OPEN ACCESS

Articles online

Trajectory-Based Models and Remote Sensing for Biomass Burning Assessment in Bangladesh

Category: PM2.5, Atmospheric Aerosols and Urban Air Quality

Volume: 17 | Issue: 2 | Pages: 465-475
DOI: 10.4209/aaqr.2016.07.0304
PDF | RIS | BibTeX

Afshin Ommi1, Fereshteh Emami1, Naděžda Zíková1, Philip K. Hopke 1, Bilkis A. Begum2

  • 1 Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY 13599, USA
  • 2 Chemistry Division, Atomic Energy Centre, Dhaka, Bangladesh

Highlights

Apportionments were made for 4 cities in Bangladesh in the period of 2010–2012.
PM2.5 from biomass burning is anomalously high in Rajshahi Bangladesh.
Trajectory ensemble methods were applied to source apportionment results.
MODIS fire data and the trajectories identified Nepal and northern India as source areas.
Higher wind speeds and terrain channeling may explain the higher concentrations.


Abstract

Biomass burning is a major global source of fine primary carbonaceous particles including strongly light absorbing compounds and marker compounds. In a prior study, particulate matter (PM) sampling was conducted during 2010–2012 period at sites in Rajshahi, Dhaka, Khulna, and Chittagong. PM samples were collected using dichotomous samplers in the PM2.5 and PM2.5–10 size fractions. The samples were analyzed for mass, black carbon at 370 nm (UVBC) and 880 nm (BC), Delta-C (UVBC-BC), and elemental compositions with X-ray fluorescence. Source apportionment using PMF was performed to identify and quantify the PM sources. Results showed that biomass burning contributions during winters in Rajshahi were substantially higher than in Dhaka, Khulna, or Chittagong. Agricultural burning areas of the Indo-Gangetic Plain were hypnotized as the primary source region. The present study explores the relationships between the source regions using trajectory ensemble models and determines if transported biomass PM has disproportionately affected air quality in Rajshahi. The probable source locations that were identified included Pakistan, northern India, Nepal, Bangladesh, Northeastern India, and Myanmar. To assess the model results, satellite measurements of fire radiative power (FRP) were calculated based on fire data acquired by the MODerate-resolution Imaging Spectro-radiometer (MODIS) sensor in six defined areas. High fire occurrences from MODIS coincident with the source regions identified in Nepal, Northeastern India and Myanmar in winter. The instantaneous FRP values ranged between 4.4 MW and 2449 MW. The mean winter FRP values for Nepal and Northeastern India were higher than for the other regions with Nepal having the overall highest value. Fire locations with their mean power, NASA Satellite pictures and particles speed along trajectories have been analyzed. In summary, the integrated outcome of the different techniques has identified Northern India and Nepal as the main source area responsible for the increased biomass burning concentration difference at Rajshahi.

Keywords

Biomass burning PM2.5 Trajectory ensemble models Fire radiative power (FRP) MODIS


Related Article

Small-Scale Study of Siberian Biomass Burning: II. Smoke Hygroscopicity

Olga B. Popovicheva , Natalia M. Persiantseva, Mikhail A. Timofeev, Natalia K. Shonija, Valerii S. Kozlov
Volume: 16 | Issue: 7 | Pages: 1558-1568
DOI: 10.4209/aaqr.2015.11.0648
PDF

The Simulation of Long-Range Transport of Biomass Burning Plume and Short-Range Transport of Anthropogenic Pollutants to a Mountain Observatory in East Asia during the 7-SEAS/2010 Dongsha Experiment

Ming-Tung Chuang , Joshua S. Fu, Chung-Te Lee, Neng-Huei Lin, Yang Gao, Sheng-Hsiang Wang, Guey-Rong Sheu, Ta-Chih Hsiao, Jia-Lin Wang, Ming-Cheng Yen, Tang-Huang Lin, Narisara Thongboonchoo
Volume: 16 | Issue: 11 | Pages: 2933-2949
DOI: 10.4209/aaqr.2015.07.0440
PDF

Trends of PM2.5 and Chemical Composition in Beijing, 2000–2015

Jianlei Lang , Yanyun Zhang, Ying Zhou, Shuiyuan Cheng, Dongsheng Chen, Xiurui Guo, Sha Chen, Xiaoxin Li, Xiaofan Xing, Haiyan Wang
Volume: 17 | Issue: 2 | Pages: 412-425
DOI: 10.4209/aaqr.2016.07.0307
PDF | Supplemental material
;