Evaluation of PM2.5 Surface Concentrations Simulated by NASA’s MERRA Version 2 Aerosol Reanalysis over India and its Relation to the Air Quality Index

Navinya, Chimurkar; Vinoj, V.; Pandey, Satyendra K.

doi:10.4209/aaqr.2019.12.0615

Cited by 80 publications

(45 citation statements)

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“…reported the same ranked order but with different percentages. Major contribution of NO3 in winter is also reported in other studies (Pant et al, 2015). BC fraction was 7%, which is very close to the measured fraction of 6.4% in wintertime PM1 .…”

Section: Aerosol Composition In Delhisupporting

confidence: 91%

“…BC fraction was 7%, which is very close to the measured fraction of 6.4% in wintertime PM1 . Pant et al (2015) reported averaged OC and elemental carbon concentrations of 104.4 µgm -3 and 46.3 µgm -3 , respectively, which 410 is consistent with our OC/BC ratio of 2.72. Comparing modeled BC1 data with available data for this period shows an overall measured to modeled ratio of 1.22, which is consistent with the range other studies reported (Kumar et al, 2015b;Moorthy et al, 2013).…”

Section: Aerosol Composition In Delhisupporting

confidence: 88%

“…12 and Table S2), which is mostly due to the inability of the inventory to capture the fire points over the domain and it can be attributed to both the technique and the resolution as QFED data have ~10 km resolution, whereas FINN data has ~1 km resolution. Pan et al (2020) found high uncertainty between different biomass burning emission inventories over Southeast Asia. They showed FINN is, in general, a better dataset for tropical regions 430 as its 2-days continuous fire emission compensates for the lack of daily MODIS coverage used in QFED (Pan et al, 2020;Wiedinmyer et al, 2011).…”

Section: Sensitivity To Changes In Biomass Burning Emission Inventoriesmentioning

confidence: 99%

“…First, we looked at two different emission inventories based on different methodologies and horizontal resolutions; Specifically, FINNv1.5 and QFEDv2.5r1. Both inventories rely on MODIS data; FINN is based on active fire points and estimates of burned area, whereas QFED uses FRP approach (Pan et al, 2020). Figure 420 10 shows the grid cells with biomass burning emissions based on QFED (panel a), FINN (panel b), and FINN_VIIRS composition (panel c), used in base scenario, accompanied with active fire points seen by VIIRS (panel d) based on the Fire Information for Resource Management System (FIRMS) product for Nov. 5 th .…”

Section: Sensitivity To Changes In Biomass Burning Emission Inventoriesmentioning

confidence: 99%

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Improving regional air quality predictions in the Indo-Gangetic Plain-Case study of an intensive pollution episode in November 2017

Roozitalab¹,

Carmichael²,

Guttikunda³

2020

Preprint

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Abstract. Indo-Gangetic Plain (IGP) experienced an intensive air pollution episode during November 2017. Weather Research and Forecasting model with Chemistry (WRF-Chem), a coupled meteorology–chemistry model, was used to simulate this episode. In order to capture PM2.5 peaks, we modified input chemical boundary conditions and biomass burning emissions. CAM-Chem and MERRA-2 global models provided gaseous and aerosol chemical boundary conditions, respectively. We also incorporated VIIRS active fire points to fill missing fire emissions in FINN and scaled by a factor of seven for an 8-days period. Evaluations against various observations indicated the model captured the temporal trend very well although missed the peaks on Nov. 7th, 8th, and 10th. Modeled aerosol composition in Delhi showed Secondary Inorganic Aerosols (SIA) and Secondary Organic Aerosols (SOA) comprised 30 % and 27 % of total PM2.5 concentration, respectively, during November, with a modeled OC / BC ratio of 2.72. Back trajectories showed agricultural fires in Punjab were the major source for extremely polluted days in Delhi. Furthermore, high concentrations above the boundary layers in vertical profiles suggested either the plume rise in the model released the emissions too high, or the model did not mix the smoke down fast enough. Results also showed long-range transported dusts did not affect Delhi's air quality during the episode. Spatial plots showed averaged Aerosol Optical Depth (AOD) of 0.58 (± 0.4) over November. The model AODs were biased high over central India and low over eastern IGP, indicating improving emissions in eastern IGP can significantly improve the air quality predictions. We also found high ozone concentrations over the domain, which indicates ozone should be considered in future air quality management strategies alongside particulate matters.

