7 in the size range <0.49 lm, while higher value(>4.1) was obtained in the size range of 0.49–10 lm for both clear and hazy days. In this study, the estimation of SOC was only applied in the size range <0.49 lm. The association between formation of SOA and aerosol acidity was investigated by correlation analysis between SOC/OC and inferred normalized acid concentration (free [H+]/OC). It was found significant correlation (r = 0.82, p < 0.001) between SOC/OC and [H+]/OC in the size range <0.49 lm for hazy day samples (Fig. 5), suggesting that aerosol acidity might play an important role in the enhancement of SOC production (Pathak et al., 2011). However, there was not an obvious correlation found for clear day samples, which might be due to the limited samples. Experimental work (Jang et al., 2002; Surratt et al., 2007) and field observations (Pathak et al., 2011; Ding et al., 2011) have also emphasized the importance of acid-catalyzed mechanism in the formation of SOA. 3.4. Contribution of major species to light extinction Fig. 6 shows the derived light extinction bext, reconstructed light extinction bext,cal by a revised IMPROVE method (see Supplementary material), and mean contribution (excluding set 17 and 18) from each specie to bext,cal on clear and hazy days. It can be seen that bext and bext,cal exhibited moderate correlation (r = 0.71, p < 0.001). The major deviation was found for bext,cal of set 17 and 18, overestimated by 50% and 70%, respectively. Different from other samples, the sampling time for both the sets covered a hazy day and a clear day, with visibility at 14.4 and 7.4 km (set 17), 6.2 and 17.6 km (set 18), respectively. Higher correlation coefficient (r = 0.83, p < 0.001) was obtained when excluding these two samples from the analysis. However, a general underestimation still existed, which might be mainly attributed to the difference in mixing state of aerosol components (Chandra et al., 2004; Jacobson, 2001), an important factor affecting atmospheric light extinction (Yu et al., 2010).
0.7 SOC/OC = 0.11ln([H+]/OC) + 0.32, r = 0.82 0.6
SOC/OC
0.5 0.4 0.3 0.2
Hazy days Clear days
0.1 0 0
1
2 [H+ ]/OC
3
4
Figure 5. SOC/OC ratio as a function of [H+]/[OC] for acidic samples ([H+] > 0) in the size range <0.49 lm on clear and hazy days.
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Figure 6. Comparison between derived light extinction (bext, in dash line) and reconstructed light extinction (bext,cal) from IMPROVE method (upper). Pie plot (bottom) shows the average fractional contribution of atmospheric species to bext,cal on clear (left) and hazy days (right).
From a plot in Fig. 6, it is clear that sulfate and OM played a particularly important role in visibility impairment in urban Guangzhou, responsible for approximate 40% and 30%, respectively. Nitrate was the third important contributor, representing 11% of bext,cal on clear days, while it became more important on hazy day (16%). This was close to the contribution by EC for clear and hazy days, accounting for 11% and 10% of bext,cal, respectively. The contributions of these species to light extinction budget are comparable to those obtained by Jung et al. (2009) in urban Guangzhou. Cheng et al. (2008) also reported a similar contribution to light extinction by sulfate (40%) and EC (17%) during a polluted period in a rural area of PRD region. However, the contributions by OM (17%) and nitrate (<8%) were lower than those in this study. The discrepancy was attributed to the difference in chemical pattern and meteorological condition.
