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Atmospheric Environment 42 (2008) 2208–2224

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Seasonal characteristics of lidar ratios measured with a Ramanlidar at Gwangju, Korea in spring and autumn

Young M. Noha, Young J. Kima,�, Detlef Mullerb

aAdvanced Environmental Monitoring Research Center (ADEMRC), Department of Environmental Science & Engineering, Gwangju

Institute of Science and Technology (GIST), 1 Oryong-dong, Buk-gu, Gwangju 500-712, Republic of KoreabPhysics Department, Leibniz Institute for Tropospheric Research (IfT), Permoserstr. 15, 04318 Leipzig, Germany

Received 12 July 2007; received in revised form 21 November 2007; accepted 22 November 2007

Abstract

Vertical profiles of aerosol lidar ratios at wavelengths of 355 and 532 nm were measured with the GIST/ADEMRC

(Gwangju Institute of Science & Technology/ADvanced Environmental Monitoring Research Center) multi-wavelength

Raman lidar system at Gwangju, Korea (35.101N, 126.531E) during several observation periods between February 2004

and May 2005. The total number of observed aerosol layers was 63, of which 38 and 25 were observed in spring and

autumn, respectively. Average values of the lidar ratio, Sa, were 55710 sr and 5679 sr at 355 and 532 nm, respectively, in

spring and 61.477.5 sr and 63.1712.8 sr at 355 and 532 nm, respectively, in autumn. Cases of high lidar ratio values

(465 sr) were observed more frequently in autumn than in spring for 28% and 46% of the time at 355 and 532 nm,

respectively. Mean lidar ratio value of 5176 sr at 532 nm was obtained for Asian dust particles in spring which was lower

than those for non-dust (60710 sr) and smoke (6578 sr) particles. Very high lidar ratios of 75.3715.8 sr at 532 nm were

observed above the planetary boundary layer (PBL) in autumn. These high values are believed to have largely resulted

from an increased amount of light-absorbing particles mostly in the fine mode of the particle size distribution, generated by

coal combustion and agricultural biomass burning. Lidar ratios, Angstrom exponents and effective radii values retrieved

from collocated sunphotometer data were similar to those obtained from Raman lidar measurements.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Lidar ratio; Angstrom exponent; Raman lidar; Sunphotometer

1. Introduction

East Asia and in particular China often experi-ence a very high loading of the atmosphere withaerosol pollution due to the combined effects ofexpanding arid dust emission regions and increasing

e front matter r 2007 Elsevier Ltd. All rights reserved

mosenv.2007.11.045

ing author. Tel.: +82 62 970 3401;

3404.

ess: yjkim@gist.ac.kr (Y.J. Kim).

regional population and fossil fuel usage (Xia et al.,2005; Luo et al., 2001; Papayannis et al., 2007). Theaerosol particles are transported over long distancesand dispersed over large downwind areas in amanner that is dependent on meteorological condi-tions. Due to its downwind location in East Asia,the Korean peninsula is often affected by long-rangetransported aerosols such as Asian dust, biomass-burning smoke pollution, and anthropogenic parti-cle pollution (Kim et al., 2005; Lee et al., 2006).

.

ARTICLE IN PRESSY.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–2224 2209

Therefore, the characterization of optical propertiesof atmospheric aerosols over the Korean peninsulais important for assessing both the changing state ofthe atmosphere in that region and its impact on theenvironment.

Radiative effects of atmospheric aerosols need tobe characterized in order to assess and predictglobal and regional climatic change more accurately(IPCC, 2007). Furthermore, knowledge of thevertical distribution of atmospheric aerosols andtheir optical properties is important for determiningtheir direct radiative forcing (Haywood and Ra-maswamy, 1998). Column-integrated optical prop-erties of atmospheric aerosols in East Asia havebeen studied with sunphotometers (Eck et al., 2005;Kim et al., 2004a) and UV-MFRSR (UltravioletMultifilter Rotating Shadowband Radiometer)(Kim et al., 2006). Although information regardingthe vertical distribution of optical properties ofatmospheric aerosols above the Korean peninsula isquite important, only a few efforts have been madeso far to study the aerosol properties above theKorean peninsula (Noh et al., 2007; Kim et al.,2005; Hong et al., 2004).

Light detection and ranging (Lidar) system canmeasure the vertical distribution of optical particleproperties, such as the particle backscatter coefficient.The so-called elastic backscatter lidar can provideaccurate profiles of the extinction coefficient only ifthe profile of the extinction-to-backscatter ratio (lidarratio, Sa) is known. The lidar ratio depends on theparticle size distribution, particle chemical composi-tion and the shape of the particles, as well as relativehumidity (Kovalev and Eichinger, 2004).

Ackermann (1998) calculated lidar ratios with aparticle model on the basis of Mie-scattering theory.The author reported values ranging from 15 to 80 srat Nd:YAG laser wavelengths (355, 532, and1064 nm). The values were calculated on the basisof various aerosol types and varying relativehumidity. However, aerosol composition and sizedistribution along the laser beam path must beaccurately known in order to derive the correctvalue from the particle model. The lidar ratio can bemeasured by a 1801 backscatter nephelometer at thesurface (Anderson et al., 2000). Column-averagedlidar ratios have been measured with combinedbackscatter lidar and sunphotometer observations(Takamura et al., 1994), and with a multi-angleslant path lidar (Reagan et al., 1988).

Cattrall et al. (2005) derived lidar ratios at 550 nmfor different aerosol types using sunphotometer

data collected at 26 Aerosol Robotic Network(AERONET) sites across the globe. Wide range oflidar ratio values were obtained; 27 sr for marineaerosols, 42 sr for desert dust, 60 sr for biomass-burning aerosols, 71 sr for urban/industrial pollu-tion, and 58 sr for East Asia pollution particles,respectively. However, sunphotometer data repre-sent column-integrated measurements. It was alsoreported that lidar ratio in East Asia varieddepending on source region and atmospheric trans-port pattern (Noh et al., 2007). Raman lidarobservation results show that different types ofaerosol particles can be present at different alti-tudes. For that reason, it is crucial to conductvertically resolved Raman lidar observation ofatmospheric aerosols over East Asia.

