Chemical characterization and source apportionment of aerosol over mid Brahmaputra Valley, India

被引:65
作者
Bhuyan, Pranamika [1 ]
Deka, Pratibha [1 ]
Prakash, Amit [1 ]
Balachandran, S. [2 ]
Hoque, Raza Rafiqul [1 ,3 ]
机构
[1] Tezpur Univ, Dept Environm Sci, Tezpur 784028, India
[2] Visva Bharati, Dept Environm Studies, Bengal, India
[3] Univ Rochester, Dept Publ Hlth Sci, Rochester, NY USA
关键词
Aerosol; Source apportionment; PM10; PCA-MLR; CMB; PARTICLE-SIZE DISTRIBUTION; POLYCYCLIC AROMATIC-HYDROCARBONS; PM2.5 SOURCE CONTRIBUTIONS; SOLUBLE IONIC COMPOSITION; SECONDARY ORGANIC-CARBON; PARTICULATE MATTER; ELEMENTAL CARBON; SEASONAL-VARIATIONS; AMBIENT AIR; ATMOSPHERIC AEROSOL;
D O I
10.1016/j.envpol.2017.12.009
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Aerosol samples (as PM10, n = 250) were collected from three rural remote receptor locations in the mid Brahmaputra plain region and were chemically characterized for metals (Al, Fe, Co, Cu, Cr, Cd, Mn, Ni, Pb), ions (Ca2+, Mg2+, Na+, K+, NHS, F-, Cl-, NO3-, Sail, and carbon. Vital ratios like NO3-/SO42-, EC/OC, K+/EC, K+/OC, enrichment factors and inter-species correlations were exploited to appreciate possible sources of aerosol. These empirical analyses pointed towards anthropogenic contributions of aerosol, particularly from biomass burning, vehicular emission, and road dust. The chemically characterized concentration data were subsequently fed into two receptor models viz. Principal Component Analysis-Multiple Linear Regression (PCA-MLR) and Chemical Mass Balance (CMB) for apportionment of sources of aerosol. The PCA-MLR estimates identified that the combustion sources together accounted for similar to 42% of aerosol and the contribution of secondary formation to be 24%. Road and crustal dusts have been well apportioned by PCA-MLR, which together accounts for similar to 26% of the aerosol. The CMB model estimates explained that the combustion sources taken together contributed similar to 47% to the aerosol, which includes biomass burning (27%), vehicular emission (13%), coal (1%), kerosene (4%), and petroleum refining (2%). Other major sources that were apportioned were road dust (15%), crustal dust (26%), and construction dust (6%). There are inherent limitations in the source strength estimations because of uncertainty present in the source emission profiles that have been applied to the remote location of India. However, both the models (PCA-MLR and CMB) estimated the contribution of combustion sources to 42 and 47% respectively, which is comparable. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:997 / 1010
页数:14
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