Inferring aerosol types over the Indo-Gangetic Basin from ground based sunphotometer measurements

Srivastava, Atul; Tripathi, Sachchida Nand; Dey, Sagnik; Kanawade, Vijay P.; Tiwari, Suresh

doi:10.1016/j.atmosres.2012.02.010

Cited by 99 publications

(60 citation statements)

References 76 publications

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“…The same is seen at Gandhi College, but AOD is higher, showing that both sites differ in aerosol loading (Srivastava et al, 2012). Nainital shows an increase in winter but AOD is low as compared to the other two stations.…”

Section: Resultssupporting

confidence: 59%

“…These three sites are entirely different with regard to aerosol climatology, land type, atmospheric condition, etc. (Srivastava et al, 2012). Kanpur is an extremely polluted and urban site (Tripathi et al, 2005b;Giles et al, 2011), Gandhi College (Srivastava et al, 2011) is a rural site, and Nainital (Dumka et al, 2011) is a relatively clean site.…”

Section: Introductionmentioning

confidence: 99%

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Study of MODIS derived AOD at three different locations in the Indo Gangetic Plain: Kanpur, Gandhi College and Nainital

Choudhry

Misra²,

Tripathi³

2012

Ann. Geophys.

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Abstract. Moderate resolution imaging spectroradiometer (MODIS) sensors, onboard Terra and Aqua, have been observing the Earth since start of 2000 and mid 2002, respectively. The present study provides a comparison of Collection 5 (C005), aerosol optical depth (AOD) retrieved by MODIS, with AERONET-observed AOD over Kanpur (an urban site), Gandhi College (a rural site) and Nainital (a relatively clean site) in the Indo Gangetic Plain (IGP). The results show that at Kanpur, MODIS retrievals are well within the prelaunch uncertainty ± 0.05 ±0.15 τ , and a good correlation (R 2 > 0.7 for both Terra and Aqua). Nainital also shows good retrieval (R 2 > 0.8 for Terra and R 2 > 0.68 for Aqua), as more than 66 % of total collocations are within the prelaunch uncertainty. However, it is seen that there is significant overestimation in this case, especially in the months of winter. Gandhi College poses a challenge to MODIS retrieval, as here <57 % of MODIS-retrieved AOD values lay within the prelaunch uncertainty and the correlation is very poor (R 2 ∼ 0.5 for Aqua and R 2 ∼ 0.4 for Terra); also there is persistent underestimation in this case. Small value of slope shows that assumed model results in underestimation, and large intercept values for the linear regression fit show that errors due to surface reflectance are high here. Our comparison shows that MODIS retrieval works well over Kanpur, and Nainital with winter as an exception. However, MODIS retrieval is poor for Gandhi College which is a rural area. The aerosol properties at Kanpur are currently used as representative of the entire subcontinent in the MODIS C005 algorithm, which is not an accurate assumption. The large variability in land use and climate over India makes it a site too complex for a single aerosol model to be used over the entire area. Therefore further study with as many sites as possible over the Indian subcontinent would help provide more realistic modeling for the Indian subcontinent.

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Section: Resultssupporting

confidence: 59%

Section: Introductionmentioning

confidence: 99%

Study of MODIS derived AOD at three different locations in the Indo Gangetic Plain: Kanpur, Gandhi College and Nainital

Choudhry

Misra²,

Tripathi³

2012

Ann. Geophys.

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“…For example, Bellouin et al (2005) have separated the anthropogenic and natural aerosols based on the accumulation mode fraction threshold values. A combination of accumulation mode fraction and single scattering albedo (SSA) was utilized by Srivastava et al (2012) to infer the dominant aerosol types in the Indo-Gangetic Basin. Another popular way to infer about dominant aerosol types includes analysis of τ and Angstrom Exponent (e.g.…”

Section: Introductionmentioning

confidence: 99%

Inter‐annual variations in natural and anthropogenic aerosol loadings over the seas adjoining India using a hybrid approach

Das

Dey

Dash

2013

Atmospheric Science Letters

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We report the inter-annual variations of natural and anthropogenic aerosol loading over the Arabian Sea (AS) and Bay of Bengal (BoB) for the period 2001-2010 using a hybrid approach. Mean (±1 standard deviation) decadal contributions of maritime, dust and anthropogenic aerosols to aerosol optical depth, τ are 16.6 ± 4.2 and 17.5 ± 4.6%, 44.3 ± 22.6 and 37.4 ± 20% and 39 ± 23.4 and 45 ± 20.5%, respectively, over the AS and BoB. Significant increase in τ (>0.007 or 2.3% per year) is mainly driven by anthropogenic aerosols. The results can be used for improved estimates of aerosol radiative forcing in these regions.

