Aerosol hygroscopicity and its impact on atmospheric visibility and radiative forcing in Guangzhou during the 2006 PRIDE-PRD campaign

Atmospheric Environment 60 (2012) 59e67

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Aerosol hygroscopicity and its impact on atmospheric visibility and radiative forcing in Guangzhou during the 2006 PRIDE-PRD campaign Xingang Liu a, b, Yuanhang Zhang b, *, Yafang Cheng b, Min Hu b, Tingting Han a a b

State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China

h i g h l i g h t s < We quantify the relation of aerosol chemical compositions and optical properties. < We assess the impact of relative humidity on atmospheric visibility and aerosol direct radiative forcing. < We investigate the influence of relative humidity on aerosol asymmetry factor and up-scatter fraction.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 14 January 2012 Received in revised form 31 May 2012 Accepted 6 June 2012

The objective of this study is to quantify the relation of aerosol chemical compositions and optical properties, and to assess the impact of relative humidity (RH) on atmospheric visibility and aerosol direct radiative forcing (ADRF). Mass concentration and size distribution of aerosol chemical compositions as well as aerosol optical properties were concurrently measured at Guangzhou urban site during the PRD (Pearl River Delta) campaign from 1 to 31 July, 2006. Gaseous pollutant NO2 and meteorological parameter were simultaneously monitored. Compared with its dry condition, atmospheric ambient extinction coefficient sext(RH) averagely increased about 51% and atmospheric visibility deceased about 35%, among which RH played an important role on the optical properties of water soluble inorganic salts. (NH4)2SO4 is the most important component responsible for visibility degradation at Guangzhou. In addition, the asymmetry factor g increased from 0.64 to 0.74 with the up-scatter fraction b decreasing from 0.24 to 0.19 when RH increasing from 40% to 90%. At 80% RH, the ADRF increased about 280% compared to that at dry condition and it averagely increased about 100% during the campaign under ambient conditions. It can be inferred that aerosol water content is a key factor and could not be ignored in assessing the role of aerosols in visibility impairment and radiative forcing, especially in the regions with high RH. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: Aerosol hygroscopicity Visibility impairment Radiative forcing PRIDE-PRD campaign

1. Introduction Water content of atmospheric particles governs the total mass concentration of airborne particles, aerosol atmospheric lifetime, their aqueous phase chemical reaction rates, their ability to act as cloud condensation nuclei (CCN), their acidity, and the amount of light they scatter (Day and Malm, 2001; Cheng et al., 2008; Massoli et al., 2009). The diameter and refractive index will change when hydrophilic aerosols uptake ambient water vapor, which will inevitably affect the light radiation: in the horizontal direction showed the influence of atmospheric visibility, performance in the vertical direction for the atmospheric radiation balance effects. So,

* Corresponding author. Tel.: þ86 10 62756592; fax: þ86 10 62751927. E-mail address: [email protected] (Y. Zhang). 1352-2310/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.atmosenv.2012.06.016

the conserved water is one of the major and important components of suspended particulate matter in the atmosphere, especially at the high relative humidity (RH) area, for example at the coastal cities. To date, many studies have investigated the humidity response of both laboratory-generated and atmospheric ambient aerosols by experimental or by model methods and addressed the effect of water uptake by aerosols on aerosol scattering ability as well as applications to the effects of aerosols on the Earth’s radiative balance (Tang and Munkelwitz, 1994; Tang, 1996; Kotchenruther et al., 1999; Yoon and Kim, 2006; Cheng et al., 2008; Massoli et al., 2009; Liu et al., 2009, 2010). The role of RH on aerosol optical property is fundamental and important. On one hand, atmospheric visibility will be worsened when RH is higher with the same level of aerosol mass concentration (Malm et al., 2000; Day and Malm, 2001). On the other hand, global circulation modeling

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X. Liu et al. / Atmospheric Environment 60 (2012) 59e67

studies found that the negative radiative forcing of the aerosols was significantly higher when the ambient RH was accounted for (Grant et al., 1999). Result from Massoli et al. (2009) also showed that including aerosol hygroscopic properties in climate calculations is critical for improving estimates of aerosol forcing on climate. Most satellite algorithms to retrieve aerosol properties still simplified hygroscopic properties of ambient aerosols and thus worsened the accuracy of the retrievals (Wang and Martin, 2007). Meanwhile, most of the research did not take the dependence of the up-scatter fraction and the asymmetry factor on RH into consideration when calculating the ADRF (Charlson et al., 1992; Kotchenruther et al., 1999; Yoon and Kim, 2006). Thus, it is essential to accurately estimate the response of the aerosol optical properties on RH. In China, few researches on atmospheric visibility and radiative forcing were carried out based on chemical components and even rarely took the RH into account. It is imperative to investigate the relationship between atmospheric optical properties and chemical components, and to quantitatively estimate the role of RH on visibility impairment and ADRF. Meanwhile, in order to draw up a strategy for the visibility improvement in China, policy-makers would like to know the relative contributions to light extinction by the atmospheric constituents. 2. Experimental 2.1. Experiment site Pearl River Delta (PRD), located in the southeastern of China. Compared with the history of PRD, the size of the total population of 12.6 million people by 1980 had reached to nearly 43 million by 2006, which accounted for 3% of the national population by the time. Meanwhile, its gross domestic product (GDP) reached 138 billion dollars, accounting for 10% of the national GDP. High degree of population concentration and economic level, as well as rapid increasing in urbanization and infrastructure construction result in poor air quality in PRD (Zhang et al., 2008). For example, the hazy days (visibility 10 km and RH 90%) in Guangzhou urban area was 70 days in 2001, 83 days in 2002; 93 days in 2003; 144 days in 2004; 131 days in 2005 (Wu et al., 2007). To improve the regional air quality and ensure the environmental requirements for the Asian Game held in Guangzhou in 2010, the regional integrated experiments on air quality over PRD (PRIDE-PRD 2006) were carried out from 1 to 31 July, 2006. The Guangzhou urban super-site (23.1 N, 113.3 E) was located w60 km northwest of the South China Sea and the instruments were installed on the roof (w50 m above ground level) of a building, which is located to the Dongfeng middle road that is one of the main traffic lines of the city. At the urban super-site, aerosol sources, which determined their hygroscopic properties, were marine aerosol, local vehicular traffic, combustion of fuels for cooking, local industrial activities and the transported pollutants (Liu et al., 2008).

