Diurnal and seasonal characteristics of the optical properties and direct radiative forcing of different aerosol components in Seoul megacity

Science of the Total Environment 599–600 (2017) 400–412

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Diurnal and seasonal characteristics of the optical properties and direct radiative forcing of different aerosol components in Seoul megacity Sang-Keun Song a, Zang-Ho Shon b,⁎, Yeon-Hee Park a a b

Department of Earth and Marine Sciences, Jeju National University, Jeju 63243, Republic of Korea Department of Environmental Engineering, Dong-Eui University, Busan 47340, Republic of Korea

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• The temporal variations of direct radiative forcing of aerosols (DARF) from surface observations in Seoul were analyzed. • The water-soluble component was predominant over all other components in terms of the concentration, AOD, and DARF. • The forcings of most aerosol components were highest in spring and lowest in late fall or early winter. • The DARFSFC of most aerosol components (except for water-soluble) showed morning peaks during most seasons. • The DARFTOA (except for BC) showed morning peaks in spring and/or winter and afternoon peaks in summer and/or fall. • The direct radiative forcing at the atmosphere of black carbon accounted for approximately 64% of the total.

a r t i c l e

i n f o

Article history: Received 1 February 2017 Received in revised form 26 April 2017 Accepted 26 April 2017 Available online xxxx Editor: D. Barcelo Keywords: Aerosol components Direct aerosol radiative forcing AOD Short-term time resolution Seoul megacity

a b s t r a c t The temporal variations (diurnal and seasonal) of the optical properties and direct aerosol radiative forcing (DARF) of different aerosol components (water-soluble, insoluble, black carbon (BC), and sea-salt) were analyzed using the hourly resolution data (PM2.5) measured at an urban site in Seoul, Korea during 2010, based on a modeling approach. In general, the water-soluble component was predominant over all other components (with a higher concentration) in terms of its impact on the optical properties (except for absorbing BC) and DARF. The annual mean aerosol optical depth (AOD, τ) at 500 nm for the water-soluble component was 0.38 ± 0.07 (0.06 ± 0.01 for BC). The forcing at the surface (DARFSFC) and top of the atmosphere (DARFTOA), and in the atmosphere (DARFATM) for most aerosol components (except for BC) during the daytime were highest in spring and lowest in late fall or early winter. The maximum DARFSFC occurred in the morning during most seasons (except for the water-soluble components showing peaks in the afternoon or noon in summer, fall, or winter), while the maximum DARFTOA occurred in the morning during spring and/or winter and in the afternoon during summer and/or fall. The estimated DARFSFC and DARFATM of the water-soluble component were in the range of − 49 to − 84 W m−2 and +10 to + 22 W m−2, respectively. The DARFSFC and DARFATM of BC were −26 to −39 W m−2 and +32 to +51 W m−2, respectively, showing highest in summer and lowest in spring, with morning peaks regardless of the season. This positive DARFATM of BC in this study area accounted for

⁎ Corresponding author at: Dept. of Environment Engineering, Dong-Eui University, 995 Eom Gwang No, Busan Jin Gu, Busan 47340, Republic of Korea. E-mail address: [email protected] (Z.-H. Shon).

http://dx.doi.org/10.1016/j.scitotenv.2017.04.195 0048-9697/© 2017 Elsevier B.V. All rights reserved.

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

401

approximately 64% of the total atmospheric aerosol forcing due to strong radiative absorption, thus increasing atmospheric heating by 2.9 ± 1.2 K day−1 (heating rate efficiency of 39 K day−1 τ−1) and then causing further atmospheric warming. © 2017 Elsevier B.V. All rights reserved.

1. Introduction Atmospheric aerosols play a pivotal role in the Earth's climate because of their effects on the Earth's radiative balance (IPCC, 2013). The radiative forcing (RF) of aerosols is a useful way of comparing the different causes of perturbations in the Earth's climate system. This is achieved directly through the scattering and absorption of solar and terrestrial (infrared) radiation by aerosols (i.e. direct aerosol radiative forcing, DARF) in a cloud free sky (Bellouin et al., 2005; Charlson et al., 1992), and indirectly, by changing the properties (cloud albedo) and lifetime of clouds (Albrecht, 1989; Rosenfeld, 2000; Twomey, 1974). The aerosol effect on climate change has often been investigated through the magnitude of aerosol RF estimated at the top of the atmosphere (TOA) (Giorgi et al., 2002; Xu, 2001). On the other hand, recent studies have focused on evaluating the aerosol RF at the surface level (SFC), where the influence of aerosols on the global and/or local climate is higher, particularly under cloud-free conditions (di Sarra et al., 2013; Valenzuela et al., 2012). Various aerosol components have different effects on the sign and magnitude of aerosol RF (Kaskaoustis et al., 2007). Most aerosol components, such as water-soluble ions have a cooling effect on climate, whereas black carbon (BC) causes a warming effect (IPCC, 2013). The source intensities of anthropogenic aerosols in urban areas, particularly organic carbon (OC) and BC, have been enhanced significantly compared to those in background areas (Pöschl, 2005). The number and mass concentrations of urban aerosols were reported to be more than one order of magnitude higher than those of the background aerosols (Seinfeld and Pandis, 2006). The chemical composition of urban particles was also significantly different from those of the maritime clean atmosphere and continental background. For example, the concentrations of OC and BC in the urban air of central Europe were significantly higher than those in the rural and high alpine air, indicating BC/total carbon ratios of approximately 50% in urban air and 30% in rural and high alpine air (Pöschl, 2005). According to IPCC (2013), the global mean DARFs of individual aerosol components in 2005, such as sulfate (SO2− 4 ), OC, BC (including BC snow albedo), and mineral dust, were estimated to be − 0.40, − 0.19, + 0.36, and − 0.10 W m−2, respectively, due to their emissions and changes since 1750. The DARF of the individual components is quite valuable for understanding the changes in the DARF and air temperature in urban areas because of the enhancement of the OC and BC concentrations, compared to the remote marine and rural atmosphere. In general, the DARF by anthropogenic aerosols has been estimated using spatial- or temporal-averaged quantities (Yu et al., 2006). The concentrations of anthropogenic aerosols are not distributed uniformly in space and time because they are short-lived, ranging from minutes to a few weeks (depending on the size and chemical composition) in air and their sources are highly localized geographically (Seinfeld and Pandis, 2006). Therefore, the DARF due to urban aerosols can vary significantly on monthly and seasonal timescales. Most studies of the DARF were often carried out in a remote or clean atmosphere (Kim et al., 2006; Kim et al., 2011). On the other hand, few studies have examined the DARF in urban areas, especially for individual chemical components and/or in Asia (Chubarova et al., 2011; Ramachandran and Kedia, 2010; Singh et al., 2010). In addition, there have been few studies of DARFs considering both individual aerosol components (Kim et al., 2006) and high time (hourly) resolution of aerosol measurements (Ramachandran, 2005).

