Features in wavelength dependence of aerosol absorption observed over central India

Ganguly, Dilip; Jayaraman, A.; Gadhavi, Harish; Rajesh, T. A.

doi:10.1029/2005gl023023

Cited by 46 publications

(42 citation statements)

References 23 publications

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“…The M BC reported by us was measured at a wavelength of 880 nm. The reason for this choice was that the BC is the principal absorber at this wavelength (Ganguly et al, 2005). The sample flow rate to the aethalometer was 3 L/min at a scan time of 5 minutes.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Diurnal and Seasonal Variation of Submicron Outdoor Aerosol Mass and Size Distribution in a Northern Indian City and Its Correlation to Black Carbon

Baxla

Roy

Gupta

et al. 2009

Aerosol Air Qual. Res.

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The seasonal and diurnal behavior of atmospheric submicron aerosol was studied in the northern Indian city of Kanpur in the Indo Gangetic Plain during July 2006-May 2007. The size distribution and mass concentration of the aerosol in the range of 15-700 nm was measured using a scanning mobility particle sizer (SMPS). Simultaneously, black carbon (BC) measurement was made using an aethalometer. The measurements were recorded for four different seasons, viz. monsoon, post-monsoon, winter and pre-monsoon. The diurnal variation of BC and submicron aerosol mass followed very similar trends in all the seasons. This is evident by the fact that BC had strong positive correlation with the submicron aerosol mass (0.83 ≤ R ≤ 0.96, where R is the Pearson's correlation coefficient). Both peaked once in the morning [07:00-09:00 local time (LT)], and once in the night (20:00-22:00 LT). The peak concentrations varied from season to season, which could be attributed to seasonal variation in anthropogenic activity, traffic movement and atmospheric boundary layer conditions. The background aerosol number concentration in winter (~10 5 #/cm 3 ) was an order of magnitude higher than that observed in other seasons (~10 4 #/cm 3 ); and on a foggy day in the winter, it was twice as high as that seen on a clear winter day. The fraction (F BC ) of the BC mass concentration in the submicron aerosol was observed to be highest in monsoon (0.18 ± 0.13), followed by pre-monsoon (0.08 ± 0.02) and post-monsoon (0.05 ± 0.01), with the lowest in winter (0.03 ± 0.01).

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Section: Methodsmentioning

confidence: 99%

Analysis of Diurnal and Seasonal Variation of Submicron Outdoor Aerosol Mass and Size Distribution in a Northern Indian City and Its Correlation to Black Carbon

Baxla

Roy

Gupta

et al. 2009

Aerosol Air Qual. Res.

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“…The spectral dependence of absorption (i.e., AAE) depends upon particle size and the imaginary refractive index, and excellent overviews of the relationship between AAE and aerosol microphysics are provided by Moosmüller et al (2009Moosmüller et al ( , 2011. Generally, AAE is obtained from photoacoustic measurements (Lewis et al, 2008;Chow et al, 2009;Gyawali et al, 2009;Flowers et al, 2010;Lack et al, 2012b;Chakrabarty et al, 2013;Utry et al, 2014), particle soot absorption photometer measurements (Roden et al, 2006), aethalometer measurements (Ganguly et al, 2005), the solar-flux-AOD technique (Russell et al, 2010), integrating plate methods (Schnaiter et al, 2003), differencing extinction and scattering coefficients , or aerosol robotic network (AERONET) retrievals (Bahadur et al, 2012;Chung et al, 2012b;Giles et al, 2012;Cazorla et al, 2013;Xu et al, 2013;Russell et al, 2014).…”

Section: G L Schuster Et Al: Understanding the Aae For Remote Sensmentioning

confidence: 99%

Remote sensing of soot carbon – Part 2: Understanding the absorption Ångström exponent

et al. 2016

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Abstract. Recently, some authors have suggested that the absorption Ångström exponent (AAE) can be used to deduce the component aerosol absorption optical depths (AAODs) of carbonaceous aerosols in the AERONET database. This AAE approach presumes that AAE 1 for soot carbon, which contrasts the traditional small particle limit of AAE = 1 for soot carbon. Thus, we provide an overview of the AERONET retrieval, and we investigate how the microphysics of carbonaceous aerosols can be interpreted in the AERONET AAE product. We find that AAE 1 in the AERONET database requires large coarse mode fractions and/or imaginary refractive indices that increase with wavelength. Neither of these characteristics are consistent with the current definition of soot carbon, so we explore other possibilities for the cause of AAE 1. AAE is related to particle size, and coarse mode particles have a smaller AAE than fine mode particles for a given aerosol mixture of species. We also note that the mineral goethite has an imaginary refractive index that increases with wavelength, is very common in dust regions, and can easily contribute to AAE 1. We find that AAE 1 can not be caused by soot carbon, unless soot carbon has an imaginary refractive index that increases with wavelength throughout the visible and near-infrared spectrums. Finally, AAE is not a robust parameter for separating carbonaceous absorption from dust aerosol absorption in the AERONET database.

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“…For example, Gadhavi and Jayaraman (2010) showed that the spectral dependence of absorbing aerosols can reduce the radiative forcing at top of the atmosphere by about 8%. Over the locations in the central India, Ganguly et al (2005a) found varying nature of composition and sources of absorbing aerosols. Further, they reported up to 30% of excess absorption by absorbing aerosols coming mainly from biofuel burning used for cooking.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Aerosol Products Retrieved from AERONET, MICROTOPS and MODIS over a Tropical Urban City, Pune, India

Kumar

Gupta

et al. 2013

Aerosol Air Qual. Res.

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Aerosol Optical Depth (AOD) measurements from Aerosol Robotic NETwork (AERONET; level 2.0), Microtops -II sun-photometer and MODerate Resolution Imaging Spectroradiometer (MODIS) (Terra and Aqua; level 2, collection 5, dark target) were compared and used to characterize aerosols over Pune, India. AODs from Microtops and MODIS were compared with those measured by AERONET to evaluate the measurement quality. To the best of our knowledge, this is the first systematic comparison of MODIS aerosol products over Pune, India. The results of the analysis show that during 2008-10, 68% to 84% of the MODIS AODs fell within an expected error, as defined by the MODIS science team, and thus the retrievals from this system are validated and accepted. In addition, during pre-monsoon periods MODIS retrievals are better-matched with ground-based measurements. On the seasonal scale, MODIS retrievals corroborate well with ground-based measurements, with correlation coefficients ranging from 0.62 to 0.93. Despite an overall satellite-ground agreement, MODIS tends to under-estimate AOD during winter, and this may be due to improper assumptions of surface reflectance and the incorrect selection of aerosol types. AERONET retrieved single scattering albedo (SSA) values in winter (0.82-0.86), suggesting the dominance of absorbing aerosols, slightly increased (0.87-0.89) in pre-monsoon season, indicating more scattering type of aerosols. These values are about 8.9%-1.1% lower than those of the assumed SSA values in the MODIS algorithm.

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Features in wavelength dependence of aerosol absorption observed over central India

Cited by 46 publications

References 23 publications

Analysis of Diurnal and Seasonal Variation of Submicron Outdoor Aerosol Mass and Size Distribution in a Northern Indian City and Its Correlation to Black Carbon

Analysis of Diurnal and Seasonal Variation of Submicron Outdoor Aerosol Mass and Size Distribution in a Northern Indian City and Its Correlation to Black Carbon

Remote sensing of soot carbon – Part 2: Understanding the absorption Ångström exponent

Comparison of Aerosol Products Retrieved from AERONET, MICROTOPS and MODIS over a Tropical Urban City, Pune, India

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