Schonlinner, 2004), NOeNO2eNOx analyzer (Ecotech, model 9841), and automatic meteorological station, respectively. It should be noted that the wavelengths that the optical instruments used were different, so, all parameters were scaled to values at the wavelength of 550 nm by using a power-law wavelength dependence. Elemental carbon (EC) and organic carbon (OC) were monitored by a semi-continuous OC/EC analyzer with the thermaleoptical transmittance method (Kondo et al., 2006). Two micro-orifice uniform deposit impactor (MOUDI) aerosol samplers (Marple et al., 1991) were concurrently operated for the mass size distribution of WSIC (Naþ, NH4 þ , Kþ, Mg2þ, Ca2þ, Cl, NO3  , SO4 2 ) and OC/EC with time resolution of 12 h. The mass concentrations of PM10 were analyzed by a TEOM monitor (Model R&P 1400a). All of the instruments mentioned above were calibrated according to their manufactures’ manual. There were periods of intermittent rainfall brought by two typhoons (Liu et al., 2008). Additionally, the measurement was broken off due to the calibration and maintenance of MOUDI, PILS and other instruments. In total, 11 days data, which were hourly averaged, are available for analysis.

3. Results and discussion 3.1. Mass concentration of aerosol chemical species In this study, the mass concentration of particle organic matter (POM) was estimated by multiplying the measured mass concentration of OC by a factor of 1.6 (Turpin and Lim, 2001). The mass of undetected fraction (the Residual) was estimated gravimetrically by subtracting the mass of WSIC, POM, and EC from PM10. Time series of the mass concentration of WSIC, POM, EC, and the Residual in PM10 are illustrated in Fig. 1 and statistically summarized in Table 1. During the campaign, the average (standard deviation) mass fraction of WSIC in PM10 was 42.0% (12.3%), of which SO4 2 , NO3  , NH4 þ , Cl, Naþ, Ca2þ, Kþ, NO2  , and Mg2þ accounted for 25.5% (8.3%), 4.9% (2.4%), 7.0% (3.8%), 2.9% (2.3%), 1.6% (1.3%), 1.6% (1.1%), 1.0% (0.5%), 0.5% (0.2%), and 0.3% (0.2%), respectively. The POM, EC and the Residual accounted for 17.3% (5.5%), 6.0% (2.4%), and 32.7% (9.4%) of the mass concentration of PM10, respectively. Furthermore, the sum mass concentrations of SO4 2 , NO3  and NH4 þ accounted for 82.1% (8.8%) of the WSIC. Mass size distribution for SO4 2, NO3  , Cl, NH4 þ , Naþ, Mg2þ, Kþ are illustrated in Fig. 2(a). The mass size distributions of these components were bimodal distribution except that of Naþ, Cl and Mg2þ, which were mainly transported from the sea. The mass of SO4 2 , NH4 þ and Kþ mainly lied in the accumulation mode (0.1 < Dp < 1 mm), but, the mass of NO3  , Cl, Naþ, and Mg2þ mainly

2.2. Measurements As a part of the campaign, the physical and optical properties of aerosols along with the size distribution of chemical species were monitored. Such water-soluble ionic components (WSIC) as cations (Naþ, NH4 þ , Kþ, Mg2þ, Ca2þ) and anions (Cl, NO2  ; NO3  ; SO4 2 ) in PM10 were measured by an in-situ particle-into-liquid sampler (PILS) system (Orsini et al., 2003). Atmospheric extinction coefficient sext, aerosol scattering coefficient at dry conditions ssp, aerosol absorption coefficient sap, the concentration of nitrogen dioxide NO2 and RH were measured by transmissiometer (Malm and Persha, 1991), integrating nephelometer (Anderson and Ogren, 1998), multi-angle absorption photometer (MAAP) (Petzold and

Fig. 1. The temporal distribution of the mass concentration of water-soluble ionic species, POM, EC, and the Residual in PM10.

X. Liu et al. / Atmospheric Environment 60 (2012) 59e67

accounted for 33.5% (8.5%), 6.1% (1.8%), 4.5% (2.8%), 17.3% (5.5%), 6.0% (2.4%), and 32.7% (9.4%) of the mass concentration of PM10.