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“…The Sunphotometer takes measurements of the direct-beam radiances within the spectral range 340-1020 nm. Typically, the total uncertainty in spectral AOD is about ± 0.01 to ± 0.02, and is spectrally dependent with the higher errors in the UV band (Srivastava et al, 2012). The calibration accuracy becomes an obstacle because it causes an error in measuring AOD (± 0.01) that is at least of the order of 5-10% of the calculated optical depth for AOD 440 < 0.2, and comparable with the absorption partition in the total optical depth (Dubovik et al, 2002).…”

Section: Aeronet Instrumentationmentioning

confidence: 99%

“…They have significance at local, regional and global scales and have received prominent attention in the past few years (Penner et al, 1994;Seinfeld and Pandis, 2006). The climatic and environmental effects of atmospheric aerosols are the critical issues in global science community because aerosols, derived from natural and anthropogenic emission sources, are well known to affect the air quality, human health, and radiation budget (IPCC, 2007, Srivastava et al, 2012. Uncertainty in quantifying the climatic impacts of aerosols continues to be greater than that of greenhouse gases (IPCC, 2007) due to variety of their sources, varying trends in aerosol loading and extreme heterogeneity in the spatial and temporal variability of their optical and microphysical properties (Morgan et al, 2006;Kaskaoutis et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Identification and Classification of Different Aerosol Types over a Subtropical Rural Site in Mpumalanga, South Africa: Seasonal Variations as Retrieved from the AERONET Sunphotometer

Kumar

Sivakumar

Reddy

et al. 2014

Aerosol Air Qual. Res.

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This paper reports the observational results of aerosol optical characteristics, modification processes and discrimination of key aerosol types over Skukuza (24.9°S, 31.5°E, and 150 m), a subtropical rural site in South Africa (SA), using CIMEL Sunphotometer data, part of the AErosol RObotic NETwork (AERONET), from December 2005 to November 2006. The results show that a pronounced spectral and temporal variability in the optical properties of aerosols is mainly due to anthropogenic emissions. The discrimination of different aerosol types over Skukuza is also made using the daily mean values of aerosol optical depth at 500 nm (AOD 500 ) and Ångström exponent (α ) by applying the threshold values. The results of the analysis indentified three individual components (biomass burning/urban (BU), desert dust (DD) and clean maritime (CM) aerosol types) of differing origin, composition and optical characteristics, and revealed that the percentage contribution of each of type of aerosol changed significantly from season to season. We also derived the curvature of a 2 in an attempt to obtain information on aerosol-particle size and type, although the results revealed that the curvature alone is not enough to achieve this. In addition,, we analyzed the seasonal changes in aerosol characteristics using the classification scheme introduced in Gobbi et al. (2007) based on the measured scattering properties (α, dα) derived from the Sunphotometer data. The results show that during spring an extremely large fraction of fine-mode aerosols (η > 70%, R f ~0.1 µm) in the turbid atmosphere was mainly caused by local anthropogenic pollution or biomass aerosol transported from forest fires. Whereas in summer, the low AOD (< 0.2) and smaller α (< 1.0) and η < 50% suggest the influence of transported mineral dust (coarse) over the region.

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Inferring aerosol types over the Indo-Gangetic Basin from ground based sunphotometer measurements

Cited by 99 publications

References 76 publications

Study of MODIS derived AOD at three different locations in the Indo Gangetic Plain: Kanpur, Gandhi College and Nainital

Study of MODIS derived AOD at three different locations in the Indo Gangetic Plain: Kanpur, Gandhi College and Nainital

Inter‐annual variations in natural and anthropogenic aerosol loadings over the seas adjoining India using a hybrid approach

Identification and Classification of Different Aerosol Types over a Subtropical Rural Site in Mpumalanga, South Africa: Seasonal Variations as Retrieved from the AERONET Sunphotometer

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