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Atmospheric Environment 73 (2013) 92e102

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Atmospheric Environment

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Absorption characteristics of aerosols over the northwestern region ofIndia: Distinct seasonal signatures of biomass burning aerosols andmineral dust

Mukunda M. Gogoi*, S. Suresh Babu, K. Krishna Moorthy, M.R. Manoj, Jai Prakash ChaubeySpace Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram 695 022, India

h i g h l i g h t s

� Distinct seasonal signatures of the absorption characteristics of aerosols.� Dominant biomass burning source in winter and fossil fuel combustions in summer.� Presence of elevated dust layers during summer.� Strong spectral dependence of absorption during winter, attributed to long range transport.

a r t i c l e i n f o

Article history:Received 26 November 2012Received in revised form28 February 2013Accepted 4 March 2013

Keywords:Black carbonDustAbsorption coefficientLong-range transportWestern India

* Corresponding author. Tel.: þ91 471 256 2786; faE-mail addresses: mukunda.mg@gmail.com

(M.M. Gogoi).

1352-2310/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.atmosenv.2013.03.009

a b s t r a c t

Continuous measurements of aerosol black carbon (BC) mass concentrations made over a period of 3years from a semi-arid, near-coastal, remote and sparsely inhabited location along with satellite-baseddata of aerosol absorption index, optical depth and extinction profiles in western India are used tocharacterize the distinct nature of aerosols near the surface and in the free troposphere and their sea-sonality. Despite being far remote and sparsely inhabited, significant levels of BC are observed in theambient during winter (1.45 � 0.71 mg m�3) attributed to biomass burning aerosols, advected to the sitefrom the north and west; while during summer the concentrations are far reduced (0.23 � 0.11 mg m�3)and represent the apparent background concentrations. The spectral absorption coefficients suggest theBC during summer be mostly of fossil fuel combustions. The strong convective boundary layer dynamicsproduces significant diurnal variation during winter and modulates to a lesser extent the seasonalvariation. Examination of aerosol (absorption) index from OMI data for the study period showed aseasonal pattern that is almost opposite to that seen at the surface; with high aerosol index in summer,showing a significant difference between the surface and columnar aerosol types in summer. MISR andMODIS-derived columnar AOD follow the OMI pattern. Analysis of the vertical profiles of aerosolextinction and volume depolarization ratio (VDR), derived from CALIPSO data indicates the presence ofstrong dust layers with VDR w 0.3 in the altitude region 4e6 km, contributing to the high aerosol indexin the OMI data, while the surface measurements show absorptive properties representing fossil fuel BCaerosols.

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1. Introduction

Aerosol characterization over Asia, in general, and India, inparticular, has assumed greater relevance in the recent yearsprimarily due to their spatio-temporal heterogeneity (Moorthyet al., 2009), large abundance of natural and anthropogenic

x: þ91 471 270 6535., dr_mukunda@vssc.gov.in

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species (Satheesh et al., 2006) and above all their implications toglobal and regional climate forcing through direct and indirecteffects. In this context the role of Black Carbon (BC) assumesimportance due to their large absorption of solar radiation thatimparts significant atmospheric warming. Aerosol BC, producedmainly due to incomplete combustion of fossil fuel or biomass, isamongst the strongest contributors to the radiative warming ofthe atmosphere (Jacobson, 2001), through its strong absorptionover a wide wavelength range (from UV to IR). This warming dueto BC is believed to partly offset the ‘white house effect’ of scat-tering aerosols (Schuster et al., 2005). According to IPCC (2007)

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e102 93

estimates, the direct radiative forcing by black carbon aerosols(from fossil fuel and biomass burning) lies in the range of þ0.27toþ0.54Wm�2, while organic carbon offsets the forcing by�0.04to �0.41 W m�2 (Jacobson, 2001). In comparison, mineral dustover Indian region has significant absorption in the short wave-length (blue and UV) and in the IR (Moorthy et al., 2007) becauseof their higher haematite content (Mishra et al., 2008). While dustis of natural origin, BC is primarily of anthropogenic origin. Eventhough attempts are being made to model the global radiativeeffects of BC aerosols (Reddy and Boucher, 2007), large un-certainties still persist due to inaccurate representation ofregional BC in climate models. In this context, spectral absorptionproperties of black carbon aerosols provide useful information inthe identification of the sources and their differentiationwith dust(Bergstrom et al., 2007). Even though the spectral absorptioncoefficients can be approximated by a power law expression forthe monotonous decrease of absorption coefficients with wave-lengths, the slope of the absorption depends on aerosol types.Climate models treat BC as the only typical light absorbing aerosolcomponent (light absorption vary weakly with wavelengths), yetthere are other aerosol components which exhibits stronger ab-sorption at shorter wavelengths (Kirchstetter et al., 2004). Mea-surements of spectral aerosol absorption at different fieldcampaigns (e.g., TARFOX, SAFARI-2000, ACE Asia, PRIDE, ICARTTetc.) reveal that while dust aerosols show highest spectral de-pendency, the biomass burning aerosols also show significantlystronger spectral dependence compared to that originated fromurban pollution (Bergstrom et al., 2007).

In addition to this direct forcing, BC, and to a lesser extent dust,also contributes to indirect forcing through modifying cloudproperties (Ackerman et al., 2000) and surface albedo by changingsnow/glacier properties (Hansen and Nazarenko, 2004; Babu et al.,2011). However, BC aerosols, being in the fine size range (mediandiameters in the range 100e200 nm), are easily respirable and havelong life time; thereby leading to deterioration of air quality andhealth hazards (Janssen et al., 2012). The Asian regionwith its largepopulation, developing industrialization and diverse living habitatsis believed to be one of the hot-spots of carbonaceous aerosols(Oshima et al., 2012; Bonasoni et al., 2010) and several efforts havebeen made to characterize them over distinct environments (Streetet al., 2001; Carrico et al., 2003; Marinoni et al., 2010; Yoo et al.,2011; Moorthy and Satheesh, 2011; Ramanathan and Carmichael,2008; Cappa et al., 2012; Shindell et al., 2012). However large gapareas still exist geographically. In perspectives, study of BC char-acteristics over different geographic locations over India assumesimportance. It has been reported that biomass burning and fossilfuel combustion contribute w49% of the total fine mode aerosolburden over the Indian sub-continent (Gabriel et al., 2002), makingthe characterization of BC aerosols more important. Similarly thelong dry season (March to June) and the vast Arid regions of westAsia, Arabian and desert are conducive of raising large amount ofmineral dust in the atmosphere (Moorthy et al., 2007; Mishra et al.,2008).

