Introduction
The optical property of aerosol particles is a very important parameter for
understanding the aerosol effects on radiative forcing and climate change.
Spatiotemporal distributions of aerosol particles are needed to accurately
calculate radiative forcing in the global climate system (Li et al., 2016).
Atmospheric chemical transport models (CTMs) are useful tools for estimating
the spatial distributions and concentrations of aerosol particles on
regional to global scales. In addition to CTMs, satellite remote sensing is
widely used to characterize aerosol particles and their impact on climate
change and air quality (van Donkelaar et al., 2010). However, both methods
are uncertain due to lack of regional specific optical properties. Thus, to
improve the accuracy of CTMs and satellite remote sensing, it is essential
to validate these approaches using ground-based remote sensing techniques
and surface optical measurements.
With rapid economic growth and urbanization, megacities in China have
experienced severe air pollution problems (Chan and Yao, 2008; Liu et al.,
2013; Wang et al., 2014). In addition to anthropogenic pollutants, Asian
dust originating from major deserts located in northern and western parts of
China (e.g., the Gobi desert and Taklimakan desert) influences the air quality
of China (Bi et al., 2016; Li et al., 2016). Asian dust has a high light
scattering property (single scattering albedo, ω at 550 nm = 0.935) and a low wavelength dependence of optical properties (Ångström
exponent, Å at 440–870 nm = ∼ 0.2) (Bi et al.,
2016), whereas anthropogenic pollutants from megacities in China have relatively
high light-absorbing properties (ω at 532 nm = 0.82 (Guangzhou),
0.86 (Beijing), 0.83 (Shanghai)) and strong wavelength dependence (Å at
450–700 nm = 1.46 (Guangzhou), 1.42 (Beijing)) (Garland et al., 2008,
2009; Cheng et al., 2015).
Severe haze over China can influence the air quality of downwind areas of
the Asian continent and regional environments over east Asia through
long-range transport (LRT) by the prevailing westerly (Aikawa et al., 2010;
Jung and Kim, 2011; Kaneyasu et al., 2014; Jung et al., 2015). LRT haze can
also affect the regional radiation budget directly by scattering or
absorbing solar radiation and indirectly by altering the physical properties
of clouds and the efficiency of precipitation (Ramanathan et al., 2007; Gao
et al., 2014; Jeong et al., 2014; Jung et al., 2015). Zhang et al. (2007)
reported that the Asian pollution outflow influences precipitation over the
North Pacific. To investigate the impact of LRT haze on regional
environments over downwind areas of the Asian continental outflows, it is
necessary to characterize the chemical and optical properties of LRT haze.
The ω is the key parameter used to determine the aerosol effect on
radiative forcing and climate change (IPCC, 2013). Thus, accurate
measurements of scattering and absorption properties of aerosol particles
are important for the better estimation of aerosol radiative forcing.
Spectral ω and the backscattering ratio, defined as the ratio of
light scattered in the backward hemisphere to the total light scattered,
also provide information for the accurate determination of aerosol radiative
forcing (Gopal et al., 2014). However, in situ observations of spectral aerosol
optical properties under Asian continental outflows are rare; thus, an
intensive characterization of aerosol optical properties is needed.
In Shanghai, China, the ω measured at the surface shows a weak
seasonal variation, whereas a ground-based remote sensing technique shows the
highest ω during the fall season. The ω measured by
ground-based remote sensing (0.9–0.93) is ∼ 10 % higher
than values measured at the surface (0.8–0.9) (Cheng et al., 2015). From
one year's worth of observations in Seoul, South Korea, a trend of increasing
ω with wavelength was observed during Asian dust events, whereas
little spectral dependence of ω was observed during LRT haze events
(Jung et al., 2010). During the Campaign of Air Quality Research in Beijing
2006 (CAREBeijing-2006), ω was found to be closely related to the
inflow of air to Beijing. Relatively low ω (< 0.8) was
observed for the air mass originating from the north and passing over Beijing,
whereas relatively high ω was observed for the air mass originating
from the south of Beijing (Garland et al., 2009). Garland et al. (2009)
found that relatively low ω for the air mass from the north was
caused by the high emission of soot from combustion sources in Beijing.
The objective of this study is to characterize the spectral optical
properties of the LRT haze and Asian dust originating from the Asian
continent during winter 2014. Because fossil fuel consumption increases
during winter for space heating and northwesterly winds are dominant during
winter, this study focused on winter. Size-segregated mass, chemical, and
optical measurements of aerosol particles were carried out at Daejeon, South Korea,
during January 2014 to characterize the optical properties of different
types of haze. Temporal variations in spectral optical properties under
stagnant atmospheric conditions are discussed with reference to aerosol
chemical composition. From identified Asian continental outflows, we also
investigated the wavelength dependence of aerosol optical properties.
