Inorganic ions in ambient fine particles over a National Park in central India: Seasonality, dependencies between SO42−, NO3−, and NH4+, and neutralization of aerosol acidity

Kumar, Santosh; Raman, Ramya Sunder

doi:10.1016/j.atmosenv.2016.08.037

Cited by 29 publications

(20 citation statements)

References 27 publications

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“…The equivalent concentration ratios of

{normalN normalH}_{4}^{+}

{SO}_{4}^{2 prefix-}

in fine mode (average 2.3) indicate that there is enough NH 3 after neutralization of H 2 SO 4 to form NH 4 NO 3 . However, NH 4 NO 3 is highly volatile [ Huang et al ., ; Kumar and Raman , ], and thus, high ambient temperature in Raipur during the campaign may enhance the dissociation of NH 4 NO 3 into gaseous NH 3 and HNO 3 . Moreover, the vapor pressure on the surface of fine particles is usually higher than that of coarse particles, and thus, thermal decomposition of NH 4 NO 3 in fine particles under high temperature is significant, leading to lower the concentrations of

{NO}_{3}^{-}

in fine mode particles.…”

Section: Resultsmentioning

confidence: 99%

Sources and formation processes of water‐soluble dicarboxylic acids, ω‐oxocarboxylic acids, α‐dicarbonyls, and major ions in summer aerosols from eastern central India

et al. 2017

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The sources and formation processes of dicarboxylic acids are still under investigation. Size‐segregated aerosol (nine‐size) samples collected in the urban site (Raipur: 21.2°N and 82.3°E) in eastern central India during summer of 2013 were measured for water‐soluble diacids (C2‐C12), ω‐oxoacids (ωC2‐ωC9), α‐dicarbonyls (C2‐C3), and inorganic ions to better understand their sources and formation processes. Diacids showed the predominance of oxalic acid (C2), whereas ω‐oxoacids showed the predominance of glyoxylic acid (ωC2), and glyoxal (Gly) was a major α‐dicarbonyl in all the sizes. Diacids, ω‐oxoacids, and α‐dicarbonyls as well as SO42prefix−, NO3−, and normalNnormalH4+ were enriched in coarse mode, where Ca2+ peaked, suggesting that they are preferentially produced in coarse mode via adsorption as well as heterogeneous and aqueous‐phase oxidation reaction of precursors on the surface of water‐soluble mineral dust particles having more alkaline species. Strong correlations of diacids and related compounds with NO3− (r = 0.66–0.91) and aerosol water content (AWC) (r = 0.63–0.93) further suggest the importance of heterogeneous and aqueous‐phase production in coarse mode. We found strong correlations of C2/(C2‐C12), C2/ωC2, and C2/Gly ratios with AWC in coarse mode (r = 0.83, 0.86, and 0.85, respectively), indicating that enhanced AWC is favorable for the production of C2 diacid through aqueous‐phase oxidation of its higher homologous diacids, ωC2, and Gly. These results demonstrates unique reactivity of water‐soluble mineral dust particles for the enhanced production of diacids and related compounds in aqueous‐phase, having implications on the aerosol‐cloud interaction, solubility, and hygroscopicity of a dominant fraction of water‐soluble organic aerosol mass.

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“…The equivalent concentration ratios of

{normalN normalH}_{4}^{+}

{SO}_{4}^{2 prefix-}

{NO}_{3}^{-}

in fine mode particles.…”

Section: Resultsmentioning

confidence: 99%

Sources and formation processes of water‐soluble dicarboxylic acids, ω‐oxocarboxylic acids, α‐dicarbonyls, and major ions in summer aerosols from eastern central India

et al. 2017

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“…Emission magnitudes of NH 3 could affect secondary nitrate, which typically contributes to less than 5 % of PM 2.5 mass (Fig. 5a, c; Kumar and Sunder Raman, 2016;Ram and Sarin, 2011;Rastogi et al, 2016), thus not influencing overall results in any significant manner. The model focuses on the temporal and spatial evolution of aerosols and gaseous compounds using meteorological datasets, emission inventories and equations that represent the physics and chemistry of the atmosphere.…”

Section: Model Simulations and Evaluationmentioning

confidence: 99%

“…5) at a regional background site (Bhopal, 23.2 • N, 77.4 • E; Fig. 5a, b, c; PM 2.5 , sulfate, nitrate; methods described in Kumar and Sunder Raman, 2016) and a western urban site (Ahmedabad, 23.0 • N, 72.5 • E; Fig. 5d, BC; aethalometer measurements in Ramachandran and Rajesh, 2007).…”

Section: Model Simulations and Evaluationmentioning

confidence: 99%

“…the GAINS model (Amann et al, 2011), to generate scenarios of air pollutants (Klimont et al, , 2018Purohit et al, 2010;Stohl et al, 2015). Indian emissions for 2008 and 2010 under the HTAP_v2 framework (Janssens-Maenhout et al, 2015) originate from the MIX inventory (M. , based on earlier Asia inventories like INTEX-B (Lu et al, 2011;Lu and Streets, 2012) and REAS (Kurokawa et al, 2013). Inconsistencies are reported from merging datasets, calculating different pollutants using differing assumptions (M. .…”

