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Extraction of tracer elements of particulate matter emission source using association rule mining
The source marker species represent the emission source in the ambient air. It aids in identifying specific emission sources, but it can deliver ambiguous results when similar species exhibit different emission sources. Therefore, robust marker/tracer species are always needed to clearly identify em...
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Published in: | Atmospheric pollution research 2024-06, Vol.15 (6), p.102109, Article 102109 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The source marker species represent the emission source in the ambient air. It aids in identifying specific emission sources, but it can deliver ambiguous results when similar species exhibit different emission sources. Therefore, robust marker/tracer species are always needed to clearly identify emission source. This study collected tracer elemental species for possible emission sources from Indian published literature and processed them by using machine learning-based apriori algorithm to obtain robust elemental marker of the emission source. Initially, significant rules were chosen with support >10% and lift >1.0. Subsequently, elemental markers have obtained by applying constraint i.e. conviction ≥1.1, lift ≥1.4 and confidence ≥20%. As an outcome, it reveals elemental markers of crustal emission (CE) (Al, Si, Fe, Ca, Mg, Ti), sea salt (SS) (Na, K), biomass burning (BB) (K), solid waste burning (SWB) (Ba, Cd, Cr, Sr), coal combustion (CC) (As, Se, Cr, Cd), oil combustion (OC) (V, Ni, S, As), and traffic emission (TE) (Cu, Pb, Zn, Mn, Cd, Ni). Finally, robust elemental markers corresponding to their respective emission source were derived by applying constraint of conviction ≥1.1, lift ≥1.5 and confidence ≥50% on the previously extracted association rule. Consequently, it defined CE by Mg, Al, Ca, Si, Fe, SS by Na, K, TE by Cu, Pb, Mn, Zn, SWB by Ba, Cr, Cd, Sr, OC by V, Ni, S, and CC by Se, As. Additionally, this study also demonstrate the successful implementation of the apriori algorithm for the aforementioned task.
•Apriori algorithm is used to extract tracer element of the emission activities.•Cu, Pb, Mn, and Zn are the source marker of Vehicular emission.•S, V, and Ni represent oil combustion and As, Se shows Coal combustion.•K represent biomass burning and Ba, Cd, Cr, and Sr for Solid waste burning.•Al, Si, Fe, Ca, Mg shows Crustal/Soil/Mineral/Construction dust emission marker. |
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ISSN: | 1309-1042 1309-1042 |
DOI: | 10.1016/j.apr.2024.102109 |