Characteristics of aerosol optical depth and Ångström parameters over Mohal in the Kullu Valley of Northwest Himalayan Region, India

Sharma, Nand Lal; Kuniyal, Jagdish Chandra; Singh, Mahavir; Sharma, Manum; Guleria, Raj Paul

doi:10.2478/s11600-010-0046-1

Cited by 7 publications

(5 citation statements)

References 42 publications

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“…The monsoon season (July to September) also receives heavy rain. While the autumn season (October to November) characterised with average temperature and unusual and torrent rainfall (Kuniyal et al 2007;Sharma et al 2011).…”

Section: Site Description and General Meteorologymentioning

confidence: 99%

Five years surface ozone behaviour in a semi-rural location at Mohal-Kullu in the north-western Himalaya, India

Kuniyal¹,

Choudhary²,

Sharma³

2021

Preprint

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Surface ozone is one of the most important Green House Gases (GHGs). Five years (2011–2015) measurements of surface ozone (O3) and one of its precursors- oxides of nitrogen (NOx) were carried out at a semi-rural location, Mohal (77.12°E, 31.91°N, 1154 m amsl) in the north-western Indian Himalaya. The concentration of O3, NO, NO2 and NOx was measured maximum 74.6 ± 23.2 ppb in 2013, 27.5 ± 7.5 ppb in 2013, 51.8 ± 13.2 ppb in 2013, and 60.8 ± 13.2 ppb in 2012, respectively. Seasonally, O3 concentration was highest during summer while lowest in monsoon. The O3 concentration shows unimodal peak while its precursors show bimodal peaks. A reasonable decrease in percent change was found in terms of O3 (-13), NO2 (-6), and NOx (-3) due to imposing regulations imposed by local government in compliance with the order of Hon’ble National Green Tribunal (NGT) of the country in 2015. However, NO (9) is increasing due to vehicular activities in the nearby area which is one of the famous tourist spots. Washout effect due to increasing rainfall by 8% might have also affected O3 concentrations. Biomass burning for heating and cooking purposes and forest fire for tender livestock forage and transported gaseous pollutants from the Middle East countries and Indo-Gangetic Plain (IGP) could be major contributors of surface ozone and its precursors. HYSPLIT air-mass back trajectories drawn for external ozone sources showed the maximum air masses reached the study location either with the western desert countries or IGP polluted regions.

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Section: Site Description and General Meteorologymentioning

confidence: 99%

Five years surface ozone behaviour in a semi-rural location at Mohal-Kullu in the north-western Himalaya, India

Kuniyal¹,

Choudhary²,

Sharma³

2021

Preprint

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“…The validity of theÅngström Power Law is stated after Junge Power Law (Junge 1955) for a limited range of particles, where significant extinction takes place and the spectral variation of the refractive index does not impose any significant variations on the Mie extinction factor . For more details of α and β and its computation techniques, see Bhuyan et al (2005); Gogoi et al (2008) and Sharma et al (2011).…”

Section: 2ångström Exponent (α) and Turbidity Coefficient (β)mentioning

confidence: 99%

“…Spectral aerosol optical depth (AOD, τ pλ ) contains information pertaining to ASD and is used to computeÅngström exponent (α) and turbidity coefficient (β) usingÅngström Power Law (Schuster et al 2006;Kaskaoutis et al 2007Kaskaoutis et al , 2010Gogoi et al 2008;Kedia and Ramachandran 2009;Sharma et al 2010Sharma et al , 2011.Ångström exponent is a quantitative indicator of the ASD and the turbidity coefficient is a measure of total aerosol loading in a vertical column (Schuster et al 2006;Gogoi et al 2008;Kedia and Ramachandran 2009;Kaskaoutis et al 2010;Sharma et al 2011). In general,Ångström Power Law is applicable to the entire wavelength spectrum, only if the ASD fits to the Junge Power Law (Kedia and Ramachandran 2009).…”

