a new classification of aerosol sources and types as ...properties over jaipur in north-western...

Aerosol and Air Quality Research, 15: 985–993, 2015 Copyright © Taiwan Association for Aerosol Research ISSN: 1680-8584 print / 2071-1409 online doi: 10.4209/aaqr.2014.07.0143

A New Classification of Aerosol Sources and Types as Measured over Jaipur, India Sunita Verma1, Divya Prakash1, Philippe Ricaud2, Swagata Payra1,2,3*, Jean-Luc Attié2,3, Manish Soni1

1 Centre of Excellence in Climatology, Birla Institute of Technology Mesra, Jaipur Campus, Jaipur 302017, Rajasthan, India 2 CNRM GAME, Météo-France, CNRS UMR3589, Toulouse, France 3 Laboratoire d'Aérologie, Université de Toulouse, CNRS UMR5560, Toulouse, France ABSTRACT

The aerosol properties retrieved from the AErosol RObotic NETwork (AERONET) measurements during the period 2009 to 2012 over Jaipur (26.9°N, 75.8°E, 450m asl) in Northwestern India are used for the first time to identify the types of aerosols. In order to consider the appropriate threshold of aerosol optical thickness (τ) at 500 nm (τ500) and Angstrom exponent (α) in the spectral band 440–870 nm, a novel approach has been conducted and applied for the identification process. Five prevailing aerosol classes are identified: desert dust, biomass, maritime, arid background and mixed aerosols. Arid background and desert dust type aerosols are the most common at Jaipur (34.7% and 13.6%, respectively), with a wide variability in both τ and α. In about 8.4% of the cases, aerosols can be classified as maritime, although mixing with other aerosols (33.6%) is substantial. The ground-based spectral optical thickness and the refractive index estimated at visible and near-infrared wavelengths are used to account for the type of atmospheric aerosols. They are compared with four more AERONET sites located in India based upon their geographical distribution and extensive data availability. Simultaneously, single scattering albedo of dust is also inferred for all the available AERONET sites for the same period over India. The comparison results suggest that Jaipur arid background is more scattering in nature than Northern and Western regions in India. Finally, the absorption is less in summer than in winter over the Jaipur site. Keywords: Aerosols; Optical thickness; Desert dust; Arid; Biomass; Angstrom exponent. INTRODUCTION

The role of atmospheric aerosols on the Earth system is a subject of growing interest due to their impact on the Earth-atmosphere climate system, air quality and human health. Ground-based remote sensing has emerged as a powerful technique for characterizing the suspended aerosol (Dubovik and King, 2000; Dubovik et al., 2002). Due to the heterogeneous nature of particles suspended in the atmosphere and their short lifetime, it is difficult to characterize the types of aerosols. Aerosol mixtures (dust, sulfate, carbon, sea-salt, or mixtures) pose a challenge to satellite and sub-orbital remote sensing techniques (Jeong et al., 2005; Levy et al., 2007; Kalapureddy et al., 2009; Eck et al., 2010; Toledano et al., 2011; Giles et al., 2012). Ground-based remote sensing techniques are an important * Corresponding author.

Tel.: 91-9610895724 E-mail address: [email protected]

to improve accuracy of satellite retrievals and assessments of the aerosol radiative impacts on the climate. Advances in ground-based and satellite data can now produce a global view of the aerosol system (Kaufman et al., 2002) and characterize key aerosol species that affect global climate (biomass burning, desert dust, sea salt, and pollution).

Atmospheric aerosol concentrations and their optical properties are considered as one of the largest sources of uncertainty in current assessments and predictions of global climate change (Hansen et al., 2000; IPCC, 2007). There has been growing concern to monitor aerosols with coordinated research efforts throughout the world under international programs (e.g., Global Earth Observation System of Systems {GEOSS}), multiple platforms (e.g., ground-based networks, satellites, ships, and aircrafts) and different measurement techniques (e.g., in-situ and remote sensing observations). The AErosol RObotic NETwork (AERONET) program (Holben et al., 1998) has been continuously providing systematic observations of optical, microphysical and radiative aerosol properties from the surface around many parts of the world. The long-term AERONET dataset has been used in various local studies (e.g., Dubovik et al., 2002; Dey et al., 2004;

Verma et al., Aerosol and Air Quality Research, 15: 985–993, 2015 986

Perrone et al., 2005; Saha et al., 2010; Dey and Girolamo, 2011; Verma et al., 2013).

