Determination of wood burning and fossil fuel contribution of black carbon at Delhi, India using aerosol light absorption technique

Environ Sci Pollut Res Int. 2015 Feb;22(4):2846-55. doi: 10.1007/s11356-014-3531-2. Epub 2014 Sep 14.

Abstract

A comprehensive measurement program of effective black carbon (eBC), fine particle (PM2.5), and carbon monoxide (CO) was undertaken during 1 December 2011 to 31 March 2012 (winter period) in Delhi, India. The mean mass concentrations of eBC, PM2.5, and CO were recorded as 12.1 ± 8.7 μg/m(3), 182.75 ± 114.5 μg/m(3), and 3.41 ± 1.6 ppm, respectively, during the study period. Also, the absorption Angstrom exponent (AAE) was estimated from eBC and varied from 0.38 to 1.29 with a mean value of 1.09 ± 0.11. The frequency of occurrence of AAE was ~17 % less than unity whereas ~83 % greater than unity was observed during the winter period in Delhi. The mass concentrations of eBC were found to be higher by ~34 % of the average value of eBC (12.1 μg/m(3)) during the study period. Sources of eBC were estimated, and they were ~94 % from fossil fuel (eBCff) combustion whereas only 6 % was from wood burning (eBCwb). The ratio between eBCff and eBCwb was 15, which indicates a higher impact from fossil fuels compared to biomass burning. When comparing eBCff during day and night, a factor of three higher concentrations was observed in nighttime than daytime, and it is due to combustion of fossil fuel (diesel vehicle emission) and shallow boundary layer conditions. The contribution of eBCwb in eBC was higher between 1800 and 2100 hours due to burning of wood/biomass. A significant correlation between eBC and PM2.5 (r = 0.78) and eBC and CO (r = 0.46) indicates the similarity in location sources. The mass concentration of eBC was highest (23.4 μg/m(3)) during the month of December when the mean visibility (VIS) was lowest (1.31 km). Regression analysis among wind speed (WS), VIS, soot particles, and CO was studied, and significant negative relationships were seen between VIS and eBC (-0.65), eBCff (-0.66), eBCwb (-0.34), and CO (-0.65); however, between WS and eBC (-0.68), eBCff (-0.67), eBCwb (-0.28), and CO (-0.53). The regression analysis indicated that emission of soot particles may be localized to fossil fuel combustion, whereas wood/biomass burning emission of black carbon is due to transportation from farther distances. Regression analysis between eBCff and CO (r = 0.44) indicated a similar source as vehicular emissions. The very high loading of PM2.5 along with eBC over Delhi suggests that urgent action is needed to mitigate the emissions of carbonaceous aerosol in the northern part of India.

MeSH terms

  • Absorption, Physicochemical
  • Aerosols
  • Air Pollutants / chemistry*
  • Biomass
  • Carbon / analysis*
  • Carbon Monoxide / analysis
  • Environmental Monitoring / methods
  • Environmental Monitoring / statistics & numerical data*
  • Fossil Fuels / analysis*
  • India
  • Particulate Matter / analysis
  • Regression Analysis
  • Seasons
  • Soot / analysis*
  • Vehicle Emissions / analysis*
  • Wood / chemistry*

Substances

  • Aerosols
  • Air Pollutants
  • Fossil Fuels
  • Particulate Matter
  • Soot
  • Vehicle Emissions
  • Carbon
  • Carbon Monoxide