Table 1 Statistical summary of the mass concentration, mass mean diameters and geometric standard deviations for main species in the model. Species

SO4 2 NO3  Naþ OC EC Residual

Mass (mean  s.d.)

19.96 3.51 1.21 9.73 4.39 26.18

     

11.97 1.32 0.59 4.98 1.72 13.80

Minimum Maximum Fine mode

5.02 0.84 0.30 2.69 1.48 2.00

65.80 9.92 3.05 32.77 11.08 71.10

Coarse mode

Dg, mm

sg, mm

Dg, mm

sg, mm

0.52 0.32 0.55 0.68 0.41 0.43

0.86 0.27 1.05 0.92 1.51 0.73

4.23 3.85 4.27 8.06 7.50 3.49

4.02 6.30 7.48 5.93 7.05 6.34

3.2. Numerical simulation of atmospheric optical properties based on measurements Firstly, a multiple logenormal mode fitting was applied to the mass fraction size distribution of the chemical species derived from MOUDI. The mass mean diameters and geometric standard deviations for six species in the model were summarized in Table 1. Secondly, the mass fraction was multiplied by the mass concentration measured by PILS to find the mass concentration in each size bin for each chemical species. Then, the particle mass concentration in each size bin for each chemical species is converted to size-resolved number (Ni) distribution of each chemical species by equation (4) (Liu et al., 2009).

lied in the coarse mode (Dp > 1 mm) with a little fraction in the accumulation mode. Mass size distribution and molar ratio were combined to investigate the chemical form of these components. Molar ratio of SO4 2 to NH4 þ and cations (Naþ, Kþ, Mg2þ) to anions (Cl, NO3  ) is depicted in Fig. 3(a) and (b), respectively. Ammonium firstly combines with sulfate when sulfate, nitrate and chloride coexist since ammonium sulfate is more stable. Furthermore, the molar ratio of 2*½SO4 2  to ½NH4 þ  is nearly to one in Fig. 3(a). So, it can be inferred that SO4 2 existed in the form of (NH4)2SO4. In addition, because of high concentration of NaCl at coastal city Guangzhou, gaseous HNO3 can react with NaCl in the coarse mode to form sodium nitrate NaNO3, which is so-called chloride deficit (Seinfeld and Pandis, 2006). Moreover, the molar ratio of anions (Cl, NO3  ) to cations (Naþ, Kþ, Mg2þ) is 1.2 (the slope in Fig. 3(b)), and it can be concluded that NO3  may exist in the form of NaNO3 and Cl in the form of NaCl. The excess NO3  and Cl might combine with Mg2þ or Kþ. The uncertainty induced by species assumption will be estimated in Section 3.5. The mass concentration of (NH4)2SO4, NaNO3, and NaCl, is respectively calculated by the following equations.

i h  ðNH4 Þ2 SO4 ¼ 1:375* SO4 2




Ni ðDs Þ ¼

(2)

i h ½NaCl ¼ 1:65* Cl

(3)

The mass size distribution for PM10, (NH4)2SO4, NaNO3, NaCl, POM, EC, and the Residual are depicted in Fig. 2(b). Throughout the measurements, (NH4)2SO4, NaNO3, NaCl, POM, EC and the Residual

d M /d lo g (D P ) ( μ g m )

-3

-3

d M /d lo g (D P ) ( μ g m )

NH Na Mg K

10

0 .1

1

10

A e ro d yn a m ic d ia m e te r D P ( μ m )

b

(N H ) S O

NO Cl

0 0 .0 1

(4)

PM

a

SO

20

Mi ¼ p r ðDs Þ3 6 i

100

50

30

Mi

ri Vi ðDs Þ

Where Ds is volume-equivalent Stokes diameter; Mi is the mass concentration for a particular size bin; and ri is the specific density for particular component. Density and refractive indices of atmospheric species at dry condition used in this study is listed in Table 2. The diameter hygroscopic growth factor d(RH) and refractive index m for (NH4)2SO4, NaNO3, NaCl had been introduced by Tang and Munkelwitz (1994). The d(RH) for EC was assumed to be 1 due to its hydrophobicity. The diameter of POM and the Residual in this study is assumed growing linearly from 1 to 1.1 with RH increasing from 40% to 95% (Virkkula et al., 1999). Meanwhile, the refractive index of POM is assumed linearly decreases from 1.55 to 1.45 as well as the Residual from 1.53 to 1.43 with RH increasing from 40% to 95%. Aerosols are assumed to be spherical and homogenously externally mixed. Aerosol scattering coefficients at both dry and ambient conditions and aerosol absorption coefficient can be calculated by Mie model with the aerosol size distribution, theoretically refractive index, and incident wavelength (550 nm) as input parameters (Bohren and Huffman, 1998). As to the Rayleigh scattering coefficient by atmospheric molecule ssg, the U.S. Standard Atmosphere (U.S. GPO, Washington, D.C., 1976) is used and the value of ssg is 13 Mm1 at 550 nm. Light absorption by gases sag is mainly due to the light absorption by gaseous pollutant NO2 and can be calculated by empirically function (Hodkinson, 1966).