Extensive characterization of aerosols over distinct regions ofIndia is being carried out as a part of the Aerosol Radiative Forcingover India (ARFI) project of ISRO-GBP using a network of obser-vatories spread across the mainland and islands (Moorthy andSatheesh, 2011). Some efforts on regional synthesis have beenmade by Beegum et al. (2009) over the Indian region from thedatabase collected over network stations during the IntegratedCampaign for Aerosols, gases and Radiation Budget (ICARB, 2006;Moorthy et al., 2008). Recent field experiments have revealedelevated (at free tropospheric altitude) layers of enhanced BCconcentration over Indian regions, especially during spring (Babuet al., 2011). Despite significant gap exist in the western part of

northern India characterized by the vast marshy area of Kachchhand the desert/arid regions spreading from western India toArabia.

In the above backdrop, the continuous measurements of aerosolBC, made from the sparsely inhabited, semi-arid, near-coastal re-gion, Naliya, in the Western India over a period of 3 years areexamined to understand the aerosol absorption properties over thisremote rural environment; and the changes in the spectral ab-sorption associatedwith changes in the dominant source types. Theresults are synthesized with other aerosol properties derived fromsatellite data (OMI, MODIS, CALIPSO and MISR) to evolve acomprehensive characteristic of aerosol over this region.

2. Experimental site and database

The study area, Naliya (22.23�N, 68.89�E, 50 m amsl; Fig. 1),located on the western end of Kachchh district in Gujarat state ofIndia, is a remote continental station with highly subdued humanactivity. The district ranks the lowest in population density in thestate, with the figures for 2011 standing at 46 inhabitants km�2

(2011 census data, http://www.censusindia.gov.in/2011-prov-re-sults/prov_data_products_gujarat.html). Kachchh is a virtual is-land, with the Arabian Sea to the west; the Gulf of Kachchh to thesouth and southeast, the Rann of Kachchh (marshy) to the northand northeast, and connected to the mainland through its east asin Fig. 1. Owing to its geographical features, Kachchh has threemajor ports: Mundra, Kandla and Mandavi. Measurements of BCwere carried out from the premises of an Air Force Station (AFS),located at a distance of w120 km off the Main City Kachchh. TheAFS contributed to a significant fraction of the total population ofNaliya, which stood at around 10,500 in 2011. Agriculture of cropspecies that consume low water is the major occupation.

Continuous measurements of BC have been made from Naliyasince November 2007 and the data till June 2010 (details are givenin Table 1) are used for this study. The measurements have beenmade using a seven channel aethalometer (Model AE-30 of MageeScientific, USA) operating at a flow rate of 3 LPM and time base of5 min. A 2.5 microns sharp cut cyclone was used at the inlet of thesampling pipe to avoid dust and other coarse particle. Details of theaethalometer principle, operation, uncertainties involved and errorbudget are reported in several earlier literature (Weingartner et al.,2003; Arnott et al., 2005; Nair et al., 2008). In general, the instru-mental uncertainty of the aethalometer ranges from 50% at0.05 mg m�3 to 6% at 1 mg m�3 (Corrigan et al., 2006). To reduce thepossible shadowing errors due to excessive particle loading on thefilter tape, the instrument was operated at the 50% maximumattenuation option. Supplementary daily meanmeteorological datais obtained from an automatic weather station (AWS) at Dwarka(22.46�N, 69.07�E) through MOSDAC (www.mosdac.gov.in) forrepresentative meteorological information at the western part ofthe country.

Apart from the ground based measurements, the satellite dataused for this study involved the Aerosol Index (AI) from OMI (DailyOMTO3d.003 product), columnar aerosol optical depth fromMODIS Terra (MOD08_D3.051) and Aqua (MYD08_D3.051) productand MISR (MIL3DAE.004 product), and extinction coefficients anddepolarization ratio from CALIPSO (CAL_LID_L2_05kmAPro-Prov-V3), obtained for 1� � 1� spatial extent centred at Naliya.

3. General meteorology

The general meteorological conditions that prevailed overNaliya are characteristics of a semi-arid location having coastalproximity (Arabian Sea) and the Gulf of Cambay (inlet of theArabian Sea along the west coast of India), leading to a moist and

Fig. 1. Geographical position of Naliya in the coastal region of northwest India.

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e10294

sweltering summer (June to September). The winter season(December through February) is pleasant (minimumtemperature w 15 �C); while summer season is extremely hotwith maximum temperatures soaring up to 48 �C on certain days.The climatological average annual rainfall is around 350 mm,which occurs mostly during June to August. The temporal vari-ations of meteorological parameters during the measurementperiod are shown in the top panel in Fig. 2. As can be seen, dailymean temperature varies between 20 and 25 �C in winter, whileduring spring (Mar to May) and summer (June to September), thedaily mean temperatures go up to as high as w35 �C. The relativehumidity is generally moderate (w55% throughout the period ofobservations) in summer; with average rainfall varying from 33to 150 mm.

The winds however are highly seasonal, with low and moderate(<6 m s�1) easterlies/east-northeasterlies dominating the winter,changing over to stronger (4e8 m s�1) southwesterlies in springand summer season and moderate to weak (<4 m s�1) and varyingwinds in autumn as shown by the polar diagram in the bottompanel of Fig. 2. Examining this with the geography of the station, itemerges that there is a strong marine airmass influence duringAprileSeptember while the winds arrive mostly from central In-dian landmass during the rest of the year.

Table 1Climatological seasonal mean values of MB, sabs and aabs.

