Chemical Composition and Source Apportionment of Total Suspended Particulate in the Central Himalayan Region

Sheoran, Rahul; Dumka, U. C.; Kaskaoutis, Dimitris G.; Grivas, Georgios; Ram, Kirpa; Prakash, Jai; Hooda, Rakesh K.; Tiwari, Rakesh; Mihalopoulos, N.

doi:10.3390/atmos12091228

Cited by 12 publications

(14 citation statements)

References 96 publications

(189 reference statements)

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“…dian plains [10,[56][57][58][59][60]. In contrast, the Indian Himalayan region (IHR) still lacks systematic studies focused on the characterization of aerosols [61][62][63][64][65][66][67][68][69] and source apportionment [61,70,71] using RMs.…”

Section: Methodology 21 Experimental Sitesmentioning

confidence: 99%

“…The site is expected to be emblematic of local and regional environments for climatic change studies [37,74,75]. Additional details about the location are available in the literature [71,72,76]. E, 31.9 • N, and 1154 m above sea level (a.s.l).…”

Section: Experimental Sitesmentioning

confidence: 99%

“…Several studies on aerosol chemical compositions have been conducted over the Tibetan Plateau [49][50][51][52][53][54][55], in the northern part of the Himalayas, and over the Indian plains [10,[56][57][58][59][60]. In contrast, the Indian Himalayan region (IHR) still lacks systematic studies focused on the characterization of aerosols [61][62][63][64][65][66][67][68][69] and source apportionment [61,70,71] using RMs.…”

Section: Introductionmentioning

confidence: 99%

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Chemical Characterization and Source Apportionment of PM10 Using Receptor Models over the Himalayan Region of India

Choudhary,

Rai,

Kuniyal

et al. 2023

Atmosphere

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This study presents the source apportionment of coarse-mode particulate matter (PM10) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), water-soluble organic carbon (WSOC), carbon fractions (organic carbon (OC) and elemental carbon (EC)), and trace elements of PM10 were analyzed over the IHR. Nainital (62 ± 39 µg m−3) had the highest annual average mass concentration of PM10 (average ± standard deviation at 1 σ), followed by Mohal Kullu (58 ± 32 µg m−3) and Darjeeling (54 ± 18 µg m−3). The annual total ∑WSIIS concentration order was as follows: Darjeeling (14.02 ± 10.01 µg m−3) > Mohal-Kullu (13.75 ± 10.21 µg m−3) > Nainital (10.20 ± 6.30 µg m−3), contributing to 15–30% of the PM10 mass. The dominant secondary ions (NH4+, SO42−, and NO3−) suggest that the study sites were strongly influenced by anthropogenic sources from regional and long-range transport. Principal component analysis (PCA) with an absolute principal component score (APCS), UNMIX, and Positive Matrix Factorization (PMF) were used for source identification of PM10 at the study sites of the IHR. All three models showed relatively similar results of source profiles for all study sites except their source number and percentage contribution. Overall, soil dust (SD), secondary aerosols (SAs), combustion (biomass burning (BB) + fossil fuel combustion (FFC): BB+FFC), and vehicular emissions (VEs) are the major sources of PM10 identified by these models at all study sites. Air mass backward trajectories illustrated that PM10, mainly attributed to dust-related aerosols, was transported from the Thar Desert, Indo-Gangetic Plain (IGP), and northwestern region of India (i.e., Punjab and Haryana) and Afghanistan to the IHR. Transported agricultural or residual burning plumes from the IGP and nearby areas significantly contribute to the concentration of carbonaceous aerosols (CAs) at study sites.

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Section: Methodology 21 Experimental Sitesmentioning

confidence: 99%

Section: Experimental Sitesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Chemical Characterization and Source Apportionment of PM10 Using Receptor Models over the Himalayan Region of India

Choudhary,

Rai,

Kuniyal

et al. 2023

Atmosphere

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“…The relationships were found through statistical analysis of variance and the p-value was used to calculate the statistical level of significance in terms of the correlation coefficient (R). For probability value (p) < 0.05, the value of R will be considered significant [49]. The correlation between BC and OC is determined to be 0.93, indicating that both originate from a single source, that is, the source of combustion [46].…”