(1)

i h ½NaNO3  ¼ 1:371* NO3 

40

61

100

80

N aN O N aC l POM

60

EC R e s iu d a l

40

20

0 0 .0 1

0 .1

1

10

100

A e ro d yn a m ic d ia m e te r D P ( μ m )

Fig. 2. (a) The mean and standard deviation of the mass size distribution for SO4 2, NO3  , Cl, NH4 þ , Naþ, Mg2þ, Kþ; (b) mean and standard deviation of the mass size distribution for particulate matter (PM), (NH4)2SO4, NaNO3, NaCl, POM, EC, and the Residual.

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X. Liu et al. / Atmospheric Environment 60 (2012) 59e67

0.30

1.0

a

1:1

0.8

3

4

M 2 *S O -

0.25

M N O - + C l-

Fit

0.6

b

1:1 Fit

0.20 0.15

0.4 0.10 0.2 Y=(0.95 ± 0.03)*X+(0.16 ± 0.008) 0.0 0.0

N=195, R=0.94, P<0.0001 0.2

0.4

0.6

0.8

1.0

M NH +

0.05 0.00 0.00

Y=(1.2 ± 0.02)*X N=195, R=0.76, P<0.0001 0.05

0.10

0.15

0.20

0.25

0.30

M N a + +K + +2*M g 2+

4

Fig. 3. (a) The molar ratio of SO4 2 to NH4 þ ; (b) the molar ratio of anions (Cl, NO3  ) to cations (Naþ, Kþ, Mg2þ).

The asymmetry factor which is defined as the intensityweighted average cosine of the scattering angel was derived by equation (5).

Zp g ¼

cos qPðcos qÞsin qdq

(5)

0

Where q is the angle of incident radiation and P is the usual scattering phase function. The up-scatter fraction b is the fraction of the upward hemisphere relative to the local horizon compared to the integral over the angular distribution of the scattered radiation. HenyeyeGreenstein phase function as illustrated by equation (6) was used to replace the more realistic Mie phase functions in multiple scattering calculations, with no more than a few percent error in computed fluxes (Wiscombe and Grams, 1976).

b¼

    1g 2 ð1 þ gÞK g 2  1 2g p

(6)

where K(g2) is the complete elliptic integral of the first kind:



K g

2



¼

Zp=2

 1 2 1  g 2 sin2 q dq

(7)

0

3.3. Impacts of RH on visibility impairment 3.3.1. Chemical apportionment of extinction coefficient under dry condition sext(dry) Chemical apportionment of the sext under dry condition is illustrated in Fig. 4(a), (c) and (d) for daytime (6:00 ame19:00 pm, local time), night (20:00 pme5:00 am, local time), and overall day, respectively. The difference of day and night on chemical Table 2 The density r and refractive indices m of atmospheric species at dry condition used in this study. Substance

(NH4)2SO4 NaNO3 NaCl POM EC Residual

r 1.76 2.261 2.165 1.4 1.5 2.3

m ¼ n þ ik

References

n

k

1.53 1.587 1.544 1.55 1.95 1.53

0 0 0 0 0.66 0.005

Tang (1996) Tang (1996) Tang (1996) Sloane (1986) Sloane (1986) Massling et al. (2007)

apportionment is slight except (NH4)2SO4 and EC. The fraction of (NH4)2SO4 is slightly larger at daytime maybe due to active photochemical reaction, on the other hand, the fraction of EC is slightly larger at night maybe due to higher emission of EC. (NH4)2SO4, NaNO3, NaCl, POM, EC, NO2, atmospheric molecule and the Residual contributes 35%, 2%, 2%, 17%, 22%, 5%, 6%, and 11%, respectively to the atmospheric extinction throughout day. Obviously, (NH4)2SO4 plays an important role in visibility impairment. One reason is to its high mass concentration fraction (33.5%) in particulate matter, on the other hand, (NH4)2SO4 mainly lies in the fine mode (1 mm) which is sensitive to the incident wavelength (550 nm) and its mean mass scattering efficiency (standard deviation) is 3.4 (0.2) m2 g1. Conversely, NaNO3 and NaCl account for little fraction to the atmospheric extinction because both of them exist in the coarse mode whose extinction efficiency is very small: 0.9 (0.1) for NaNO3 and 1.3 (0.3) for NaCl. The same condition is with the Residual, whose mass fraction lies in the coarse mode. The mass scattering efficiency and absorption efficiency for the Residual are 1.2 (0.1) and 0.1 (0.01), respectively. Relative to the mass fraction in PM10 (17.3%), extinction fraction by POM is slightly lower (17%). The mass scattering efficiency for POM is 3.5 (0.2). It should be noted that the extinction contribution of EC consists of both scattering (5%) and absorption (17%) part and extinction contribution of EC (22%) is significantly higher than its mass fraction (6%) in PM10. This is due to that EC not only has a large imaginary part of refractive index (0.66) but also has the larger real part of refractive index (1.95). The mass scattering efficiency and absorption efficiency for EC are 2.8 (0.2) and 5.4 (1.1), respectively. 3.3.2. Chemical apportionment of extinction coefficient under ambient condition sext(RH) The ambient sext(RH) was directly measured by the transmissiometer. The temporal series stacked column of scattering coefficient for (NH4)2SO4, NaNO3, NaCl, POM, EC, the Residual under ambient RH and atmospheric molecule as well as absorption coefficient for EC and NO2 are illustrated in Fig. 5(a), the modeled sext can well describe temporal distributions of the directly measured sext and reproduce its low and peak values. In Fig. 5(b), the correlation coefficient (R ¼ 0.91) of them is high and the slope of the regression line is 1.07, implying that the difference between the measured and the modeled sext is 7%. Extinction coefficient by each aerosol chemical component under ambient RH is calculated and their mean contribution fraction to atmospheric extinction is illustrated in Fig. 4(b), (d) and (f) for daytime, night, and all day, respectively. The difference of day and night on chemical apportionment is also slight except NaCl due