In particular, aerosols over and around India not only affect the Indian monsoon but also the global climate (Satheesh et al., 2006). The Indo-Gangetic Plains (IGP) in India is one of the most interesting regions for aerosol and climate studies. This area is surrounded by the main sources of natural and anthropogenic aerosols: the Himalayas on the north, the Thar desert on the west and highly populated and industrialized states in IGP on the east. The aerosol radiative forcing estimates as indicated by several studies are among the highest in the world (Dey et al., 2004; Mallet et al., 2011). In the Ganga Basin (GB) of the North-western India, dust storms occur frequently during the pre-monsoon (April–June) season every year (Middleton, 1986; Dey et al., 2004). High aerosol loading exists over the IGP in pre-monsoon period. This may significantly impact on the monsoon activity over the IGP (Lau et al., 2006), however this remains highly uncertain. It is also well established that the aerosol sources over the Indian landmasses are highly variable and have a distinct feature. Northern India is dominated by greater dust influence during the pre-monsoon season. However, the western and eastern regions are quite different in terms of aerosol optical/radiative properties as recently documented by radiometric observations from Gautam et al. (2011) and Dey and Girolama (2011). To reduce the current uncertainties, long-term monitoring of the aerosol properties at as many locations as possible are required from all regions in India to generate representative measurements and understanding on such large-scale phenomena. Characterization of aerosol properties over Jaipur in North-western India is thus important since this region is adjacent to the Thar desert, which is the significant dust source in the Asia, and India. Previous studies performed over Jaipur were mainly focused on 1) examining the variations in seasonal pattern of aerosol properties under specific events, such as dust transport, and 2) comparing the observations of polluted and dust storm days (Prakash et al., 2013; Verma et al., 2013). The effect of the transported dusts on the aerosol optical properties in the Jaipur area (Northwestern India) has been investigated earlier in Verma et al. (2013) based on air mass trajectories and satellite data. In the present paper, ground-based retrievals of aerosol properties have been further explored from the global AERONET aerosol network (Holben et al., 1998) to identify several key aerosol types (biomass burning, mineral dust, marine and anthropogenic pollution). The types of aerosols are analyzed for cloud free level 2 AERONET data collected during 2009–2012 in Jaipur to strengthen the inference about the dust sources as indicated by the air mass trajectories. The present study is among the first over Jaipur focusing on the aerosol types and associating them with regional climatology. REGIONAL CHARACTERISTICS, METEOROLOGY AND DATA SET Site Description

Jaipur (26.9°N, 75.8°E, 450 m altitude) is situated in eastern region of Rajasthan (India). North India’s regional weather and climate are strongly influenced by the Himalayas

(North) and the Thar Desert (West). The Himalayas act as a barrier to the cold north winds from central Asia, so that northern India is comparatively warmer or only mildly cooler during winter and hotter during summer. Meteorological Patterns

Aerosols play a crucial role on monsoon features over India as they act as cloud condensation nuclei (CCN) which, in combination with the available moisture in the atmosphere, determine the amount of rainfall occurring over the India region (Lau et al., 2006). During pre-monsoon season (March–May), a low-pressure system starts developing due to increased heating over land with a higher pressure over the Arabian Sea (AS) and the Bay of Bengal (BoB) (Pandithurai et al., 2007). The dust content over northwestern India (Thar Desert and its adjacent) is at a maximum during pre-monsoon often affecting the Jaipur area.

National Center for Environmental Prediction (NCEP) – National Center for Atmospheric Research (NCAR) reanalysis of wind and air temperature at the 850 mb pressure level were used to study the prevailing synoptic meteorological conditions over India (Fig. 1) during summer and winter seasons for the study period. The magnitude of wind speed is represented by arrows (in m/s) and shaded color shows the air temperature with the embedded values in contour. Results reveal that the study region (Jaipur) is mostly characterized by westerly or south-westerly winds in summer. These winds pass through the Thar desert which is situated at the western edge of Jaipur. In general, temperature diurnal amplitude is found to be much higher during the pre-monsoon season than during the remaining of the year. The average surface temperature of about 25–30°C occurs during summer (Fig. 1) with maximum temperature reaching 48°C as observed on 14th June, 2010 during our study period. In winter, December and January are typically the coldest months with mean surface temperatures of (10–15°C) but the minimum temperature can reach 2°C as observed on 18th January, 2012. The average precipitation for the study period is 56.4 mm (with a maximum of ~60 mm).