Experimental methods
General description of measurement
Online measurements of aerosol optical properties and daily PM2.5
(particulate matter with a diameter ≤ 2.5 µm) sampling were
conducted at an air quality monitoring station in the megacity of Daejeon,
central South Korea (36.19∘ N, 127.24∘ E), during 8–31 January 2014 (Fig. 1). Because Daejeon is located downwind of Asian
continental outflows, it is frequently affected by long-range transported
pollutants and Asian dust (Jung et al., 2016). Light scattering and
absorption coefficients were continuously measured inside a monitoring
building (∼ 15 m above the ground) of the National Institute
of Environmental Research in South Korea. PM2.5 samples were collected on
pre-baked quartz fiber filters (Pall-Life Sciences, 47 mm diameter) at a
flow rate of 16.7 L min-1. An aerosol sampler (APM Korea, model
PMS-103) was installed on the rooftop of the monitoring building. Before and
after sampling, filter samples were stored in a freezer at -20 ∘C and wrapped with aluminum foil. A total of 23 filter samples were collected.
Additionally, field blank filters were collected before and after the
sampling period. Hourly precipitation data were obtained from a nearby
weather monitoring station of the Korea Meteorological Agency.
Map of the measurement site (36.19∘ N, 127.24∘ E) in Daejeon, South Korea (base map is from Google Maps).
Online measurement of aerosol chemical composition
PM10 and PM2.5 mass concentrations were measured by a
beta-attenuation monitor (Met One Instruments, BAM 1020) with an hourly
interval. The detection limit of the beta-attenuation technique is reported
as 3.6 µg m-3 by the manufacturer. Hourly PM10 calcium (Ca)
concentrations were continuously measured by X-ray fluorescence (XRF)
(Cooper Environmental Service (CES), model Xact 620). The air samples were
introduced through a PM10 inlet at a flow rate of 16.7 L min-1 and
drawn through filter tape. The online Xact 620 monitor was calibrated using
thin film standards for each element of interest, which was provided by CES.
These standards were manufactured by depositing vapor-phase elements on
blank Nuclepore (Micromatter Co.). For a 1 h time resolution, the minimum
detection limit for Ca has been reported to be 0.32 ng m-3 (Park et
al., 2014).
Online measurements of PM2.5 organic carbon (OC) and elemental carbon
(EC) were conducted using a semi-continuous carbon analyzer (Sunset
Laboratory Inc., model RT3140) based on the thermal–optical transmittance
(TOT) protocol for pyrolysis correction and the NIOSH (National Institute
for Occupational Safety and Health) 5040 method temperature profile (Birch
and Cary, 1996; Jung et al., 2010). Measurement condition of the carbon
analyzer was described in detail by Jung et al. (2016). The detection limit
of both OC and EC was 0.5 µg C m-3 for 1 h time resolution, as
reported by the manufacturer. The uncertainty of OC and EC measurements has
been reported to be 5 % (Polidori et al., 2006). Hourly averaged mass
concentrations of PM2.5, OC, and EC were used in this study.
Online measurement of aerosol optical properties
Light scattering coefficients (σs) and hemispheric
backscattering coefficients (σbs) of aerosol particles at three
wavelengths (λ= 450, 550, and 700 nm) were continuously measured
using an integrating nephelometer (TSI inc., model 3563). The nephelometer
was operated at a flow rate of 5 L min-1 with a 5 min averaging time.
The clean air and span gas (pure CO2) calibrations were carried out
every hour and once a month, respectively. The uncertainty of the
nephelometer measurements was determined to be less than 2 % with a 5 min
interval. For a 5 min resolution, the detection limits of σs were
determined to be 6, 3, and 3 Mm-1 at 450, 550, and 700 nm,
respectively, calculated as 3σ of the clean air measurement.
Systematic biases caused by angular truncation errors and a non-Lambertian
light source were corrected for scattering measurement data using the
Ångström exponents of σs (Anderson et al., 1996;
Anderson and Ogren, 1998; Garland et al., 2009). The corrected systematic
biases were ∼ 12 % of the measured values. The relative
humidity (RH) of the sampled air inside the nephelometer chamber was 21 ± 10 %.