Raman lidar can measure the vertical distribu-tions of extinction coefficients and backscattercoefficients without prior assumptions on the lidarratio, and can therefore provide useful additionalinformation that cannot be derived with conven-tional backscatter aerosol lidars. Raman lidarallows the direct, unambiguous and simultaneousdetermination of vertical profiles of the particleextinction coefficient, backscatter coefficient, andlidar ratio (Ansmann and Muller, 2005). A fewmeasurements of lidar ratios for various tropo-spheric and stratospheric aerosols have been madewith Raman lidar (Wandinger et al., 1995; Muller etal., 2001; Ansmann et al., 2002; Balis et al., 2004;Matthias et al., 2004). Since the European AerosolResearch Lidar Network (EARLINET) was estab-lished in 2000, a long time series on aerosol verticaldistribution and lidar ratios for different particletypes has become available on a continental scale inEurope on the basis of Raman lidar measurements(Muller et al., 2003; Mattis et al., 2004). However,there exist only a few direct measurements of lidarratios in Northeast Asia. The vertical distribution ofaerosol optical properties has been observed at 355and 532 nm with a Raman lidar in Japan (Mur-ayama et al., 2004).

The spaceborne lidar CALIOP (Cloud-AerosolLIdar with Orthogonal Polarization) aboard CA-LIPSO (Cloud-Aerosol Lidar and Infrared Pathfin-der Satellite Observations) was launched on 28April 2006 (Winker et al., 2003, 2004). This lidarmaps the global aerosol distribution in terms ofheight profiles of the 1801 particle volume back-scatter coefficient. Global sets of aerosol extinctioncoefficient profiles can be determined from the dataif the lidar ratio is available for the region under

ARTICLE IN PRESSY.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–22242210

investigation. Lidar ratios can be used to track backpollution outbreaks because of their dependence onaerosol type, particle size distribution, and chemicalcomposition (Kovalev and Eichinger, 2004).Furthermore, since the lidar ratios measured simul-taneously at ultraviolet and visible wavelength areuseful for the identification of aerosol type (Nohet al., 2007; Mattis et al., 2002), variations in lidarratios at two wavelengths were investigated in thisresearch.

For the first time in Korea, extensive Raman lidarobservations of vertically resolved lidar ratios at 355and 532 nm were conducted at Gwangju, Korea(35.101N, 126.531E) using the GIST/ADEMRCRaman lidar system (Noh et al., 2007). In thisstudy, vertical profiles of aerosol extinction coeffi-cient, backscattering coefficient, depolarization ra-tio, and lidar ratio were investigated to characterizeoptical properties of dominant aerosols over theKorean peninsula in the spring and autumn seasonsof 2004 and the spring season of 2005. Angstromexponent (a), single-scattering albedo (SSA), andsize distribution were determined. We compare ourresults to corresponding values obtained fromRaman lidar measurements. In Section 2, we brieflydescribe the methodology for determining theoptical particle properties. The Raman lidar resultsare discussed in Section 3. In Section 4, thesunphotometer results are compared with thoseobtained from Raman lidar measurements. Finally,Section 5 presents our concluding remarks.

2. Observations

The GIST/ADEMRC multi-wavelength lidarsystem, which was initially built in 2000 incooperation with Nagoya University, Japan, wasoperated at Gosan, Jeju Island, Korea, during theACE-Asia period (Hong et al., 2004). The systemwas moved to Gwangju, Korea (35.101N, 126.531E),and Raman channels were added in 2002. Detailedinformation on the GIST/ADEMRC multi-wave-length Raman lidar system and its specifications isgiven elsewhere (Noh et al., 2007). The Ramanlidar measurement was performed at the campus ofthe Gwangju Institute of Science and Technology(GIST), located in the Korean city of Gwangju.Raman lidar observations were conducted from 10February to 11 March, 12 to 15 June, 6 October to14 December 2004, and 23 February to 9 May 2005.Measurements were suspended on heavilycloudy days and rainy days. The lidar observation

was suspended during rainy season from middle ofJune to August. The measurement was also notperformed from 16 December 2004 to 20 February2005 due to laser problem. Observation resultsfor very clean days are not included in thisstudy because extinction coefficients were too lowfor an accurate determination of the lidar ratio.The observation period comprised a total of95 days and lidar ratio data at wavelengthsof 355 and 532 nm were obtained for 45 days, ofwhich 26 days occurred in the spring and 19 inautumn.

The backscattered signals were collected with aphoton counting system with a temporal resolutionof 10min and a spatial resolution of 7.5m. SinceRaman signals are usually 103–104 times weakerthan the signals from elastic backscattering, thespatial resolution was reduced to 120m for thenitrogen Raman signal by summing 16 data pointsalong the beam path. For the temporal resolution,the signals were summed at least 3 h of signals fromelastic backscattering (216,000 layer shots). TheRaman lidar signals were normally summed over aperiod ranging from 3 to 8 h in this work. Moredetails about GIST lidar system and data processprocedure were described elsewhere (Noh et al.,2007). Profiles of the particle volume extinctioncoefficients at 355 and 532 nm were derived withnitrogen vibrational Raman signals detected at 387and 607 nm, respectively, with the method describedby Ansmann et al. (1990). Particle backscattercoefficients at 355 and 532 nm were calculated withthe method described by Ansmann et al. (1992) andWhiteman et al. (1992). The lidar ratios weredetermined from the ratios of the extinction andbackscatter coefficients at two wavelengths, 355 and532 nm. The Angstrom exponent a was thenobtained from the spectral aerosol optical depth(AOD) calculated by integrating the profiles of theextinction coefficients at 355 and 532 nm. Based onthe ‘Error propagation equation’ (Bevington andRobinson, 1992), typical statistical errors for back-scatter coefficient, extinction coefficient and lidarratio were acquired as shown in Fig. 1. Extinctionprofiles at 355 and 532 nm were derived afterapplying a sliding average to the range-correctednitrogen Raman signals over a 360m path below2800m altitude, and over a 600m path above it. Thevertically averaged values of the lidar ratio werecalculated only with values that had o30%statistical error. Signals polarized perpendicularly(532P) and horizontally (532S) to the plane of

