T. Saud

Emission Estimates of Particulate PAHs from Biomass Fuels Used in Delhi, India

ABSTRACT The emission factors for particulate-phase polycyclic aromatic hydrocarbons (PAHs) were evaluated for various biomass fuels (fuelwood, dung cakes, and agricultural residue) that are being commonly used in Delhi as a source of energy. Emission factors of total particulate PAHs varied from 35.9 ± 1.9 to 59.7 ± 4.4 mg/kg. Higher levels of total PAHs and particulate matter (PM) were found from dung cakes as compared to fuelwood and agricultural residue. The emission factors for PM from dung cake, fuelwood, and agricultural residue are 25 ± 8, 15 ± 3.2, and 12.1 ± 9.4 g/kg, respectively. The total PAH emissions showed an increase with high particulate matter emission rates and lower combustion efficiency. Fluoranthene, pyrene, benzo[a]anthracene, chrysene, benzo[b]fluoranthene, and benzo[a]pyrene constituted the major fraction of PAH emissions from all biomass fuels. The annual budget estimates (total emissions per year) for PAHs and PM from biomass fuels used in Delhi are 30.5 ± 2.3 Mg (Megagrams) and 11.6 ± 4.4 Gg (Gigagrams), respectively. An attempt has also been made to evaluate the preliminary budget estimates of PAHs and PM emitted from the use of biomass fuels as a source of energy in India by using the emission factors obtained in the present study.

Source apportionment of particulates by receptor models over Bay of Bengal during ICARB campaign

Source apportionment study of aerosols over Bay of Bengal (BOB) were investigated during Integrated Campaign on Aerosol Radiation Budget (ICARB) in the pre–monsoon (March–April 2006) and winter (December–January 2008–09) seasons. Positive matrix factorization (PMF) was applied to identify sources of ambient particulate matter using daily chemical composition data collected in the pre–monsoon (total suspended particles, TSP) and winter season (particles with a diameter < 10 µm, PM10). Sea salt (SS), secondary aerosol (SA), Si–dust, fossil fuel combustion (FFC), biomass burning (BB) sources have been identified in both seasons, however their relative contributions were different. The combined contribution of Si–dust, secondary aerosol and fossil fuel combustion, constitute 67% of particulate matter in pre–monsoon, whereas, secondary aerosols and biomass burning were the major contributors (63.2%) to particulate matter in winter. The identified sources effectively predict the measured particulate concentration in the pre–monsoon (r 2 =0.74) and winter season (r 2 =0.82). Another receptor model, principal component analysis (PCA) was done to increase the plausibility of the results obtained by PMF. PCA resulted in the identification of the sources that were comparable to the PMF outputs. PCA of TSP in the pre–monsoon season resulted in the extraction of three components (crustal dust + secondary aerosol, biomass burning, fossil fuel combustion + industrial emissions) that explained the 83% of the variance in the data. Similarly, in winter season, PCA resulted in the extraction of four components (biomass burning + secondary aerosol, industrial emission, crustal dust, sea salt) that explained the 86% of the variance of the data.