The aim of this study was to estimate the optical properties and DARFs of different chemical components (e.g. water-soluble, insoluble, BC, and sea-salt) of PM2.5 in a diverse range of time frames (e.g. diurnal and monthly/seasonal) using the hourly resolution data (PM2.5) in a megacity (Seoul, South Korea), based on an aerosol optical model and an atmospheric radiative transfer model. The impacts/contributions of the different aerosol components on the optical properties and DARF as well as the atmospheric heating of these components were evaluated in the target area. In addition, the observed (ground-based and satellitebased) and predicted aerosol optical depth (AOD) were also compared. 2. Materials and methods 2.1. Measurement site and sampling High time-resolution chemically apportioned DARF and the optical properties of aerosols (e.g. PM2.5) in an urban area were calculated during 2010. The PM2.5 aerosol sampling was conducted at a sampling site of Gwangjin district (Guui-dong, 127° 05.44′, 37° 32.40′) in Seoul on an hourly basis during the study period (Fig. 1). Operation of this aerosol monitoring site has been managed by the Seoul Public Health and Environment Research Institute, which has implemented quality assurance (QA) and quality control (QC) for chemical analysis. Seoul, the target city in this study, is the capital city of South Korea and a megacity with a population of approximately 10.3 million (as of 2015) (http:// kosis.kr/eng/). It is also one of the most densely populated cities in the world, having an area of approximately 605 km2 and a population density of approximately 17,000 people km−2 (as of 2014) (http://kosis.kr/ eng/). The city is surrounded by various urban environments (e.g. roads and residential, commercial, and industrial areas) with a vehicle registration of 3.1 million (as of 2015). The sampling site (Gwangjin district) in this study was located on the eastern side of Seoul, encompassed by roads, residential areas, and public parks (Fig. 1). Therefore, it is expected that the air quality (e.g. atmospheric aerosol) and climate of the study site can be affected mainly by the traffic-related emissions from the adjacent roads but not from other strong anthropogenic sources. The mean PM10 concentrations during the recent years (2010–2015) and the mean PM2.5 concentrations in 2015 at our study site were in the range of 41 ± 27–50 ± 34 μg m−3 and 22 ± 15 μg m−3, respectively, which were similar to those (41 ± 26–50 ± 40 μg m−3 and 23 ± 15 μg m−3, respectively) measured at all air quality sites in Seoul (Korean Ministry of Environment (KMOE), 2011–2016). According to the analysis of variance (ANOVA), there was no statistically significant difference in the mean concentrations between our study and the all air quality sites during most years (p-value b 0.01). PM2.5 (Particulate Matter with an aerodynamic diameter of ≤2.5 μm) has been monitored continuously from 1 January to 31 December 2010. An analysis of PM2.5 was made by a model ADI 2080 online β ray analyzer (MARGA, Applikon Analytical B.V Corp., Netherlands). The MARGA system was used to measure the concentrations of major water-soluble inorganic ions at the time resolution of 1 h. This system consists of a sampling box and an analytical box with a particle collection efficiency of 99.7%. Ambient air is drawn into the sampling box at a flow rate of 1 m3 h−1 through the impactor inlet. The gaseous species are caught up in the liquid film (0.0035% H2O2) that is formed by one Wet Rotating Denuder (WRD). Particles in the residual airflow go through a supersaturated steam (0.0035% H2O2, 120–140 °C) erupted from a single Steam Jet Aerosol collector (SJAC). The aqueous solutions from the WRD and

402

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

Fig. 1. Geographical location of the urban sampling site (Guui-dong) at Gwangjin district in Seoul, Korea (Shon et al., 2012). The open circle in the upper left panel of this figure indicates an observation site (Sun photometer observation) in Gwangju provided by the Aerosol Robotic Network (AERONET) program (http://aeronet.gsfc.nasa.gov/).

SJAC are subsequently analyzed by ion chromatography (IC) for the soluble anions and cations. Besides, the analysis of ionic components in the MARGA system was made by the comparison of equivalent conductivity between standard and unknown samples. As the basic QA for the analytical setups, the system performance was examined with respect to reproducibility, detectability, and blank levels. The method detection limit (MDL) for the major ionic species was calculated as three times of standard deviation obtained from the seven replicate analyses. In addition, the concentrations of OC and elemental carbon (EC) were analyzed using a thermal/optical-transmittance carbon aerosol analyzer (Manufacturer, Sunset Laboratory Inc.). More detailed information on the analysis of PM2.5 samples including the MDL values of each ionic component was provided in our previous studies (Shon et al., 2012, 2013). 2.2. Estimation of the optical properties of aerosol components The following optical properties of aerosols are critical to an estimation of the DARF: extinction (σex), scattering (σsc), and absorption coefficients (σab); single scattering albedo (SSA); asymmetry parameter (ASYM); aerosol optical depth (AOD, τ); and phase function. The phase function (or scattering phase function) provides the angular distribution of the light intensity scattered by a particle at a given wavelength. In this study, the Optical Properties of Aerosols and Clouds (OPAC) model was used to calculate the above optical parameters and their temporal variations (e.g. diurnal and seasonal). Seasonal groupings were as follows: spring (March–May), summer (June–August), fall (September–November), and winter (December–February). A detailed description of the OPAC was given by Hess et al. (1998). The OPAC model provides the

microphysical and optical properties of aerosol and clouds in the solar and terrestrial spectral range (e.g. 61 wavelengths of 0.25–40 μm for aerosols and water clouds). The optical properties of aerosol particles and cloud droplets were modeled using Mie theory under the assumption of spherical particles (Quenzel and Müller, 1978). In the case of aerosol components that can absorb water, the data for eight relative humidity (RH) values (0%, 50%, 70%, 80%, 90%, 95%, 98%, and 99%) are given within the model. In this study, a RH of 70% was selected due to the closeness to the mean RH (66%) during the entire period of 2010 (Table 1). Moreover, as the aerosol particles in the atmosphere exist as a mixture of several aerosol components, their optical properties can be estimated based on the external mixing approach of the OPAC model. The advantage of this model is that it provides the optical properties of different aerosol components that are divided into water-soluble, insoluble, soot (BC), sea-salt, mineral dust, and sulfate droplets. In this study, four aerosol components such as water-soluble, insoluble, soot (BC), and sea-salt were used due to the lack of measurements for sulfate droplets and major mineral dust, such as silica (Si), aluminum (Al), and iron (Fe). For the OPAC simulation, the water-insoluble part of aerosol particles was assumed to be organic material (OM) and soot (BC). In this study, the measured EC was assumed to be BC due to lack of BC measurements. Although they are not exactly the same because they are each defined by the way they are measured (e.g. BC by optical measurement (light absorption) and EC by thermal optical protocols (thermally refractory carbon with a graphitic structure)), these two carbonaceous species are often well correlated (Jeong et al., 2004). In general, EC that is strongly light absorbing is characterized as BC when comparing

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

403

Table 1 Concentrations of aerosol chemical components in PM2.5 and their optical properties (RH = 70%) at a wavelength of 500 nm estimated by OPAC model at the Guui-dong site in Seoul during the year 2010. Concentration (μg m−3)

Component

Spring PM2.5 mass con. Sum of componentsa Water-soluble Insoluble EC (or BC) Sea-salt Temp (°C) RH (%) WS (m s−1) UV (mW cm−2)

b

27 ± 15 34 ± 16 32 ± 15 4.7 ± 2.1 1.5 ± 1.1 1.0 ± 0.8 11 ± 7.0 61 ± 20 2.4 ± 1.3 0.6 ± 0.5

Optical property

Summer

Fall

Winter

Average

24 ± 15 32 ± 15 29 ± 15 6.2 ± 3.5 1.9 ± 1.1 0.5 ± 0.3 26 ± 3.0 75 ± 16 1.8 ± 0.7 0.7 ± 0.5

24 ± 18 31 ± 19 28 ± 18 5.8 ± 3.3 2.7 ± 2.0 0.4 ± 0.6 15 ± 8.0 68 ± 19 2.0 ± 1.1 0.6 ± 0.4

28 ± 16 32 ± 17 29 ± 15 4.0 ± 1.8 2.2 ± 1.8 1.2 ± 1.2 −0.8 ± 6.0 61 ± 19 2.2 ± 1.2 0.4 ± 0.3

26 ± 16 32 ± 17 30 ± 16 5.2 ± 2.9 2.1 ± 1.6 0.8 ± 0.9 13 ± 11 66 ± 19 2.1 ± 1.1 0.6 ± 0.5

σab (Mm−1)

σsc (Mm−1)

σex (Mm−1)

AOD (τ500 nm)

3.49/3.05/2.98/2.97c 0.48/0.63/0.58/0.41 12.6/15.8/22.2/18.3 b0.001

220/192/188/187 1.23/1.60/1.48/1.04 3.68/4.61/6.46/5.34 3.84/1.72/1.38/4.73

223/195/191/190 1.71/2.22/2.07/1.44 16.3/20.4/28.6/23.7 3.84/1.72/1.38/4.73

0.42/0.37/0.36/0.36 0.02/0.02/0.02/0.02 0.05/0.06/0.07/0.06 0.03/0.02/0.02/0.03

The σex, σsc, and σab are calculated by σex (σsc, σab) = Ʃ σ1ex (σ1sc, σ1ab) N, where σ1ex, σ1sc, and σ1ab represent the extinction, scattering, and absorption coefficients of the aerosol or cloud, normalized to 1 particle cm−3, respectively. N is the total number density in particles (cm−3) (Hess et al., 1998). a + 2+ − + The sum of [SO2− ], [Ca2+], [Na+], [Cl−], [OC], and [EC]. 4 ], [NO3 ], [NH4 ], [K ], [Mg b Mean ± standard deviation. c Spring/summer/fall/winter values.