X. Liu et al. / Atmospheric Environment 60 (2012) 59e67

a

b

EC 21%

N aC l 1%

NaNO 3 2%

M o le c u le 5%

POM 18%

63 N aC l 3%

POM 14%

M o le c u le 3%

R e s id u a l 12% N aN O 3 2%

R e s id u a l 9% NO2 4%

NO2 5% (N H 4 )2 S O 4 50%

(N H 4 )2 S O 4 36%

c

EC 15%

d

EC 24% N aC l 2%

N aN O 3 3%

M o le c u le 7%

POM 17%

NaCl 6%

POM 11%

EC 15%

M o le c u le 4%

R e s id u a l 11%

R e s id u a l 7% NO2 3%

NO2 5%

N aN O 3 2%

(N H 4 )2 S O 4 51%

(N H 4 )2 S O 4 32%

e

f

EC 22%

N aC l 2%

N aN O 3 3%

M o le c u le 6%

POM 17%

N aC l 4%

POM 13%

M o le c u le 3%

R e s id u a l 11%

N aN O 3 2%

EC 15%

R e s id u a l 8% NO2 4%

NO2 5%

(N H 4 )2 S O 4 50%

(N H 4 )2 S O 4 35%

Fig. 4. Percentage contributions of the major chemical species to the atmospheric extinction coefficient at (a) daytime, (c) night, and (e) day and night under dry condition as well as these at (b) daytime, (d) night, and (f) day and night under ambient conditions.

(NH 4 )2 SO 4 Residual

NaNO 3 NO 2

NaCl molecule

POM

EC

Atmos. extin. coeffi.

1000

b

a

1:1

800

800 m o d e le d

A tm o s . e x tin . c o e ff. (1 /M m )

1000

600 400 200

600 400 200 Y=(1.07 ± 0.012)*X

0 7-7

N=193, R=0.91, P<0.0001

0

7-9

7-11

7-19 Date (m-d)

7-21

7-23

0

200 400 600 800 1000

measured

Fig. 5. (a) Time series of the measured atmospheric extinction coefficient under ambient relative humidity and that predicted by Mie model with chemical components; (b) comparison between the measured and modeled atmospheric extinction coefficient.

64

X. Liu et al. / Atmospheric Environment 60 (2012) 59e67

to its higher mass fraction at night. Throughout the day, the mean contribution fraction of (NH4)2SO4, NaNO3, NaCl, POM, EC, NO2, atmospheric molecule and the Residual to atmospheric extinction is 50%, 3%, 4%, 13%, 15%, 4%, 3%, and 8%, respectively under ambient condition. Compared to its contribution fraction under dry condition, extinction fraction for hydrophilic aerosols, especially (NH4)2SO4, NaNO3, and NaCl, significantly increased. Moreover, (NH4)2SO4 nearly accounts for one half of the atmospheric extinction under ambient condition. However, hydrophobic POM and the Residual as well as non-hydrophilic EC, NO2, and atmospheric molecule contribute decreasing fraction of atmospheric extinction with RH increasing. In-depth analysis on the hygroscopic properties of water-soluble chemical species helps to understand the relationship between atmospheric extinction and RH. The influence of RH on aerosol scattering is generally depicted by hygroscopic factor for aerosol scattering, f(RH), which is defined with the ratio of aerosol scattering coefficient at high RH to that at dry condition. Fig. 6(a) depicts the response of (NH4)2SO4, NaNO3, NaCl, POM, and the Residual on ambient RH during the measurement and Fig. 6(b) illustrates the function relationship between f(RH) of each chemical species and RH. The f(RH) of (NH4)2SO4, NaNO3, and NaCl aerosols has the same tendency to increase with increasing RH. But, the value of f(RH) for POM and the Residual is nearly to one.