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1

2

3

4

5

6

0.0 0.000 0

Lidar ratio [sr]Backscatter

532 nm

355 nm

Extinction

Coefficient [km-1] Coefficient [km-1sr-1]

HE

IGH

T [km

]

0.30.20.1 0.0120.0080.004 10080604020

Fig. 1. Extinction coefficient (a), backscatter coefficient (b), and lidar ratio (c) at 355 and 532 nm with error bars averaged over a period

between 22:20 h 15 June and 04:10 16 June (local time) 2004. A sliding average was applied for extinction profiles over 360m paths below

2800m altitude and over 600m paths above it.

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–2224 2211

polarization of the emitted laser beam at 532 nmwere used to determine the linear total (molecule-s+particles) depolarization ratio (d), which can beconsidered an indicator of the non-spherical geo-metry of the aerosols.

Radiosondes were launched four times a day(03:00, 09:00, 15:00, and 21:00 h, local time) atGwangju airport about 5 km from the lidar ob-servation site. The sondes provided vertical profilesof pressure, relative humidity, potential tempera-ture, and water vapor mixing ratio. When multipleaerosol layers were observed by lidar, they wereclassified into two categories: within or above theplanetary boundary layer (PBL). The height of thePBL was determined from the vertical profiles ofpotential temperature, relative humidity and thewater vapor mixing ratio derived by radiosonde andthe backscattering coefficient profile obtained byRaman lidar. The top of the PBL altitude waswithin a 1.2–2.0-km range for cases considered inthis study. If multiple aerosol layers were detectedabove the PBL, an average lidar ratio wascalculated for each layer at the wavelengths 355and 532 nm. However, the particle extinctioncoefficient and lidar ratio were only determinedfor heights above 0.8 km except 6 October 2004 due

to the limitation imposed by the overlap function.The overlap function was determined with themethod described by Wandinger and Ansmann(2002).

Cloud-screened level 1.5 sunphotometer datafrom the collocated AERONET (http://aero-net.gsfc.nasa.gov) site at Gwangju were used tocharacterize the physical and optical properties ofaerosols during the lidar measurement periods.Total column-integrated volume size distributions,effective radius (reff) and SSA (oo) from almucantarsky radiance scans, and spectral AOD at 440 nm,and Angstrom exponents (a) for the wavelengthrange from 440 to 870 nm were determined with theAERONET retrieval algorithm (Dubovik andKing, 2000; Dubovik et al., 2002, 2006). The lidarratio S at 550 nm was calculated from the sunphot-ometer results with the following formula (Mulleret al., 2003; Dubovik et al., 2006):

SaðlÞ ¼4p

ooPðl; 180�Þ,

where the term P is the phase function at 1801. Thevalues of oo and P at 550 nm were calculatedthrough the linear interpolation of the values at 440and 675 nm.

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3. Seasonal difference of the lidar ratio

Each aerosol layer observed in this study wascategorized as lying within the PBL or above thePBL according to the altitude of the layer. TheAOD, Angstrom exponent, lidar ratio, depolariza-tion ratio, and relative humidity for each aerosollayer are listed in Tables 1 and 2 for the spring andautumn seasons, respectively. Table 3 summarizesthe number of aerosol layers and presents averagevalues of the lidar ratio within and above the PBL inthe two seasons. The total number of observedaerosol layers was 63, of which 38 and 25 wereobserved in the spring and autumn season, respec-tively. In spring, more layers were detected abovethe PBL (22 cases) than within the PBL (16 cases).In contrast, more layers (19 cases) were observedwithin the PBL than above it (6 cases) during theautumn. This means that the possibility of the long-range transport of atmospheric aerosol is higher inspring than in autumn according to the atmosphericconditions during this research period.

The AOD of each aerosol layer was calculated byintegrating the aerosol extinction coefficient fromthe bottom to top of each aerosol layer. On 1 March2005, the maximum AOD value was 0.88 and 0.57at 355 and 532 nm, respectively. Most of the highAOD values (40.5 at 355 nm) were observed inspring. This observed seasonal difference in AOD,which shows higher values in spring than in autumn,is believed to be due to the more frequent transportof aerosol from the Asian continent eastward duringspring.

The average value of the lidar ratio for all 63layers was found to be 58710 sr and 59711 sr at355 and 532 nm, respectively. The lidar ratio of eachaerosol layer showed a wide variation: 32–82 sr and37–95 sr at 355 and 532 nm, respectively. The lidarratios of all aerosol layers have been statisticallyevaluated for two seasons; spring and autumn.Frequency histograms of the lidar ratio in steps of5 sr are shown in Fig. 2. In spring, lidar ratio wasobserved predominantly between 45 and 65 sr(71%) at both wavelengths. High values (465 sr)were observed more frequently at 532 nm than at355 nm; 21% vs 13%. In autumn, the observed355 nm lidar ratio showed similar frequency dis-tribution when compared to the spring althoughhigher values (465 sr) were observed more often;28% vs 13%. However, clearly different frequencydistribution was observed at 532 nm with increasedoccurrence (45%) of high lidar ratio (465 sr).

