Source Apportionment of Particulate Matter in Urban Snowpack Using End-Member Mixing Analysis and Positive Matrix Factorization Model

Mikhail Y. Semenov, Natalya A. Onishchuk, Olga G. Netsvetaeva and Tamara V. Khodzher
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Mikhail Y. Semenov: Limnological Institute of Siberian Branch, Russian Academy of Sciences, Ulan-Batorskaya St. 3, 664033 Irkutsk, Russia
Natalya A. Onishchuk: Limnological Institute of Siberian Branch, Russian Academy of Sciences, Ulan-Batorskaya St. 3, 664033 Irkutsk, Russia
Olga G. Netsvetaeva: Limnological Institute of Siberian Branch, Russian Academy of Sciences, Ulan-Batorskaya St. 3, 664033 Irkutsk, Russia
Tamara V. Khodzher: Limnological Institute of Siberian Branch, Russian Academy of Sciences, Ulan-Batorskaya St. 3, 664033 Irkutsk, Russia

Sustainability, 2021, vol. 13, issue 24, 1-17

Abstract: The aim of this study was to identify particulate matter (PM) sources and to evaluate their contributions to PM in the snowpack of three East Siberian cities. That was the first time when the PM accumulated in the snowpack during the winter was used as the object for source apportionment study in urban environment. The use of long-term integrated PM samples allowed to exclude the influence of short-term weather conditions and anthropogenic activities on PM chemistry. To ascertain the real number of PM sources and their contributions to air pollution the results of source apportionment using positive matrix factorization model (PMF) were for the first time compared to the results obtained using end-member mixing analysis (EMMA). It was found that Si, Fe and Ca were the tracers of aluminosilicates, non-exhaust traffic emissions and concrete deterioration respectively. Aluminum was found to be the tracer of both fossil fuel combustion and aluminum production. The results obtained using EMMA were in good agreement with those obtained using PMF. However, in some cases, the non-point sources identified using PMF were the combinations of two single non-point sources identified using EMMA, whereas the non-point sources identified using EMMA were split by PMF into two single non-point sources. The point sources were clearly identified using both techniques.

Keywords: particulate matter; snowpack; Eastern Siberia; sources; tracers; EMMA; PMF (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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