coefficient increased about 43% and then atmospheric visibility deceased about 30% due to aerosol water uptaking. Stock et al. (2011) also suggested that a significant fraction of up to 50e70% of the visibility degradation caused by the uptake of water by the particles at under typical daytime RH (70e80%) compared to the dry particle state over the coastal area. 3.4. Impacts of RH on aerosol radiative properties 3.4.1. Dependence of aerosol asymmetry factor and upper scatter fraction on RH The asymmetry factor g and up-scatter fraction b for ambient aerosol clusters was depicted by Fig. 8. The asymmetry factor g increased with RH increasing and this is consistent with Andrews et al. (2006) as well as Yoon and Kim (2006). In Fig. 8, g increased from 0.64 to 0.74 when RH increasing from 40% to 90%. The g is 0.68 at the daytime average ambient RH (67.5%) during the campaign. Cheng et al. (2008) also retrieved the very close value that is from 0.67 to 0.75 when RH from 30% to 90% at Xinken site (22.6 N, 113.6 E) which lies at the 70 km southeastern of the Guangzhou city. Andrews et al. (2006) derived values of g ranged from 0.60 (0.03) for dry aerosols to 0.65 (0.05) for aerosols at ambient conditions in Oklahoma. On the contrary, the up-scatter fraction b, that is, the radiation backscattered into sky decreased with the RH increasing in Fig. 8. b decreased by w21% from 0.24 to 0.19 with RH increasing from 40% to 90%, which is consistent with the modeling results from Cheng et al. (2008) who figured out that b decreased from 0.23 to 0.19 when RH increasing from 30% to 90% at Xinken site. Im et al. (2001) indicated that the up-scatter fraction decreased from 0.24 at 40% RH to 0.21 at 90% RH in the Blue Ridge Mountains of western North Carolina. It was also comparable to Stock et al. (2011) who showed that b dropped down from w0.23 to 0.18 when the RH from dry to 92% for ambient aerosols over the Eastern Mediterranean. Kotchenruther et al. (1999) also figured out that the values of b(RH) generally decreased linearly with increasing RH and the average value of b was 0.28 at 30% RH and 0.23 at 80% RH, a decrease of 18% for aerosols off the mid-Atlantic coast of the United States. The general empirical characterization of the hygroscopic properties of the asymmetry factor is fitted by statistical equation (8) and the value of the fitting parameter is 0.61, 9*105, 1.6 for a, b, c, respectively as illustrated in Fig. 8. Similarly, the hygroscopic properties of up-scatter fraction is fitted by equation (9) and the value of the fitting parameter is 0.25, 1*105, 1.8 for a, b, c, respectively.

3.3.3. Impacts of RH on visibility impairment Both directly measured and modeled ambient visibility are shown in Fig. 7(a) and their relationship is linearly fitted in Fig. 7(b). Temporal distribution of atmospheric visibility under dry condition is also illustrated in Fig. 7(a). The RH shows a clear diurnal change with a mean (standard deviation) value of 73.5% (12.6%) during the measurement. The averaged modeled sext under dry condition is 274 Mm1 and its corresponding visibility is 16.4 km calculated by the Koschmeider equation (Seinfeld and Pandis, 2006). The averaged modeled sext(RH) was 411 Mm1 and its corresponding visibility was 10.8 km. That is, the atmospheric extinction coefficient increased about 51% and then atmospheric visibility deceased about 35% due to the aerosol water uptaking. The visibility during daytime is of most interest. The average (standard deviation) RH during daytime from July 7 to 23 is 67.5% (12.2%) with the maximum value is 91%. During the daytime, the mean (standard deviation) modeled sext under dry condition is 308 Mm1 and its corresponding visibility is 14.3 km. The modeled sext(RH) was 439 Mm1 and its corresponding visibility was 10 km under ambient condition. That is, the atmospheric extinction

(NH 4 ) 2 SO 4 POM

NaNO 3 Residual

RH

100

10

8

80

8

NaNO 3

6

60

6

NaCl POM Residual

4

40

2

20

2

0

0 20

0 7-7

7-9

7-11 7-19 7-21 Date (m -d)

7-23

(NH 4) 2SO 4

f(R H )

a

R H (% )

10

f(R H )

NaCl

b

4

40 60 80 RH (% )

100

Fig. 6. (a) Temporal distribution of scattering hygroscopic growth factor f(RH) for (NH4)2SO4, NaNO3, NaCl, POM and the Residual. (b) The relationship between relative humidity and f(RH) for (NH4)2SO4, NaNO3, NaCl, POM and the Residual.

X. Liu et al. / Atmospheric Environment 60 (2012) 59e67

dry

Modeled

Measured

65

RH

35

100

30

80

25

20

60

15

40

10 5 0 7-7

a 7-9

7-11

7-19

7-21

R H (% )

V is ib ility (K m )

25

M o d e le d

Y=(1.02 ± 0.01)*X

30

1:1

N=195, R=0.90, P<0.0001

20 15 10

20

5

0

0

7-23

b 0

5

10

15

20

25

30

Measured

Date (m-d)

Fig. 7. (a) Temporal distribution of atmospheric visibility under dry condition and ambient relative humidity, among the blue one is directly measured and the green one is modeled; (b) comparison between the measured and modeled atmospheric visibility under ambient condition. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

(8)

Y ¼ a  b*ðRHÞc

(9)

3.4.2. Dependence of aerosol direct radiative forcing on RH Aerosol direct radiative forcing (ADRF) is the difference in the net short wave radiative fluxes (down minus up) with and without aerosols in the atmosphere. The influence of water on ADRF is depicted by hygroscopic factor for ADRF, x(RH, Dry), which is defined as ratio of ADRF at ambient RH to ADRF at dry condition. The function relationship between x(RH, Dry) and RH is investigated with equation (10) (Kotchenruther et al., 1999).

xðRH; 40%Þ ¼

ð1  Rs Þ2 bðRHÞas f ðRHÞ  2Rs aa

(10)