Seasons Database(days)

MB (mg m�3) sabs, 880 nm

(Mm�1)aabs

Winter 202 1.45 � 0.71 17.05 � 7.67 1.24 � 0.14Spring 245 0.68 � 0.55 8.16 � 3.64 1.07 � 0.14Summer 197 0.23 � 0.11 2.71 � 1.02 0.86 � 0.19Autumn 132 1.14 � 0.89 10.66 � 7.01 1.12 � 0.18

4. Results and discussions

4.1. Temporal variations of BC mass concentrations

Temporal variations of BC mass concentration (MB), at diurnaland monthly time scales, are shown in Fig. 3, while those of theclimatological (for the entire data length) monthly mean BC areshown by the box and whisker plot in Fig. 4. It is seen that despitethe large variation at shorter time scales, the average annual vari-ation has a consistent seasonality over the years with a conspicuouswinter (DJF) peak (when the mean BC is w1.45 � 0.71 mg m�3) andsummer low (with a seasonal mean of 0.23 � 0.11 mg m�3), anannual amplitude (ratio of max/min) of w6.

At the diurnal time scales, BC concentration revealed a daytimelow with an afternoon minimum, followed by a nocturnal peakoccurring around mid-night, followed by a gradual fall towardsmorning; typical to the pattern seen over continental sites (Nairet al., 2007; Balakrishnaiah et al., 2011). Shortly after sunrise, asharp peak appears associated with fumigation effect arising out ofthe entrainment of particles from the nocturnal residual layer asthe nighttime stable layer is lifted up by the developing convectivemotions after the sunrise (for e.g., Gogoi et al., 2011) which is alsoseen generally over continents. Contribution due to traffic andother human activities remains subdued over this location due toits sparse inhabitation and the diurnal variations are closely asso-ciated with the atmospheric boundary layer (ABL) dynamics; thedeepening convective boundary layer leading to a larger dispersionand dilution of the concentration during daytime and theconfinement by the shallow nighttime boundary layer (NBL) lead-ing to increasing concentration during nighttime.

The diurnal variations are pronounced during winter season(DeceFeb), primarily due to the stronger confinement by the

Fig. 2. Surface meteorological parameters at Dwarka at different seasons, which show the daily mean values of temperature (T), pressure (P), relative humidity (RH) and daily totalrainfall (Rain), while the bottom panel shows the daily mean wind speeds as a function of wind directions at different seasons.

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e102 95

Fig. 3. Diurnal variations of climatological monthly mean BC.

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nocturnal boundary layer, which would be very shallow (for e.g.,Nair et al., 2007) in winter months due to the low nighttime tem-perature (w15 �C). As the season changes, the increased solarelevation and heating results in deepening of the convectiveboundary layer from winter to spring (MareMay), increased ver-tical mixing and the near surface concentration keeps decreasingdue to increased ventilation. Ventilation coefficient, product ofboundary layer height and horizontal wind speed, play a major rolein the vertical dispersion of aerosols and hence the near surfaceaerosol concentration (Nair et al., 2007). The high values of BCduring winter are partly attributed to the reduced ventilation co-efficient, associated with the shallow atmospheric boundary layer(ABL) (due to low surface temperature) and low wind speed,confining the particles closer to the surface as well the dry condi-tions prevailed over the study region with practically no precipi-tation. In addition, during winter the prevailing wind over thestudy region is mostly north-easterly or north-westerly, bringingBC rich continental air from the source regions. In contrast to this,during summer, the increase in ABL height (due to increased sur-face temperature) and horizontal wind speed leads to increase inthe ventilation coefficient and reduction in surface BC concentra-tion. During summer, the precipitation and change in synopticairmass type lead to further decrease in BC. The box-and-whiskerplots in Fig. 4 clearly indicate these systematic variations. The

Fig. 4. Box-and-whisker plot of monthly mean BC concentrations illustrating the mean(sphere), median (the horizontal bar in the box), 25th and 75th percentile (the lowerand upper ends of the box), 1 and 99th percentile (horizontal top and bottom lines)and maximum and minimum values (open circles) for different months. The whiskershows the standard deviations of the mean.

figure illustrates the monthly mean BC concentrations (spheres),median (the horizontal bars inside the box), 25th and 75thpercentile (the lower and upper end of the box), 1 and 99thpercentile (horizontal top and bottom lines) and maximum andminimum values (open circles) for different months. The whiskersshow the standard deviations of the mean. The distributions arehighly skewedwith higher mean values than themedian values (50percentile) during all the months indicating the occurrence of highvalues of BC that lift up the monthly mean, despite occurring lessfrequently. The monthly mean BC concentrations ranged fromhighest value of 1.61�0.86 mgm�3 in January to the lowest value of0.23 � 0.02 mg m�3 during August. The minimum values of BCremained more or less similar during all the months, while themaximum values showed significant variations. The climatologicalseasonal mean values of BC are given in Table 1.

Notwithstanding the above, the seasonal mean values of BC atNaliya are significantly lower than those reported over severalcontinental locations of India. For example, at Ahmedabad(23.03�N, 72.5�E, 55 m amsl, urban centre due north-east of Naliya)a mean value of 11.6 � 2.9 mg m�3 has been reported during winter(Ramachandran and Kedia, 2010); while over a tropical semi-aridlocation Anantapur in southern peninsular region with values5 mg m�3 in winter and >1.0 mg m�3 in summer are reported byBalakrishnaiah et al. (2011) from long-term measurements; andover Kharagpur, located towards the east coast of Indo-GangeticPlains (IGP), BC concentration was as high as w16.2 mg m�3 dur-ing winter (Nair et al., 2007); or even the foothills of Himalayas,such as Dehradun due north of Naliya, the mean concentration ofBC is w6.7 mg m�3 in winter and w2.6 mg m�3 in summer (Babuet al., 2011). It has also been found that the BC values at Naliyaare significantly lower than the values reported over other coastallocations of India, e.g., Trivandrum (MB w 5 mg m�3; Babu andMoorthy, 2001) and Goa (MB w 3 mg m�3; Leon et al., 2001) dur-ing dry months.