The meteorological conditions in Northeast Asiaare different between the two seasons. In spring, airmass transport pattern is affected by strongwesterly. As shown in Fig. 3, for the most of timeair mass moved fast from west or northwestdirections to the observation site in spring exceptfor the smoke cases when it passed over thenorthern part of Korean peninsula. Dust aerosolscan be easily distinguished from other aerosols bythe depolarization ratio. The smoke aerosolsobserved in spring was clearly distinguishable byits unique air mass movement pattern. Thus, dustand non-dust aerosols were classified by thedifferences in depolarization ratio in spring. Forautumn cases, classification by depolarization ratiowas not feasible. Most of aerosol layers weredetected within PBL. However, the air masstrajectory patterns were clearly distinguishable inautumn as shown in Fig. 5. Thus, categorization byair mass movement patterns was adopted forautumn cases.

3.1. Spring cases

The average lidar ratio in spring was 55710 srand 5779 sr at 355 and 532 nm, respectively.The particle depolarization ratio was used todistinguish dust and non-dust aerosol. Sakaiet al. (2003) recorded depolarization ratios of0.15–0.3 for Asian dust observed in NortheastAsia. Values above 0.15 were classified as casesof dust aerosol and values below 0.15 wereregarded as non-dust aerosol. However, thedepolarization ratio was not measured from 26April to 9 May 2005 because of signal detectionproblems with the 532S channel. That period istreated as the non-categorized group in the follow-ing discussion.

The average lidar ratio of each group is listed inTable 4. The lidar ratio of dust aerosol was higher at355 nm (56710 sr) than at 532 nm (5176 sr). Thisreverse spectral behavior agrees with the character-istic lidar ratio of dust observed over Tokyo, Japan(Murayama et al., 2004) and Leipzig, Germany(Mattis et al., 2002). Mattis et al. (2002) reportedthat the lidar ratios at 355 nm were higher by10–30% than the values at 532 nm, which isprobably caused by enhanced light-absorption ofdust aerosol in the ultraviolet region of theelectromagnetic spectrum.

Lidar ratio values observed in this study arehigher than those of other Asian dust dominant

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Table 1

Optical characteristics of each aerosol layer observed in spring with the GIST Raman lidar system

Spring Date Height (km) AODb ac Sad (sr) de RHf (%)