Section: Relationships Between Mass Concentration Optical and Meteoro...mentioning

confidence: 99%

Exploring the Spatiotemporal Variation in Light-Absorbing Aerosols and Its Relationship with Meteorology over the Hindukush–Himalaya–Karakoram Region

et al. 2023

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Light-absorbing aerosols such as black carbon (BC), organic carbon (OC), and dust can cause the warming and melting of glaciers by absorbing sunlight. Further research is needed to understand the impact of light-absorbing aerosols on the Hindukush–Karakoram–Himalaya region in northern Pakistan. Therefore, spatiotemporal variation in absorbing surface mass concentration retrieved from Modern-Era Retrospective analysis for Research and Applications, optical properties such as aerosol optical depth (AOD) and absorption aerosol optical depth (AAOD) from the ozone monitoring instrument, and meteorological parameters from the European Centre for Medium-Range Weather Forecasts Reanalysis were investigated over northern Pakistan from 2001 to 2021. The BC concentration was lowest in May and highest in November, having a seasonal maximum peak in winter (0.31 ± 0.04 µg/m3) and minimum peak in spring (0.17 ± 0.01 µg/m3). In addition, OC concentration was found to be greater in November and smaller in April, with a seasonal higher peak in autumn (1.32 ± 0.32 µg/m3) and a lower peak in spring (0.73 ± 0.08 µg/m3). The monthly and seasonal variabilities in BC and OC concentrations are attributed to solid fuels, biomass burning, changes in vegetation, agricultural activities, and meteorology. In contrast, the dust concentration was high in July and low in December, with a seasonal average high concentration in summer (44 ± 9 µg/m3) and low concentration in winter (13 ± 2 µg/m3) due to drier conditions, dust activity, long-range transport, and human activities. Moreover, the seasonal variation in AOD and AAOD was identical and higher in the summer and lower in the winter due to dust aerosol loading and frequent dust activities. AOD and AAOD followed a similar pattern of spatial variation over the study area. Meteorological parameters greatly impact light-absorbing aerosols; therefore, low temperatures in winter increase BC and OC concentrations due to shallow boundary layers, while severe precipitation in spring decreases concentrations. During summer, dry conditions cause soil erosion and increase the amount of dust suspended in the atmosphere, leading to higher AOD and AAOD values. Conversely, higher precipitation rates and speedy winds disperse the dust aerosols in winter, resulting in lower AOD and AAOD values.

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“…OC and EC are emitted from various sources, including fossil fuel combustion, industrial emissions, biomass burning, vehicular exhaust, and residential solid fuel use. Source apportionment studies have identified biomass burning, vehicular exhaust, mineral dust, and coal combustion as key contributors to the total aerosol mass found in the Himalayan region. − Several studies have observed an increase in the contribution of total carbonaceous aerosols at specific locations in the Himalayas. ,, Furthermore, a long-term study conducted from September 2005 to March 2016 in the central Himalayas found that the concentration of BC has been increasing at a rate of 2% per year . However, research on optical properties in the Himalayan region is limited.…”

Section: Introductionmentioning

confidence: 99%

Optical Properties of Fine Mode Aerosols over High-Altitude Himalayan Glacier Regions

Verma

Pervez

Chow

et al. 2023

ACS Earth Space Chem.

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During the summer and winter periods of 2019−2020, we conducted sampling of fine mode ambient aerosols in the western Himalayan glacial region (WHR; Thajiwas glacier, 2799 m asl), central Himalayan glacial region (CHR; Gomukh glacier, 3415 m asl), and eastern Himalayan glacial region (EHR; Zemu glacier, 2700 m asl). We evaluated the aerosol optical properties, which included the mass absorption coefficient, mass absorption efficiency, mass scattering efficiency, absorption angstrom exponent, single scattering albedo, as well as their simple radiative forcing efficiencies. We observed the highest absorption in the near ultraviolet−visible wavelength range (200−400 nm), with CHR showing the highest absorption compared to the other two sites, WHR and EHR, respectively. Across the wavelength range of 200−1100 nm, the overall contribution of black carbon to light attenuation was greater than that of brown carbon. However, brown carbon dominated the absorption in the near UV−visible wavelengths, providing evidence of its non-trivial presence over the Himalayan region. Additionally, we observed a positive radiative forcing (W/g), which leads to net warming at these sites. The findings of this ground-based study contribute to our understanding of the light-absorbing nature of carbonaceous aerosols and their impact on the Himalayan glacier regions.

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Chemical Composition and Source Apportionment of Total Suspended Particulate in the Central Himalayan Region

Cited by 12 publications

References 96 publications

Chemical Characterization and Source Apportionment of PM10 Using Receptor Models over the Himalayan Region of India

Chemical Characterization and Source Apportionment of PM10 Using Receptor Models over the Himalayan Region of India

Exploring the Spatiotemporal Variation in Light-Absorbing Aerosols and Its Relationship with Meteorology over the Hindukush–Himalaya–Karakoram Region

Optical Properties of Fine Mode Aerosols over High-Altitude Himalayan Glacier Regions

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