The optical attenuation coefficients (σATN) of aerosol
particles were measured using the aethalometer (Magee Scientific, model
AE31) at seven wavelengths (370, 470, 520, 590, 660, 880, and 950 nm)
(Hansen, 2005). Air samples were drawn through the PM2.5 cyclone (BGI
Inc., SCC1.829) at a flow rate of 4 L min-1. The light absorption
coefficient (σa) was retrieved from σATN, as
described by Jung et al. (2010), by considering the “shadowing effect” and
multiple scattering within the filter. The detection limit of the
aethalometer σa, defined as 3σ of the dynamic blank,
was determined to be 2 Mm-1. The measurement uncertainty of the
aethalometer is reported to be ± 5 % by the manufacturer (Hansen,
2005). Hourly averaged light scattering and absorption coefficients were
used in this study.
Water-soluble ions analysis of PM2.5 filter samples
A quarter of each filter sample was extracted with 10 mL of ultrapure water
under ultrasonication (for 30 min). Water extracts were then passed through
a disk filter (Millipore, Millex-GV, 0.45 mm) to remove filter debris and
water-insoluble particles. Water extracts were stored in a refrigerator at
4 ∘C prior to analysis. The total organic carbon (TOC) level of the
ultrapure water was maintained below 4 ppb using a LabPure S1 filter and an
ultraviolet (UV) lamp (ELGA, PureLab Ultra).
Water-soluble inorganic ions were analyzed using an ion chromatograph
(Thermo Fisher Scientific, Dionex ICS-15000). Analytical conditions of
anions (Cl-, NO3-, SO42-) and cations (Na+,
NH4+, K+, Ca2+, Mg2+) were described in detail by
Jung et al. (2016). The detection limits of Cl-, NO3-, and
SO42-, which are defined as 3 times the standard deviation of
field blanks, were determined to be 0.02, 0.01, and 0.11 µg m-3,
respectively. The analytical error of Cl-, NO3-, and
SO42- measurements was 2.0, 1.7, and 2.3 %,
respectively. The detection limits of NH4+ and K+ were
determined to be 0.03 and 0.006 µg m-3, respectively. The
analytical errors of NH4+ and K+ were determined to be
1.4 and 0.73 %, respectively. Daily average water-soluble ions were
used in this study.
Satellite RGB (red, green, blue) images and air mass backward
trajectories
Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were
obtained from the NASA/MODIS web site (https://modis.gsfc.nasa.gov/). Air mass backward trajectories ending at
the measurement site were calculated for heights of 200, 500, and 1000 m
above ground level (AGL) using the HYSPLIT (HYbrid Single-Particle
Lagrangian Trajectory) model (Draxler and Rolph, 2016; Rolph, 2016). All
back trajectories were ended at 00:00 and 12:00 UTC (09:00 and 21:00 LT, respectively) and extended 96 h backwards.
Intensive optical properties
Ångström exponent of aerosol light scattering
The wavelength-dependent aerosol scattering can be expressed by a power law
(Ångström, 1929) as follows:
σs,λ=σs,λrλλr-Å,
where σs,λr is the scattering coefficient at a reference
wavelength λr and Å is the Ångström exponent. The
Ångström exponent can be retrieved from the slope of a
double-logarithmic plot of σs versus λ as follows:
Åλ1λ2=-logσs,λ1σs,λ2logλ1λ2.
Backscattering fraction, single scattering albedo, and mass scattering
efficiency
The backscattering coefficient is defined as the scattered light intensity
in the backward hemisphere of the particle (90–180∘)
(Anderson and Ogren, 1998). The backscattering ratio is used to derive the
slope of the particle size distribution and also provides an estimate of the
bulk refractive index of particles in the atmosphere (Gopal et al., 2014).
The hemispheric backscattering fraction, bλ, is defined as the
ratio of the backscattering coefficient to the total scattering coefficient
at a given wavelength (λ=450, 550, and 700 nm), calculated as
bλ=σbs,λσs,λ.
The single scattering albedo, ωλ, is the ratio of the
scattering coefficient to the extinction coefficient at a given wavelength.
Here, ωλ at a certain λ can be calculated as
follows:
ωλ=σs,λσs,λ+σa,λ.
Because σa was not measured at 550 nm by an aethalometer,
σa at λ= 520 nm is converted to σa at
λ= 550 nm as follows:
σa,500=σa,520⋅λ(550nm)λ(520nm)-∝,
where α is the absorbing Ångström exponent, which was
determined from spectral aerosol light absorption as follows:
∝=-logσa,590-log(σa,520)log590nm-log(520nm).