4. Conclusion The study presented chemical characterization of size-segregated aerosol samples and numberbased size distribution of submicron particles, during fall-winter period from 23th October 2010 to 10th January 2011. Average mass concentration of fine aerosol on hazy days was 130.2 ± 25.4 lg m3, 1.62 times that on clear days. Mean concentrations for OM (39.3 lg m3) and (5.3 lg m3) EC in PM10
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on hazy days were significantly higher than clear days (24.8 and 3.2 lg m3, respectively). Major WSII þ (SO2 4 , NO3 and NH4 ) in PM10 also remarkably increased on hazy days, 1.6, 2.6 and 1.8 times higher than clear days, respectively. It signifies the favorable formation of secondary aerosols, particularly NO 3 on hazy days. The results also showed that the major enhancement of these species on hazy days was in the size range of 0.49–0.95 lm and 0.95–1.5 lm, although the dominant mode of these species was in the size range <0.49 lm. The aerosol acidity might be associated with formation of SOA in the size range <0.49 lm. In addition, light extinction of these species was reconstructed and the result suggests that sulfate and OM played a dominant role in the visibility impairment, followed by nitrate and EC, while nitrate becoming more important on hazy days. However, the bias from many other factors (e.g., mixing state and/or RH) still existed in the estimation, and thus future research on the mixing state and hygroscopicity of the aerosol needs to be addressed for further understanding. Acknowledgments This work was supported by the National Nature Science Foundation of China (No. 41073077), ‘‘Strategic Priority Research Program (B)’’ of the Chinese Academy of Sciences (XDB05020205) and Guangzhou Institute of Geochemistry (GIGCAS 135 project Y234161001). The authors gratefully thank our group members Bo Huang, Ming Liu and Zhaofang Ren for their assistance in the deployment of sampling instruments and analysis of aerosol samples. This is contribution No. 1678 from GIGCAS. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http:// dx.doi.org/10.1016/j.uclim.2013.05.002. References Anlauf, K., Li, S.M., Leaitch, R., Brook, J., Hayden, K., Toom-Sauntry, D., Wiebe, A., 2006. 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Quan, J., Zhang, Q., He, H., Liu, J., Huang, M., Jin, H., 2011. Analysis of the formation of fog and haze in North China Plain (NCP). Atmos. Chem. Phys. 11, 8205–8214. Russell, L.M., 2003. Aerosol organic-mass-to-organic-carbon ratio measurements. Environ. Sci. Technol. 37, 2982–2987. Schichtel, B.A., Husar, R.B., Falke, S.R., Wilson, W.E., 2001. Haze trends over the United States, 1980–1995. Atmos. Environ. 35, 5205–5210. Streets, D.G., Yu, C., Wu, Y., Chin, M., Zhao, Z., Hayasaka, T., Shi, G., 2008. Aerosol trends over China, 1980–2000. Atmos. Res. 88, 174–182. Sun, Y.L., Zhuang, G.S., Tang, A.H., Wang, Y., An, Z.S., 2006. Chemical characteristics of PM2.5 and PM10 in haze-fog episodes in Beijing. Environ. Sci. Technol. 40, 3148–3155. Surratt, J.D., Lewandowski, M., Offenberg, J.H., Jaoui, M., Kleindienst, T.E., Edney, E.O., Seinfeld, J.H., 2007. Effect of acidity on secondary organic aerosol formation from isoprene. Environ. Sci. Technol. 41, 5363–5369. 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Size-segregated chemical characteristics of aerosol during haze in an urban area of the Pearl River Delta region, China Guohua Zhang a,b, Xinhui Bi a,⇑, Lo Yin Chan a, Xinming Wang a, Guoying Sheng a, Jiamo Fu a,c a State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, PR China b Graduate University of Chinese Academy of Sciences, Beijing 100049, PR China c School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, PR China
a r t i c l e
i n f o
Article history: Received 30 September 2012 Revised 5 April 2013 Accepted 6 May 2013
Keywords: Haze Size distribution Particle Chemical composition Light extinction PRD
a b s t r a c t This study focuses on the chemical characteristics of size-segregated aerosols and the size distribution of submicron aerosol in an urban area of Pearl River Delta (PRD) region, China during 23th October 2010 and 10th January 2011. Light dry haze, with mean PM3 concentration at 130.2 ± 25.4 lg m3, approximately 1.6 times that for clear days, was frequently observed throughout this period. A particle mass build-up period from 27th October to 06th November 2010 was obtained corresponding to the enhanced light extinction. The results show that organic matter (OM), SO2 4 , þ NO 3 and NH4 increased remarkably on the hazy days, and the major enhancement of these species was found in the size range of 0.49–1.5 lm. Higher fraction of SO2 4 and NO3 in the size range of 0.95–1.5 lm on hazy days increased the water uptake and also the mass concentration. The yield of secondary organics in the size range <0.49 lm showed strong dependent on the aerosol acidity on the hazy days. Light extinction coefficients of different chemical components were also estimated by IMPROVE protocol. Sulfate and OM played an important role in visibility impairment, followed by nitrate (being more important on hazy days) and elemental carbon (EC). The results would help us to better understand the physical and chemical properties of atmospheric aerosols and their influence on the formation of haze in the PRD region. Ó 2013 Elsevier Ltd. All rights reserved.