More interestingly, the Naliya values are comparable to thoseseen over polluted coastal Oceanic regions of Arabian Sea, adjoiningIndian peninsula (remaining < 0.70 mg m�3) during the pre-monsoon season of “ICARB-2006 (Moorthy et al., 2008)”, butsignificantly higher than most part of the north Arabian Sea(MB < 0.40 mg m�3) as reported by Nair et al. (2008). However, allthese indicate a rather clean environment with relatively lowabundance of BC over western part of India. At the same time, theBC levels in the environment observed during our observations aresignificant, if we consider the sparse inhabitation and remote na-ture of Naliya and the absence of any major industry or other ac-tivity in its proximity. This clearly indicates themajor role played bythe long range transport of aerosols from nearby pollution sourceregions in the enhancement of BC.

4.2. Absorption properties

From the raw attenuation data as a function of l from theaethalometer, the absorption coefficients (sabs) for each set ofmeasurements were estimated as

sabsðlÞ ¼ 1CR

*

�DATNðlÞ

DtAQ

�(1)

where A is the filter spot area, Q the volumetric flow rate and DATN(l) is the change in attenuation at the wavelength l due to particleload on the filter media during the time interval Dt. The parametersC and R are correction factors for minimizing the inherent uncer-tainty associated with aethalometer, arising from multiple scat-tering of light in the filter matrix and the change in the optical pathlength due to successive aerosol loadings. The correction for these

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e102 97

uncertainties was done following Weingartner et al. (2003) incor-porating values of C¼ 2.14 and R¼ 1 for loading effect and multiplescattering corrections respectively.

The estimated values of the absorption coefficient (sabs) at550 nmvaried between the highest value ofw17.05� 7.67Mm�1 inwinter and the lowest value w2.71 � 1.02 Mm�1 in summer(Table 1). The seasonal variation of MB and sabs is indicative ofcontributions from different aerosol sources, the relative abun-dance of which change seasonally; either due to seasonal nature ofthe sources or due to change in the advection pathways or both, inaddition to the change in the local meteorology (e.g., wind speed,Temperature, ABL height etc.) at different seasons. With a view toexamining the contribution of natural or anthropogenic aerosolsources, the spectral variations of sabs are examined, assuming apower law dependence of sabs with l of the form

sabsðlÞ ¼ babsl�aabs (2)

where babs is a constant and aabs represents the absorption(Angstrom) exponent. For BC (elemental) aerosols, originating fromfossil fuel combustions, aw 1.0 (Kirchstetter et al., 2004). However,if the wavelength dependence of aabs significantly deviates from1.0, it is indicative of the presence of the absorbing species such asdust or carbonaceous aerosols resulting from biomass burning orbrown carbon, the spectral absorption of which increases morerapidly towards lower wavelengths, thereby giving a higher valuefor aabs. For example, for biomass smoke aerosols an average valueof a z 2 (Kirchstetter et al., 2004; Bergstrom et al., 2007) has beenreported. Light absorption by dust aerosols has also been reportedto depict steeper spectral dependency (aabs w 2.0). The monthlyvariation of aabs in Fig. 5 (months being represented by the right Y-axis) clearly indicates a seasonal change; aabs being highest inwinter and lowest in summer seasons. Viewed these with the lightof the spectral absorption of different species as discussed above, itemerges that the winter season with higher aabs indicates higherdominance of biomass burning aerosols, whereas aabs remains<1.0during the summer months showing prevalence of fossil fuelgenerated BC.

With a view to examining the weightings of the contribution ofbiomass smoke or fossil fuel combustions or dust, the frequencydistribution aabs is generated separately for each season and shownin Fig. 5 superposed with the monthly variation of aabs. It clearlyemerges from the figure that, notwithstanding the variation in thedailymean values of aabs, thewinter season is characterized by high

Fig. 5. Monthly variation of aabs along with their frequency distribution at differentseasons.

spectral values with a median value of 1.35 for aabs; with more than95% of the values being >1.0. In contrast, during summer >72% ofthe values were <1.0, with a median value of aabs ¼ 0.9. During theother seasons the median values were w1.1. The fact is morediscernible from the scatter plot of BC and aabs in Fig. 6, whichclearly shows that for seasons in which BC concentration showslarge variations from values as low as 0.013 mg m�3 to as high as3.43 mg m�3, the values of aabs are generally high (>1) and mostlylie between 1.0 and 1.5. This shows that the large increase in BCconcentration during winter is mostly connected to aerosols havingsteeper l-dependence such as biomass burning aerosol sources ordust. As the season advances from winter to spring, there is adecrease in the BC concentration, as well as decrease in aabs (variedbetween 0.5 and 1.3). During summer, aabs decreased to lowest(w0.25) and remained <1.0 for more than 90% of observationswhen the BC mass concentration was also lowest. This indicatesthat the prevailing BC aerosols during summer are due to fossil fuelcombustions.

4.3. Source apportionment

With a view to examining the influence of distinct sources to theseasonal variation of BC mass concentrations and their spectralbehaviour, 7-day isentropic HYSPLIT back-trajectory and concen-tration weighted trajectory (CWT) analyses are carried out for eachseason, considering an ending height of 500 m AGL at the receptorsite, following the details given in Gogoi et al. (2011) and referencescited therein. Trajectory clusters are made from the ensemble oftrajectories, based on their origin following the angleedistancealgorithm (Sirois and Bottenheim, 1995) and the mean seasonalpatterns are shown in Fig. 7. The trajectory clusters clearly showthat the mean pathways distinctively differ with seasons. Thedominant trajectory clusters of continental origin during wintergradually change their path to ‘continental plus marine’ duringspring and completely of the marine origin during summer andspreads up again to mixed origin (continental and marine) duringautumn. The distribution of the values of aabs with respect to tra-jectory clusters (in Table 2) indicates that the strong spectraldependence of aerosol absorption (mean aabs ¼ 1.27 � 0.23) duringwinter season is associated with the dominant advection (w53%)from the locations northwest of Naliya, and from the IGP (cluster-3;for which aabs ¼ 1.22 � 0.12). The CWT plots in Fig. 7 also indicatethat strong potential sources contributing to higher aabs duringwinter is extended over the west Asian landmasses.