optical differences between carbonaceous species (NARSTO, 2003; Venkatachari et al., 2006). Thus, BC and EC are often used interchangeably. It is important to note that the mean BC/EC concentration ratio was approximately 1.07 in an urban area of South Korea (Salako et al., 2012). In addition, BC was separated from the water-insoluble part of aerosol particles (Eq. (3)) in the OPAC model and water-insoluble OM was estimated using the OM to OC ratio and OC (Eq. (2)). The OM/OC ratios for summer and winter were 2.06 and 1.48, respectively, and the ratios for spring and fall were the average value (1.77) of these two values (Bae, 2011). The water-soluble part of aerosol particles is generally formed by primary emission and/or the gas to particle conversion process. The category of water-soluble in the OPAC model are seven chemical components − + 2+ , Mg2+, and including major inorganic ions (SO2− 4 , NO3 , NH4 , Ca − + , NO K+) and OC. Secondary inorganic ions, such as SO2− 4 3 , and NH4 , can be formed by reactions between their precursor gases originating from various anthropogenic sources (e.g. traffic-related sources and fossil fuel combustion) (Seinfeld and Pandis, 2006; Shon et al., 2013). Metallic ions, such as Ca2+, Mg2+, and K+, are generally produced from road dust, soil, sea-salt, and/or biomass burning (Shon et al., 2013). The OC measured by the thermal/optical-transmittance carbon aerosol analyzer was assumed to be water-soluble OC due to its lack of measurement. The water-soluble OC in the target city was a predominant component in total OC (the water-soluble OC/OC ratio of 0.7–0.9) (Park et al., 2014; M.S. Bae, private communication). Note that the water-soluble part represents the non-sea-salt (NSS) water-soluble components (Eq. (1)). The mass concentrations of NSS-K+, NSS-Mg2+, NSS-Ca2+, and NSS-SO2− 4 were calculated using the relation, [ion]obs − [Na] × (mass ratio of ions to Na+ in seawater). The ratios for K+, Mg2+, Ca2 +, and SO24 − were 0.036, 0.121, 0.041, and 0.252, respectively (Pilson, 1998). In this study, Na+, Cl−, and the other major ions of sea water were separated from the water-soluble part and grouped into the sea-salt part of aerosol particles (Eq. (4)). The total mass concentrations of sea-salt were calculated by the sum of [Cl−] and 1.47[Na+], where 1.47 represents the seawater − + ratio of (Na+ + K+ + Mg2+ + Ca2+ + SO2− 4 + HCO3 ) / Na . This approach assumed that all measured Cl− and Na+ is derived from seawater (Holland, 1978). Finally, the BC (or EC) component was assumed not to grow with increasing RH because it is insoluble in water (Hess et al., 1998). Therefore, the components of the aerosol particles are as follows:   ½Water‐soluble ¼ NSS−Kþ

−

ð1Þ

þ½NSS−Mg2þ þNSS−Ca2þ þNSS−SO4 2 þNO3 − þNH4 þ þOC ½Insoluble ¼ f½OC  ½OM=½OCg−½OC

ð2Þ

½BC ¼ ½EC

ð3Þ

  − ½Sea‐salt ¼ ½Cl  þ 1:47 Naþ

ð4Þ

where the number density of each aerosol component was calculated using the mass concentration of a single particle to estimate the optical properties of the individual components in the OPAC model (Hess et al., 1998). In the absence of measurements of vertical profile of aerosols in the study area, the default aerosol profile within the model was used in the calculation. On the other hand, the vertical distributions of aerosol mass and chemical compositions were assumed to be uniform within the boundary layer (≈2 km). 2.3. Measurements of the optical properties The ground-based and satellite-based data were derived from the Sun photometer observation provided by the Aerosol Robotic Network (AERONET) (http://aeronet.gsfc.nasa.gov/) and Moderate Resolution Imaging Spectroradiometer (MODIS) (http://modis-atmos.gsfc.nasa.gov/) observation, respectively. In this study, we used the AOD from the AERONET Level 2.0 (cloud-screened and quality-assured) data derived from Sun photometer measurements at a wavelength of 500 nm. Because there was no AERONET AOD corresponding to this study period in Seoul, the daily mean AOD in Gwangju (the southwestern city in South Korea, 35.1°N, 126.8°E, Fig. 1) during 2010 was used for comparison (http://aeronet.gsfc.nasa.gov/). In addition, the daily mean MODIS AOD (at 550 nm) used in this study was obtained from MODIS Terra Level 2.0 data, which passes through the middle part of the Korean peninsula (37.5°N, 127°E) with a spatial resolution of 1° × 1°. More detailed information on the MODIS is available at http://modis-atmos.gsfc.nasa. gov. For comparison of the AOD between the OPAC model and various measurements, the AODs derived from satellite-based data as well as the AERONET were used for the different years and locations (e.g. several countries in Asia). 2.4. Estimation of direct aerosol radiative forcing and heating rate The DARF are generally defined as the difference in the net (down minus up) radiation flux (solar plus long wave) with and without an aerosol (Eq. (5)). In this study, the DARFs and heating rate of four different aerosol components and their temporal variations were estimated using the radiative transfer model. These DARFs were quantified by calculating downward and upward fluxes with and without the aerosol in the wavelength range, 0.3–4.0 μm, at 1-h intervals during 2010. To estimate the DARF of the aerosol components under the assumption of

404

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

cloud free skies, the days showing a cloud fraction of 100% (100% overcast) were excluded and the fraction of the other type clouds was set to 0%. Therefore, the DARFs of the four aerosol components at the TOA and SFC were derived from the following expression (Meloni et al., 2005): DARFTOA;SFC ¼ F↓ −F↑


TOA;SFC

− Fw=o ↓ −Fw=o ↑


TOA;SFC

ð5Þ

where F and Fw/o indicate the radiation fluxes with and without aerosol, respectively. The arrows indicate the direction of the radiation fluxes (down and up). The DARF in the atmosphere (DARFATM) was estimated as the difference between the RF at two levels (i.e. DARFTOA − DARFSFC). The radiative transfer model used in this study was the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model, which was developed at the University of California, Santa Barbara (Ricchiazzi et al., 1998). The SBDART model uses a large number of parameters to estimate the radiation flux at different layers in the atmosphere. The key parameters for the model simulation were the AOD, SSA, ASYM, atmospheric profiles (e.g. temperature, pressure, and ozone density), solar geometry of the location (e.g. solar zenith angle (SZA)), phase function, and surface albedo. The AOD, SSA, ASYM, and phase function were calculated using the OPAC model, as described in Section 2.2. The SZA was calculated on an hourly basis from the specified time and geographic coordinates using an internal solar ephemeris algorithm within the SBDART model. In addition, the atmospheric profile (temperature, pressure, and ozone density) and surface albedo were fixed by choosing the US62 atmospheric profile and the land cover of urban or vegetation out of the available options in the SBDART model, respectively. Note that the US62 profile includes a high resolution of 100 m (up to 2 km) in the lower layer close to the surface and a low resolution (a few to 15 km) at heights above 2 km. 3. Results and discussion 3.1. Diurnal variability of optical properties This study investigated the diurnal variations of AOD at 500 nm (RH = 70%) for each aerosol component and their concentrations (μg m−3), on a seasonal basis during the daylight hours (Fig. 2 and Supplementary

Fig. 1). In general, the total AOD (for all aerosol components) was higher in the late morning (9:00–11:00 local standard time (LST)) and lower in the late afternoon (16:00–19:00 LST), except for fall. In fall, the total AOD gradually increased until 15:00 LST and then decreased. The diurnal variations of the AOD for all the aerosol components were similar to those of their concentrations (Fig. 2 and Supplementary Fig. 1). The hourly AOD for the water-soluble aerosol component showed a morning peak (09:00–11:00 LST) in spring and winter, but afternoon peaks in summer (14:00 LST) and fall (14:00–15:00 LST) (Fig. 2). The relatively high AOD in the morning and vice versa in the afternoon during most seasons might be primarily due to strong diurnal variations (high in the morning and low in the early or late afternoon) of secondary inor+ ganic aerosols such as NO− 3 and NH4 (Shon et al., 2013; Song and Shon, + 2014). These diurnal variations in NO− 3 and NH4 showed a similar temporal distribution pattern during most seasons, suggesting the production pathways related to the formation of NH4NO3 produced by the reaction between NH3 and HNO3 gaseous precursors. In particular, the + concentrations of NO− 3 and NH4 in the afternoon during most seasons decreased due possibly to the enhancement of NH4NO3 evaporation at high air temperatures and high boundary layer heights (dilution effect) (Shon et al., 2013). On the other hand, the peak and/or high AOD (concentrations) for the water-soluble component in the afternoon during concentrasummer and/or fall might be due primarily to the high SO2− 4 tions in the afternoon during these seasons (Shon et al., 2013). The con+ 2− centrations of major inorganic ions (NO− 3 , NH4 , and SO4 ) accounted for approximately 41%, 13%, and 18% of the water-soluble aerosol component (Eq. (1)), respectively. More detailed discussion on the chemical characteristics of water-soluble aerosols was given in previous studies (Shon et al., 2012; Shon et al., 2013). The AOD for BC showed a peak in the morning (09:00–10:00 LST) and a minimum in the afternoon (15:00–16:00 LST), regardless of the seasons (Fig. 2). In contrast, no distinct diurnal variations in the AODs for insoluble and sea-salt components were observed. The time difference in the maximum of the relative AOD contribution for the individual aerosol components might result from their source strength pattern. The water-soluble aerosol component was likely to be produced by the gas to particle conversion process of their precursor gases such as HNO3, SO2,

Fig. 2. Diurnal variations of aerosol optical depth (AOD) at 500 nm (RH = 70%) for each aerosol chemical component in PM2.5 during four seasons in 2010.