⇑ Corresponding author. Tel.: +86 20 85290195; fax: +86 20 85290288. E-mail address: [email protected] (X. Bi). 2212-0955/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.uclim.2013.05.002
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1. Introduction Pearl River Delta (PRD) region, especially its urban areas, has been subjected to substantial air pollution under a rapid industrialization (Chan and Yao, 2008; Streets et al., 2008). Haze occurred frequently (approximately 150 days year1) for the years between 1980 and 2006 (Huang et al., 2008; Deng et al., 2008), and causes a deep concern due to its strong impact on various aspects of our living environment, such as health related problems, visibility impairment and regional climate change (Ma et al., 2010; Quan et al., 2011). Schichtel et al. (2001) demonstrated the correlation between a declination of haze over the United States and the reduction of PM2.5 and sulfur emission. Variations of chemical compositions in the atmospheric aerosols can strongly impact the optical properties of particles and lead to the formation of haze under certain meteorological conditions (Kim Oanh and Leelasakultum, 2011; Wu et al., 2005). Several studies on the chemical and physical characteristics of atmospheric aerosols have revealed high levels of water soluble inorganic ions þ (WSII) (e.g., SO2 4 , NO3 , NH4 ) and secondary organic aerosol (SOA) during haze episodes in the PRD region (Tan et al., 2009). Combination of ambient observations and theoretical calculation, Cheng et al. (2008) and Yu et al. (2010) suggested the important role of elemental carbon (EC), organic matter (OM), ammonium sulfate and ammonium nitrate on the atmospheric light extinction in the PRD region. Cheng et al. (2008) also indicated that increase of aerosol water content ([H2O]) on hazy days may substantially contribute to the enhanced light extinction. Knowledge on the size-resolved chemical composition is a necessary prerequisite to understand the physical and chemical atmospheric processes affecting aerosol properties during hazy episodes (Cheng et al., 2011; Huang and Yu, 2008). In this study, chemical characteristics of size-segregated aerosols, coupled with size distribution of submicron particles, was investigated in an urban area of PRD region. The concentrations of chemical compositions were further applied to calculate the aerosol acidity and their contribution to light extinction. The aim is to improve the understanding on the difference in physical and chemical properties of atmospheric aerosols between the clear and hazy days. 2. Material and methods 2.1. Ambient sampling Particulate matter smaller than 10 lm was collected on Whatman quartz fiber filter using an Andersen model SA235 sampler, equipped with a size-selective inlet high volume cascade impactor (Andersen Instruments Inc.). The sampler, with air flow rate at 1.13 m3 min1, was set up on the rooftop of a 15 m-high building in Guangzhou Institute of Geochemistry, Chinese Academy of Sciences. The sampling site is surrounded by heavily trafficked roads and dense residential areas, representing a typical urban location. The sampling lasted for 24 h or 48 h, generally starting at 8:00 a.m. Before sampling, filters were pre-heated at 600 °C for 4 h. The filters were also conditioned before and after sampling in an electronic hygrothermostat for 24 h, at 25 °C and 50% relative humidity (RH). The filters were stored in a refrigerator at 40 °C to prevent the evaporation of semi-volatile components before an analysis. Particle concentration of each sample set, named by time sequence (set 1, set 2, set 3, . . ., set 22), and the corresponding sampling periods are listed in Table S1 of the Supplementary material. A total of 22 set size-segregated aerosol filter samples were collected during the 23th October 2010 to 10th January 2011. Due to the sampling period overlapping with the Asian Game held in Guangzhou (between 1st November and 20th December 2010), the air quality guarantee program and the traffic restriction were enforced, the number of vehicles on the roads during the Asian Games were about half that of normal. Other dominant emission sources such as power plants and substandard factories were also restricted under this program. Each sample set consisted of six stages, representing the following size ranges: <0.49, 0.49–0.95, 0.95–1.5, 1.5–3.0, 3.0–7.2, and 7.2–10.0 lm. The cut size of 3.0 lm was used to divide PM10 into fine and coarse particles since the cut size of 2.5 lm was not available with the cascade impactor in this study. A hazy day can be defined when daily mean visibility is below 10 km with the absence of other factors (e.g., extremely high RH, precipitation or dust
