Srishti Jain

Bio: Srishti Jain is an academic researcher from Council of Scientific and Industrial Research. The author has contributed to research in topics: Particle & Mass concentration (chemistry). The author has an hindex of 10, co-authored 13 publications receiving 453 citations. Previous affiliations of Srishti Jain include Academy of Scientific and Innovative Research.

Source Apportionment of PM2.5 in Delhi, India Using PMF Model.

Abstract: Chemical characterization of PM2.5 [organic carbon, elemental carbon, water soluble inorganic ionic components, and major and trace elements] was carried out for a source apportionment study of PM2.5 at an urban site of Delhi, India from January, 2013, to December, 2014. The annual average mass concentration of PM2.5 was 122 ± 94.1 µg m−3. Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon. A receptor model, positive matrix factorization (PMF) was applied for source apportionment of PM2.5 mass concentration. The PMF model resolved the major sources of PM2.5 as secondary aerosols (21.3 %), followed by soil dust (20.5 %), vehicle emissions (19.7 %), biomass burning (14.3 %), fossil fuel combustion (13.7 %), industrial emissions (6.2 %) and sea salt (4.3 %).

Chemical characteristics and source apportionment of PM2.5 using PCA/APCS, UNMIX, and PMF at an urban site of Delhi, India

Abstract: The present study investigated the comprehensive chemical composition [organic carbon (OC), elemental carbon (EC), water-soluble inorganic ionic components (WSICs), and major & trace elements] of particulate matter (PM2.5) and scrutinized their emission sources for urban region of Delhi. The 135 PM2.5 samples were collected from January 2013 to December 2014 and analyzed for chemical constituents for source apportionment study. The average concentration of PM2.5 was recorded as 121.9 ± 93.2 μg m−3 (range 25.1–429.8 μg m−3), whereas the total concentration of trace elements (Na, Ca, Mg, Al, S, Cl, K, Cr, Si, Ti, As, Br, Pb, Fe, Zn, and Mn) was accounted for ∼17% of PM2.5. Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon seasons. The chemical composition of the PM2.5 was reconstructed using IMPROVE equation, which was observed to be in good agreement with the gravimetric mass. Source apportionment of PM2.5 was carried out using the following three different receptor models: principal component analysis with absolute principal component scores (PCA/APCS), which identified five major sources; UNMIX which identified four major sources; and positive matrix factorization (PMF), which explored seven major sources. The applied models were able to identify the major sources contributing to the PM2.5 and re-confirmed that secondary aerosols (SAs), soil/road dust (SD), vehicular emissions (VEs), biomass burning (BB), fossil fuel combustion (FFC), and industrial emission (IE) were dominant contributors to PM2.5 in Delhi. The influences of local and regional sources were also explored using 5-day backward air mass trajectory analysis, cluster analysis, and potential source contribution function (PSCF). Cluster and PSCF results indicated that local as well as long-transported PM2.5 from the north-west India and Pakistan were mostly pertinent.

Spatio-temporal variation in chemical characteristics of PM10 over Indo Gangetic Plain of India

Abstract: The paper presents the spatio-temporal variation of chemical compositions (organic carbon (OC), elemental carbon (EC), and water-soluble inorganic ionic components (WSIC)) of particulate matter (PM10) over three locations (Delhi, Varanasi, and Kolkata) of Indo Gangetic Plain (IGP) of India for the year 2011. The observational sites are chosen to represent the characteristics of upper (Delhi), middle (Varanasi), and lower (Kolkata) IGP regions as converse to earlier single-station observation. Average mass concentration of PM10 was observed higher in the middle IGP (Varanasi 206.2 ± 77.4 μg m(-3)) as compared to upper IGP (Delhi 202.3 ± 74.3 μg m(-3)) and lower IGP (Kolkata 171.5 ± 38.5 μg m(-3)). Large variation in OC values from 23.57 μg m(-3) (Delhi) to 12.74 μg m(-3) (Kolkata) indicating role of formation of secondary aerosols, whereas EC have not shown much variation with maximum concentration over Delhi (10.07 μg m(-3)) and minimum over Varanasi (7.72 μg m(-3)). As expected, a strong seasonal variation was observed in the mass concentration of PM10 as well as in its chemical composition over the three locations. Principal component analysis (PCA) identifies the contribution of secondary aerosol, biomass burning, fossil fuel combustion, vehicular emission, and sea salt to PM10 mass concentration at the observational sites of IGP, India. Backward trajectory analysis indicated the influence of continental type aerosols being transported from the Bay of Bengal, Pakistan, Afghanistan, Rajasthan, Gujarat, and surrounding areas to IGP region.

World air particulate matter: sources, distribution and health effects

Abstract: Particulate matter (PM) is both a major driver of climate change and a source of toxicity for health. In the upper atmosphere, particulate matter modifies the earth radiation budget, cloud formation and acts as a reaction center for air pollutants. In the lower atmosphere, particulate matter changes atmospheric visibility and alters biogeochemical cycles and meteorology. Most critical effects are observed in ambient air, where particulate matter degrades human health. Here we review the sources, spatial and temporal variability, and toxicity of PM10, the particulate matter having particle sizes 10 micrometers or less in diameter, in world regions. For that we analyzed information from the world wide web and databases from government organizations after the year 2000. Findings show that PM10 is a major risk in both developed and developing countries. This risk is more severe in Asian countries compared to Europe and USA, where decreasing trends are recorded during the last two decades. Meteorological factors modify particulate matter variations at local and regional levels. PM2.5/PM10 ratio provides information of particulate matter sources under different environment conditions. Crustal matter, road traffic and combustion of fuels are major sources of particulate matter pollution. Health studies indicate that long-term exposure to particulate matter has multiple health effects in people from all age groups. Identification of possible sources and their control with regular epidemiological monitoring could decrease the impact of particulate matter pollution.