The north-westerly contribution continues (cluster-1) duringspring too, making aabs nearly consistent (w1.21 � 0.1); however,the cluster mean value of aabs became lower when the air massesshift to oceanic regions (cluster-2), bringing in cleaner air to thesite. During summer, the trajectory clusters originate only from theoceanic region and lead to the lowest value of aabs, and BC. If this isconsidered as representing background conditions thatprevail then these BC appear to originate from fossil fuel combus-tions. The large reduction in the BC concentration during this sea-son is due to lower source strength, coupled with rain washout andstrong winds. During autumn, the continental influence builds upagain, advecting biomass burning components from the IGP, whichis noticeable from the increased cluster mean value of aabs(¼1.17 � 0.27).

MODIS fire counts (cloud corrected fire pixels) data are used toidentify the role of potential biomass burning regions in modu-lating the absorption properties of aerosols at Naliya. The spatialdistribution of fires in Fig. 8 indicates that during winter, thoughthe total area infested by forest fires and biomass burning are notvery high (compared to spring), presence of strong biomassburning regions are seen over the north-western and southeastern

Fig. 6. Scatter plot of BC mass concentration against aabs.

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e10298

locations of Naliya. The CWT map also shows large contribution toaabs from these regions. On the other hand, though the fire activitiesare strongest in spring, the advections from these locations toNaliya are absent. This lends further support to the significantcontribution of BC from biomass burning to the BC abundance overNaliya during winter, leading to the highest values of BC and itssteep wavelength variation (high aabs). During summer, fire eventsare absent around Naliya on the one hand and the advectionpathways are conducive for brining-in clean marine airmass on theother, leaving only the local and regional contributions to dominatethe BC concentration and determine its absorption properties.These, representative of the background conditions at this location,

Fig. 7. Cluster of trajectories and CWT

appear to arise from fossil fuel combustion as revealed by the lowvalues of aabs which remains around 1, typical value for aged BCaerosols of fossil fuel origin (Kirchstetter et al., 2004).

4.4. Examination of satellite data

With a view to examining the BC characteristics based on thesurface measurements from one location at Naliya to a regionalperspective, we analysed the UV aerosol index using the OMI(Ozone Monitoring Instrument) data. This was also aimed atexamining the role of dust aerosols that absorb strongly at shorterwavelengths. Another intension was to examine, whether the

map of aabs at different seasons.

Table 2Cluster mean values of aabs with respect to different trajectory clusters duringdifferent seasons.

Cluster Trajectories (%) Mean Std. dev.

Winter1 (W) 18.8 1.14 0.162 (NE) 12.6 1.15 0.363 (E) 14.8 1.22 0.124 (NW) 53.8 1.27 0.23Spring1 (NW) 16.1 1.21 0.12 (SW) 48.4 1.04 0.113 (W) 35.5 1.10 0.12Summer1 (SW) 83.7 0.86 0.162 (SW) 16.3 0.82 0.27Autumn1 (NE) 20.7 1.17 0.272 (SW) 23.1 1.01 0.083 (N) 23.1 1.06 0.404 (NW) 33.1 1.08 0.26

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e102 99

observed dilution of BC near the surface is due to increased verticaldispersion during summer. The Aerosol Index (AI) product fromOMI on-board AURA satellite is used for this purpose [see Torreset al. (1998) for details theoretical basis of OMI]. The AI is a mea-sure of howmuch the wavelength dependence of backscattered UVradiation from an atmosphere containing aerosols (Mie scattering,Rayleigh scattering, and absorption) differs from that of a puremolecular atmosphere (pure Rayleigh scattering). The UVabsorbing aerosols, clouds and scattering aerosols are delineatedrespectively by positive, near zero and negative values of AI.Quantitatively, the UVAI results from the comparison betweenmeasured and calculated radiances (Lobsl

and Lcall

respectively) inthe range 330e390 nmwhere gas absorption effects are negligible.Among all types of aerosols, dust is the main contributor to the AIsignal (Li et al., 2009). In the present study, we have used OMTO3ddaily data, the monthly variation of which is shown in Fig. 9. Quiteinterestingly the annual variation of monthly mean AI is nearlyopposite to that of aabs (shown in Fig. 5), with higher values duringsummer and lower in winter. As AI is a columnar measure of

Fig. 8. Cloud and overpass corrected MODIS fire pixels count at d

aerosols, our observations reveal that during summer season, whenfossil fuel combustions sources are the only contributors to thenear-surface BC concentrations over Naliya, significant amount ofabsorbing aerosols are present in the upper atmosphere leading tohigher values of (columnar) AI. This is further borne out by themonthly variation of columnar aerosol optical depth (AOD) overNaliya, which are estimated from the daily values, obtained fromMODIS (Terra and Aqua, at 550 nm) and MISR (at 555 nm) data (weused version 3, MODIS collection 5.1 and V004 MISR Level 3 dailydata). The monthly variation of AOD in Fig. 9 clearly shows that thecolumnar abundance of aerosols are highest during the summerseason, as indicated by the highest values of AOD (as high asw1.0),while the values of AOD go as low as 0.2 during winter seasonwhich shows the presence of large additional aerosol abundance inthe column (during summer) most probably above the atmosphericboundary layer. This provides a clear indication of possible elevatedlayers of absorbing aerosols which make the columnar character-istics to differ significantly from that seen at the surface.

To ascertain the above possibility, the altitude profiles ofextinction coefficients at 532 nmwere examined from CALIOP, on-board CALIPSO (the NASA-CNES Cloud-Aerosol Lidar and InfraredPathfinder Satellite Observations, Winker et al., 2007) (CAL_-LID_L2_05kmAPro-Prov-V3), during the summer and winter sea-sons of 2009 and 2010. The cloud discriminated mean aerosolextinction profiles averaged over the two contrasting seasons areshown in Fig. 10. It clearly emerges that during summer, the valuesof extinction coefficients remain >0.2 km�1 in the entire altituderange (0e6 km) with the presence of a secondary peak (extinctioncoefficient w 0.4 km�1) at the altitude region of 5e6 km. However,during winter the extinction coefficients are lower and decreasegradually with altitude (up to a height of 4 km) to very low values ofw0.05 km�1 and become insignificant thereafter (above 4 km).While the fractional extinction due to aerosols above w2 km (ABL)was <40% during winter, it is significantly higher (>60%) duringsummer season. This confirms again the presence of elevatedabsorbing layers of aerosols possibly mineral dust advected by thestrong westerlies from the arid regions to the west of Naliya. Asthese particles resided above the ABL, the aabs as measured by theaethalometer did not convey its signature, while the OMI data

ifferent seasons (climatological) during Nov 2007eJun 2010.