The mass scattering efficiency, MSEλ, is the ratio of the
scattering coefficient to the mass concentrations at a given wavelength,
expressed as
MSEλ=σs,λPM2.5mass.
Results and discussion
Temporal variations in PM mass and light scattering coefficient (σs)
Temporal variations in (a) hourly average wind speed and
precipitation, (b) PM2.5 and PM10 mass concentrations, (c) PM2.5 / PM10 mass ratio, and light scattering coefficient (σs) at 450, 550, and 700 nm at the Daejeon site during January 2014.
Figure 2 shows temporal variations in wind speed and hourly precipitation,
PM10 and PM2.5 mass, the PM2.5 / PM10 mass ratio, and the
light scattering coefficient (σs) at the measurement site in
Daejeon during 8–31 January 2014. The PM10 mass concentrations ranged
from 19 to 270 µg m-3 with an average of 83 ± 42 µg m-3, and
PM2.5 mass concentrations ranged from 8 to 147 µg m-3 with an average of 57 ± 30 µg m-3 during the
measurement period. The average PM2.5 mass concentration in this study
is much higher than the US EPA NAAQS (National Ambient Air Quality
Standards) for PM2.5 of 35 µg m-3 (24 h average). Average
PM2.5 / PM10 mass ratios ranged from 0.41 to 0.93 with an average of
0.68 ± 0.1. σs at 550 nm ranged from 12.7 to 678.4 Mm-1 with an average of 189.1 ± 142.0 Mm-1. The average
σs in this study is comparable with the annual mean of 217 Mm-1 measured in the Shanghai region, China, during 2010–2012 (Cheng et
al., 2015) but is lower than the annual mean of 360 Mm-1 in the Beijing
region, China, measured during 2009–2010 (Jing et al., 2015). Because light
scattering is caused mainly by aerosol particles and the scattering
measurements of the present study were performed under dry conditions (RH < 30 %), similar temporal patterns were observed for PM mass and
σs (Fig. 2).
As shown in Fig. 2, three haze episodes were observed on 12, 17, and 20 January 2014 with peak PM10 mass concentrations of 173, 210, and 270 µg m-3,
respectively. PM2.5 / PM10 mass ratios during the
episodes were measured as 0.71, 0.69, and 0.54, respectively, during the
three episodes. The first and second haze episodes were caused mainly by the
accumulation of pollutants for 3–4 days under stagnant atmospheric
conditions with relatively low wind speed (< 1 m s-1) (Fig. 2).
After 3–4 days of aerosol accumulation, PM mass concentrations showed a
sharp decrease with relatively high wind speeds (> 2 m s-1). A
sharp increase in PM10 mass was observed during the third episode when
a relatively high wind speed was observed (Fig. 2a). A similar temporal
pattern was observed for σs and PM10 mass concentrations
during the three haze episodes. The light scattering coefficient at 550 nm
reached peak values of 494.2, 594.4, and 678.4 Mm-1 during the first,
second, and third episodes, respectively (Fig. 2d).
During the first and second haze episodes, no precipitation was observed,
whereas before and after the third haze episode light precipitation was
observed with an hourly average of 0.5–1.5 mm h-1. Sharp decrease of
σs and PM10 mass concentrations during the third haze
episode was mainly attributed to precipitation. However, the first and
second haze episodes were not influenced by precipitation.
Single scattering albedo (ω), Ångström exponent (Å), and
backscattering fraction (b)
Figure 3 shows temporal variations in aerosol optical properties, including
σs, Å, backscattering fraction (b), and ω. The Å value
between 450 and 700 nm (Å(450/700)) ranged from 0.94 to 1.99 with an average
of 1.60 ± 0.19, which is comparable to the Å(450/550) value of 1.59 ± 0.21 and Å(550/700) value of 1.61 ± 0.19 listed in Table 1. The
Å(450/700) value obtained in this study is slightly higher than that obtained
in Beijing, China, during summer 2006 (1.42 ± 0.19; Garland et al.,
2009) and that obtained in Guangzhou, China, during summer 2006 (1.51 ± 0.20; Garland et al., 2008). Because Å is negatively correlated with particle
diameter (Eck et al., 1999), the slightly higher Å observed in this study
compared with those from mainland China implies larger aerosol particles in
this study.
Summary of aerosol optical parameters observed in Daejeon, South
Korea, during January 2014.