ð1  Rs Þ2 bð40%Þas f ð40%Þ  2Rs aa

Where Rs is the surface reflecting albedo and its value (0.17) at 550 nm is from the NOAA (National Oceanic and Atmospheric Administration) MODIS (Moderate Resolution Imaging Spectroradiometer) product (http://modland.nascom.gov/cgi-bin/browse/ getDetail.cgi/). as is aerosol mass scattering efficiency, and aa is aerosol mass absorption efficiency, being the ratio of the measured aerosol scattering coefficient and absorption coefficient to the mass concentration of particulate matter, respectively. In this study, the value of as is 3.2 m2 g1 and aa being 0.8 m2 g1. Data of f(RH) is

0 .8 0

0 .3 0

β (R H ) -5

fit Y = 0 .6 1 + 9 *1 0 *(R H )

0 .7 6

-5

g (R H )

fit Y = 0 .2 5 -1 *1 0 *(R H )

1 .6

0 .2 7

1 .8

0 .7 2

0 .2 4

0 .6 8

0 .2 1

0 .6 4

0 .1 8

0 .6 0

0 .1 5 100

β (R H )

g (R H )

from the aerosol hygroscopic measurements during the PRIDE-PRD campaign (Liu et al., 2008). The x(RH, 40%) is shown in Fig. 9 and its value increases gradually with the RH ascending. At 80% RH, the direct radiative forcing of aerosols increases about 280% compared to that at dry condition. That is, about 2.8 times more cooling effect is contributed by RH. At a RH of 80%, the ADRF increased by a factor x(80%, 30%) of 1.98 in case of anthropogenic sources and a factor x(80%, 30%) of 1.55 for urban or industrial aerosols partly affected by sea salt off the midAtlantic coast of the United States during the tropospheric aerosol radiative forcing observational experiment (TARFOX) (Kotchenruther et al., 1999). Additionally, an averaged enhancement factor x(80%, 30%) of 1.45 at 80% RH was achieved by Im et al. (2001) for continental, marine and polluted continental air masses. This research result is consistent with the result (x(90%, 30%) ¼ 2.7) which is also estimated at PRD area in 2004 by Cheng et al. (2008). The average (standard deviation) RH during daytime from July 7 to 23 is 67.5 (12.2) as said above, then, the ADRF would increase by about 100%. This result implies that the hygroscopic growth due to water-soluble or hydrophilic particles in the lower troposphere may significantly modify the magnitude of ADRF. The characterization of x(RH, 40%) can be fitted by equation (11). The fitting parameters for the x(RH, 40%) curve are illustrated in 9

ζ (R H )= F (R H )/F (D ry )

Y ¼ a þ b*ðRHÞc

fit

40

50

60

70

80

90

R H (% ) Fig. 8. Variance of aerosol asymmetry factor g and upper scatter fraction b with relative humidity and curves fitting with nonlinear equations.

4.0

6

3

0 40

30

Y = 1 + 4 .8 *(R H /1 0 0 )

50

60

70

80

90

100

R H (% ) Fig. 9. Scatter plot of humidification factor for aerosol direct radiative forcing x(RH) and its curve fitting. Red dots denote higher values of x(RH) due to larger mass fraction of water-soluble ionic species in aerosols. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

66

X. Liu et al. / Atmospheric Environment 60 (2012) 59e67

Table 3 The uncertainty of the modeled extinction coefficient induced by instruments and parameters used in the model.

Dsext(%)

PILS

OC/EC analyzer

MOUDI

NOx analyzer

rPOM

rResidual

m(RH)POM

m(RH)Residual

d(RH)POM

d(RH)Residual

Species assumed

Total

3

10

9

1

4

3

2

2

3

2

10

18

Table 4 The uncertainty of the aerosol direct radiative forcing induced by input parameters.

Dx (%)

Rs

b(RH)

as

aa

f(RH)

Total

0.5

5.8

5.3

5.2

12.9

16

Fig. 9 with b being 4.8 and c 4.0. There are many scattered red dots in Fig. 9 due to large mass fraction (55e67%) of WSIC during measurement (Liu et al., 2008). If these scattered dots were neglected, the fitting parameter b would be 4.4 and c 4.0.

Y ¼ 1 þ b*ðRHÞc

(11)