Fig. 10. Mean vertical profile of aerosol (a) extinction coefficient (km�1) at 532 nm, (b) depolarization ratio during summer and winter season of 2009 and 2010.

Fig. 9. Monthly mean values of OMI Aerosol Index (AI) and columnar AOD (MODIS andMISR) during the period of study.

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e102100

being column integrated, is affected. With a view to confirming therole of dust, we examined the volume depolarization ratios(defined as the ratio of the perpendicular to the parallel compo-nents of the range corrected aerosol backscatter) estimated fromthe profiles and the seasonal means are shown in the right panel ofFig.10. The depolarization signatures allow discrimination betweenspherical and non-spherical particles, liquid aerosol droplets anddust or cloud droplets and the crystals (Winker et al., 2007). The180� backscatter from spherical particles retains the polarization ofoutgoing 532-nm linearly polarized laser pulses, whereas back-scatter from non-spherical or irregular particles is depolarized.Thus, the higher depolarization ratios (>0.3) during summer sea-son in Fig. 10 at higher altitude regions demonstrate the notableconsistency of the presence of non-spherical particles (e.g., dust),which contribute to the large aerosol extinction at higher levels,without affecting the near-surface observations.

Measurement of depolarization ratios of major types of tropo-spheric aerosol particles (Asian and Saharan mineral dust, sea salt,and ammonium sulphate) using laboratory chamber has been re-ported to have highest depolarization ratio (w0.39) for dust in thesuper-micrometre range and moderate (between 0.17 and 0.14) inthe sub-micrometre range; while sea-salt and ammonium sulphatecrystals show lower depolarization ratios (0.08 and 0.04

respectively, Sakai et al., 2010). Similar to dust, volcanic aerosolsalso cause depolarization ratios >0.3 at 532 nm (Ansmann et al.,2012). There are several examples of higher values of dust depo-larization ratio (w0.3) reported elsewhere. For example, lidarmeasurements close to the Saharan dust source (Freudenthaleret al., 2009) and its long-range transport towards Europe(Wiegner et al., 2011) and Cape Verde (Tesche et al., 2011) also showvalues ranging from 0.3 to 0.35 in lofted dust-dominated aerosollayers. Associated with the long-range transport of mineral dustfrom the desert regions in western and northern China, higherdepolarization ratios (0.3e0.35) are reported over Japan (Sakaiet al., 2003).

The net dust production at any location depends on the com-bined effect of wind and soil moisture. If both wind speed and soilmoisture are high, the dust production rate will be low. Duringwinter, the soil moisture is very low over the deserts over North-west India (Rajasthan). However, surfacewindswere also low. FromMarch onwards, the low soil moisture and simultaneous high windspeed caused the uplift of surface dust to the atmosphere(Deepsikha et al., 2006).

5. Conclusions

Using ground based measurements of near surface spectralabsorption of aerosols and concurrent data on aerosol optical depthand UV aerosol index from satellites for a period of 3 years, theabsorbing property of atmospheric aerosols over the northwesternarid region of India has been characterized. The seasonality ofdifferent sources, natural and anthropogenic, pre-dominating theobserved seasonality in the absorption characteristics is delineated.The major findings are:

� BC depicted highest mass concentrations (MB) during winter(MB ¼ 1.45 � 0.71 mg m�3) and lowest in summer(MB¼0.23�0.11mgm�3) revealing the remotenature of the site.

� Similar to MB, aabs also showed highest value (1.24 � 0.14) inwinter and lowest (w0.86 � 0.19) in summer. During the otherseasons, the median values of aabs are low (w1.1).

� Synthesizing the data with the cluster and concentrationweighted trajectory analyses and the spatial distribution ofMODIS fire counts, it emerges that the strong spectral depen-dence of aerosol absorption during winter season is associatedwith the dominant advection (w53%) of biomass burningaerosols from the northwestern locations of Naliya and the IGP.

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e102 101

During summer, the BC concentration appears to arise fromfossil fuel combustions as revealed by the low values of aabs.

� Examination of the seasonal variation of aerosol index (AI),columnar AOD along with the vertical profiles of aerosolextinction coefficients and depolarization ratio indicate thepresence of elevated layers of dust aerosols during the summerseason, however the surface observations are unaffected. Thepotential atmospheric warming by the absorbing dust layers inthe free troposphere would have implications to synopticsystems such as the Asian monsoon, through elevated heatpump process.

Acknowledgement

This study was carried out under the Aerosol Radiative Forcingover India (ARFI) project of ISRO-Geosphere Biosphere Program(ISRO-GBP). We acknowledge Air Vice Marshal Dr. Ajith Tyagi forfacilitating the measurements and wing commander Mr. HarishKumar and the Indian Air Force, Naliya in supporting these mea-surements. We also acknowledge NOAA Air Resources Laboratoryfor the provision of the HYSPLIT transport and dispersion modeland READY website (http://www.arl.noaa.gov/ready.html) used inthis publication. The CALIPSO data were obtained from the NASALangley Research Center Atmospheric Sciences Data Center. TheOMI AAI, MODIS and MISR AOD data used in this study were ac-quired using the GES-DISC Interactive Online Visualization andanalysis Infrastructure as part of the NASA’s Goddard Earth SciencesData and Information Services Center.

References

Ackerman, A.S., Toon, O.B., Taylor, J.P., Johnson, D.W., Hobbs, P.V., Ferek, R.J., 2000.Effects of aerosols on cloud albedo: evaluation of Twomey’s parameterization ofcloud susceptibility using measurements of ship tracks. Journal of AtmosphericSciences 57, 2684e2695. http://dx.doi.org/10.1175/1520-0469.