Methods

The Cimel Sun photometer at Jaipur belonging to the AERONET program provides aerosol optical thickness (τ) at seven spectral bands between 340 and 1020 nm. The τ derived at 500 nm (τ500) and the Angstrom Exponent (α) calculated at wavelengths between 440 and 870 nm are used in present study since they represent the most optically stable wavelengths, particularly at low optical depths (Smirnov et al., 1996; Holben et al., 2001).

All the measurement sequence and data processing are carried out within AERONET protocols. Direct sun measurements performed by CIMEL were cloud-screened with the AERONET standard cloud-screening algorithm (Smirnov et al., 2000). Absolute error for τ retrieval with the Cimel sun photometer is 0.01–0.02 (Holben et al., 1998; AERONET web page). The details of the instrument, method of analysis and errors are discussed earlier in detail by several investigators (Holben et al., 1998 and references therein; Smirnov et al., 2000).


a) b)

Fig. 1. Prevailing synoptic meteorological conditions over India in a) summer and b) winter seasons using NCEP/NCAR data for winds and temperature at 850 hPa during the period 2009–2012.

The AERONET data from April 2009 to March 2012 were analyzed in this study. The aerosol types are determined on the basis of combination of τ and α information following Kaskaoutis et al. (2009). CIMEL sun/sky radiometer Level 2.0 daily data of τ500 and α at 440 and 870 nm have been used to represent the dominant aerosol size modes at Jaipur. The 440–870 nm band was selected as it provides information on the relative influence of coarse versus fine mode aerosols (Reid et al., 1999). Single Scattering Albedo (SSA) has also been used to compare the aerosol absorption/ scattering to distinguish absorbing from non-absorbing aerosols at four more AERONET locations (Gual Pahari (28.43°N, 77.15°E, 384 m asl), Kanpur (26.51°N, 80.23°E, 123 m asl), Gandhi College (25.87°N, 84.13°E, 60 m asl) and Pune (18.54°N, 73.80°E, 559 m asl) in India. The AERONET data with 15-minute temporal resolution are used to produce aerosol types in subsequent analyses.

Climatological and statistical analyses of τ and α daily mean values were performed to characterize the aerosol columnar properties. Based on the seasonality of aerosol properties studied previously (Prakash et al., 2013; Verma et al., 2013), five major types of aerosols are categorized and listed in Table 1. RESULTS AND DISCUSSION

The results obtained from the measurements of spectral sun and sky radiances over Jaipur are presented in this section. From the concept of aerosol classification, data products associated with α and τ from AERONET are used to classify aerosol types. Long-Term Characteristics of the Aerosol Optical Depth

Fig. 2 illustrates the daily averaged aerosol optical depth

at 500 nm for the three year record (2009–2012) at Jaipur representing cloud-free days. Daily average values of τ500 show very large day-to-day variations (ranging from 0.07 to 1.9). The yearly average value of τ500 is about 0.45 ± 0.21. The monthly average τ500 values are observed to be generally higher (0.62) in summer than in winter (0.15) (Verma et al., 2013) with some sporadic high values during the pre-monsoon (dust dominant) season and the winter periods. Climatologically and Statistical Analysis

The frequency distribution for τ at 440 (τ440) and 870 nm (τ870) is presented in Fig. 3 together with α. This graph shows the relative frequency of all available level 2 data. The frequency distribution of τ440 for the 3-year period has a yearly average of 0.48 ± 0.29. The maximum relative frequency of τ870 and τ440 is found between 0.2–0.3 and 0.4–0.5, respectively. Values of τ870 and τ440 less than 0.5 represent 88 and 63 % of total observations, respectively. For longer wavelengths, the histograms are narrower and the data move to lower τ, as do the frequency maxima: 0.4 at 440 nm and 0.2 at 870 nm. The τ distribution is unimodal while the α distribution is bimodal. Also, the frequency distribution of τ870 for the 3-year period has a yearly average of 0.328 ± 0.18. It denotes that coarser particles are more pristine (less attenuation of incident light) than finer particles because τ less than 0.5 has more contribution at 870 nm than at 440 nm.

