Source apportionment of polycyclic aromatic hydrocarbons in urban air using positive matrix factorization and spatial distribution analysis

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@article{be9e081bcb5f4e7cbd953e8fb49aadc3,
title = "Source apportionment of polycyclic aromatic hydrocarbons in urban air using positive matrix factorization and spatial distribution analysis",
abstract = "Polycyclic aromatic hydrocarbons (PAH) are currently generating a great deal of interest because of their recognised toxicity, including carcinogenicity. In this study, source apportionment (SA) has been carried out using Positive Matrix Factorisation (PMF) with a dataset of 29 individual PAH (sum of vapour and particulate forms) collected by the UK National Network between 2002 and 2006. Analysis of data from 14 urban sites revealed four major source categories corresponding to unburned petroleum, diesel combustion, wood combustion and coal combustion. When a separate set of sites known to be influenced by local industrial sources was analysed, three source categories were identified corresponding to the unburned petroleum, diesel combustion and coal combustion seen in the full data analysis. When SA data were applied to the individual sites, the estimated apportionment could be explained in terms of local emission characteristics. Unburned petroleum showed the highest contribution to the sum of PAH, averaging 51.9% across the network, but benzo(a)pyrene (BaP) was more influenced by the coal combustion source which contributed 59.5% across the entire network. At the subset of sites with local industrial influence, industry was both the main contributor to the sum of PAH (accounting for 48.4% of PAH mass) and of BaP (67.9% of mass). A spatial analysis was also conducted in which the traffic source was evaluated by the difference between a roadside and a nearby urban background site, the urban source by difference between urban background and a rural site, and the industrial source by difference between a site close to a major steelworks subtracting data from a local urban background site. This showed considerable similarity between the net urban contribution and the road traffic factor, and between the net industrial contribution and the PMF coal factor profile. In both cases the congener profiles corresponded fairly well to UK national emissions inventory data. When PMF was applied separately to a more recent dataset for particle-bound PAH (2008-10) in three site groupings, it was able to distinguish the domestic coal burning source from the industry-related coal combustion source. For the urban sites, vehicle exhausts contributed the largest amount of particulate PAH and BaP across the whole year, with significant attribution to domestic coal combustion seen in the cold season.",
keywords = "Polycyclic aromatic hydrocarbons, Source apportionment, Receptor modelling, PMF",
author = "E. Jang and M.S. Alam and R.M. Harrison",
year = "2013",
month = nov
day = "1",
doi = "10.1016/j.atmosenv.2013.06.056",
language = "English",
volume = "79",
pages = "271--285",
journal = "Atmospheric Environment",
issn = "1352-2310",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Source apportionment of polycyclic aromatic hydrocarbons in urban air using positive matrix factorization and spatial distribution analysis

AU - Jang, E.

AU - Alam, M.S.

AU - Harrison, R.M.

PY - 2013/11/1

Y1 - 2013/11/1

N2 - Polycyclic aromatic hydrocarbons (PAH) are currently generating a great deal of interest because of their recognised toxicity, including carcinogenicity. In this study, source apportionment (SA) has been carried out using Positive Matrix Factorisation (PMF) with a dataset of 29 individual PAH (sum of vapour and particulate forms) collected by the UK National Network between 2002 and 2006. Analysis of data from 14 urban sites revealed four major source categories corresponding to unburned petroleum, diesel combustion, wood combustion and coal combustion. When a separate set of sites known to be influenced by local industrial sources was analysed, three source categories were identified corresponding to the unburned petroleum, diesel combustion and coal combustion seen in the full data analysis. When SA data were applied to the individual sites, the estimated apportionment could be explained in terms of local emission characteristics. Unburned petroleum showed the highest contribution to the sum of PAH, averaging 51.9% across the network, but benzo(a)pyrene (BaP) was more influenced by the coal combustion source which contributed 59.5% across the entire network. At the subset of sites with local industrial influence, industry was both the main contributor to the sum of PAH (accounting for 48.4% of PAH mass) and of BaP (67.9% of mass). A spatial analysis was also conducted in which the traffic source was evaluated by the difference between a roadside and a nearby urban background site, the urban source by difference between urban background and a rural site, and the industrial source by difference between a site close to a major steelworks subtracting data from a local urban background site. This showed considerable similarity between the net urban contribution and the road traffic factor, and between the net industrial contribution and the PMF coal factor profile. In both cases the congener profiles corresponded fairly well to UK national emissions inventory data. When PMF was applied separately to a more recent dataset for particle-bound PAH (2008-10) in three site groupings, it was able to distinguish the domestic coal burning source from the industry-related coal combustion source. For the urban sites, vehicle exhausts contributed the largest amount of particulate PAH and BaP across the whole year, with significant attribution to domestic coal combustion seen in the cold season.

AB - Polycyclic aromatic hydrocarbons (PAH) are currently generating a great deal of interest because of their recognised toxicity, including carcinogenicity. In this study, source apportionment (SA) has been carried out using Positive Matrix Factorisation (PMF) with a dataset of 29 individual PAH (sum of vapour and particulate forms) collected by the UK National Network between 2002 and 2006. Analysis of data from 14 urban sites revealed four major source categories corresponding to unburned petroleum, diesel combustion, wood combustion and coal combustion. When a separate set of sites known to be influenced by local industrial sources was analysed, three source categories were identified corresponding to the unburned petroleum, diesel combustion and coal combustion seen in the full data analysis. When SA data were applied to the individual sites, the estimated apportionment could be explained in terms of local emission characteristics. Unburned petroleum showed the highest contribution to the sum of PAH, averaging 51.9% across the network, but benzo(a)pyrene (BaP) was more influenced by the coal combustion source which contributed 59.5% across the entire network. At the subset of sites with local industrial influence, industry was both the main contributor to the sum of PAH (accounting for 48.4% of PAH mass) and of BaP (67.9% of mass). A spatial analysis was also conducted in which the traffic source was evaluated by the difference between a roadside and a nearby urban background site, the urban source by difference between urban background and a rural site, and the industrial source by difference between a site close to a major steelworks subtracting data from a local urban background site. This showed considerable similarity between the net urban contribution and the road traffic factor, and between the net industrial contribution and the PMF coal factor profile. In both cases the congener profiles corresponded fairly well to UK national emissions inventory data. When PMF was applied separately to a more recent dataset for particle-bound PAH (2008-10) in three site groupings, it was able to distinguish the domestic coal burning source from the industry-related coal combustion source. For the urban sites, vehicle exhausts contributed the largest amount of particulate PAH and BaP across the whole year, with significant attribution to domestic coal combustion seen in the cold season.

KW - Polycyclic aromatic hydrocarbons

KW - Source apportionment

KW - Receptor modelling

KW - PMF

UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-84880942131&partnerID=8YFLogxK

U2 - 10.1016/j.atmosenv.2013.06.056

DO - 10.1016/j.atmosenv.2013.06.056

M3 - Article

AN - SCOPUS:84880942131

VL - 79

SP - 271

EP - 285

JO - Atmospheric Environment

JF - Atmospheric Environment

SN - 1352-2310

ER -