Ansmann, A., Seifert, P., Tesche, P., Wandinger, U., 2012. Profiling of fine and coarseparticle mass: case studies of Saharan dust and Eyjafjallajokull/Grimsvotnvolcanic plumes. Atmospheric Chemistry and Physics 12, 9399e9415.

Arnott, W.P., Hamasha, K., Moosmuller, H., Sheridan, P.J., Ogren, J.A., 2005. Towardsaerosol light-absorption measurements with a 7-wavelength aethalometer:evaluation with a photoacoustic instrument and 3-wavelength Nephelometer.Aerosol Science and Technology 39 (1), 17e29.

Babu, S.S., Moorthy, K.K., 2001. Anthropogenic impact on aerosol black carbon massconcentration at a tropical coastal station: a case study. Current Science 81 (9),1208e1214.

Babu, S.S., et al., 2011. High altitude (w4520 m amsl) measurements of black carbonaerosols over western trans-Himalayas: seasonal heterogeneity and sourceapportionment. Journal of Geophysical Research 116, D24201. http://dx.doi.org/10.1029/2011JD016722.

Balakrishnaiah, et al., 2011. Anthropogenic impact on the temporal variations ofblack carbon and surface aerosol mass concentrations at a tropical semi-aridstation in southeastern region of India. Journal of Asian Earth Sciences 42,1297e1308.

Beegum, S.N., et al., 2009. Spatial distribution of aerosol black carbon over Indiaduring pre-monsoon season. Atmospheric Environment 43, 1071e1078.

Bergstrom, R.W., et al., 2007. Spectral absorption properties of atmospheric aero-sols. Atmospheric Chemistry and Physics Discussions 7, 10669e10686.

Bonasoni, P., et al., 2010. Atmospheric brown clouds in the Himalayas: first twoyears of continuous observations at the Nepal Climate Observatory-Pyramid(5079 m). Atmospheric Chemistry and Physics 10, 7515e7531. http://dx.doi.org/10.5194/acp-10-7515-2010.

Cappa, et al., 2012. Radiative absorption enhancements due to the mixing state ofatmospheric black carbon. Science 337, 1078. http://dx.doi.org/10.1126/science.1223447.

Carrico, C.M., Bergin, M.H., Shrestha, A.B., Dibb, J.E., Gomes, L., Harris, J.M., 2003. Theimportance of carbon and mineral dust to seasonal aerosol properties in theNepal Himalaya. Atmospheric Environment 37, 2811e2824.

Corrigan, C.E., Ramanathan, V., Schauer, J.J., 2006. Impact of monsoon transitions onthe physical and optical properties of aerosols. Journal of Geophysical Research111 (D18208). http://dx.doi.org/10.1029/2005JD006370.

Deepsikha, S., Satheesh, S.K., Srinivasan, J., 2006. Dust aerosols over India andadjacent continents retrieved using METEOSAT infrared radiance, part-I: sour-ces and regional distribution. Annales Geophysicae 24 (1), 37e61.

Freudenthaler, V., Esselborn, M., Wiegner, M., Heese, B., Tesche, M., Ansmann, A.,Müller, D., Althausen, D., Wirth, M., Fix, A., Ehret, G., Knippertz, P., Toledano, C.,

Gasteiger, J., Garhammer, M., Seefeldner, M., 2009. Depolarization ratio profilingat several wavelengths in pure Saharan dust during SAMUM 2006. Tellus B 61,165e179. http://dx.doi.org/10.1111/j.1600-0889.2008.00396.x.

Gabriel, R., Mayol-Bracero, O.L., Andreae, M.O., 2002. Chemical characterization ofsubmicron aerosol particles collected over the Indian Ocean. Journal ofGeophysical Research 107 (D19). http://dx.doi.org/10.1029/2000JD000034.

Gogoi, M.M., Pathak, B., Moorthy, K.K., Bhuyan, P.K., Babu, S.S., Bhuyan, K., Kalita, G.,2011. Multi-year investigations of near surface and columnar aerosols overDibrugarh, northeastern location of India: heterogeneity in source impacts.Atmospheric Environment 45 (9), 1714e1724.

Hansen, J., Nazarenko, L., 2004. Soot climate forcing via snow and ice albedos.Proceedings of the National Academy of Sciences 101, 423e428. http://dx.doi.org/10.1073/pnas.2237157100.

Intergovernmental Panel on Climate Change (IPCC), 2007. Climate Change 2007: thephysical science basis. In: Solomonn, S., et al. (Eds.), Contribution of WorkingGroup 1 to the Fourth Assessment Report of the Intergovernmental Panel onClimate Change. Cambridge Univ. Press, Cambridge, UK.

Jacobson, M.Z., 2001. Strong radiative heating due to the mixing state of blackcarbon in atmospheric aerosols. Nature 409, 695e698.

Janssen, et al., 2012. Health Effects of Black Carbon. World Health Organization,ISBN 978 92 890 0265 3.

Kirchstetter, T., Novakov, T., Hobbs, P., 2004. Evidence that the spectral dependenceof light absorption by aerosols is affected by organic carbon. Journal ofGeophysical Research 109 (D21). http://dx.doi.org/10.1029/2004JD004999.

Leon, J.F., Chazette, P., Dulac, F., 2001. Large-scale advection of continental aerosolduring INDOEX. Journal of Geophysical Research 106 (D22), 28427e28440.

Li, J., Carlson, B.E., Lacis, A.A., 2009. A study on the temporal and spatial variabilityof absorbing aerosols using Total Ozone Mapping Spectrometer and OzoneMonitoring Instrument Aerosol Index data. Journal of Geophysical Research 114,D09213. http://dx.doi.org/10.1029/2008JD011278.

Marinoni, A., et al., 2010. Aerosol mass and black carbon concentrations, a two yearrecord at NCO-P (5079 m, Southern Himalayas). Atmospheric Chemistry andPhysics 10, 8551e8562. http://dx.doi.org/10.5194/acp-10-8551-2010.

Mishra, S.K., Dey, S., Tripathi, S.N., 2008. Implications of particle composition andshape to dust radiative effect: a case study from the Great Indian Desert.Geophysical Research Letters 35, L23814. http://dx.doi.org/10.1029/2008GL036058.