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

and NH3 during the enhanced photochemical reactivity period according to our previous studies (Shon et al., 2012, 2013). BC was strongly emitted by anthropogenic sources, such as mobile sources (e.g. road traffic sources) during the morning (Allen et al., 1999; Kondo et al., 2014). In the study area (Seoul), the BC concentrations were high in the morning (08:00–11:00 LST) and/or late afternoon (e.g. evening rush hours) during most seasons (except for nighttime in spring), possibly due to road traffic-related sources (not shown). A similar maximum in the concentration and σab (and σsc) of BC in the morning (06:00–09:00 LST) was also observed in the rural site (within a 15 km radius of an industrial zone) of India (Praveen et al., 2012). 3.2. Monthly variations of the optical properties Fig. 3 and Supplementary Table 1 present the monthly variations of the AOD and other optical properties at a wavelength of 500 nm (RH = 70%) for four aerosol components during the study period, respectively. Overall, there were some differences in the optical properties for each aerosol component across the year. The σex and AOD for the watersoluble component, which was the most dominant component, were highest in January (274 Mm−1 and 0.50, respectively), followed by April (241 Mm−1 and 0.45), and lowest in September (119 Mm−1 and 0.23). The σex and AOD of the insoluble component were also lowest (1.2 Mm−1 and 0.023) in September, with the highest values (2.9 Mm−1 and 0.026, respectively) in June. In the case of BC, its σex and AOD were highest (28 Mm−1 and 0.07, respectively) in November and lowest (14 Mm−1 and 0.045) in March. The σex and AOD of the sea-salt component were lowest (0.9 Mm−1 and 0.022, respectively) in November and highest (6.2 Mm−1 and 0.031) in December. These temporal variations of optical properties for each aerosol component might result from those of their concentrations (Fig. 3 and Supplementary Table 1). The monthly variations (0.34–0.62) of the total AOD (τ500 nm) with a maximum in January in the study area during 2010, as shown in Fig. 3, were compared with those (τ500 nm) in the principal AERONET Sun/sky radiometer sites over East Asia (e.g. Anmyon and Gosan in Korea, Beijing in China, and Dalanzadgad in Mongolia) during April 2000 to June 2005 (Kim et al., 2007) and those (τ550 nm) retrieved from different satelliteborne sensors on the Indo-Gangetic plains from April to August during 2007–2013 (Bibi et al., 2015). Of the AERONET site, the aerosol loading (e.g. AOD) over Beijing was highest, with a monthly mean AOD ranging from 0.5 to 1.2 (Kim et al., 2007). In general, the AERONET sites showed a maximum AOD in June and summer, except for the Dalanzadgad site (May and spring during the observation period). In addition, the monthly mean MODIS AOD (τ550 nm, 0.3–0.7) over East Asia including the above AERONET sites during 2000–2004 showed a maximum AOD in spring, which is in close agreement with the general distribution patterns (Kim et al., 2007). Meanwhile, the monthly variation of the total AOD

405

(τ500 nm) in the study area was similar to those (0.31–0.76, τ550 nm) by four different sensors of the MODIS Standard/Deep Blue, Multiangle Imaging Spectroradiometer (MISR), Ozone Monitoring Instrument (OMI), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) instrumentation on the Indo-Gangetic plains during 2007– 2013 (Bibi et al., 2015). A comparison of the observed (satellite- and ground-based) and model-predicted AOD was conducted during the study period of 2010 (Supplementary Fig. 2). In this study, the total mean AODs at 550 nm (τ550 nm) and 500 nm (τ500 nm) calculated using the OPAC model for all four components were 0.42 ± 0.17 and 0.48 ± 0.20, respectively (Supplementary Table 1 and Fig. 1). The MODIS AOD (τ550 nm) (satellitebased observations) in the middle part of the Korean peninsula showed a total mean of 0.42 ± 0.33 during 2010. The total mean AERONET AOD (τ500 nm) (ground-based observations) was available at the southwestern city (Gwangju, Fig. 1) of South Korea and it was 0.40 ± 0.28 during the same year (2010). The OPAC τ550 nm and τ500 nm exhibited moderate correlations (r = 0.421 (p b 0.001) and r = 0.506 (p b 0.001), respectively) with the MODIS τ550 nm and the AERONET τ500 nm, respectively. The differences between the OPAC and MODIS and between the OPAC and AERONET might be due to the difference in area coverage and in part from the dust effect. For example, MODIS-derived AOD represents the total aerosol loading in a vertical atmospheric column, which includes a dust layer above the boundary layer and covers a larger area (including rural area). In other words, the satellite overpass is at specific times and large spatial coverage (1° × 1°). In general, the SSA and ASYM provide important information on the scattering and absorption capability of aerosols and are used as key parameters for controlling the aerosol contribution to forcing (Adesina et al., 2014; Alam et al., 2011). The SSA represents the ratio between the scattering efficiency and total extinction efficiency, whereas the ASYM represents the cosine-weighted average of the scattering angle for the scattered radiation. In this study, the monthly variations of the SSA and ASYM at 500 nm for urban aerosols were examined. The mean SSA was 0.91 ± 0.02 (Fig. 4), while the maximum SSA (0.93 ± 0.01) occurred in March and the minimum SSA (0.88 ± 0.02) in September. The mean ASYM was 0.69 ± 0.01 with a maximum of 0.70 ± 0.01 in June and a minimum of 0.68 ± 0.01 in September. The SSA estimated in the study area generally showed high values, possibly due to the low concentrations (1.5–2.7 μg m−3) of absorbing BC (or EC) aerosol, compared to those found in other areas such as Delhi (4–15 μg m−3 with low SSA of 0.74–0.90, Singh et al., 2010). In addition, the temporal variation of the SSA was slightly different from that of the BC. Despite the highest BC concentration in November, the lowest SSA in September might be due in part to the lowest concentration of scattering water-soluble aerosol (much higher scattering than the other components, Table 1) in September (not shown). Similar patterns between the SSA and aerosol component concentrations were observed in Pune city (Panicker et al., 2010),

Fig. 3. Monthly variations of AOD at a wavelength of 500 nm (RH = 70%) for each aerosol chemical component in PM2.5 at the Guui-dong site in Seoul from January to December 2010.

406

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

Fig. 4. Monthly variations of (a) single scattering albedo (SSA) and asymmetry parameter (ASYM) estimated by the OPAC model and (b) BC concentrations in Seoul during the day in 2010. The vertical bars denote the 1σ standard deviation from the mean values.