3.5. Sensitivity and uncertainty of the model study In this study, the uncertainty of modeling is from the measurement accuracy of instruments, the species assumption, and physical parameters involved. The uncertainty of OC/EC analyzer (10%) and MOUDI (9%) are derived from comparisons on a parameter measured by different ways (Malm et al., 2005). The uncertainty of PILS and NOeNO2eNOx analyzer is 3% (Orsini et al., 2003) and 1% according to open literature and instrument manual. As to the uncertainties caused by the assumptions on the density, refractive index m and d(RH) of POM and the Residual, a control run is first performed using the average literature values (Sloane, 1983, 1986; Massling et al., 2007; Seinfeld and Pandis, 2006) listed in Table 2. The maximum uncertainty caused by each individual parameter is determined by comparing the simulation results when the parameter is set to the maximum or minimum literature value with the result of the control run. The uncertainties of sext(RH) induced by the density, refractive index and the d(RH) of POM and the Residual are given in Table 3. The sext(RH) is relatively sensitive to variations in the hygroscopic properties of POM and the Residual. Another important source of uncertainty is the assumptions for the speciation which related to the refractive index and d(RH). The sext(RH) of all possible combinations of species was calculated and the maximum deviation is 10%. Assuming that all uncertainties are propagated as a quadratic sum of all associated errors, the maximum uncertainty of the simulated atmospheric extinction coefficient is about 18%. Uncertainties of ADRF caused by parameters in equation (10) are estimated by comparing the calculated result using the values described in Section 3.4.2 with the result when the parameter vary with its maximum deviation. The uncertainties of ADRF induced by Rs, b(RH), as, aa and f(RH) is 0.5, 5.8, 5.3, 5.2, and 12.9 as listed in Table 4. All uncertainties are propagated as a quadratic sum of all associated errors, and the maximum uncertainty of the calculated ADRF is about 16%. 4. Conclusions The subject of this paper is to investigate the optical properties changes due to water uptake of aerosols under ambient conditions. As a part of the PRIDE-PRD 2006 campaign which were carried out from 1 to 31 July, 2006, aerosols optical and physical properties as well as their chemical species, gaseous pollutant NO2, and RH were concurrently monitored. Ambient atmospheric extinction coefficient under different RH was calculated by Mie model with aerosol

size distribution, theoretically refractive index, and RH as input parameters. This study investigates the contribution fraction of each chemical species to atmospheric visibility under dry and ambient conditions. During the field campaign, (NH4)2SO4, NaNO3, NaCl, POM, EC and the Residual accounted for 33.5% (8.5%), 6.1% (1.8%), 4.5% (2.8%), 17.3% (5.5%), 6.0% (2.4%), and 32.7% (9.4%) of the mass concentration of PM10. Under dry condition, (NH4)2SO4, NaNO3, NaCl, POM, EC, NO2, atmospheric molecule and the Residual contributes 33%, 2%, 2%, 17%, 22%, 5%, 6%, and 11%, respectively to the atmospheric extinction coefficient. However, the mean contribution fraction of (NH4)2SO4, NaNO3, NaCl, POM, EC, NO2, atmospheric molecule and the Residual to atmospheric extinction is 50%, 3%, 4%, 13%, 15%, 4%, 3%, and 8%, respectively under ambient conditions. It is concluded that (NH4)2SO4 is the most important WSIC responsible for visibility degradation during the campaign. The asymmetry factor g increased with the RH increasing. On the contrary, the up-scatter fraction b decreased with the RH increasing. Specifically, g increased from 0.64 to 0.74 with b decreasing from 0.24 to 0.19 when RH increasing from 40% to 90%. Study on the influence of RH on aerosol direct radiative forcing showed that the x(RH, 40%) increase gradually with the RH ascending. At 80% RH, the direct radiative forcing of aerosols increases about 280% compared to that at dry condition and it averagely increased about 100% during the campaign under ambient conditions. Acknowledgments This work was supported by the Ministry of Science and Technology of China (Grant No. 2006AA06A306), the National Natural Science Foundation of China (Grant Nos. 41005063 and 41175018) and European Commission (Grant No. 212095). The authors would like to thank Dr. Jinsang Jung and his research group for their elaborate work. References Anderson, T.L., Ogren, J.A., 1998. Determining aerosol radiative properties using the TSI 3563 integrating nephelometer. Aerosol Sci. Tech. 29, 57e69. Andrews, E., Sheridan, P.J., Fiebig, M., McComiskey, A., Ogren, J.A., Arnott, P., Covert, D., Elleman, R., Gasparini, R., Collins, D., Jonsson, H., Schmid, B., Wang, J., 2006. Comparison of methods for deriving aerosol asymmetry parameter. J. Geophys. Res. 111 (D5). http://dx.doi.org/10.1029/2004JD005734 Bohren, C.F., Huffman, D.R., 1998. Absorption and Scattering of Light by Small Particles. John Wiley and Sons, New York. Charlson, R.J., Schwartz, S.E., Hales, J.M., Cess, R.D., Coakley Jr., J.A., Hansen, J.E., Hofmann, D.J., 1992. Climate forcing by anthropogenic aerosols. Science 255 (5043), 423e430. Cheng, Y.F., Wiedensohler, A., Eichler, H., Heintzenberg, J., Tesche, M., Ansmann, A., Wendisch, M., Su, H., Althausen, D., Herrmann, H., Gnauk, T., Bruggemann, E., Hu, M., Zhang, Y.H., 2008. Relative humidity dependence of aerosol optical properties and direct radiative forcing in the surface boundary layer at Xinken in Pearl River Delta of China: an observation based numerical study. Atmos. Environ. 42, 6373e6397. Day, D.E., Malm, W.C., 2001. Aerosol light scattering measurements as a function of relative humidity: a comparison between measurements made at three different sites. Atmos. Environ. 35, 5169e5176. Grant, K.E., Chuang, C.C., Grossman, A.S., Penner, J.E., 1999. Modeling the spectral optical properties of ammonium sulfate and biomass burning aerosols: parameterization of relative humidity effects and model results. Atmos. Environ. 33 (17), 2603e2620. Hodkinson, R.J., 1966. Calculations of colour and visibility in urban atmospheres polluted by gaseous NO2. Int. J. Air Water Pollut. 10, 137e144.

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