Assessment of light extinction at a European polluted urban area during wintertime: Impact of PM1 composition and sources

Assessment of light extinction at a European polluted urban area during wintertime: Impact of PM1... In this paper, results from receptor modelling performed on a well-characterised PM1 dataset were combined to chemical light extinction data (bext) with the aim of assessing the impact of different PM1 components and sources on light extinction and visibility at a European polluted urban area. It is noteworthy that, at the state of the art, there are still very few papers estimating the impact of different emission sources on light extinction as we present here, although being among the major environmental challenges at many polluted areas. Following the concept of the well-known IMPROVE algorithm, here a tailored site-specific approach (recently developed by our group) was applied to assess chemical light extinction due to PM1 components and major sources.PM1 samples collected separately during daytime and nighttime at the urban area of Milan (Italy) were chemically characterised for elements, major ions, elemental and organic carbon, and levoglucosan. Chemical light extinction was estimated and results showed that at the investigated urban site it is heavily impacted by ammonium nitrate and organic matter. Receptor modelling (i.e. Positive Matrix Factorization, EPA-PMF 5.0) was effective to obtain source apportionment; the most reliable solution was found with 7 factors which were tentatively assigned to nitrates, sulphates, wood burning, traffic, industry, fine dust, and a Pb-rich source. The apportionment of aerosol light extinction (bext,aer) according to resolved sources showed that considering all samples together nitrate contributed at most (on average 41.6%), followed by sulphate, traffic, and wood burning accounting for 18.3%, 17.8% and 12.4%, respectively. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Transportation Research Part C: Emerging Technologies Elsevier

Assessment of light extinction at a European polluted urban area during wintertime: Impact of PM1 composition and sources

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0968-090X
D.O.I.
10.1016/j.envpol.2017.10.059
Publisher site
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Abstract

In this paper, results from receptor modelling performed on a well-characterised PM1 dataset were combined to chemical light extinction data (bext) with the aim of assessing the impact of different PM1 components and sources on light extinction and visibility at a European polluted urban area. It is noteworthy that, at the state of the art, there are still very few papers estimating the impact of different emission sources on light extinction as we present here, although being among the major environmental challenges at many polluted areas. Following the concept of the well-known IMPROVE algorithm, here a tailored site-specific approach (recently developed by our group) was applied to assess chemical light extinction due to PM1 components and major sources.PM1 samples collected separately during daytime and nighttime at the urban area of Milan (Italy) were chemically characterised for elements, major ions, elemental and organic carbon, and levoglucosan. Chemical light extinction was estimated and results showed that at the investigated urban site it is heavily impacted by ammonium nitrate and organic matter. Receptor modelling (i.e. Positive Matrix Factorization, EPA-PMF 5.0) was effective to obtain source apportionment; the most reliable solution was found with 7 factors which were tentatively assigned to nitrates, sulphates, wood burning, traffic, industry, fine dust, and a Pb-rich source. The apportionment of aerosol light extinction (bext,aer) according to resolved sources showed that considering all samples together nitrate contributed at most (on average 41.6%), followed by sulphate, traffic, and wood burning accounting for 18.3%, 17.8% and 12.4%, respectively.

Journal

Transportation Research Part C: Emerging TechnologiesElsevier

Published: Jan 1, 2018

References

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