Component
Unit
Min–max (average ± SD)
Light scattering coefficient, σs,450
Mm-1
16.5–805.0 (256.9 ± 183.7)
σs,550
Mm-1
12.7–678.4 (189.1 ± 142.0)
σs,700
Mm-1
9.3–531.6 (129.1 ± 101.3)
Backscattering coefficient, σbs,450
Mm-1
2.4–77.2 (27.6 ± 16.9)
σbs,550
Mm-1
1.7–61.3 (21.3 ± 13.3)
σbs,700
Mm-1
1.4–57.2 (17.8 ± 11.7)
Ångström exponent of σs, Å(450/550)
0.85–2.06 (1.59 ± 0.21)
Å(450/700)
0.94–1.99 (1.60 ± 0.19)
Å(550/700)
1.0–1.97 (1.61 ± 0.19)
Hemispheric backscattering fraction, b450
0.08–0.17 (0.12 ± 0.02)
b550
0.08–0.17 (0.12 ± 0.02)
b700
0.1–0.19 (0.15 ± 0.02)
Single scattering albedo, ω450
0.57–0.95 (0.85 ± 0.07)
ω550
0.58–0.95 (0.85 ± 0.07)
ω700
0.56–0.95 (0.84 ± 0.08)
During the measurement period, b at 550 nm (b550) ranged from 0.08 to
0.17 with an average of 0.12 ± 0.02, which is comparable with
b450 (0.12 ± 0.02) but slightly lower than b700 (0.15 ± 0.02). Similar patterns of b with wavelength were observed in Beijing owing
to a decrease in particle size with increasing wavelength (Garland et al.,
2009). The ω at 550 nm (ω550) ranged from 0.58 to 0.95
with an average of 0.85 ± 0.07, which is comparable with ω450 (0.85 ± 0.07) and ω700 (0.84 ± 0.08). The
average ω550 is close to the values reported from other
locations in and around Beijing and Guangzhou (ω550= 0.82–0.85)
(Bergin et al., 2001; Andreae et al., 2008; Cheng et al., 2008;
Garland et al., 2008, 2009).
Temporal variations in (a) hourly average σs,550, (b) the Ångström exponent of σs (Å), (c) the backscattering
fraction (b), and single scattering albedo (ω) at 450, 550, and 700 nm. Å(450/550) represents the Ångström exponent calculated from
σs at 450 and 550 nm.
Dynamic temporal patterns in Å, b, and ω were observed during the
measurement period (Fig. 3). Gradual decreases in Å with increasing σs were observed during the first and second haze episodes, whereas a
sharp decrease in Å was observed with increasing σs during the
third episode. It was also found that b was negatively correlated with
σs during the three episodes. Meanwhile, ω increased
gradually with σs during the first and second episodes. These
results indicate that temporal variations in Å, b, and ω are closely
related to those in σs. In this study, Å and b were negatively
correlated with σs, whereas ω was positively correlated
with σs.
Scatter plot of σs,550 versus (a) ω550 and
(b) Å(450/700) during the entire measurement period.
Figure 4 clearly shows that ω550 increases with σs,550. When ω550 was less than 200 Mm-1,
ω550 varied widely from 0.6 to > 0.9. The
Å(450/700) value increased with σs,550 when σs,550 was lower than ∼ 150 Mm-1. However, when
σs,550 was higher than ∼ 150 Mm-1,
Å(450/700) gradually decreased with increasing σs,550.
Figure 5a shows a scatter plot of ω550 versus b550 as a
function of σs,550, where ω550 is observed to
decrease as b550 increases. A scatter plot of b550 versus
Å(450/700 m) is shown in Fig. 5b. A positive correlation is observed between
Å(450/700) and b550 when σs,550 is higher than 200 Mm-1, whereas a poor correlation is observed when σs,550 is lower than 200 Mm-1. In addition, a relatively
small b550 is observed as σs,550 increases (Fig. 5a
and b).
Scatter plots of (a) b550 versus ω550 and (b) Å(450/700) versus b550 as a function of σs,550.
Aerosol optical properties during severe haze episodes
Classification of haze episodes
As shown in Fig. 2b, three haze episodes were observed during 11–12,
14–17, and 20 January 2014. This study defines haze episodes when PM2.5
mass concentration is higher than 80 µg m-3 or PM10 mass
concentration is higher than 150 µg m-3. These threshold values of
the haze episode correspond to visibility of ∼ 8 km estimated
by Jung et al. (2009b). This study focused on the second and third haze
episodes, which peaked on 17 and 20 January 2014. Figure 6 shows MODIS RGB
images during 14–17 January 2014. A dense haze layer is clearly seen over
east China during 14 January. This layer moved slowly to the Korean
Peninsula from 15 to 17 January. Air mass backward trajectories ending at
the measurement site also show the transport of air masses from east China
to the Korean Peninsula on 17 January 2014, as shown in Fig. 7a. During the
second haze episode, very low wind speeds of < 1 m s-1 were
observed (Fig. 2a). Thus, the second haze episode is classified as a period
of accumulation of LRT pollutants from the Asian continent (LRT haze).
