Literature DB >> 25217282

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

S Tiwari1, A S Pipal, A K Srivastava, D S Bisht, G Pandithurai.   

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.

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Year:  2014        PMID: 25217282     DOI: 10.1007/s11356-014-3531-2

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  12 in total

1.  Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols.

Authors:  M Z Jacobson
Journal:  Nature       Date:  2001-02-08       Impact factor: 49.962

2.  Climate effects of black carbon aerosols in China and India.

Authors:  Surabi Menon; James Hansen; Larissa Nazarenko; Yunfeng Luo
Journal:  Science       Date:  2002-09-27       Impact factor: 47.728

3.  Contribution of anthropogenic aerosols in direct radiative forcing and atmospheric heating rate over Delhi in the Indo-Gangetic Basin.

Authors:  Atul K Srivastava; Sachchidanand Singh; S Tiwari; D S Bisht
Journal:  Environ Sci Pollut Res Int       Date:  2011-10-18       Impact factor: 4.223

4.  Residential biofuels in South Asia: carbonaceous aerosol emissions and climate impacts.

Authors:  C Venkataraman; G Habib; A Eiguren-Fernandez; A H Miguel; S K Friedlander
Journal:  Science       Date:  2005-03-04       Impact factor: 47.728

5.  Spatial analysis of air pollution and mortality in Los Angeles.

Authors:  Michael Jerrett; Richard T Burnett; Renjun Ma; C Arden Pope; Daniel Krewski; K Bruce Newbold; George Thurston; Yuanli Shi; Norm Finkelstein; Eugenia E Calle; Michael J Thun
Journal:  Epidemiology       Date:  2005-11       Impact factor: 4.822

Review 6.  Health effects of fine particulate air pollution: lines that connect.

Authors:  C Arden Pope; Douglas W Dockery
Journal:  J Air Waste Manag Assoc       Date:  2006-06       Impact factor: 2.235

7.  A simple procedure for correcting loading effects of aethalometer data.

Authors:  Aki Virkkula; Timo Mäkelä; Risto Hillamo; Tarja Yli-Tuomi; Anne Hirsikko; Kaarle Hämeri; Ismo K Koponen
Journal:  J Air Waste Manag Assoc       Date:  2007-10       Impact factor: 2.235

8.  Using aerosol light absorption measurements for the quantitative determination of wood burning and traffic emission contributions to particulate matter.

Authors:  Jisca Sandradewi; Andre S H Prévôt; Sönke Szidat; Nolwenn Perron; M Rami Alfarra; Valentin A Lanz; Ernest Weingartner; Urs Baltensperger
Journal:  Environ Sci Technol       Date:  2008-05-01       Impact factor: 9.028

9.  SEM-EDX analysis of various sizes aerosols in Delhi India.

Authors:  Arun Srivastava; V K Jain; Anchal Srivastava
Journal:  Environ Monit Assess       Date:  2008-04-03       Impact factor: 2.513

10.  Sources and characteristics of carbonaceous aerosols at Agra "World heritage site" and Delhi "capital city of India".

Authors:  A S Pipal; S Tiwari; P G Satsangi; Ajay Taneja; D S Bisht; A K Srivastava; M K Srivastava
Journal:  Environ Sci Pollut Res Int       Date:  2014-04-11       Impact factor: 4.223

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  1 in total

1.  Characteristics and source apportionment of black carbon aerosols over an urban site.

Authors:  T A Rajesh; S Ramachandran
Journal:  Environ Sci Pollut Res Int       Date:  2017-02-10       Impact factor: 4.223

  1 in total

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