Thus two main aerosol scenarios are present at the site. The first one, with low α near 0.3 at 870 nm, corresponds to coarser aerosols at the station, and it can be labeled as arid background aerosol. Additionally, a number of high turbidity episodes are present, with sharp peaks near 0.5 at 440 nm, lasting several days.

Similarly, the frequency histogram of α is presented in Fig. 3 and shows two different frequency modes, bimodal


Table 1. Threshold values of Aerosol Optical Thickness (τ500) at 500 nm and Angstrom Exponent (α) in various wavelength ranges for different aerosol types.

LOCATION τ500 α Type of aerosol References Hyderabad > 0.50

> 0.60 α380–870 < 1.0 α380–870 < 0.70

Urban/Industrial Desert Dust

Kaskaoutis et al. (2009)

Dibrugarh < 0.20 > 0.45

α380–1025 < 1.4 α380–1025 < 0.7

Continental Average Desert dust

Pathak et al. (2012)

Jaipur > 0.45 < 0.40 > 0.45

< 0.4 < 0.4 > 1.2

1 < α > 0.4

Desert Dust (DD) Marine (MR) Biomass (BB)

Arid Background (AB)

Present Study

Fig. 2. Daily averaged Aerosol Optical Thickness (τ over the period 2009–2012 from AERONET over Jaipur, India.

Fig. 3. Relative frequency distribution of τ and α over the period 2009–2012 from AERONET over Jaipur, India.

mode. The maximum relative frequencies are found in the ranges 0.2–0.3 and 1.2–1.4. The first and principal mode is centered at 0.3, and the second one at 1.3. Both modes have a normal distribution and overlap for α values around 0.8. So, the mean value (0.8) is the result of two different populations, but does not represent any of them. The bi-modal frequency distribution for α shows that 60% of the year the aerosol particles are of arid background (τ < 1) clearly indicating that Jaipur is a coarse particle dominant station.

Identification of Aerosols Types The Jaipur city, location of the present study, represents

an urban environment but relatively more influenced by nearby dust source region and less influenced by industrial activities.

We propose here a realistic characterization of the aerosol types using the relationship between τ and α because of their strong wavelength dependence. These τ patterns have been observed at several locations and for different aerosol


types (e.g., biomass smoke, anthropogenic aerosols, desert dust) (Masmoudi et al., 2003; Kim et al., 2004; Ogunjobi et al., 2004; Eck et al., 2010). Different aerosol types have been identified earlier over Indian landmass surrounding the oceanic regions e.g. over the Arabian Sea (Kalapureddy et al., 2009) and over the Bay of Bengal (Kaskaoutis et al., 2011) by relating aerosol load (i.e., τ500 and α).

Using the τ versus α cluster analysis approach, a detailed spectral information is derived in different pairs of wavelengths for discriminating between the different aerosol types (Eck et al., 1999; Cachorro et al., 2001; Pace et al., 2006; Kalapureddy et al., 2009; Kaskaoutis et al., 2011; Pathak et al., 2012). We thus performed a 2-dimensional binning of τ500 vs. α, which is presented in Fig. 4. When τ is low, α covers the whole range of values (0–2), mainly concentrated in a region around 0.5–1.5. For the highest values of τ500, the situation is clearer; α shows 2 maxima at ~0.1, and ~1.2. The study of this plot reveals the presence of different aerosol types, as we describe below.

Over Jaipur, the average τ500 is 0.44 which depicts an almost pristine atmosphere. The average α is 0.64 which shows the dominance of coarse particles. Furthermore, the source of these coarse particles is inferred from back-trajectory analyses which indicate that air masses originated from the Thar Desert (Verma et al., 2013) via transport pathways. Thus the dust aerosol type is assumed to be present as additional background aerosols named as arid background (AB). The dust originated by the action of wind, particularly in western deserts including the coarse mode aerosols are labeled as Desert Dust (DD). These two types are discriminated consistently with the earlier study of Kalapureddy et al. (2009) over the Arabian Sea, Kaskaoutis et al. (2009) over Hyderabad and Kaskaoutis et al. (2011) over the Bay of Bengal. The criteria followed for distinguishing aerosol types over Jaipur are listed in Table 1. The threshold values 1) for DD are τ500 > 0.45 and α < 0.4 and 2) for AB are when α is comprised between 0.4 to 1.0. Note that we have used lower α for DD than that considered

over the Dibrugarh area by Pathak et al. (2012). Dibrugarh is far from the dust origin and coarse particles may deposit by the gravitational settling so that α value is much larger over Dibrugarh than over Jaipur. In addition, marine aerosols are defined when τ500 < 0.4 and α < 0.4 with industrial/ biomass burning when τ500 > 0.45; α > 1.2. The remaining aerosols are considered as undetermined or mixed type (MT) (Pace et al., 2006; Pathak et al., 2012). Relative Contribution