MODIS RGB images over east Asia during 14–17 January 2014.
Air mass backward trajectories arriving at the measurement site on
(a) 16 and (b) 20 January 2014. Red, blue, and green lines represent
backward trajectories arriving at heights of 200, 500, and 1000 m,
respectively.
During the third haze episode on 20 January, very high concentrations of Ca
(maximum: 9.4 µg m-3, average: 3.2 ± 3.4 µg m-3)
were observed (Table 2). The air mass backward trajectory for 20 January
clearly shows that the air mass originating from the Inner Mongolia desert area
had an impact on the Korean Peninsula (Fig. 7b). During the third haze
episode, relatively high wind speeds of > 2 m s-1 were
observed (Fig. 2a). Thus, the third haze episode is classified as an Asian
dust episode.
Comparison of PM mass, chemical components, and intensive optical
properties during long-range transported (LRT) haze and Asian dust episodes
observed at Daejeon, South Korea, during January 2014.
LRT hazea
Asian dustb
Min–max (average ± SD)
PM10 (µg m-3)
133–210 (163.9 ± 25.0)
126–270 (211.3 ± 57.5)
PM2.5 (µg m-3)
100–145 (121.6 ± 12.8)
86–147 (121.5 ± 22.7)
PM2.5 / PM10 ratio
0.68–0.84 (0.75 ± 0.06)
0.48–0.68 (0.59 ± 0.06)
EC / PM10 ratio
0.026–0.047 (0.033 ± 0.006)
0.023–0.032 (0.026 ± 0.003)
Ca (µg m-3)
0.02–0.3 (0.2 ± 0.1)
0.2–9.4 (3.2 ± 3.4)
σs,550 (Mm-1)
358.8–594.4 (503.4 ± 60.5)
276.1–678.4 (560.9 ± 151)
σa,550 (Mm-1)
29.3–105.4 (51.9 ± 21.9)
29.4–46.1 (39.4 ± 7.3)
Å(450/700)
1.30–1.47 (1.39 ± 0.05)
0.94–1.25 (1.08 ± 0.14)
ω550
0.84–0.94 (0.91 ± 0.03)
0.90–0.94 (0.92 ± 0.02)
a LRT haze: 17 January 2014, 00:00–23:00 LT.
b Asian dust: 20 January 2014, 13:00–18:00 LT.
Temporal variations in the chemical and optical properties of LRT
haze
Temporal variations in (a) mass concentrations of PM2.5
chemical components and (b) PM2.5 mass fractions of major components
during 14–17 January 2014.
Figure 8 shows temporal variations in the chemical composition of PM2.5
during the LRT haze episode (14–17 January 2014). As mentioned above, the
LRT haze episode was caused mainly by the accumulation of long-range
transported pollutants from the Asian continent. Gradual increases in total
PM2.5 mass were observed during the LRT haze episode (Fig. 8a). The
relative contribution of PM2.5 chemical composition is also shown in
Fig. 8b. Organic aerosol (OA) dominated the PM2.5 mass composition,
followed by NO3-, SO42-, and NH4+. Even though
a small decrease in OA mass fraction was observed during 15 January, the
mass fractions of the major PM2.5 chemical components were invariant
from 14 to 17 January. These results suggest that the increase in PM2.5
mass concentration observed during the LRT haze episode was caused mainly by
the accumulation of LRT pollutants.
Figure 9 shows temporal variations in the daily average intensive optical
properties of the LRT haze. The Å(450/700) and b550 values decreased
during the accumulation period from 14 to 17 January, while MSE550 and
ω550 increased. Average Å(450/700) decreased from 1.74 ± 0.09 on 14 January
to 1.39 ± 0.05 on 17 January. Average b550
decreased from 0.15 ± 0.01 on 14 January to 0.10 ± 0.003 on 17 January.
Average MSE550 of PM10 increased from 1.73 ± 0.40 m2 g-1 on 14 January to 3.11 ± 0.46 m2 g-1 on 17 January.