Delhi city (Singh et al., 2010), and a coastal site (Goa) of India (Menon et al., 2014), and in Pretoria of South Africa (Adesina et al., 2014). The low SSAs of the aerosol mixtures in India were ascribed to the possible mixing of dust and smoke aerosols (e.g. BC) (Jacobson, 2001). 3.3. Seasonal variations of the concentrations and optical properties of aerosol components The seasonal variations of concentrations and optical properties, such as σab, σsc, σex, and AOD (τ) of four aerosol components in PM2.5 were investigated during the study period (Table 1). Their optical properties were derived from the values calculated under a representative RH of 70% and a wavelength of 500 nm. Overall, the temporal variations of the optical properties for all four components could result from those of their concentrations (Che et al., 2014). Therefore, the high values of optical properties for the water-soluble component occurred most frequently in spring, while the insoluble, BC (or EC), and sea-salt occurred most frequently in summer, fall, and winter, respectively. The mass concentrations of PM2.5 (by a β-ray absorption method) and the sum of the PM2.5 components (chemical analysis of the samples taken by a gravimetric method) were 26 ± 16 μg m−3 and 32 ± 17 μg m−3, respectively (Table 1). The former concentration was a factor of 0.81 lower than the latter. The difference between the two concentrations in this study might be because the PM2.5 mass was measured using the β-ray method. In general, the PM2.5 mass concentration determined by the β-ray method tends to be somewhat lower, due to the partial evaporation (or loss) of the low-molecular-weight volatile carbon component (e.g. OC) in the overheating process to remove the moisture effect (Kong et al., 2010; Jeon et al., 2015). When comparing these two methods, the slope (and correlation coefficient) between the PM2.5 mass and the sum of

components for the hourly (24 h) concentrations during the study period were 0.87 (and 0.83), respectively, with a slope of 0.91 (and 0.86) for the daily mean concentrations (Supplementary Fig. 3). Note that the difference between the PM2.5 mass and the sum of its components in this study was within the analytical error or uncertainty. As shown in Table 1, the σab, σsc, and σex of the water-soluble component were predominant among the four aerosol components, except for the σab of BC. For example, the total σsc of the water-soluble component (187–220 Mm−1) was two orders of magnitude higher than those of the others (BC, insoluble, and sea-salt) (b 10 Mm−1). Moreover, the σex values of the BC, insoluble, and sea-salt components accounted for approximately 7% (spring) to 15% (fall), 0.8% (winter) to 1.1% (summer), and 0.7% (fall) to 2.5% (winter) of the water-soluble component, respectively. These optical properties of the water-soluble component were attributed mainly to its significantly higher concentration than those of the other three components. For instance, the highest concentration (about 14 μg m−3) of NO− 3 , which was the most dominant species of the water-soluble component, was observed in spring, followed by winter in our previous study (Shon et al., 2013; Song and Shon, 2014). The seasonal differences in NO− 3 concentrations can be ascribed to many factors such as the difference in consumption of fossil fuel, NH4NO3 evaporation, and meteorological effects (temperature, solar radiation, and boundary layer height) (Shon et al., 2013). In contrast, the σab of BC was a factor of 3.6 (spring) to 7.5 (fall) higher than that of the water-soluble aerosol. The relatively high σab of BC was primarily because the BC is a strong absorber of radiation in the visible and near-infrared regions of the solar spectrum. In addition, the AOD (τ500 nm) of the water-soluble component (0.36–0.42) was also the most dominant, accounting for approximately 77% (fall or winter) - 81% (spring) of the total aerosol components, whereas that of BC (0.05–0.07) accounted for 10% (spring) - 15% (fall) of the total AOD. The AOD of BC was higher than those of the insoluble and sea-salt aerosol components, by a factor of 2.5 and 3.0 on average, respectively. In general, BC is emitted into the urban atmosphere mainly by combustion processes, such as biomass burning, industrial process, and vehicle exhaust. Therefore, BC (as well as OC) can be one of the key aerosol components in urban environments and its optical properties in the urban area are somewhat different from those in remote areas. In other words, the magnitude of the optical properties (e.g. σab and σex) of BC in urban aerosols was significantly higher than that in the clean atmosphere, due to higher BC concentrations in urban areas (Kim et al., 2006; Kim et al., 2011; Lee et al., 2009). For example, Kim et al. (2006) estimated the relative contribution of σex of BC to the total σex to be 5.9% in a remote island (Gosan, Jeju Island) of Korea. The contribution of σab of BC to the total σab of all four aerosol components was approximately 71% (6.8% for all extinction) at Gosan and 94% (43% for all extinction) at the polluted site in Seoul, due to the high BC concentrations (a mean of 5.8 μg m−3) (Lee et al., 2009). In the current estimation, the contributions of σab of BC to total σab and σex of BC to total σex were comparable to those in previous studies, showing 76% (spring) to 86% (fall) and 7.0% (spring) to 13% (fall), respectively, possibly due to higher BC concentrations in Seoul (2.1 ± 1.6 μg m−3) (Table 1).

3.4. Impacts of each aerosol component on the DARF The diurnal and monthly/seasonal variations of DARF of the four aerosol components and their impacts on the DARF were analyzed during the study period. Figs. 5 and 6 show the diurnal variations of DARFTOA and DARFSFC of four aerosol components, respectively, on a seasonal basis. In Fig. 5, the peaks of the negative forcing for the water-soluble, insoluble, and sea-salt components appeared in the morning during spring and winter (except for the noon peak for the water-soluble component in winter), whereas the afternoon peaks appeared during summer and fall (except for the morning peak for sea-salt in summer). Unlike this, the positive DARF for BC showed a peak in the morning (up to

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

407

Fig. 5. Diurnal variations of direct aerosol radiative forcing (DARF, W m−2) at the TOA for each aerosol chemical component and total net DARF in PM2.5 during four seasons in 2010. The vertical line represents the uncertainties corresponding to one standard deviation. The number within the figures represents the maximum value for each aerosol chemical component.

+ 15 W m−2 around 11:00 LST) and a minimum in the afternoon (≤+5 W m−2 around 18:00 LST), regardless of the seasons. The diurnal patterns of DARFSFC of all four components were distinguished from those of DARFTOA. Peaks (or maximum values) of negative forcing of all aerosol components at the SFC clearly appeared in the morning in spring. During the other three seasons, the maximum negative forcing of most aerosol components at the SFC mostly appeared in the morning (except for the afternoon or noon peaks of the watersoluble components in the three seasons) (Fig. 6). The afternoon radiative forcing peak of the water-soluble component might be associated in part with the diurnal pattern of SO2− 4 , showing the highest concentration in the afternoon (12:00–16:00 LST) during summer, due to increased photochemical production via fast gas to particle conversion (Shon et al., 2013). The diurnal differences in these DARF values might be due to the differences in optical properties (e.g. AOD), local time (or SZA), and their mass concentrations (Russell et al., 1999; Won et al., 2004). Fig. 7 presents the monthly mean variations in their DARFs at the SFC (DARFSFC) and in the ATM (DARFATM) derived over Seoul in the daytime

during 2010, including those at the TOA (DARFTOA) for the daytime and 24 h (Supplementary Table 2). The total mean DARFSFC and DARFTOA during daytime were −110 and −46 W m−2, respectively, giving rise to the DARFATM of +64 W m−2. The total DARFSFC and DARFTOA showed a maximum during spring (−136 and −61 W m−2, respectively in April) and a minimum during fall (−91 and −36 W m−2 in November). The maximum and minimum DARFATM were observed in June (+80 W m−2) and December (+55 W m−2), respectively. In addition, the DARFTOA of the water-soluble component accounted for approximately 85% (winter)– 88% (spring or summer) of the total DARFTOA for the other three aerosol components. For the DARFSFC, the contribution of water-soluble and BC components accounted for 52% (fall)–62% (spring) and 25% (spring)– 35% (fall) of the total DARFSFC for all components, respectively, with their DARFATM comprising 19–28% (water-soluble) and 59–70% (BC). Although BC contributed only 4–7% to the total aerosol loads (Table 1), it contributed a mean of approximately 64% to the total atmospheric forcing (DARFATM) due to the strong radiative absorption, thereby enhancing the warming effect. This contribution was slightly higher than that (55%) estimated in an urban area (Pune) of India (Panicker et al., 2010). On the

408

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

Fig. 6. Same as Fig. 5 except for the direct aerosol radiative forcing (DARF, W m−2) at the surface (SFC).

other hand, there were no distinct effects (≤10%) of insoluble and seasalt components on the DARF, regardless of the season. As shown in Fig. 7 and Supplementary Table 2, the relative impacts of the individual components on the DARF varied significantly across the months. The impacts of the water-soluble component on the DARFSFC, DARFTOA, and DARFATM predominated over the other three components (except for BC), with the highest in spring (especially, −84, −63, and +22 W m−2, respectively in April) and lowest during late fall or early winter (− 49, − 38, and + 10 W m−2). The monthly patterns of the DARF of sea-salt component were similar to those of water-soluble component, but the magnitude of the former DARFs was much (about one order) lower than that of the latter. Unlike the water-soluble component, the small negative impacts of the insoluble component on the DARFSFC and DARFTOA were highest in May (− 10 W m−2) and February (− 2.0 W m−2) and lowest in November (− 7.2 W m−2) and August (−1.4 W m−2), respectively. In the case of BC, its negative or positive impacts on the DARFSFC, DARFTOA, and DARFATM were highest in June (−39, +11, and +51 W m−2, respectively) and lowest in March (−26, +6.7, and 32 W m−2, respectively). On the other hand, the monthly patterns of the DARFs for all four components estimated over a 24 hour period (by a factor of 2 lower than the daytime DARF) were distinguished from those during the day. The DARFs of each aerosol component as well as the total aerosol DARF were highest during summer (especially, June) and lowest in winter or late fall. The uncertainties in the DARF calculated in this study were estimated using the standard deviations (1σ) of the optical properties of the individual components, such as AOD and SSA (Singh et al., 2010). The uncertainties in the DARFs for four aerosol components (water-soluble, insoluble, BC, and sea-salt) in the daytime were found to be 28, 15, 31, and 20%, respectively (Figs. 5 and 7 and Supplementary Table 2). If considering the errors from the water-soluble OC/OC ratio of 0.7 in Section 2.2 (Eqs. (1) and (2)), the DARFs of the water-soluble and insoluble components using the ratio of 0.7 were similar to those (a factor of 0.96 lower and a factor of 1.01 higher, respectively) estimated without such consideration. In addition, the DARF of BC derived from the BC/EC concentration ratio of 1.07 (Eq. (3)) was also similar to that (a factor of 1.04 higher) estimated without this consideration. As for the heating of the atmosphere, daily variations of the heating rate (HR) and scattered plots of HR per unit AOD (at 500 nm) for each