Fig. 5 shows the relative contribution of each of the five different aerosol types in the Jaipur region depending on the seasons (summer/winter) and overall data. Considering all the seasons, arid Background and Desert Dust type aerosols are the most common at Jaipur (34.7% and 13.6% of the cases, respectively), with a wide variability in both τ and α. Only in about 8.4% of the cases can aerosol be classified as maritime. However, mixing with other aerosol (33.6%) is also substantial. This indicates that the aerosols transported over Jaipur are composed of both fine and coarse particles. The highest values in mixed aerosols are attributed to the anthropogenic aerosols, which are identified in the present study.

In Figs. 5(b) and 5(c), we further separate the aerosol data into summer and winter seasons, respectively. The relative contributions of the aerosols are found to show significant dependence on the seasonal variations. The relative contribution during the winter period indicates a clear dominance of anthropogenic aerosols as mixed type (73%) whereas, during the summer season, dust aerosols (49%) represent the major fraction.

Comparative Analysis

The types of anthropogenic aerosols and their distribution are rather complex over Jaipur due to a large variety of sources with respect to location and season. Four more AERONET sites were selected for the present analysis based on the availability of an extensive dataset and the geographic

Fig. 4. Scatter plot diagram of τ500 versus α for the five aerosol types over Jaipur: Marine (MR) (blue crosses), Industrial/biomass burning (BB) (black crosses), desert dust (DD) (purple crosses), Arid Background (AB) (green crosses) and mixed type (MT) (red crosses).


(a) All Seasons

(b) Summer

(c) Winter

Fig. 5. Relative contribution of different aerosol types in the Jaipur region for (a) all the seasons, (b) summer and (c) winter for the study period: Marine (MR) (blue sectors), Industrial/biomass burning (BB) (black sectors), desert dust (DD) (purple sectors), Arid Background (AB) (green sectors) and mixed type (MT) (red sectors).

distribution among aerosol source regions over India (Fig. 1): Gual Pahari, Kanpur, Gandhi College and Pune. Dominant τ is investigated during the winter and the summer seasons for four AERONET stations throughout India as shown in Fig. 6. This comparison shows the seasonality and the general magnitude of τ at the different sites. As the dust absorption characteristics can differ depending on the extent of mixing with other constituents (such as black carbon (BC) for example) and as this would be different for different seasons (depending on the wind pattern, dust abundance, BC abundance, and so on), we examined the above association separately for two seasons: April, May and June (AMJ) for summer and December–January (DJ) for winter, when our databases contain a significant number of measurements. The results are shown in Fig. 6. High τ (~0.8) at low wavelengths (300–500 nm) in summer suggests that the western and

northern parts of India (Jaipur) are affected by dust from the Arabian Peninsula and from the north-eastern part of India in AMJ.

The refractive index estimated at visible and near-infrared wavelengths (Table 2) is used to account for the nature of atmospheric aerosols to be compared with other AERONET sites located in India based upon their geographical distribution and extensive data availability. If we consider the imaginary refractive index at all wavelengths, the Jaipur station shows less absorption compare to any other stations in the whole study period. This clearly means that black carbon is less available in this site than in any other sites considered in our study over India.