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storm) (Wu et al., 2007). Under the criteria, there were seven sample sets (sets 2, 3, 4, 8, 10, 19, 20) and 15 sample sets for clear and hazy days, respectively. The meteorological parameters, such as temperature, RH, wind speed, and visibility during the sampling period were available from http:// www.wunderground.com. 2.2. Analysis of OC, EC and WSII The concentrations of organic carbon (OC) and EC were analyzed by the thermal/optical carbon analyzer (Sunset laboratory, OR, USA) and the analysis protocol followed the NIOSH Method 5040 (Birch and Cary, 1996). Four temperature steps (325, 500, 620, and 870 °C) were applied in the first stage of analysis with the presence of pure helium. After cooling down to 550 °C, another program started with four temperature steps (625, 700, 775, and 850 °C) in a mixture of 2% O2/98% He. Charring correction using optical transmittance is only applied to the filter at backup stage (<0.49 lm) of uniform deposition, since it is not appropriate to determine the OC and EC split point for other filters of non-uniform deposition in cascade impactor (Huang and Yu, 2008). The OC and EC split point for other filters was set as the same value of that for the backup filter. Duplicate measurements for each sample showed good analytical precision, with the average relative standard deviation lower than 6% for both OC and EC. This application should be acceptable for the determination of OC and EC split point, although there is still some limitation (Huang and Yu, 2008). In the thermal/optical method, OC evolves in the inert atmosphere and produces pyrolyzed organic carbon (POC), which is expected to be dependent on chemical composition of aerosols and vary among aerosols within different size bins. POC may have the similar light attenuation coefficient with native EC, and evolves before the native EC in the oxidizing atmosphere (2% O2/98% He) (Han et al., 2010). The artifacts may be inevitable in this study. The limits of detection for EC and OC were 0.2 and 0.5 lg m3, respectively. A factor of 1.4 was applied in order to convert OC to OM (Turpin and Lim, 2001; Russell, 2003). Differences among different size ranges were not taken into account because of insufficient knowledge on accurate chemical compositions of OM. The concentrations of WSII were analyzed according to the procedure given by Peltier et al. (2008). Aliquot of filter was extracted with 10 mL ultrapure water (Milli-Q Grandient, Millipore Company, USA) in an ultrasonic bath for 30 min. The extract was filtered using a 0.45 lm Teflon filter, and subsequently analyzed by ion chromatography (Metrohm, Houston, TX). The limits of detection were 3 2 + 0.022, 0.032, 0.136, 0.018, 0.010, 0.014, 0.046, 0.017 and 0.041 lg m3 for Cl, NO 3 , PO4 , SO4 , Na , þ + 2+ 2+ NH4 , K , Mg and Ca , respectively. The reproducibility tests showed that the relative standard deviation of each ion was generally lower than 5%. 2.3. Determination of submicron particle size distributions A cylindrical scanning differential mobility analyzer, collocated with a butanol-based condensation particle counter (SMPS + C 5.401, GRIMM Aerosol Technik GmbH & Co. KG) was operated to measure the particle size distribution from 23th October to 06th November 2010. An operating cycle took approximate 7 min to complete a logarithmic scan from a mobility diameter of 11.1 nm to 1083.3 nm with 44 channels. The sheath and excess flow of 3.0 L min1 were used, with a 10:1 flow rate ratio of sheath-to-aerosol. A conversion of mobility diameter to aerodynamic diameter was performed using the method described by DeCarlo et al. (2004), assuming the particles were spherical with mass density of 1.7 g cm3 (Cheng et al., 2006). Therefore, the converted aerodynamic diameter covered the size range between 19 and 1000 nm (mobility diameter between 11.1–595 nm) and only this fraction was involved in the discussion. Overall, more than 2300 valid size distributions were obtained. 