aerosol chemical component in the daytime during 2010 were analyzed (Fig. 8). Note that two aerosol components (insoluble and sea-salt) were excluded in the calculation of aerosol heating rate efficiency (aerosol heating rate per unit AOD) due to very weak correlation between the HR and AOD (r ≤ 0.2). The mean heating rates of water-soluble, insoluble, and BC components were 0.9 ± 0.5, 0.5 ± 0.1, and 2.9 ± 1.2 K day−1, respectively, whereas that for sea-salt was very low (≤0.001 K day−1). Our aerosol HRs were comparable to those (means of up to 2.3 K day−1 during summer and 1.8 K day−1 during winter) estimated in the megacities of Pakistan during 2010–2011 (Alam et al., 2012), those (1.3– 2.8 K day−1) in Cairo of Egypt from October 2001 to March 2006 (ElMetwally et al., 2011), and those (0.6–1.4 K day−1) in Pune of India during 2004–2009 (Kumar and Devara, 2012). In addition, the heating rate efficiency for water-soluble and BC components were estimated to be 2.2 and 39 K day−1 per unit AOD with correlation coefficients (r) of 0.76 and 0.78, respectively. This estimation was somewhat different from the heating rate efficiency from dust (4 K day−1 per unit AOD, r = 0.88) estimated in southern India in May 2007 (Das et al., 2013). The high HRs in this study area might be attributed to high atmospheric absorption (especially by BC). Compared to the other locations (Fig. 9 and Supplementary Table 3), the mean DARFSFC and DARFTOA of aerosols (except for dust aerosols) at urban sites in India ranged from −12.5 (Dibrugarh) to −110 W m−2 (Delhi) (Pathak et al., 2010; Singh et al., 2010) and − 0.6 (Pune) to + 21 W m−2 (Delhi), respectively (Panicker et al., 2010; Singh et al., 2010). The negative mean DARFs of the aerosols (except for dust aerosols) in other urban areas such as in Karachi of Pakistan (Alam et al., 2011), Lahore of Pakistan (Alam et al., 2014b), and Cairo of Egypt (ElMetwally et al., 2011) were estimated to be up to − 96, − 98, and −99 W m−2 at the surface and up to −35, −28, and −32 W m−2 at the TOA, respectively. These DARFs of the urban aerosols were comparable to the present estimation (e.g. up to −63 and −48 W m−2 for watersoluble at the SFC and TOA, respectively). In addition, the monthly mean clear-sky DARFs due to BC in mega-city Delhi, India were significantly high, e.g. up to −110 W m−2 for DARFSFC and up to +21 W m−2 for DARFTOA (Singh et al., 2010). This positive DARFTOA might be due mainly to the significant absorption of upward diffuse radiation by the enhanced BC concentration (3.3–17 μg m−3) in Delhi, India (Singh et al., 2010;

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

409

Fig. 7. Monthly variations of direct aerosol radiative forcing (DARF, W m−2) at the SFC and TOA, and in the ATM for each aerosol chemical component in PM2.5 at the Guui-dong site in Seoul from January to December 2010. The vertical line represents the uncertainties corresponding to one standard deviation.

Seinfeld and Pandis, 2016). The fractions of DARFSFC of BC in diurnallyaveraged total DARF in the remote clean atmosphere (Gosan, Jeju Island) in Korea during April 2001 comprised approximately 26% (−10.1 W m−2, Kim et al., 2006). This fraction of BC was slightly lower than those (DARFSFC of 25%–36%) estimated in the present study due primarily to the slightly higher BC concentrations in Seoul. Dust aerosols can significantly affect the DARF at the SFC as well as the TOA. The mean DARFSFC and DARFTOA of the dust aerosols in the remote and urban areas derived from radiance measurements ranged from −13 (Granada, Spain) to −194 W m−2 (Lahore, Pakistan) (Alam et al., 2014a; Valenzuela et al., 2012) and − 4 (Granada, Spain) to + 24 W m−2 (New Delhi, India) (Pandithurai et al., 2008; Valenzuela et al., 2012), respectively. In addition, the DARF of different aerosol components was estimated at background locations, such as Gosan in Korea (Kim et al., 2006; Kim et al., 2010; Kim et al., 2011; Takamura et al., 2007; Won et al., 2004; Yoon and Kim, 2006) and Bay of Bengal, Indo-Gangetic Plains, and Arabian Sea around India (Kedia et al., 2010; Prasad et al., 2007; Ramachandran, 2005). With the exception of dust aerosols, the DARFSFC (− 4.3 (Gosan) to − 31 W m−2 (Bay of Bengal)) and the DARFTOA (− 2.7 to + 0.5 W m−2 (Gosan)) in most background areas were significantly lower than those in urban areas (Kim et al., 2011;

Ramachandran, 2005; Yoon and Kim, 2006), due possibly to the different location, study period, and wavelength used in the SBDART model. In addition, the DARFTOA at Gosan ranged from − 4.5 to + 0.5 W m−2 bewas the dominant tween 1994 and 2007, while the NSS-SO2− 4 contributor to the total DARF with a negative effect (Kim et al., 2011). The net DARF at the TOA could be either positive or negative, depending on several key parameters, such as the surface albedo, particle size, dust vertical profiles, and the imaginary part of the refractive index (Liao and Seinfeld, 1998). 4. Summary and conclusions The temporal characteristics of the optical properties and DARF of different aerosol components (water-soluble, insoluble, BC, and seasalt) were examined using the OPAC and SBDART models, respectively, based on the aerosol sampling composition data (time resolution of 1 h) in Seoul during 2010. High values of the optical properties (e.g. σex and AOD) throughout the year were observed frequently in spring for the water-soluble, summer for insoluble, fall for BC, and winter for seasalt, due mostly to the monthly/seasonal patterns in their concentrations. Generally, the strong impact of aerosols on the optical properties

410

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

Fig. 8. Daily variations of atmospheric heating rate and scattered plots of heating rate per unit AOD (heating rate efficiency = regression slopes) for each aerosol chemical component in PM2.5 from January to December 2010. The days showing a cloud fraction of 100% were excluded and the best fit was calculated with heating rate per unit AOD.

and DARF was dominated by the water-soluble component (except for the σab and DARFATM of BC) during the entire study period, whereas those of the insoluble and sea-salt components were insignificant. In addition, the high SSA in spring (March) was affected significantly by the high water-soluble (scattering) and low BC (absorbing) concentrations, whereas a low SSA in fall (September) by low water-soluble and/or high BC concentrations. In the diurnal variation, the time difference in the maximum or minimum AODs for the individual components appears to be due to their source strength patterns (e.g. anthropogenic sources), mostly showing morning peaks and the minimum in the afternoon. The monthly mean total DARFSFC and DARFTOA during the daytime varied in the range, −91 to −136 W m−2 and -36 to −61 W m−2, respectively, and in the atmosphere (DARFATM), it was in the range, +55 to +80 W m−2. The water-soluble component during the day showed the highest negative forcing in spring and the lowest in late fall or early

winter, ranging from − 49 to − 84 W m−2 (DARFSFC) and − 38 to −63 W m−2 (DARFTOA) with a DARFATM of + 10 to + 22 W m−2. For BC, its negative DARFSFC and positive DARFTOA were highest in summer (− 39 and + 11 W m−2, respectively in June) and lowest in spring (− 26 and + 6.7 W m−2 in March) with a DARFATM of + 32 to +51 W m−2. The positive DARFATM might result in an increase in the atmospheric heating rate, e.g., by 2.9 ± 1.2 K day−1 (heating rate efficiency of 39 K day−1 τ−1) for the BC component. In the sensitivity test, if considering the water-soluble OC/OC ratio of 0.7 and BC/EC concentration ratio of 1.07, the DARFs of the water-soluble and insoluble components and the BC, respectively, were similar to those estimated without such considerations (differences of b 5%). The negative DARFTOA of most of the aerosol components (except for BC) showed morning peaks in spring and winter (except for the noon peak for the water-soluble component in winter) and afternoon peaks

Fig. 9. Comparison of direct aerosol radiative forcing (DARF, W m−2) at the SFC between different studies.