An increase in MSE550 with increasing PM mass concentration
during the haze episodes was also observed in Beijing and Guangzhou, China,
during summer 2006 (Jung et al., 2009a, b). For example, in Beijing the
MSE550 of PM10 increased from 1.4 ± 0.89 m2 g-1
during relatively clean conditions to 3.1 ± 0.9 m2 g-1
during relatively polluted conditions (Jung et al., 2009a). At most
monitoring sites in the United States, dry MSE increased with increasing mass
concentration (IMPROVE, 2006).
Average ω550 increased from 0.81 ± 0.07 on 14 January to
0.90 ± 0.03 on 17 January. A similar pattern was observed as pollution
increased in Beijing during summer 2006 (Jung et al., 2009a). Average
ω550 increased from ∼ 0.75 during relatively
clean conditions to ∼ 0.86 during relatively polluted
conditions in Beijing during summer 2006 owing to an increase in
SO42-, NO3-, NH4+, and organic aerosols (Jung
et al., 2009a). Because EC is a strong light-absorbing aerosol, changes in
EC mass fraction in PM2.5 mass can be used as an indicator of ω. As shown in Fig. 8b, EC mass fraction in PM2.5 was invariant from 14
to 17 January. These results indicate that an increase in mass concentration
of secondary aerosols such as SO42-, NO3-,
NH4+, and secondary organic aerosol cannot explain the increase in
ω550 under stagnant conditions during the LRT haze episode. On
the other hand, an increase in MSE550 under stagnant conditions (Fig. 9b)
can enhance ω550, resulting in an increase in ω550
under stagnant conditions.
Temporal variations in (a) daily average Å(450/700) and b550, (b) mass scattering efficiency at 550 nm (MSE550), and (c) ω550
during 14–17 January 2014.
The amount of light scattered by aerosol particles can be accurately
estimated using Mie theory when the size distribution and refractive index
of the particles are known (Mie, 1908; Hess et al., 1998; Seinfeld and
Pandis, 1998). Light scattering efficiencies of (NH4)2SO4 and
organic aerosols at 550 nm were calculated using Mie theory using refractive
indices for 1.53–0i and 1.55–0i, respectively (Liu et al., 2009), as shown
in Fig. 10. Light scattering efficiencies of (NH4)2SO4 and
organic aerosols at 550 nm increase as particle size increases to 600 nm.
Freshly formed aerosol particles have a diameter (Dp) of less than 100 nm (Yue et al., 2010) and grow into the accumulation mode (100 nm < Dp < 1000 nm)
through the condensation of gas vapors or
coagulation (collisions between particles; Seinfeld and Pandis, 1998). Thus,
larger particles (in the accumulation mode) are observed under polluted
stagnant conditions. An increase in Dp under stagnant conditions can
enhance light scattering, resulting in an increase in MSE. Å and b are also
closely related to the size of aerosol particles. For example, Eck et al. (1999) reported that coarse-mode particles had relatively low Å compared with
fine-mode particles. Nemesure et al. (1995) reported that the forward
scattering fraction increases as particle size increases, resulting in a
decrease in b. This suggests that the temporal variations in intensive
optical properties shown in Fig. 9 are closely related to the change in size
of aerosol particles under stagnant conditions.
Scattering efficiency of (NH4)2SO4 and organic
aerosols as a function of particle diameter, as calculated from Mie theory.
Because the LRT haze from the Asian continent reached the Korean
Peninsula on 14 January, as shown in Fig. 6, aerosol optical properties on 14 January can be used to evaluate aerosol mixing state or aging during the
atmospheric transport. When intensive optical properties of aerosols on 14 January were compared with those obtained at the air mass source regions in China,
no big difference between them was observed. For example, MSE550 of
PM10 (1.73 ± 0.40 m2 g-1) on 14 January was similar to
those (1.4 ± 0.89 m2 g-1) during relatively clean condition
in Beijing, China, but much lower than those (3.1 ± 0.9 m2 g-1)
during relatively polluted conditions (Jung et al., 2009a).
ω550 (0.81 ± 0.07) on 14 January was also similar to
those (∼ 0.75) during relatively clean conditions in Beijing.
These results imply that aerosol aging is insignificant during the
atmospheric transport from China to the Korean Peninsula in winter.
Intercomparison of the aerosol optical properties of LRT haze versus Asian
dust particles
Comparison of (a) average σs,550 during the severe
long-range transported haze episode (17 January) and during the Asian dust
episode (20 January). Comparisons of Å(450/700), b550, and ω550 are shown in (b), (c), and (d), respectively.