Section: Estimated Emission Evolution (2015-2050)mentioning

confidence: 99%

“…4) and its chemical constituents (Fig. 5) were evaluated against available PM 2.5 measurements, satellite observations of columnar aerosol optical depth (AOD) and available monthly chemical composition measurements (Kumar and Sunder Raman, 2016;Ramachandran and Kedia, 2010;Ramachandran and Rajesh, 2007). Model performance was evaluated through normalized mean bias (NMB) (Eq.…”

Section: Model Simulations and Evaluationmentioning

confidence: 99%

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Source influence on emission pathways and ambient PM<sub>2.5</sub> pollution over India (2015–2050)

et al. 2018

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Abstract. India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015-2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM 2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by populationweighted aggregation to national and state levels. We find that PM 2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM 2.5 annual standard (40 µg m −3 ). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM 2.5 in India. About 60 % of India's mean population-weighted PM 2.5 concentrations come from anthropogenic source sectors, while the remainder are from "other" sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM 2.5 . Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coalbased electricity generation, significant reductions in PM 2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger exPublished by Copernicus Publications on behalf of the European Geosciences Union. 8018 C. Venkataraman et al.: Source influence on emission pathways and ambient PM 2.5 pollution pansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.

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Seasonal variation and sources of PM_2.5 bound water‐soluble ions at Jammu city in the foothills of the North‐western Himalayas, India

et al. 2023

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In this study, PM2.5 aerosols were collected from the campus of the University of Jammu situated along the Shivalik foothills of the North‐western Himalayas in the Jammu urban area to understand the seasonal variability of PM2.5 mass concentrations and associated water‐soluble inorganic ions (WSIIs). Results showed that the annual average PM2.5 mass concentrations were average 65.02 μg/m3 which significantly exceeded the annual National Ambient Air Quality Standards (40 μg/m3) by ~1.6 times. In addition, PM2.5 and WSIIs mass concentrations exhibited significant seasonal variability with the highest average concentrations observed during winter and the least during monsoon. Furthermore, WSIIs accounted for 24.56% of PM2.5 mass annually. Cl−, Na+, Ca2+ and Mg2+ depicted higher concentrations in summer whereas higher mass concentrations of SO42−, NO3− and NH4+ observed during winter pointed to their formation from gas to particulate conversion mechanisms. The variability of source strength during peak tourist seasons in holidays, festivities and new year appears to have significantly accounted for high PM2.5 in the study area. Additionally, meteorological conditions also appear to have played an important role in secondary aerosol formation which is noticeable from the high correlation observed among SO42−–NO3− (0.97), NH4+–SO42− (0.69), K+–Cl− (0.85), NH4+–NO3− (0.64), SO42−–K+ (0.63), NH4+–Cl− (0.65) at p < .05 during winter. On the other hand, significant correlations (p < .01) observed between Ca2+–Mg2+ (0.94), SO42−–Ca2+ (0.78) and SO42−–Mg2+ (0.89) during summer indicated their primary origin as crustal‐based sources.

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Inorganic ions in ambient fine particles over a National Park in central India: Seasonality, dependencies between SO42−, NO3−, and NH4+, and neutralization of aerosol acidity

Cited by 29 publications

References 27 publications

Sources and formation processes of water‐soluble dicarboxylic acids, ω‐oxocarboxylic acids, α‐dicarbonyls, and major ions in summer aerosols from eastern central India

Sources and formation processes of water‐soluble dicarboxylic acids, ω‐oxocarboxylic acids, α‐dicarbonyls, and major ions in summer aerosols from eastern central India

Source influence on emission pathways and ambient PM<sub>2.5</sub> pollution over India (2015–2050)

Seasonal variation and sources of PM_2.5 bound water‐soluble ions at Jammu city in the foothills of the North‐western Himalayas, India

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Inorganic ions in ambient fine particles over a National Park in central India: Seasonality, dependencies between SO42−, NO3−, and NH4+, and neutralization of aerosol acidity

Cited by 29 publications

References 27 publications

Sources and formation processes of water‐soluble dicarboxylic acids, ω‐oxocarboxylic acids, α‐dicarbonyls, and major ions in summer aerosols from eastern central India

Sources and formation processes of water‐soluble dicarboxylic acids, ω‐oxocarboxylic acids, α‐dicarbonyls, and major ions in summer aerosols from eastern central India

Source influence on emission pathways and ambient PM&lt;sub&gt;2.5&lt;/sub&gt; pollution over India (2015–2050)

Seasonal variation and sources of PM2.5 bound water‐soluble ions at Jammu city in the foothills of the North‐western Himalayas, India

Contact Info

Product

Resources

About

Source influence on emission pathways and ambient PM<sub>2.5</sub> pollution over India (2015–2050)

Seasonal variation and sources of PM_2.5 bound water‐soluble ions at Jammu city in the foothills of the North‐western Himalayas, India