Simultaneously, the Single Scattering Albedo (SSA) of dust is also inferred for all the considered sites. All available data during the summer (AMJ) and the winter (DJ) seasons are used from 2009 to 2012 for comparison amongst all the stations and shown in Figs. 7(a) and 7(b), respectively. The weighted average of summer season data (Fig. 7(a)) is used which shows clear higher SSA values at Jaipur for all wavelengths than SSA values at all the other stations. The spectral shape exhibits a steep spectrum of increasing SSA values with increasing wavelengths for greater dust loading conditions while a relatively less pronounced SSA spectrum is found in case of background aerosols condition. Lower SSA at shorter wavelengths (i.e., SSA = 0.89 at 440 nm and relatively higher values at longer wavelengths SSA = 0.96 at 1020 nm) indicates high dust loading over the region. For winter season, the data is not available at Gandhi College. At Gual Pahari, data is only available for December and January. Consequently, due to unavailability of data, we can compare the weighted average with other stations for December–January. During winter (Fig. (7b)), the value of SSA over Jaipur is found higher at all wavelengths except at 440 nm than over all the other stations. Increase in SSA is thus due to the abundant dust loading in the region, that can be attributed to the scattering state of the atmosphere.

The comparative analysis of the Jaipur site with other sites over India suggests that Jaipur desert background is more scattering in nature than Northern and western regions with an absorption less in summer than in winter. The Jaipur area has less industrial activity than the Kanpur, Gual Pahari and Pune areas. Because the atmosphere is more stable in winter than in summer, the pollution contribution is mainly local in winter over Jaipur. In summer, the prevailing winds are westerly. As Jaipur is situated west side of the Indo Gangetic Plain which has an industrial belt and is thus polluted, the Jaipur area is consequently less affected by pollution due to transport than the three other areas. CONCLUSIONS

Jaipur is the first AERONET site in the Northwestern India. The average Angstrom coefficient α is 1.05 (± 0.43), indicating a mixed aerosol type during winter. The different aerosol types present at Jaipur have been classified based on the relationship between aerosol optical thickness τ and α. The availability of more spatial ground-based observations together with the aerosol classification has an immense


(a) (b)

Fig. 6. Comparision of Aerosol Optical Thickness (τ500) at 500 nm for the 5 AERONET sites in India during a) summer and b) winter for the period 2009–2012: Gual Pahari (light blue line), Kanpur (dark blue line), Gandhi College (dark pink line), Pune (yellow line) and Jaipur (light pink line).

Table 2. Yearly averaged of Real (REFR) and Imaginary (REFI) parts of Refractive Index at all wavelengths.

Sites REFR (440)

REFR (674)

REFR (870)

REFR (1020)

REFI (440)

REFI (674)

REFI (870)

REFI (1020)

Kanpur 1.4634 1.4959 1.5064 1.4989 0.0100 0.0079 0.0071 0.0071 Gual Pahari 1.4996 1.5307 1.5375 1.5326 0.0123 0.0105 0.0085 0.0079

Pune 1.4636 1.4813 1.5095 1.5094 0.0170 0.0148 0.0151 0.0156 Jaipur 1.4650 1.5005 1.5058 1.4998 0.0077 0.0067 0.0057 0.0057

(a) (b)

Fig. 7. Same as Fig. 6 but for Single Scattering Albedo (SSA).

importance as it helps to quantify the radiation budget and its impact on the Earth climate. Two modes around 1.2 and 0.5 in the frequency histogram of α have been found: 1) one is related to the ordinary situation with mixed marine aerosols, and 2) the other one is linked to the low α values during the desert dust events. The Arid background aerosols are predominant, with 35% of occurrence, and in general they are mixed with continental or local-pollution aerosols. The desert-dust outbreaks reaching the south-western Jaipur, which are more frequent during the pre-monsoon months, have a clear impact on the seasonal pattern of τ and have an occurrence around 50% at Jaipur.

The single scattering albedo of dust is also inferred for all the available AERONET sites for the same period over India. The comparative analysis with all the other sites suggests that, in Jaipur, arid background is more scattering in nature than Northern and Western regions in India. Finally, the absorption is less in summer than in winter over the Jaipur site. ACKNOWLEDGMENTS

This work is supported through research project under DST-IGBP program. We appreciate the efforts of AERONET


team, especially Brent Holben and Ilya Slutsker for maintaining the Jaipur AERONET site. Authors thank NCEP Reanalysis data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/ in. Authors also thank the Director, BIT/BISR, for constant encouragement and support. We would like to thank the editor and the anonymous reviewer(s) to provide useful suggestions that has indeed improved overall clarity of the manuscript substantially. REFERENCES Cachorro, V.E., Vergaz, R. and De Frutos, A.M. (2001). A

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Received for review, July 25, 2014

Revised, October 6, 2014 Accepted, December 23, 2014

a new classification of aerosol sources and types as ...properties over jaipur in north-western...

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