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Section: Aerosol Composition In Delhisupporting

confidence: 91%

Section: Aerosol Composition In Delhisupporting

confidence: 88%

Section: Sensitivity To Changes In Biomass Burning Emission Inventoriesmentioning

confidence: 99%

Section: Sensitivity To Changes In Biomass Burning Emission Inventoriesmentioning

confidence: 99%

See 2 more Smart Citations

Improving regional air quality predictions in the Indo-Gangetic Plain-Case study of an intensive pollution episode in November 2017

Roozitalab¹,

Carmichael²,

Guttikunda³

2020

Preprint

View full text Add to dashboard Cite

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“…All AOD products are monthly averaged over the given coordinates from 2013-2017. The details about MERRA-2 and MODIS products and its validity/comparison over Indian region can be found elsewhere [34][35][36][37].…”

Section: Atmospheric Composition Datamentioning

confidence: 99%

Source Profiling of Air Pollution and its Association with Acute Respiratory Infections in the Himalayan Bound Region of India

Wani

Mishra

Sharma

et al. 2020

Preprint

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The studies related to air pollution and its association with human health over the mountainous region are of utmost importance, and are sparse especially over the Himalayan region of India. This study gives an understanding of increase in the occurrence of respiratory diseases due to the accumulation of pollutants during winter season in the Himalayan region (Kashmir valley). The linkages between various atmospheric variables and clinically validated data have been done using various datasets procured from the satellite, model reanalysis and surface observations. Monthly managed data from 2013-2017 for upper and lower respiratory tract infections is obtained from the Ministry of health, Government of India. Aerosol optical depth, air temperature, and wind speed are significantly related (p <0.001) to the incidence of acute respiratory infections with its peak during winter. Model derived particulate matters having aerodynamic diameters less than 2.5 µm (PM2.5) shows high contribution of black carbon, organic carbon and sulphate during winter. This is mainly due to the burning of biomass and biofuels (both indoor and outdoor) with low planetary boundary layer height, accumulating high air pollution and deteriorating air quality during winter months that affects the respiratory health of the habitants. The wind roses generated shows the passage of winds from western side of the region surrounded by Pir panjal Himalayan sub division. Concentrated weighted trajectory analysis has shown that most of the winds coming from the western side are taking southward direction before reaching the study area and may be bringing pollutants from Indo-Gangetic Plain. Our study shows that the accumulation of pollutants in the Himalayan valley is owing to the meteorological stability with significant emissions from burning of biomass and biofuels during winter season, that significantly correlated with the incidence of acute respiratory infections in the region.

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Relational Study of PM2.5 Surface Concentration with MODIS Level 3 AOD Data Over India

Scaria

Avanthika

Jose

et al. 2022

Lecture Notes in Civil Engineering

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Evaluation of PM2.5 Surface Concentrations Simulated by NASA’s MERRA Version 2 Aerosol Reanalysis over India and its Relation to the Air Quality Index

Cited by 80 publications

References 0 publications

Improving regional air quality predictions in the Indo-Gangetic Plain-Case study of an intensive pollution episode in November 2017

Improving regional air quality predictions in the Indo-Gangetic Plain-Case study of an intensive pollution episode in November 2017

Source Profiling of Air Pollution and its Association with Acute Respiratory Infections in the Himalayan Bound Region of India

Relational Study of PM2.5 Surface Concentration with MODIS Level 3 AOD Data Over India

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