355nm 532 nm 355 nm 532 nm

Within PBLa 1 March 2004 1.14–1.92 0.23 0.15 1.04 54.474.3 68.7712.1 0.09 58.3

9 March 2004 1.02–1.92 0.20 0.13 1.09 55.176.4 49.576.8 0.2 41.5

11 March 2004 1.02–1.56 0.08 0.06 0.72 39.074.6 59.479.3 0.11 8.8

13 June 2004 0.78–2.04 0.55 0.38 0.89 50.772.7 56.575.8 0.06 67.2

14 June 2004 0.78–1.68 0.35 0.25 0.80 50.873.1 74.5712.8 0.08 55.8

15 June 2004 0.78–2.04 0.12 0.09 0.72 35.973.8 66.6712.6 0.07 24.0

23 February 2005 1.02–2.04 0.43 0.29 0.95 67.574.5 67.7712.1 0.07 33.5

24 February 2005 1.02–2.28 0.53 0.41 0.68 57.576.4 66.078.5 0.06 70.4

27 February 2005 1.02–1.56 0.13 0.07 1.48 52.778.2 51.3710.0 0.07 29.0

1 March 2005 1.02–2.04 0.88 0.57 1.06 60.7711.6 67.379.5 0.09 59.5

2 March 2005 1.02–1.96 0.20 0.11 1.46 60.4713.0 59.7715.6 0.05 21.0

3 April 2005 1.02–1.8 0.36 0.12 2.64 64.276.5 66.877.0 0.04 64.0

8 April 2005 1.02–1.92 0.62 0.39 1.13 50.778.4 55.778.7 0.06 48.0

27 April 2005 1.02–1.80 0.29 0.17 1.30 63.4711.0 50.977.0 – 88.7

3 May 2005 1.02–1.44 0.07 0.03 1.91 60.1712.6 46.479.3 – 52.0

4 May 2005 1.02–1.44 0.04 0.02 1.71 54.775.5 41.478.3 – 21.5

Average 0.32 0.20 1.22 54.978.5 59.379.5 0.08 46.5

Above PBL 10 February 2004 1.26–3.12 0.44 0.29 1.08 55.076.0 50.075.2 0.16 51.8

24 February 2004 1.86–3.46 0.13 0.08 1.24 56.4710.8 45.377.9 0.2 53.8

24 February 2004 3.54–5.28 0.06 0.04 0.95 66.4713.6 51.278.9 0.19 17.4

1 March 2004 1.98–3.24 0.29 0.22 0.67 53.773.4 65.578.0 0.13 71.3

1 March 2004 4.02–5.28 0.06 0.04 1.12 57.3714.7 54.9715.5 0.18 37.7

8 March 2004 1.38–4.8 0.29 0.18 1.13 68.777.1 54.4710.1 0.16 33.5

11 March 2004 1.98–2.88 0.07 0.06 0.36 32.274.2 62.6712.5 0.24 4.0

15 June 2004 2.22–3.24 0.14 0.08 1.31 44.476.5 61.3710.3 0.09 39.5

23 February 2005 2.34–3.00 0.06 0.05 0.49 69.178.4 75.0712.0 0.03 36.5

24 February 2005 2.34–3.96 0.09 0.07 0.76 60.3715.2 45.177.0 0.19 46.8

1 March 2005 2.10–4.08 0.29 0.20 0.90 49.5719.3 43.979.3 0.19 56.4

31 March 2005 1.38–3.12 0.91 0.45 1.71 68.178.5 61.876.4 0.11 29.0

1 April 2005 4.14–4.92 0.25 0.15 1.37 40.076.4 64.679.1 0.05 65.0

18 April 2005 1.38–3.12 0.31 0.20 1.13 61.379.0 58.7711.2 0.17 15.8

21 April 2005 1.26–3.24 0.17 0.11 1.01 63.478.2 57.378.2 0.2 22.3

23 April 2005 3.06–4.32 0.14 0.08 1.36 52.779.9 52.079.6 0.12 29.8

26 April 2005 1.50–3.36 0.13 0.07 1.61 48.4713.3 46.4713.4 – 13.8

27 April 2005 1.86–3.96 0.27 0.18 1.03 58.578.9 42.577.4 – 11.3

28 April 2005 1.50–3.24 0.18 0.12 1.06 60.4713.9 57.6714.5 – 13.0

3 May 2005 2.46–3.60 0.04 0.04 0.34 35.6712.5 52.0712.6 – 1.0

4 May 2005 2.34–3.96 0.20 0.16 0.59 48.176.9 46.8716.6 – 20.3

9 May 2005 2.10–3.36 0.10 0.07 0.77 61.7712.2 53.475.3 – 36.0

Average 0.21 0.13 1.00 55.1710.4 54.778.3 0.15 32.8

Spring average 0.26 0.16 1.09 55.079.5 56.679.0 0.12 38.1

aPBL denotes the planetary boundary layer.bAOD denotes the aerosol optical depth.ca denotes the Angstrom exponent based on AOD measured at 355 and 532 nm.dSa layer means lidar ratio.ed denotes linear total depolarization ratio.fRH represents relative humidity.

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–2224 2213

cases, which are o50 sr at both wavelengths anddeviated by 10–20% at 355 and 532 nm (Noh et al.,2007; Murayama et al., 2004).

An average Angstrom exponent of 0.9870.27was obtained in this study for aerosol categorized asdust. This relatively high Angstrom exponent value

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Table 2

Optical characteristics of each aerosol layer observed in the autumn with the GIST Raman lidar system

Autumn Date Height (km) AOD a Sa (sr) d RH (%)

355nm 532nm 355nm 532 nm

Within PBL 6 October 2004 0.66–1.92 0.15 0.11 0.90 66.476.3 69.078.6 0.07 45.7

10 October 2004 1.02–2.04 0.20 0.15 0.80 56.873.4 56.973.4 0.07 60.4

15 October 2004 0.78–1.08 0.04 0.03 1.12 43.477.5 37.976.1 0.04 79.5

16 October 2004 0.78–1.92 0.20 0.12 1.17 59.476.3 52.277.1 0.08 53.0

20 October 2004 0.78–1.8 0.13 0.10 0.68 53.276.4 58.4710.4 0.07 51.0

21 October 2004 1.02–1.92 0.55 0.42 0.64 53.077.6 54.975.7 0.09 78.5

23 October 2004 0.78–1.44 0.10 0.07 0.89 49.775.8 44.174.6 0.08 26.0

24 October 2004 0.78–1.68 0.30 0.17 1.35 58.3712.5 44.976.2 0.06 78.0

27 October 2004 0.78–1.44 0.10 0.07 0.81 54.478.4 54.174.7 0.07 53.7

28 October 2004 0.78–1.32 0.21 0.13 1.28 64.072.1 54.273.6 0.06 75.5

30 October 2004 0.78–1.62 0.23 0.16 1.19 63.877.1 64.877.9 0.07 58.5

31 October 2004 0.78–1.8 0.56 0.34 1.23 67.677.6 60.8716.6 0.09 –

16 November 2004 0.78–1.92 0.34 0.25 0.77 60.779.5 56.5714.6 0.03 60.0

18 November 2004 0.78–1.92 0.44 0.32 0.81 69.3712.9 73.6712.3 0.03 56.5

19 November 2004 0.78–1.56 0.12 0.10 0.32 65.278.9 72.2710.6 0.04 –

23 November 2004 1.08–2.04 0.12 0.09 0.81 66.1714.5 69.1713.9 0.02 –

24 November 2004 0.78–1.92 0.16 0.12 0.74 57.8713.7 67.077.3 0.04 –

28 November 2004 0.78–1.44 0.11 0.10 0.38 82.0713.8 74.1713.6 0.05 15.5

29 November 2004 0.78–1.2 0.18 0.13 0.68 61.174.8 61.572.4 0.04 68.7

Average 0.22 0.16 0.88 60.678.5 59.3710.3 0.06 57.4

Above PBL 28 October2004 2.58–3.48 0.07 0.04 1.29 81.8714.6 86.6710.6 0.05 27.0

30 October 2004 1.62–3.36 0.12 0.07 1.33 63.6710.6 95.5715.5 0.05 42.8

31 October 2004 1.88–2.88 0.11 0.07 1.09 61.779.7 66.9710.9 0.05 –

23 November 2004 2.1–3.36 0.18 0.12 1.05 61.079.8 77.277.1 0.05 –

24 November 2004 2.46–4.92 0.30 0.20 0.95 61.8712.3 75.4710.7 0.02

29 November 2004 1.26–2.4 0.16 0.11 0.96 53.373.3 49.979.8 0.04 19.7

Average 0.16 0.10 1.11 63.979.5 75.3715.8 0.04 29.8

Autumn average 0.21 0.14 0.93 61.477.5 63.1712.8 0.05 52.8

Table 3

Average lidar ratios above and within the PBL for two seasons

Classification No. of aerosol

layers

Sa (sr)

355 nm 532 nm

Total 63 58710 59711

Spring 38 5579 5779

Above PBL 22 55710 5578

Within PBL 16 5578 5979

Autumn 25 6178 63713

Above PBL 6 64710 75716

Within PBL 19 6178 59710

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–22242214

indicates that there was not only a significantcontribution by Asian mineral dust to the observedaerosol load, as shown by the high particledepolarization ratio, but that aerosol pollution

comprising fine-mode fraction particles was alsotransported with the Asian dust during the observa-tional period. It seems that fine-mode pollutionaerosols emitted from densely anthropogenic activ-ities in East Asia influenced aerosol optical proper-ties even in spring as pollution aerosol was mixedwith coarse-mode dust particles originating fromwestern source regions (Kim et al., 2004b). Weassume that the high lidar ratio presented in thisresearch (in comparison to Asian dust dominatedcases presented in previous research work (Noh etal., 2007; Murayama et al., 2004)) was affected bythis mixing with fine pollution aerosols.