3. Results and discussion 3.1. Particle mass and number concentrations The detected PM3 varied in a wide range between 47.0 and 186.1 lg m3, and its average concentration was 114.4 ± 33.4 lg m3. The ratio of PM3/PM10 ranged from 0.70 to 0.90 with an
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average of 0.80, indicating severe fine aerosol pollution in the PRD region. Compared to clear days, hazy days were typically characterized by lower visibility (7.8 ± 1.9 km) and wind speed (2.5 ± 1.2 m/s), and higher RH (52.6 ± 6.7%) and pollution level. The average PM3 concentration on hazy days was 130.2 ± 25.4 lg m3, about 1.6 times that on clear days. Information on the variations of PM3 concentrations and meteorological parameters (visibility, wind speed, RH and temperature) throughout the sampling can be found in Fig. S1. It is noted that RH at this level, 52.6 ± 6.7% was much lower than those reported on the typical hazy days (71.8 ± 7.4%) (Tan et al., 2009), and it reflected dry haze. As shown in Fig. 1, aerosol size distributions exhibited bimodal pattern with a fine mode (<0.49 lm) and a coarse mode (3.0–7.2 lm) on both clear and hazy days. Particles in the size range <0.49 lm were the most abundant compared to the other sizes, accounting for almost half of PM10. However, the particles in the size range of 0.49–0.95 lm and 0.95–1.5 lm were mainly enhanced on hazy days. This phenomenon reflects the favorable growth of particles through the formation of secondary species such as sulfate and nitrate during hazy period, and also regional transport (Yue et al., 2010). During the SMPS + C observation period (23th October–06th November 2010), number concentration of submicron particles (19–1000 nm) varied between 2.3 103 and 5.6 104 cm3. The relative occurrence frequency for total particle number concentration was distributed around the mean value of 1.1 104 cm3 with the highest frequency at (6480–8720) cm3 on clear days, and around a mean value of 1.8 104 cm3 with the highest frequency at (8720–10,960) cm3 on hazy days (Fig. S2), suggesting that the concentration of particles increased and the distribution shifted toward larger particles during the haze. A continuous built up of particle mass from 27th October to 06th November 2010 was observed. Fig. 2 illustrates the hourly averaged derived mass concentration from SMPS + C measurements and derived light extinction coefficient bext (according to Koschmieder relationship: bext = 3.912/Vis, where Vis is the mean visibility in a defined period), and a significant correlation (r = 0.75, p < 0.001) between them. The trend suggests that mass concentration of atmospheric aerosols experienced a boost, starting between 27th and 28th October, and reached the peak concentration in the morning of 06th November 2010. The highest bext (2000 Mm1) observed in the morning of the same day was consistent with the observation of SMPS + C (hourly average derived mass concentration of submicron particles: 300 lg m3). The trend of averaged derived mass concentration in 48 h from SMPS + C measurements was consistent with that of PM1.5 from filter samples (r = 0.97,
Figure 1. The mass size distribution, size-resolved mass fraction of PM10 on clear and hazy days, and the enhancement ratio of size-resolved particle mass from clear to hazy days.
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Figure 2. Hourly averaged derived mass concentration from SMPS + C measurements and derived light extinction (bext) from visibility.
p < 0.001) in Fig. S3. The discrepancy is attributed to the missing data of SMPS + C measurements and the assumption of effective density for the conversion between mobility and aerodynamic diameter.