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

in summer and fall (except for the morning peak for sea-salt in summer), whereas the positive DARFTOA of BC showed a peak in the morning and a minimum in the afternoon, regardless of the seasons. Unlike the TOA, the negative peak DARFSFC for the 3 aerosol components occurred in the morning during most seasons (except for the watersoluble component showing afternoon or noon peaks in summer, fall, or winter). This study confirmed that the impacts of urban aerosol components on the DARF tend to vary according to the time scales. Future studies should analyze the influence of the environmental conditions (e.g. particle size and RH) on optical properties of aerosols or DARF and compare the urban and remote/rural areas to better understand the regional or local behavior of the radiative effects of atmospheric aerosols. Acknowledgments This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMIPA 2015-2050. This research was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and future Planning (2015R1A2A1A10053971). Appendix A. Supplementary data Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.scitotenv.2017.04.195. References Adesina, A.J., Kumar, K.R., Sivakumar, V., Griffith, D., 2014. Direct radiative forcing of urban aerosols over Pretoria (25.75°S, 28.28°E) using AERONET Sunphotometer data: first scientific results and environmental impact. J. Environ. Sci. 26, 2459–2474. Alam, K., Trautmann, T., Blaschke, T., 2011. Aerosol optical properties and radiative forcing over mega-city Karachi. Atmos. Res. 101, 773–782. Alam, K., Trautmann, T., Blaschke, T., Majid, H., 2012. Aerosol optical and radiative properties during summer and winter seasons over Lahore and Karachi. Atmos. Environ. 50, 234–245. Alam, K., Trautmann, T., Blaschke, T., Subhan, F., 2014a. Changes in aerosol optical properties due to dust storms in the Middle East and Southwest Asia. Remote Sens. Environ. 143, 216–227. Alam, K., Sahar, N., Iqbal, Y., 2014b. Aerosol characteristics and radiative forcing during pre-monsoon and post-monsoon seasons in an urban environment. Aerosol Air Qual. Res. 14, 99–107. Albrecht, B.A., 1989. Aerosols, cloud microphysics, and fractional cloudiness. Science 245, 1227–1230. Allen, G.A., Lawrence, J., Koutrakis, P., 1999. Field validation of a semi-continuous method for aerosol black carbon (aethalometer) and temporal patterns of summertime hourly black carbon measurements in southwestern PA. Atmos. Environ. 33 (5), 817–823. Bae, M.S., 2011. Seasonal estimation of organic mass to organic carbon (OM/OC ratio). Proceedings of 49th meeting of Korean Society for Atmospheric Environment. Bellouin, N., Boucher, O., Haywood, J., Reddy, M.S., 2005. Global estimate of aerosol direct radiative forcing from satellite measurements. Nature 438, 1138–1141. Bibi, H., Alam, K., Chishtie, F., Bibi, S., Shahid, I., Blaschke, T., 2015. Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data. Atmos. Environ. 111, 113–126. 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, 423–430. Che, H., Xia, X., Zhu, J., Li, Z., Dubovik, O., Holben, B., Goloub, P., Chen, H., Estelles, V., Cuevas-Agulló, E., Blarel, L., Wang, H., Zhao, H., Zhang, X., Wang, Y., Sun, J., Tao, R., Zhang, X., Shi, G., 2014. Column aerosol optical properties and aerosol radiative forcing during a serious haze-fog month over North China Plain in 2013 based on ground-based sunphotometer measurements. Atmos. Chem. Phys. 14, 2125–2138. Chubarova, N.Y., Sviridenkow, M.A., Smirnov, A., Holben, B.N., 2011. Assessments of urban aerosol pollution in Moscow and its radiative effects. Atmos. Meas. Tech. 4, 367–378. Das, S.K., Chen, J.-P., Venkat Ratnam, M., Jayaraman, A., 2013. Investigation of radiative effects of the optically thick dust layer over the Indian tropical region. Ann. Geophys. 31, 647–663. di Sarra, A.D., Fuà, D., Meloni, D., 2013. Estimate of surface direct radiative forcing of desert dust from atmospheric modulation of the aerosol optical depth. Atmos. Chem. Phys. 13, 5647–5654. El-Metwally, M., Alfaro, S.C., Wahab, M.M.A., Favez, O., Mohamed, Z., Chatenet, B., 2011. Aerosol properties and associated radiative effects over Cairo (Egypt). Atmos. Res. 99, 263–276. Giorgi, F., Bi, X., Qian, Y., 2002. Direct radiative forcing and regional climatic effects of anthropogenic aerosols over East Asia: a regional coupled climate-chemistry/aerosol model study. J. Geophys. Res. 107 (D20), 4439.

