Articles | Volume 15, issue 20
https://doi.org/10.5194/amt-15-6051-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-6051-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Oct 2022
Research article |
| 21 Oct 2022
| 21 Oct 2022
Source apportionment resolved by time of day for improved deconvolution of primary source contributions to air pollution
Sahil Bhandari
McKetta Department of Chemical Engineering, The University of Texas at Austin, Texas, USA
Department of Mechanical Engineering, University of British Columbia, Vancouver, Canada
Zainab Arub
Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India
Gazala Habib
Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India
Joshua S. Apte
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, UC Berkeley,
Berkeley, California, USA
School of Public Health, UC Berkeley, Berkeley, California, USA
McKetta Department of Chemical Engineering, The University of Texas at Austin, Texas, USA
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Short summary
We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.
We present a new method to conduct source apportionment resolved by time of day using the...