The non-dust aerosols showed higher lidar ratiosat 532 nm wavelengths compared to dust aerosols,with average values of 60710 sr. This high value ofthe lidar ratio must be due to aerosol pollution inthe fine-mode fraction, which is corroborated by thehigh Angstrom exponent of 1.4170.67. This higher

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30

-35

35

-40

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0

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532 nm

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EQ

UE

NC

Y [

%]

LIDAR RATIO [sr]3

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532 nm

LIDAR RATIO (sr)

Fig. 2. Frequency histogram of the lidar ratio in step of 5 sr, distinguished between spring (38 values) and fall (25 values). (a) Spring and

(b) autumn.

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–2224 2215

value of lidar ratio might be due to pollutionparticles in the fine-mode fraction, which is corro-borated by high Angstrom exponent of 1.4170.67.However, the lidar ratios of non-dust aerosols werecomparable to that of dust aerosol at 355 nm. Thenon-dust aerosol particles exhibit similar spectralsignature with lidar ratio at 355 and 532 nm. Fordust-dominated cases, lidar ratios were higher at355 nm than at 532 nm. In contrast, the lidar ratiosof smoke particles were higher at 532 nm than at355 nm.

The Hybrid Single-Particle Lagrangian Inte-grated Trajectory (HYSPLIT) model (Draxler andRolph, 2003) was used to generate 5-day backwardtrajectories for air parcels arriving over the Gwang-ju observation site at the same altitude in which weobserved aerosol layers. Fig. 3 shows categories ofbackward trajectory results for spring observationsclassified as dust, non-dust, smoke, and non-categorized aerosol. Most of the air masses camedirectly from the northwesterly Asian dust sourceregion. During their travel these air masses alsocrossed highly industrialized regions in China. Thedifferences regarding air mass movement pattern ofeach categorized aerosol type cannot be seen fromthe backward trajectory analysis. It seems that fine-mode pollution aerosol emitted from industrializedand densely populated centers in China is continu-

ously transported to our observation site bywesterly winds, and dominates the aerosol opticalproperties even in spring as pollution aerosol mixeswith coarse-mode dust.

The aerosols observed in June 2004 showeddifferent air mass transport patterns compared tothe other aerosols, which arrived from the north asshown in Fig. 3(c). Higher lidar ratios were obtainedfor these aerosols at 532 nm (6578 sr) than at355 nm (4677 sr). Lidar ratios that are higher atvisible rather than ultraviolet wavelengths are acharacteristic feature of aged forest-fire smoke(Muller et al., 2005; Murayama et al., 2004;Wandinger et al., 2002). It has been reported thatsmoke aerosol originating from Siberian forest firesis sometimes transported to the Korean peninsula inspring (Lee et al., 2005). On the basis of the spectralbehavior of the lidar ratio which showed 5–15 srlower values at 355 nm than at 532 nm, these aerosolcases were categorized as smoke aerosol transportedfrom Siberia, Russia.

Fig. 4 shows the lidar ratio distribution of eachcategorized aerosol at the wavelengths of 355 and532 nm. Dust and smoke aerosols can be clearlydistinguished. However, non-dust aerosol showswide variations in the lidar ratio at both wave-lengths compared to those of the other two types ofaerosols.

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Fig. 3. Five-day air mass back-trajectories for different aerosol types in spring: dust (a), non-dust (b), smoke (c), and non-categorized (d).

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–22242216

The non-categorized aerosols showed a distribu-tion similar to the one of the dust aerosols. Meanlidar ratios of non-categorized aerosols also showedsimilar spectral behavior of Asian dust as 5479 sr

and 4975 sr at 355 and 532 nm, respectively.Therefore most cases of non-categorized aerosolscan likely be considered as the Asian dust dominantaerosols.

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Table 4

Average values of the lidar ratio, Angstrom exponent, depolarization ratio, and relative humidity for different types of aerosol observed in

spring

Sa (sr) a, 355–532nm d RH (%)

355 nm 532 nm

Dust 56710 5176 0.9870.27 0.2070.04 36.5717.3

Non-dust 5879 60710 1.4170.67 0.0970.04 41.7719.6

Smoke 4677 6578 0.9370.26 0.0870.01 46.6718.9

Non-categorized aerosol 5479 4975 1.2370.57 – 27.2725.9

3030

40

50

60

70

80

90

100

Dust

Non-dust

Smoke

Non-categorized

Lid

ar

ratio

, 5

32

nm

[sr]

Lidar ratio, 355 nm [sr]

40 50 60 70 80 90 100

Fig. 4. Lidar ratio at 355 nm vs 532 nm for different aerosol types observed in spring.

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–2224 2217

Matsuki et al. (2003) report that there is a steadytransport of dust in the lower-middle free tropo-sphere (2–6-km altitude) in East Asia during springeven if there are no visual signs of major dustoutbreaks. Persistence and the high speed of thewesterly jet would create a flux of dust from thecontinent to vast regions farther east. Values of thelidar ratio and Angstrom exponent for aerosols ofthe non-categorized class indicate the impact of dustparticles although some of them were not related todust particles.