3.2. Concentration level of chemical components The most abundant chemical species found in PM10 samples were carbonaceous species (OM and þ EC) and WSII dominated by SO2 4 , NO3 , and NH4 . Mean concentrations for OM and EC (39.3 and 3 5.3 lg m ) in PM10 on hazy days were much higher than those (24.8 and 3.2 lg m3) on clear days, despite of their similar contribution to PM10 (Table S2). Similarly, mean concentrations for SO2 4 , NO3 , þ 3 NH4 in PM10 on hazy days were 34.8, 20.9, and 10.7 lg m , respectively, and they were much higher than those on clear days (22.1, 8.2 and 6.1 lg m3). It was interesting that NO 3 represented 15% and 25% of WSII for clear and hazy days, respectively, indicating that meteorological condition might facilitate the formation of NO 3 on hazy days (Sun et al., 2006; Wang et al., 2006a). Similarly, a very 2 þ high enhancement of NO 3 than SO4 and NH4 on hazy days has also been observed in Beijing and Guangzhou, which might be an outcome of a higher conversion rate of NOx to NO 3 on hazy days (Tan et al., 2009; Wang et al., 2006b).
3.3. Size distribution of chemical components 3.3.1. Water soluble inorganic ions (WSII) þ Average mass size distribution, size-segregated mass fraction of SO2 4 , NO3 and NH4 , and their mass enhancement ratio from clear to hazy days within different size ranges are displayed in Fig. 3. It shows þ that SO2 4 , NO3 and NH4 mainly existed in the size range <0.49 lm on both clear and hazy days. The major difference between their size distributions on clear and hazy days is the appearance of second ary peaks of SO2 4 and NO3 in the size range of 0.95–1.5 lm on hazy days, however, it did not occur for þ þ NH4 . The enhancement ratio of SO2 4 , NO3 and NH4 in this size range was 3.2, 4.4, and 1.8, respectively, which is seemingly inconsistent with the total mass enhancement ratio (1.8) provided in Fig. 1. The inconsistency is mainly due to the chemically undetermined mass interpreted as water, dust and the other water insoluble components (Matta et al., 2003; Temesi et al., 2001). The undetermined mass accounted for 35% of particulate mass for clear days, while it only represented less than þ 7% for hazy days in this size range. On the contrary, SO2 4 , NO3 and NH4 together accounted for 34% and 63% of particulate mass in the size range of 0.95–1.5 lm for clear and hazy days, respectively. Therefore, the decrease of these undetermined components on hazy days should offset part of the enhancement of the major chemical constituents (i.e., sulfate, nitrate and ammonium).
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þ Figure 3. Mass size distributions of SO2 4 , NO3 and NH4 , with size-segregated enhancement ratio from clear to hazy days (left), and their mass fraction in each size range (stack bar at the right side) for clear and hazy days.
The droplet mode of SO2 4 and NO3 in the size range of 1.0–1.8 lm was similarly reported in prior studies (Anlauf et al., 2006; Guo et al., 2010; Liu et al., 2008). Since the droplet mode aerosol is dominantly produced from an aqueous mechanism such as cloud/fog processing, it is believed that particles in the size range of 0.49–1.5 lm might be influenced by the regional transport and follow-up growth. In the size range of 0.95–1.5 lm, water concentration [H2O] estimated by the Aerosol Inorganic Model (E-AIM, more details are provided in the Supplementary material) on hazy days was 5 times higher than on clear days (Table 1). Higher fraction of SO2 4 and NO3 in this size range probably increased the water uptake and thus the aerosol mass concentration (McFiggans et al., 2006). In addition, the higher [H2O] in wet aerosols might promote the production of NO 3 through enhanced hydrolysis of N2O5 (Pathak et al., 2011) and the condensation of semi-volatile nitrate (e.g., ammonium nitrate) (Hu et al., 2008), and the production of SO2 4 through aqueous-phase SO2 oxidation (Anlauf et al., 2006). Large amount of [H2O] on hazy days would further enhance the light extinction and deteriorate the visibility, supported by the moderate correlation between bext and RH in this study and it is consistent with previous results by Cheng et al. (2011). 2 þ The high occurrence of molar ratio NHþ 4 =SO4 < 2 suggested that NH4 could not completely neutralize SO2 . Consequently, acidic aerosol was presented with a reason of low concentration of other 4 cations compared to NHþ 4 . An influence of species pattern on the aerosol acidity was estimated by EAIM. The total [H+], average [H2O] and free [H+] in the fine fraction on clear and hazy days are listed in Table 1. The average total [H+] ranged from 36.9 to 171.7 nmol/m3 on hazy days and 11.9 to 117.1 nmol/m3 on clear days, respectively. The total [H+] was comparable to those observed in
