Faculty Publications

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Subject: search.filters.subject.Chemical mass balance

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    Evaluation of optimization methods for solving the receptor model for chemical mass balance
    (Serbian Chemical Society, 2015) Anu, N.; Selvasembian, S.; Rahul, A.; Selvaraju, N.
    The chemical mass balance (CMB 8.2) model has been extensively used in order to determine source contribution for particulate matters (size diameters less than 10 and 2.5 ?m) in air quality analysis. A comparison of the source contribution estimated from three CMB models was realized through optimization techniques, such as 'fmincon' (CMB-fmincon) and genetic algorithm (CMB-GA) using MATLAB. The proposed approach was validated using a San Joaquin Valley Air Quality Study (SJVAQS) California Fresno and Bakersfield PM10 and PM2.5 followed with Oregon PM10 data. The source contribution estimated from CMB-GA was better in source interpretation in comparison with CMB 8.2 and CMB-fmincon. The performance accuracies of three CMB approaches were validated using R2, reduced X2 and percentage mass tests. The R2 (0.90, 0.67 and 0.81, 0.83), X2 (0.36, 0.66 and 0.65, 0.43) and percentage mass (67.36, 55.03 and 94.24 %, 74.85 %) of CMB-GA showed high correlation for PM10, PM2.5, Fresno and Bakersfield data, respectively. To make a complete decision, the proposed methodology was bench marked with Portland, Oregon PM10 data with the best fit with R2 (0.99), X2 (1.6) and percentage mass (94.4 %) from CMB-GA. Therefore, the study revealed that CMB with genetic algorithm optimization method exhibiting better stability in determining the source contributions.
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    Source apportionment of PM2.5 particles: Influence of outdoor particles on indoor environment of schools using chemical mass balance
    (AAGR Aerosol and Air Quality Research hhyang@cyut.edu.tw, 2017) Kalaiarasan, G.; Mohan Balakrishnan, R.M.; Sethunath, N.A.; Manoharan, S.
    Children have higher lung function than adults and they spend most of their day time in schools. Also, children studying at schools located in the vicinity of busy roadways are vulnerable to childhood asthma and respiratory disorders. The present study is focused on estimating the sources of PM2.5 particles present in the indoor air quality in schools which are located adjacent to urban and suburban roadways. The indoor PM2.5 samples from all the four schools were collected using fine dust sampler from 8 a.m. to 4 p.m. The sampling was carried out for one complete week during various seasons including both working and non-working days. The chemical compositions of the PM2.5 samples were analyzed for certain elements like Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Sr, Ti, V and Zn using Inductively Coupled Plasma Optical Emission Spectrometry (ICP OES) and ions like F-, Cl-, NO3-, PO43-, SO42-, K+, Ca2+, Mg2+, NH4+, Na+ using Ion Chromatography (IC). Source apportionment study using Chemical Mass Balance was carried out using the species concentration of the collected samples. The major sources were found to be Paved Road Dust, Soil Dust, Gasoline Vehicle Emissions, Diesel Vehicle Emissions and Marine Source Emissions. Among these, vehicular emissions contribution was found to be higher for the schools located close to roadways rather than the school located at a considerable distance from highway. The difference in source type contribution at each school clearly depicts the difference in nature of location and type of activities in the vicinity of the sampling sites. © Taiwan Association for Aerosol Research.
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    Source apportionment studies on particulate matter (PM10 and PM2.5) in ambient air of urban Mangalore, India
    (Academic Press, 2018) Kalaiarasan, G.; Mohan Balakrishnan, R.M.; Sethunath, N.A.; Manoharan, S.
    Particulate matter (PM10 and PM2.5) samples were collected from six sites in urban Mangalore and the mass concentrations for PM10 and PM2.5 were measured using gravimetric technique. The measurements were found to exceed the national ambient air quality standards (NAAQS) limits, with the highest concentration of 231.5 ?g/m3 for PM10 particles at Town hall and 120.3 ?g/m3 for PM2.5 particles at KMC Attavar. The elemental analysis using inductively coupled plasma optical emission spectrophotometer (ICPOES) revealed twelve different elements (As, Ba, Cd, Cr, Cu, Fe, Mg, Mn, Mo, Ni, Sr and Zn) for PM10 particles and nine different elements (Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Sr and Zn) for PM2.5 particles. Similarly, ionic composition of these samples measured by ion chromatography (IC) divulged nine different ions (F?, Cl?, NO3 ?, PO4 3?, SO4 2?, Na+, K+, Mg2+ and Ca2+) for PM10 particles and ten different ions (F?, Cl?, NO3 ?, PO4 3?, SO4 2?, Na+, NH4 +, K+, Mg2+ and Ca2+) for PM2.5 particles. The source apportionment study of PM10 and PM2.5 for urban Mangalore in accordance with these six sample sites using chemical mass balance model (CMBv8.2) revealed nine and twelve predominant contributors for both PM10 and PM2.5, respectively. The highest contributor of PM10 was found to be paved road dust followed by diesel and gasoline vehicle emissions. Correspondingly, PM2.5 was found to be contributed mainly from two-wheeler vehicle emissions followed by four-wheeler and heavy vehicle emissions (diesel vehicles). The current study depicts that the PM10 and PM2.5 in ambient air of Mangalore region has 70% of its contribution from vehicular emissions (both exhaust and non-exhaust). © 2018 Elsevier Ltd