3.2. Autumn cases

Higher average lidar ratios (6178 sr and63713 sr at 355 and 532 nm, respectively) with a

low particle depolarization ratio o0.10 were ob-served in autumn. Classification by depolarizationratio was not feasible because of its little variations,0.05 to 0.08 in autumn. Air mass pathways for ourobservations in autumn are classified into threecategories, as shown in Fig. 5. The average opticalproperties of aerosols of the different air masspathway types are summarized in Table 5. Fig. 6shows the lidar ratio distribution at both wave-lengths for each air mass pathway type. Lidar ratiosranged from 53 to 66 sr at 355 nm, and 52 to 69 sr at532 nm for type (a). Aerosols from the northwest(type (b)) showed wide variation in lidar ratios,being 40–70 sr at both wavelengths. It seems that thedifference in the lidar ratio between types (a) and (c)were caused by the influence of different local

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Fig. 5. Five-day air mass back-trajectories in autumn arriving from the north (a), northwest (b), west (c), and above the PBL (d).

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–22242218

sources in Korea. Areas to the south of theobservation site consist mostly of farmland. How-ever, Seoul is the largest city in Korea and indus-trialized areas are located north of the observation

site. In Korea, open field burning of agriculturalwaste after the harvest is commonly practiced inautumn (Ryu et al., 2004). Type (a) seems to bemore affected by urban haze considering its air mass

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Table 5

Average values of the lidar ratio, Angstrom exponent, depolarization ratio, and relative humidity for different air mass pathway types

observed in the autumn

Lidar ratio a, 355–532nm d RH (%)

355nm 532 nm

Type (a) 5975 5876 0.9470.23 0.0770.01 56.5710.4

Type (b) 60711 59713 0.7770.31 0.0570.02 57.8724.6

Type (c) 6672 6574 1.0870.23 0.0570.03 58.575.0

Above PBL 64710 75716 1.1170.16 0.0470.01 29.8711.8

Air mass arrived from the north (type (a)), northwest (type (b)), and west (type (c)).

2020

40

60

80

100

120

Type (a)

Type (b)

Type (c)

Above PBL

Lid

ar

ratio, 532 n

m [sr]

Lidar ratio, 355 nm [sr]

40 60 80 100 120

Fig. 6. Lidar ratio at 355 nm vs 532nm for different air mass

pathways in the autumn.

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–2224 2219

pathways. Type (c) is believed to be mainly affectedby light-absorbing fresh smoke aerosols fromlocally produced biomass burning aerosols. Type(b) aerosols showed wide variation in the lidar ratioat both wavelengths, and must have been affectedby various types of aerosol.

As shown in Fig. 6, the aerosols detected abovethe PBL during the autumn possessed the highestlidar ratios: 64710 sr and 73716 sr at 355 and532 nm, respectively. Lidar ratios of 30–60 sr aretypically observed for anthropogenic, non-absorb-ing ammonium-sulfate particles (Franke et al.,2001). Lidar ratios X60–70 sr were observed forlight-absorbing particles at Hulhule Island (4.11N,73.31E) and Maldives (Muller et al., 2001). Ferrareet al. (2001) observed a high lidar ratio of 68712 srat 355 nm in the southern Great Plains of north-central Oklahoma and reported that such a highlidar ratio was associated with air masses fromurban/industrial areas. It has been reported thatlidar ratios at 355 nm were �10% higher than those

at 532 nm for urban haze and industrial aerosol(Muller et al., 2007).

However, the aerosols we observed in our studyabove the PBL in autumn showed large lidar ratiosat both wavelengths, with Angstrom exponentvalues being smaller than those recorded for urbanhaze/industrial pollution in Europe and the UnitedStates. This spectral behavior is similar to that ofSoutheast Asian aerosol observed during INDOEX(Franke et al., 2001, 2003), which originated mainlyfrom coal combustion and biomass burning used fordomestic heating and cooking (Muller et al., 2007).We believe that the high lidar ratios X60 sr weobserved at both wavelengths were affected by thetransport of light-absorbing particles.

4. Comparison with sunphotometer results

AERONET level 1.5 data (http://aeronet.gsfc.nasa.gov) of AOD and the Angstrom exponent forthe wavelength range from 440 to 870 nm werecollected with sunphotometer at the Gwangju siteduring the same periods during which we carriedout the Raman lidar observations. Sunphotometermeasurements were made during daytime while theRaman lidar observations were conducted in night-time. Although there was a time difference ofseveral hours between the two measurements,similar patterns of air mass backward trajectorieswere obtained.

Column-integrated volume size distributions,complex refractive index, and SSA were derivedthe AERONET retrieval algorithm (Dubovik andKing, 2000; Dubovik et al., 2002). Furthermore thedata were categorized into dust, non-dust, smoke,and non-categorized aerosols. For that categoriza-tion, we used the aerosol type classification as wellas the analysis of the air mass pathways (north,

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Non-categorized

dV

/d (

ln r

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m3/µ

m2

spring

fall

Fig. 7. Column-integrated volume size distributions retrieved from sunphotometer data averaged for spring and autumn seasons (a), for

different aerosol types observed in spring (b), and for different air mass pathway directions in the autumn (c).

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–22242220

northwest, and west for the autumn data) asdescribed in Section 3.

The retrieved size distributions of these aerosoltypes are shown in Fig. 7. Other optical parameters,including the lidar ratio, which has been calculatedfrom the phase functions and SSAs derived from theAERONET data, are summarized in Table 6. Lidarratios retrieved by the sunphotometer and shown inTable 6 are comparable to those of the Raman lidarmeasurements although the interval between theobservation times of the two instruments was morethan several hours apart. The lidar ratios that weobtain from the AERONET observations in spring-time are higher than the lidar ratios in autumn.