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Table 1 The average total [H+] (lg/m3), aerosol water content [H2O] (lg/m3) and free [H+] (nmol/m3) estimated from E-AIM on clear and hazy days. Free [H+]
Total [H+]
Free [H+]/total [H+]
Size bins (lm)
[H2O] Hazy
Clear
Hazy
Clear
Hazy
Clear
Hazy
Clear
<0.49 0.49–0.95 0.95–1.5 1.5–3.0
11.8 7.3 10.6 2.7
5.8 4.5 1.9 0.9
22.9 56.7 89.3 25.7
14.5 30.4 14.3 7.4
171.7 107.6 141.7 36.9
117.1 58.9 30.5 12.0
0.13 0.53 0.63 0.70
0.12 0.52 0.47 0.62
Figure 4. Mass size distributions of OC and EC, and size-segregated OC/EC ratio for both clear and hazy days.
Guanghzou (70 nmol/m3), Lanzhou (65 nmol/m3), and Hong Kong (51–103 nmol/m3), but significantly lower than Jinan, Beijing and Shanghai (220–390 nmol/m3) (Cheng et al., 2011; Pathak et al., 2003, 2009). More acidic aerosol was observed on hazy days, with free [H+] 1.6–6.2 times those on clear days, consistent with the previous observation in Jinan (Cheng et al., 2011). Aerosol acidity might have implication on the formation of SOA as discussed in the following.
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3.3.2. OC and EC Average size distributions of OC and EC both showed bimodal characteristics with a fine mode in the size range <0.49 lm and a coarse mode in the size range of 3–7.2 lm on both clear and hazy days (Fig. 4). Generally, secondary organic carbon (SOC) is estimated according to the minimum ratio method (Castro et al., 1999; Turpin and Huntzicker, 1995), which is described in the following equation:
SOC ¼ OCtotal EC ðOC=ECÞmin where OCtotal refers to the total measured ambient OC, and (OC/EC)min is the corresponding minimum OC/EC ratio in each size range. The (OC/EC)min value was 2.7 in the size range <0.49 lm, while higher value(>4.1) was obtained in the size range of 0.49–10 lm for both clear and hazy days. In this study, the estimation of SOC was only applied in the size range <0.49 lm. The association between formation of SOA and aerosol acidity was investigated by correlation analysis between SOC/OC and inferred normalized acid concentration (free [H+]/OC). It was found significant correlation (r = 0.82, p < 0.001) between SOC/OC and [H+]/OC in the size range <0.49 lm for hazy day samples (Fig. 5), suggesting that aerosol acidity might play an important role in the enhancement of SOC production (Pathak et al., 2011). However, there was not an obvious correlation found for clear day samples, which might be due to the limited samples. Experimental work (Jang et al., 2002; Surratt et al., 2007) and field observations (Pathak et al., 2011; Ding et al., 2011) have also emphasized the importance of acid-catalyzed mechanism in the formation of SOA. 3.4. Contribution of major species to light extinction Fig. 6 shows the derived light extinction bext, reconstructed light extinction bext,cal by a revised IMPROVE method (see Supplementary material), and mean contribution (excluding set 17 and 18) from each specie to bext,cal on clear and hazy days. It can be seen that bext and bext,cal exhibited moderate correlation (r = 0.71, p < 0.001). The major deviation was found for bext,cal of set 17 and 18, overestimated by 50% and 70%, respectively. Different from other samples, the sampling time for both the sets covered a hazy day and a clear day, with visibility at 14.4 and 7.4 km (set 17), 6.2 and 17.6 km (set 18), respectively. Higher correlation coefficient (r = 0.83, p < 0.001) was obtained when excluding these two samples from the analysis. However, a general underestimation still existed, which might be mainly attributed to the difference in mixing state of aerosol components (Chandra et al., 2004; Jacobson, 2001), an important factor affecting atmospheric light extinction (Yu et al., 2010).