Section: Introductionmentioning

confidence: 99%

Seasonal variability in aerosol optical and physical characteristics estimated using the application of the Ångström formula over Mohal in the northwestern Himalaya, India

et al. 2012

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Investigations of aerosol optical and physical characteristics using the application ofÅngström formula and second order polynomial fit were carried out from April 2006 to March 2009 at Mohal in the Kullu valley. The measurements of spectral aerosol optical depths (AODs) were conducted using multiwavelength radiometer (MWR). The AOD at 0.5 μm wavelength on daily basis (mean ± standard deviation) for the entire three-year study period is obtained as 0.24 ± 0.08. Seasonal variations show the highest AOD at 0.5 μm wavelength with ∼0.34 ± 0.08 during pre-monsoon (April-July), followed by ∼0.26 ± 0.08 during monsoon (August-September), ∼0.21 ± 0.05 during post-monsoon (October-November) and ∼0.20 ± 0.07 during winter (December-March). The seasonal values indicate that the AOD at 0.5 μm wavelength is decreasing from pre-monsoon to winter with a notable reduction around 41%. TheÅngström parameters using least square method is not found appropriate for size distribution particularly when coarse mode aerosols dominate. The coefficients of second order polynomial fit are more appropriate for the discrimination of aerosol size or irrespective to the dominance of either of the aerosols size. The difference in coefficient of polynomial fit is used to get confirmation on the dominant mode during different seasons. Study reveals that about 93%, 72% and 59% of AOD spectra are dominated by a wide range of fine mode fractions or mixture of modes during post-monsoon, winter and monsoon, respectively. On the other hand, during pre-monsoon, 72% of AOD spectra are found to be dominated by coarse mode aerosols.

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“…The use of aerosol optical depth (AOD) to describe aerosol size distribution has not been faulted because it contains information pertaining to aerosol size distribution, Angstrom exponent -qualitative indicator of aerosol distribution and turbidity coefficientaerosol loading indicator in vertical column (Sharma et al, 2011;Nnaemeka et al, 2015;Emetere Moses et al, 2015). The qualitative indicator with Angstrom exponent values greater than 2 indicates small particles associated with combustion byproducts while values less than 1 indicates large particles like sea salt and dust (Schuster et al, 2006a,b).…”

Section: Introductionmentioning

confidence: 99%

Parametric retrieval model for estimating aerosol size distribution via the AERONET, LAGOS station

Emetere

Akinyemi

Akin-Ojo

2015

Environmental Pollution

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The size characteristics of atmospheric aerosol over the tropical region of Lagos, Southern Nigeria were investigated using two years of continuous spectral aerosol optical depth measurements via the AERONET station for four major bands i.e. blue, green, red and infrared. Lagos lies within the latitude of 6.465°N and longitude of 3.406°E. Few systems of dispersion model was derived upon specified conditions to solve challenges on aerosols size distribution within the Stokes regime. The dispersion model was adopted to derive an aerosol size distribution (ASD) model which is in perfect agreement with existing model. The parametric nature of the formulated ASD model shows the independence of each band to determine the ASD over an area. The turbulence flow of particulates over the area was analyzed using the unified number (Un). A comparative study via the aid of the Davis automatic weather station was carried out on the Reynolds number, Knudsen number and the Unified number. The Reynolds and Unified number were more accurate to describe the atmospheric fields of the location. The aerosols loading trend in January to March (JFM) and August to October (ASO) shows a yearly 15% retention of aerosols in the atmosphere. The effect of the yearly aerosol retention can be seen to partly influence the aerosol loadings between October and February.

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Characteristics of aerosol optical depth and Ångström parameters over Mohal in the Kullu Valley of Northwest Himalayan Region, India

Cited by 7 publications

References 42 publications

Five years surface ozone behaviour in a semi-rural location at Mohal-Kullu in the north-western Himalaya, India

Five years surface ozone behaviour in a semi-rural location at Mohal-Kullu in the north-western Himalaya, India

Seasonal variability in aerosol optical and physical characteristics estimated using the application of the Ångström formula over Mohal in the northwestern Himalaya, India

Parametric retrieval model for estimating aerosol size distribution via the AERONET, LAGOS station

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