Intercomparison of Aerosol Optical Thickness Derived from MODIS and in Situ Ground Datasets over Jaipur, a Semi-arid Zone in India

Payra, Swagata; Soni, Monika; Kumar, Ashutosh; Prakash, Divya; Verma, Sunita

doi:10.1021/acs.est.5b02225

Cited by 18 publications

(7 citation statements)

References 44 publications

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“…AOD is a crucial parameter to estimate air quality. So, the level 3.0 collection version 6.1 monthly mean AOD data at 550 nm wavelength is extracted from MODIS for the study period (Payra et al, 2015;Kang et al, 2016). More details about the retrieval techniques and concepts can be found elsewhere…”

Section: Moderate Resolution Imaging Spectro-radiometer (Modis)mentioning

confidence: 99%

Impact of COVID-19 on the Air Quality over China and India Using Long-term (2009-2020) Multi-satellite Data

Soni¹,

Verma

Jethava³

et al. 2021

Aerosol Air Qual. Res.

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We have examined the air quality over China, India and demonstrated marked differences in levels of air pollution resulted from the COVID-19 restrictions during December-April, 2019-20 to that of 11 years mean of 2009-19. The criteria air quality indicators i.e. nitrogen dioxide (NO2), sulphur dioxide (SO2), Aerosol Index (AI) and aerosol optical depth (AOD) data are retrieved from the Ozone Monitoring Instrument (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and MODerate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra and Aqua satellites, respectively. Over China, during COVID-19 lockdown a significant drop in columnar abundances of tropospheric NO2 (-37%), SO2 (-64%) and AOD (-8%) for 2020 in comparison to 11 years mean (2009-19) has been observed. A noticeable difference in NO2 column burden is seen over SE (-35%), NE (-33%), NW (-13%) and SW (-5%) China. Over the SE and NE China, both NO2 and SO2 levels decreased dramatically in 2020 from that of 2009-19, by more than 40% and 65%, respectively, because of both stricter regulations of emissions and less traffic activity due to reduced social and industrial activities during COVID-19 restrictions. In contrast, the curve of monthly mean tropospheric columnar burden of NO2 and SO2 over India has shown moderate reduction of 16% and 20%, respectively because lockdown came into effect much later in March 2020. The mean NO2 and SO2 over IGP region is found to be 25% higher than whole India's mean concentration due to large scale urban settlement and crop burning events. The statistical t-test analysis results confirm significant (p<0.05) improvements in AQ during lockdown. The COVID-19 pandemic provided an unprecedented opportunity to investigate such large-scale reduction in emissions of trace gases and aerosols. Therefore, it is important to further strengthen environmental policies to tackle air quality, human health, and climate change in this part of the world.

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Section: Moderate Resolution Imaging Spectro-radiometer (Modis)mentioning

confidence: 99%

Impact of COVID-19 on the Air Quality over China and India Using Long-term (2009-2020) Multi-satellite Data

Soni¹,

Verma

Jethava³

et al. 2021

Aerosol Air Qual. Res.

Self Cite

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“…The Jaipur site (26.91 °N, 75.78 °E) is on the eastern edge of the Thar Desert, flanked on three sides by the Aravalli Mountains [33,58,59]. It is India's most populous city having 3.1 million populations.…”

Section: Synoptic Meteorology and Methodsmentioning

confidence: 99%

Investigation of the aerosol's optical properties over the dust prevalent semi-arid region at Jaipur, northwestern India

Solanki

Pathak

2023

Environmental Engineering Research

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Jaipur is a key site to study Aerosol Optical Depth (AOD) due to unpredictable variation of atmospheric Aerosols particles in the recent years. Aerosols Optical Depth (AOD) and Angstrom Exponent (AE) were investigated over the semi-arid region, Jaipur (26.9124° N, 75.7873° E) Northwestern India during the April-2009 to December-2017 utilizing AERONET CIMEL sun-photometer level-2 data for aerosols spatial and temporal characteristics. The Aerosols Optical Depth AOD500 nm, AOD440 nm, and AOD340 nm were observed maximum in July-2011 and minimum observed in March-2013. The monthly mean Angstrom Exponent (AE) was maximum (1.53 ± 0.43) for 500-870 nm, (1.49 ± 0.4) for 440-870 nm, and (1.19 ± 0.32) for 340-440 nm in September 2011, while the lowest value recorded (0.26 ± 0.12) for 340-440 nm, (0.16 ± 0.08) for 440-870 nm and (0.15 ± 0.07) for 500-870 nm during June 2014. The backward trajectories analysis was performed using the Hybrid Single-Particle Lagrangian Integrated Trajectories (HYSPLIT) model to determine the sources of large aerosol loadings over the Jaipur region, and air mass simulations from the back trajectory, suggest that the Thar desert northwestern part of India is the source of highest aerosols dust particle over the study area during the pre-monsoon season.

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“…For example, Ginoux et al [25] found that, while DB based AOD values were within the standard deviation of AERONET data in Africa, the Arabian Peninsula, and India, they were overestimated in California, Australia, and Israel. Payra et al [26] observed dependence of estimation accuracies on Monsoon in a semi-arid urban region in India. In 2013, the second generation of DB (as part of Collection 6) was proposed [27], which used a hybrid approach to account for inhomogeneously vegetated urban/built-up areas among other improvements.…”

Section: Datasets Usedmentioning

confidence: 99%

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

2017

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Urban air pollution is one of the most widespread global sustainability problems. Previous research has studied growth or fall of particulate matter (PM) levels using on-ground monitoring stations in urban regions. However, studying this worldwide is difficult because most cities do not have sufficient infrastructure to monitor air quality. Thus, satellite data is increasingly being employed to solve this limitation. In this paper, we use 16 years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) of aerosol optical depth (AOD) and Angstrom exponent (α) datasets, retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) sensors on the National Aeronautics and Space Administration's (NASA) Terra satellite to study air quality over 60 locations globally. We propose a novel technique, called AirRGB decomposition, to characterize urban air quality by decomposing AOD and α retrievals into 'components' of three distinct scenarios. In the AirRGB decomposition method, using AOD and α dataset three scenarios were investigated: 'R'-high α and high AOD, 'G'-high α and low AOD, and 'B'-low α and low AOD values. These scenarios were mapped and quantified over a triangular red, green and blue color scale. This visualization easily segregates regions having a high concentration of industrial aerosol from only natural aerosols. Our analysis indicates that a sharp divide exists between North American and European cities and Asian cities in terms of baseline pollution and slopes of R and G trends. We found that while pollution in cities in China has started to decrease (e.g., since 2011 for Beijing), it continues to increase in South Asia and Southeast Asia. e.g., R offset of Beijing and New Delhi was 54.98 and 50.43 respectively but R slope was −0.04 and 0.08 respectively. High offset (≥45) and slope (≥0.025) of B for New York, Tokyo, Sydney and Sao Paolo shows that they have clean air, which is still getting better.

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Intercomparison of Aerosol Optical Thickness Derived from MODIS and in Situ Ground Datasets over Jaipur, a Semi-arid Zone in India

Cited by 18 publications

References 44 publications

Impact of COVID-19 on the Air Quality over China and India Using Long-term (2009-2020) Multi-satellite Data

Impact of COVID-19 on the Air Quality over China and India Using Long-term (2009-2020) Multi-satellite Data

Investigation of the aerosol's optical properties over the dust prevalent semi-arid region at Jaipur, northwestern India

Novel Decomposition Scheme for Characterizing Urban Air Quality with MODIS

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