0.7 SOC/OC = 0.11ln([H+]/OC) + 0.32, r = 0.82 0.6
SOC/OC
0.5 0.4 0.3 0.2
Hazy days Clear days
0.1 0 0
1
2 [H+ ]/OC
3
4
Figure 5. SOC/OC ratio as a function of [H+]/[OC] for acidic samples ([H+] > 0) in the size range <0.49 lm on clear and hazy days.
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Figure 6. Comparison between derived light extinction (bext, in dash line) and reconstructed light extinction (bext,cal) from IMPROVE method (upper). Pie plot (bottom) shows the average fractional contribution of atmospheric species to bext,cal on clear (left) and hazy days (right).
From a plot in Fig. 6, it is clear that sulfate and OM played a particularly important role in visibility impairment in urban Guangzhou, responsible for approximate 40% and 30%, respectively. Nitrate was the third important contributor, representing 11% of bext,cal on clear days, while it became more important on hazy day (16%). This was close to the contribution by EC for clear and hazy days, accounting for 11% and 10% of bext,cal, respectively. The contributions of these species to light extinction budget are comparable to those obtained by Jung et al. (2009) in urban Guangzhou. Cheng et al. (2008) also reported a similar contribution to light extinction by sulfate (40%) and EC (17%) during a polluted period in a rural area of PRD region. However, the contributions by OM (17%) and nitrate (<8%) were lower than those in this study. The discrepancy was attributed to the difference in chemical pattern and meteorological condition.
4. Conclusion The study presented chemical characterization of size-segregated aerosol samples and numberbased size distribution of submicron particles, during fall-winter period from 23th October 2010 to 10th January 2011. Average mass concentration of fine aerosol on hazy days was 130.2 ± 25.4 lg m3, 1.62 times that on clear days. Mean concentrations for OM (39.3 lg m3) and (5.3 lg m3) EC in PM10
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on hazy days were significantly higher than clear days (24.8 and 3.2 lg m3, respectively). Major WSII þ (SO2 4 , NO3 and NH4 ) in PM10 also remarkably increased on hazy days, 1.6, 2.6 and 1.8 times higher than clear days, respectively. It signifies the favorable formation of secondary aerosols, particularly NO 3 on hazy days. The results also showed that the major enhancement of these species on hazy days was in the size range of 0.49–0.95 lm and 0.95–1.5 lm, although the dominant mode of these species was in the size range <0.49 lm. The aerosol acidity might be associated with formation of SOA in the size range <0.49 lm. In addition, light extinction of these species was reconstructed and the result suggests that sulfate and OM played a dominant role in the visibility impairment, followed by nitrate and EC, while nitrate becoming more important on hazy days. However, the bias from many other factors (e.g., mixing state and/or RH) still existed in the estimation, and thus future research on the mixing state and hygroscopicity of the aerosol needs to be addressed for further understanding. Acknowledgments This work was supported by the National Nature Science Foundation of China (No. 41073077), ‘‘Strategic Priority Research Program (B)’’ of the Chinese Academy of Sciences (XDB05020205) and Guangzhou Institute of Geochemistry (GIGCAS 135 project Y234161001). The authors gratefully thank our group members Bo Huang, Ming Liu and Zhaofang Ren for their assistance in the deployment of sampling instruments and analysis of aerosol samples. This is contribution No. 1678 from GIGCAS. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http:// dx.doi.org/10.1016/j.uclim.2013.05.002. References Anlauf, K., Li, S.M., Leaitch, R., Brook, J., Hayden, K., Toom-Sauntry, D., Wiebe, A., 2006. 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