Fig. 7(a) shows the retrieved size distributions forspring and autumn seasons. The dominance of thecoarse-mode of the particle size distribution inspring is believed to be the result of the long-range

transport of Asian dust particles. Increased frac-tions of particles in the coarse mode (particle radiiabove 1 mm) of the particle size distribution areshown for the case of dust and the non-categorizedaerosol in Fig. 7(b). Although coarse-mode aerosolsare dominant for dust aerosols, fine-mode aerosolsshow distribution characteristics that are similar tothose of the autumn cases. This suggests thataerosol pollution in the fine mode contributespredominantly to the optical depth during bothseasons in Korea, whereas Asian dust particlescontribute to total AOD mainly during spring.These characteristics of the size distribution corro-borate the result that aerosols observed in springrepresent a mixed state of Asian dust and fine-modepollution aerosols. Kim et al. (2004a, b) found thatpollution particles were transported with Asian dustparticles by forming dust particles externally mixed

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Table 6

Aerosol optical parameters derived from sunphotometer measurements

AOD (550 nm) ooa (550 nm) a, 440–870nm reff

b Lidar ratio (sr) (550 nm)

Spring 0.3970.22 0.9070.04 1.1170.29 0.3570.17 53713

Dust 0.5470.28 0.9270.02 0.8270.14 0.6570.36 48722

Non-dust 0.3570.27 0.8970.03 1.1870.25 0.2570.08 56714

Smoke 0.6170.30 0.9170.05 1.4270.11 0.2270.04 5874

X 0.4170.15 0.8970.03 0.9870.28 0.4070.12 50715

Autumn 0.3070.26 0.9270.03 1.4770.17 0.2370.05 62714

Type (a) 0.2470.05 0.9170.04 1.5970.09 0.2270.04 6176

Type (b) 0.3270.32 0.9370.03 1.3770.16 0.2470.06 62717

Type (c) 0.3270.12 0.9370.02 1.6370.02 0.1870.02 6679

aoo represents single-scattering albedo.breff denotes effective radius.

Y.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–2224 2221

with agglomerated black carbon (BC) particlesduring an Asian dust period in Korea. The SSAvalue of 0.90 (550 nm) observed in this study inspring is slightly lower than that recorded inDunhuang and Yinchuan, China, which are locatedin source regions of Asian dust (Kim et al.,2004a, b). This lower single scattering albedo duringspring might be due to extensive mixing withpolluted air masses transported from the Asiancontinent to the Gwangju site.

AERONET Angstrom exponent values (0.8270.14 for dust, 1.1870.25 for non-dust, 1.4270.11for smoke, 0.9870.28 for non-categorized, 1.5970.09 for type (a), 1.3770.16 for type (b), and1.6370.02 for type (c)) were comparable to thosederived from our Raman lidar measurements formost aerosol categories. The differences in opticalparameters between the two measurements may bethe result of different measurement times. Ramanlidar observations were carried out during thenighttime, whereas sunphotometer data were ob-tained under daytime conditions. Different humid-ity conditions may also be responsible for some ofthe observed differences. Additionally, sunphot-ometer data cover the entire atmospheric column,whereas Raman lidar results are separated intoseveral aerosol layers. Thus, the lidar data do notcontain the impact of freshly produced tiny aerosolparticles below the height of complete overlap,which might result in higher Angstrom exponentvalues.

5. Conclusion

Monitoring of lidar ratios at 355 and 532 nm wasperformed over a period of 10 months with a multi-

wavelength Raman lidar system in Gwangju,Korea. The observed lidar ratios varied widely from32 to 82 sr and 37 to 95 sr at 355 and 532 nm,respectively. Differences in lidar ratios were ana-lyzed on the basis of aerosol type, observed altitudeand season. Frequency of high lidar ratios (X60 sr)observed in spring was lower than that recorded inautumn. Lidar ratios of dust-dominant particlesshowed different spectral behaviors for the twowavelengths when compared to non-dust cases,which exhibited values that were higher by as muchas 5–10 sr at 355 nm than at 532 nm. However, lidarratios of dust aerosols in this study were slightlyhigher than those of dust dominant aerosols, whichmay have been due to a mixing with anthropogenicaerosols of the fine-mode fraction of the particle sizedistribution. Our measurements in spring wereoccasionally influenced by smoke aerosols trans-ported from Siberia, Russia. These particles can beclearly separated from dust and anthropogenicpollution because of the spectral behavior of thelidar ratio (higher lidar ratio at 532 nm than at355 nm) and the rather low Angstrom exponentvalues. The highest lidar ratios were detected abovethe PBL in autumn, and are believed to be the resultof the long-range transport of light-absorbingparticles generated by coal combustion and agri-cultural biomass burning in China. Unlike theconditions above the PBL, most of the aerosolsobserved within the PBL in autumn are consideredto consist of locally produced aerosols.

Column-integrated Angstrom exponents andSSAs retrieved from sunphotometer observationswere compared with those derived from Ramanlidar measurements. The results also support ourconclusions that seasonal differences of optical

ARTICLE IN PRESSY.M. Noh et al. / Atmospheric Environment 42 (2008) 2208–22242222

aerosol properties are caused by differences insource regions. Column-integrated volume sizedistributions retrieved from sunphotometer dataindicate that high lidar ratios observed during Asiandust periods might have been caused by extensivemixing of dust and fine-mode pollution duringtransport by the prevailing westerly wind.

This study shows that optical properties ofdifferent aerosol types can be distinguished withthe use of multi-wavelength Raman lidar measure-ments. These differences in lidar ratio with respectto season and altitude can provide useful informa-tion for an understanding of optical properties andtransport characteristics in the free troposphereover northeast Asia. These categorized values canalso be useful for the application of elastic-back-scatter lidars, such as the lidar onboard theCALIPSO satellite which cannot measure particleextinction profiles without a reasonable assumptionon lidar ratios.

Acknowledgments

This work was supported by the Korea Meteor-ological Administration Research and DevelopmentProgram under Grant CATER 2007-4108. Thisresearch was partially supported by the Brain Korea21(BK21) program for the fellowship Young M.Noh. The authors would like to thank GSFC/NASA for use of the AERONET sunphotometerdata.

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