Moorthy, K.K., Satheesh, S.K., 2011. Black Carbon Aerosols over India. In: BlackCarbon e-Bulletin, vol. 3 (2). Published by the United Nations EnvironmentProgramme (UNEP) in Collaboration with the Science Team of AtmosphericBrown Cloud (ABC).

Moorthy, K.K., Babu, S.S., Satheesh, S.K., Srinivasan, J., Dutt, C.B.S., 2007. Dust ab-sorption over the “Great Indian Desert” inferred using ground-based and sat-ellite remote sensing. Journal of Geophysical Research 112, D09206. http://dx.doi.org/10.1029/2006JD007690.

Moorthy, K.K., Nair, V.S., Babu, S.S., Satheesh, S.K., 2009. Spatial and vertical het-erogeneities in aerosol properties over oceanic regions around India: implica-tions for radiative forcing. Quarterly Journal of the Royal Meteorological Society135, 2131e2145.

Moorthy, K.K., Satheesh, S.K., Babu, S.S., Dutt, C.B.S., 2008. Integrated Campaign forAerosols, gases and Radiation Budget (ICARB): an overview. Journal of EarthSystem Sciences 117 (S1), 243e262.

Nair, V.S., Moorthy, K.K., Alappattu, D.P., et al., 2007. Wintertime aerosol charac-teristics over the Indo-Gangetic Plain (IGP): impacts of local boundary layerprocesses and long-range transport. Journal of Geophysical Research 112,D13205. http://dx.doi.org/10.1029/2006JD008099.

Nair, V.S., Babu, S.S., Moorthy, K.K., 2008. Aerosol characteristics in the marine at-mospheric boundary layer over the Bay of Bengal and Arabian Sea duringICARB: spatial distribution and latitudinal and longitudinal gradients. Journal ofGeophysical Research 113, D15208. http://dx.doi.org/10.1029/2008JD009823.

Oshima, N., et al., 2012. Wet removal of black carbon in Asian outflow: AerosolRadiative Forcing in East Asia (A-FORCE) aircraft campaign. Journal ofGeophysical Research 117, D03204. http://dx.doi.org/10.1029/2011JD016552.

Ramachandran, S., Kedia, S., 2010. Black carbon aerosols over an urban region:radiative forcing and climate impact. Journal of Geophysical Research 115,D10202. http://dx.doi.org/10.1029/2009JD013560.

Ramanathan, V., Carmichael, G., 2008. Global and regional climate changes due toblack carbon. Nature Geoscience 1, 221e227.

Reddy, M.S., Boucher, O., 2007. Climate impact of black carbon emitted from energyconsumption in the world’s regions. Geophysical Research Letters 34, L11802.http://dx.doi.org/10.1029/2006GL028904.

Sakai, T., Nagai, T., Nakazato, M., Mano, Y., Matsumura, T., 2003. Ice clouds and Asiandust studied with lidar measurements of particle extinction-to-backscatterratio, particle depolarization, and water vapour mixing ratio over Tsukuba.Applied Optics 42, 7103e7116.

Sakai, T., Nagai, T., Zaizen, Y., Mano, Y., 2010. Backscattering linear depolarizationratio measurements of mineral, sea-salt, and ammonium sulfate particlessimulated in a laboratory chamber. Applied Optics 49, 4441e4449.

Satheesh, S.K., Srinivasan, J., Moorthy, K.K., 2006. Spatial and temporal heteroge-neity in aerosol properties and radiative forcing over Bay of Bengal: sources androle of aerosol transport. Journal of Geophysical Research 111, D08202. http://dx.doi.org/10.1029/2005JD006374.

Schuster, G.L., Dubovik, O., Holben, B.N., Clothiaux, E.E., 2005. Inferring black carboncontent and specific absorption from AERONET retrievals. Journal of Geophys-ical Research 101, D10S17. http://dx.doi.org/10.1029/2004JD004548.

M.M. Gogoi et al. / Atmospheric Environment 73 (2013) 92e102102

Shindell, et al., 2012. Simultaneously mitigating near-term climate change andimproving human health and food security. Science 335, 183. http://dx.doi.org/10.1126/science.1210026.

Sirois, A., Bottenheim, J.W., 1995. Use of backward trajectories to interpretthe 5-year record of PAN and O3 ambient air concentrations at Kejim-kujik National Park, Nova Scotia. Journal of Geophysical Research 100,2867e2881.

Street, D.G., et al., 2001. Black carbon emissions in China. Atmospheric Environment35, 4281e4296.

Tesche, M., Groß, S., Ansmann, A., Muller, D., Althausen, D., Freudenthaler, V.,Esselborn, M., 2011. Profiling of Saharan dust and biomass-burning smoke withmultiwavelength polarization Raman lidar at Cape Verde. Tellus B 63, 649e676.http://dx.doi.org/10.1111/j.1600-0889.2011.00548.x.

Torres, O., Bhartia, P.K., Herman, J.R., Ahmad, Z., Gleason, J., 1998. Derivationof aerosol properties from satellite measurements of backscattered

ultraviolet radiation: theoretical basis. Journal of Geophysical Research103, 17099e17110.

Weingartner, E., Saathoff, H., Schnaiter, M., Streit, N., Bitnar, B., Baltensperger, U.,2003. Absorption of light by soot particles: determination of the absorption co-efficient by means of aethalometers. Journal of Aerosol Science 34, 1445e1463.

Wiegner, M., Groß, S., Freudenthaler, V., Schnell, F., Gasteiger, J., 2011. The May/June2008 Saharan dust event over Munich: intensive aerosol parameters from lidarmeasurements. Journal of Geophysical Research 116, D23213. http://dx.doi.org/10.1029/2011JD016619.

Winker, D.M., Hunt, B.H., McGill, M.J., 2007. Initial performance assessment ofCALIOP. Geophysical Research Letters 34, L19803. http://dx.doi.org/10.1029/2007GL030135.

Yoo, H.J., Kim, J., Yi, S.K., Zoh, K.D., 2011. Analysis of black carbon, particulate matter,and gaseous pollutants in an industrial area in Korea. Atmospheric Environ-ment 45, 7698e7704.