Optical properties of the LRT haze and Asian dust are compared in Fig. 11
and summarized in Table 2. For this comparison, data obtained on 17 January
were used to represent aged LRT haze. Elevated Ca concentrations were
observed during the Asian dust episode, with an average of 3.2 ± 3.4 µg m-3. Similar levels of PM2.5 mass were obtained during the
LRT haze and Asian dust episodes, whereas much higher PM10 mass was
obtained during the Asian dust episode compared with the LRT haze episode
(Table 2), resulting in higher PM2.5 / PM10 mass ratios during the
LRT haze episode (0.75 ± 0.0) compared with the Asian dust episode
(0.59 ± 0.06). Higher EC/PM10 mass ratios were observed during
the LRT haze episode with an average of 0.033 ± 0.00 compared with the
Asian dust episode (0.026 ± 0.003). PM2.5 / PM10 mass ratios
and EC / PM10 mass ratios during the Asian dust episode were higher than
those obtained in Seoul, South Korea, during severe Asian dust episodes in
2007–2008 (PM2.5 / PM10 < 0.4; EC / PM10 < 0.013). In addition, high PM2.5 mass concentrations during the Asian
dust episode in this study suggest that Asian dust particles mixed with LRT
haze originating from anthropogenic emissions had an impact on the
measurement site on 20 January.
Similar levels of σs were observed during the LRT haze (503.4 ± 60.5 Mm-1) and Asian dust episode (560.9 ± 151 Mm-1)
(Fig. 11a). The ω550 values obtained for the two episodes were
comparable, with averages of 0.91 ± 0.03 and 0.92 ± 0.0 observed
during the LRT haze and Asian dust episodes, respectively. However, a higher
light absorption coefficient (σa,550) was obtained during the
LRT haze episode (51.9 ± 21.9 Mm-1) compared with the Asian dust
episode (39.4 ± 7.3 Mm-1). Higher Å(450/700) was obtained during
the LRT haze episode (average of 1.39 ± 0.05) compared with the Asian
dust episode (1.08 ± 0.14), due mainly to the relatively large size
distribution during the Asian dust episode. The results of this study
suggest that PM2.5 / PM10 mass ratios and Å(450/700) can be used as
tracers to distinguish aged LRT haze and Asian dust based on differences in
the particle size distribution. This study suggests that
PM2.5 / PM10 mass ratio and Å(450/700) of < 0.6 and < 1.0, respectively, can be used as the cut-off points to indicate Asian dust
mixed with haze.
Conclusions
An intensive field campaign was conducted at an area downwind of the Asian
continental outflow (Daejeon, South Korea) during winter 2014 to characterize the
spectral optical properties of severe haze episodes. Dynamic temporal
patterns of aerosol optical properties were observed during the measurement
period. During the stagnant period (13–17 January 2014), after long-range
transport of haze from the Asian continent, no significant change in the
mass fraction of PM2.5 chemical composition was observed, with the
highest fraction being organic aerosol, followed by NO3-,
NH4+, and SO42-. On the other hand, a gradual decrease
in Ångström exponent (Å) and gradual increases in single scattering
albedo (ω) and mass scattering efficiency (MSE) were observed during
the stagnant period. Mie calculations suggest that the increase in aerosol
particle diameter under stagnant conditions enhanced light scattering,
resulting in an increase in MSE. It is also suggested that the increase in
MSE under stagnant conditions enhanced ω. These results imply that
change in particle size rather than chemical composition during the stagnant
period is the dominant factor affecting the aerosol optical properties.
During the Asian dust episode, very high values of PM10 mass and light
scattering coefficients at 550 nm, σs,550, were observed with
averages of 211.3 ± 57.5 µg m-3 and 560.9 ± 151 Mm-1, respectively. The ω550 during the LRT haze and Asian
dust episodes were comparable, with averages of 0.91 ± 0.03 and 0.92 ± 0.0, respectively, implying that aged LRT pollutants and Asian dust
particles have similar ω. A relatively small PM2.5 / PM10
ratio and Å(450/700) were observed during the Asian dust episode compared
with those during the LRT haze episode, indicating that PM2.5 / PM10
mass ratios and Å(450/700) can be used as tracers to distinguish aged LRT
haze and Asian dust.
The results of this study imply that severe haze episodes over the Korean
Peninsula are mainly caused by long-range transported pollutants from the
Asian continent. These severe haze episodes can be elevated under the
stagnant atmospheric condition. It is postulated that emissions from local
sources can also contribute to severe haze episodes under the stagnant
atmospheric condition. Thus, the contribution of local sources to severe
haze episodes needs to be classified and quantified in a future study to
better understand the characteristic behavior of aerosol optical property.