411

Hess, M., Koepke, P., Schult, I., 1998. Optical properties of aerosols and clouds: the software package OPAC. Bull. Am. Meteorol. Soc. 79, 831–844. Holland, H.D., 1978. The Chemistry of the Atmosphere and Oceans. John Wiley & Sons Inc., Hoboken, New Jersey (154 pp.). Intergovernmental Panel on Climate Change (IPCC), 2013. IPCC Fifth Assessment Report Climate Change 2013: The Physical Science Basis. Cambridge University Press, Cambridge, UK and New York, NY, USA. Jacobson, M.Z., 2001. Strong radiative heating due to mixing state of black carbon on atmospheric aerosols. Nature 409, 695–697. Jeon, H., Ahn, J., Kim, H., Oh, J., Sung, M., Moon, K., Gong, B., Park, J., 2015. A study on the contribution of each PM2.5 source in Seoul using receptor models. J. Korean Soc. Urban Environ. 15 (1), 7–16. Jeong, C.-H., Hopke, P.K., Kim, E., Lee, D.-W., 2004. The comparison between thermaloptical transmittance elemental carbon and Aethalometer black carbon measured at multiple monitoring sites. Atmos. Environ. 38, 5193–5204. Kaskaoustis, D.G., Kambezidis, H.D., Hatzianastassiou, N., Kosmopoulos, P.G., Badarinath, V.S., 2007. Aerosol climatology: on the discrimination of aerosol types over four AERONET sites. Atmos. Chem. Phys. 7, 6357–6411. Kedia, S., Ramachandran, S., Kumar, A., Sarin, M.M., 2010. Spatiotemporal gradients in aerosol radiative forcing and heating rate over Bay of Bengal and Arabian Sea derived on the basis of optical, physical, and chemical properties. J. Geophys. Res. 115, D07205. Kim, J., Yoon, S.-C., Kim, S.-W., Brechtel, F., Jefferson, A., Dutton, E.G., Bower, K.N., Cliff, S., Schauer, J.J., 2006. Chemical apportionment of shortwave direct aerosol radiative forcing at the Gosan super-site, Korea during ACE-Asia. Atmos. Environ. 40, 6718–6729. Kim, S.-W., Yoon, S.-C., Kim, J., Kim, S.-Y., 2007. Seasonal and monthly variations of columnar aerosol optical properties over East Asia determined from multi-year MODIS, LIDAR, and AERONET sun/sky radiometer measurements. Atmos. Environ. 41, 1634–1651. Kim, S.W., Choi, I.J., Yoon, S.C., 2010. A multi-year analysis of clear-sky aerosol optical properties and direct radiative forcing at Gosan, Korea (2001–2008). Atmos. Res. 95, 279–287. Kim, N.K., Kim, Y.P., Kang, C.-H., 2011. Long-term trend of aerosol composition and direct radiative forcing due to aerosols over Gosan: TSP, PM10, and PM2.5 data between 1992 and 2008. Atmos. Environ. 45, 6107–6115. Kondo, M.C., Mizes, C., Lee, J., Burstyn, I., 2014. Black carbon concentrations in a goodsmovement neighborhood of Philadelphia, PA. Environ. Monit. Assess. 186 (7), 4605–4618. Kong, B.-J., Kim, S.-K., Park, J.-S., Lee, S.-D., Kim, J.-C., Kim, J.-S., Lee, D.-W., Lee, S.-J., Shin, E.S., 2010. The characteristics of particle composition at the Baengnyeong Island. J. Korea Soc. Environ. Adm. 16 (2), 97–105. Korean Ministry of Environment (KMOE), 2011–2016. Annual Report of Ambient Air Quality in Korea 2010–2015. Kumar, S., Devara, P.C.S., 2012. A long-term study of aerosol modulation of atmospheric and surface solar heating over Pune, India. Tellus B 64, 18420. Lee, S., Ghim, Y.S., Kim, S.-W., Yoon, S.-C., 2009. Seasonal characteristics of chemically apportioned aerosol optical properties at Seoul and Gosan, Korea. Atmos. Environ. 43, 1320–1328. Liao, H., Seinfeld, J.H., 1998. Radiative forcing by mineral dust aerosols: sensitivity to key variables. J. Geophys. Res. 103, 31637–31645. Meloni, D., di Sarra, A., Di Iorio, T., Fiocco, G., 2005. Influence of the vertical profile of Saharan dust on the visible direct radiative forcing. J. Quant. Spectrosc. Radiat. Transf. 93, 397–413. Menon, H.B., Shirodkar, S., Kedia, S., Ramachandran, S., Babu, S., Moorthy, K.K., 2014. Temporal variation of aerosol optical depth and associated shortwave radiative forcing over a coastal site along the west coast of India. Sci. Total Environ. 468–469, 83–92. NARSTO, 2003. Particulate Matter Science for Policy Makers: A NARSTO Assessment. Parts 1 and 2. NARSTO Management Office, (Envair), Pasco, Washington http://www. cgenv.com/NARSTO. Pandithurai, G., Dipu, S., Dani, K.K., Tiwari, S., Bisht, D.S., Devara, P.C.S., Pinker, R.T., 2008. Aerosol radiative forcing during dust events over New Delhi, India. J. Geophys. Res. 113, D13209. Panicker, A.S., Pandithurai, G., Safai, P.D., Dipu, S., Lee, D.-I., 2010. On the contribution of black carbon to the composite aerosol radiative forcing over an urban environment. Atmos. Environ. 44, 3066–3070. Park, D.-J., Ahn, J.-Y., Shin, H.-J., Bae, M.-S., 2014. Characteristics of PM2.5 carbonaceous aerosol using PILS-TOC and GC/MS-TD in Seoul. J. Korea. Soc. Atmos. Environ. 30, 461–476. Pathak, B., Kalita, G., Bhuyan, K., Bhuyan, P.K., Moorthy, K.K., 2010. Aerosol temporal characteristics and its impact on shortwave radiative forcing at a location in the northeast of India. J. Geophys. Res. 115, D19204. Pilson, M.E.Q., 1998. An Introduction to the Chemistry of the Sea. Prentice Hall, New Jersey (431 pp.). Pöschl, U., 2005. Atmospheric aerosols: composition, transformation, climate and health effects. Angew. Chem. Int. Ed. 44 (46), 7520–7540. Prasad, A.K., Singh, S., Chauhan, S.S., Srivastava, M.K., Singh, R.P., Singh, R., 2007. Aerosol radiative forcing over the Indo-Gangetic plains during major dust storms. Atmos. Environ. 41, 6289–6301. Praveen, P.S., Ahmed, T., Kar, A., Rehman, I.H., Ramanathan, V., 2012. Link between local scale BC emissions in the Indo-Gangenic Plains and large scale atmospheric solar absorption. Atmos. Chem. Phys. 12, 1173–1187. Quenzel, H., Müller, H., 1978. Optical Properties of Single Mie Particles: Diagrams of Intensity-, Extinction-, Scattering-, and Absorption Efficiencies. vol. 34. Universität München, Meteorologisches Institut, Wiss. Mit. Nr. (Available from Meteorologisches Institut, Theresienstraße 37, D-80333 München, Germany, 59 pp.). Ramachandran, S., 2005. Aerosol radiative forcing over Bay of Bengal and Chennai: comparison with maritime, continental, and urban aerosol models. J. Geophys. Res. 110, D21206.

412

S.-K. Song et al. / Science of the Total Environment 599–600 (2017) 400–412

Ramachandran, S., Kedia, S., 2010. Black carbon aerosols over an urban region: radiative forcing and climate impact. J. Geophys. Res. 115, D10202. Ricchiazzi, P., Yang, S., Gautier, C., Sowle, D., 1998. SBDART: a research and teaching software tool for plane-parallel radiative transfer in the earth's atmosphere. Bull. Am. Meteorol. Soc. 79, 2101–2114. Rosenfeld, D., 2000. Suppression of rain and snow by urban and industrial air pollution. Science 287, 1793–1796. Russell, P.B., Hobbs, P.V., Stowe, L.L., 1999. Aerosol properties and radiative effects in the United States East Coast haze plume: an overview of the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX). J. Geophys. Res. 104 (D2), 2213–2222. Salako, G.O., Hopke, P.K., Cohen, D.D., Begum, B.A., Biswas, S.K., Pandit, G.G., Chung, Y.-S., Rahman, S.A., Hamzah, M.S., Davy, P., Markwitz, A., Shagjjamba, D., Lodoysamba, S., Wimolwattanapun, W., Bunprapob, S., 2012. Exploring the variation between EC and BC in a variety of locations. Aerosol Air Qual. Res. 12, 1–7. Seinfeld, J.H., Pandis, S.N., 2006. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. second ed. John Wiley & Sons Inc., Hoboken, New Jersey. Seinfeld, J.H., Pandis, S.N., 2016. Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. third ed. John Wiley & Sons Inc., Hoboken, New Jersey. Shon, Z.-H., Kim, K.-H., Song, S.-K., Jung, K., Kim, N.J., Lee, J.-B., 2012. Relationship between water-soluble ions in PM2.5 and their precursor gases in Seoul megacity. Atmos. Environ. 59, 540–550. Shon, Z.-H., Ghosh, S., Kim, K.-H., Song, S.-K., Jung, K., Kim, N.-J., 2013. Analysis of watersoluble ions and their precursor gases over diurnal cycle. Atmos. Res. 132–133, 309–321. Singh, S., Soni, K., Bano, T., Ranwar, R.S., Nath, S., Arya, B.C., 2010. Clear-sky direct aerosol radiative forcing variations over mega-city Delhi. Ann. Geophys. 28, 1157–1166.

Song, S.-K., Shon, Z.-H., 2014. Temporal variations in optical properties and direct radiative forcing of different aerosol chemical components in Seoul using hourly aerosol sampling. J. Korea. Soc. Atmos. Environ. 30, 1–17. Takamura, T., Sugimoto, N., Shimizu, A., Uchiyama, A., 2007. Aerosol radiative characteristics at Gosan, Korea, during the Atmospheric Brown Cloud East Asian Regional Experiment 2005. J. Geophys. Res. 112, D22S36. Twomey, S., 1974. Pollution and the planetary albedo. Atmos. Environ. 8, 1251–1256. Valenzuela, A., Olmo, F.J., Lyamani, H., Antón, M., Quirantes, A., Alados-Arboledas, L., 2012. Aerosol radiative forcing during African desert dust events (2005–2010) over Southeastern Spain. Atmos. Chem. Phys. 12, 10331–10351. Venkatachari, P., Zhou, L., Hopke, P.K., Felton, D., Rattigan, O.V., Schwab, J.J., Demerjian, K.L., 2006. Spatial and temporal variability of black carbon in New York City. J. Geophys. Res. 111, D10S05. Won, J.-G., Yoon, S.-C., Kim, S.-W., Jefferson, A., Dutton, E.G., 2004. Estimation of direct radiative forcing of Asian dust aerosols with sun/sky radiometer and lidar measurements at Gosan, Korea. J. Meteorol. Soc. Jpn. 82 (1), 115–130. Xu, Q., 2001. Abrupt change of the mid-summer climate in central east China by the influence of atmospheric pollution. Atmos. Environ. 35, 5029–5040. Yoon, S.C., Kim, J.Y., 2006. Influences of relative humidity on aerosol optical properties and aerosol radiative forcing during ACE-Asia. Atmos. Environ. 40, 4328–4338. Yu, H., Kaufman, Y.J., Chin, M., Feingold, G., Remer, L.A., Anderson, T.L., Balkanski, Y., Bellouin, N., Boucher, O., Christopher, S., DeCola, P., Kahn, R., Koch, D., Loeb, N., Reddy, M.S., Schulz, M., Takemura, T., Zhou, M., 2006. A review of measurementbased assessments of the aerosol direct radiative effect and forcing. Atmos. Chem. Phys. 6, 613–666.