Major component composition of urban PM10 and PM2.5 in Ireland

Yin, Jianxin; Allen, Andrew G.; Harrison, Roy M.; Jennings, S. G.; Wright, Evelyn; Fitzpatrick, M.; Healy, T.V.; Barry, Eugene F.; Čeburnis, Darius; McCusker, D.

doi:10.1016/j.atmosres.2005.03.006

Cited by 74 publications

(62 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…2. These values are broadly in line with those observed at a different site in Cork City from July-August 2001 (Yin et al, 2005). Seasonal variation of these variables has been discussed in detail in a previous article (Hellebust et al, 2010).…”

Section: Semi-continuous Measurements and Meteorologysupporting

confidence: 74%

Source apportionment of PM2.5 in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

et al. 2010

View full text Add to dashboard Cite

Abstract. An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed for the measurement of the size resolved chemical composition of single particles at a site in Cork Harbour, Ireland for three weeks in August 2008. The ATOFMS was co-located with a suite of semi-continuous instrumentation for the measurement of particle number, elemental carbon (EC), organic carbon (OC), sulfate and particulate matter smaller than 2.5 µm in diameter (PM 2.5 ). The temporality of the ambient ATOFMS particle classes was subsequently used in conjunction with the semi-continuous measurements to apportion PM 2.5 mass using positive matrix factorisation. The synergy of the single particle classification procedure and positive matrix factorisation allowed for the identification of six factors, corresponding to vehicular traffic, marine, long-range transport, various combustion, domestic solid fuel combustion and shipping traffic with estimated contributions to the measured PM 2.5 mass of 23%, 14%, 13%, 11%, 5% and 1.5% respectively. Shipping traffic was found to contribute 18% of the measured particle number (20-600 nm mobility diameter), and thus may have important implications for human health considering the size and composition of ship exhaust particles. The positive matrix factorisation procedure enabled a more refined interpretation of the single particle results by providing source contributions to PM 2.5 mass, while the single particle data enabled the identification of additional factors not possible with typical semi-continuous measurements, including local shipping traffic.

show abstract

Section: Semi-continuous Measurements and Meteorologysupporting

confidence: 74%

Source apportionment of PM2.5 in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

et al. 2010

View full text Add to dashboard Cite

show abstract

“…multiplying NO − 3 by 1.29 yields an estimate of the NH 4 NO 3 concentration present in the original PM 2.5 sample (Dabek-Zlotorzynska et al, 2011). PMC has been used to apportion contributions to urban and rural PM 10 , PM 2.5 and PM 2.5−10 in Ireland (Yin et al, 2005), coastal, rural and urban PM 10 in Scotland (Gibson et al, 2009), urban background and roadside locations in England (Harrison et al, 2003) and to urban, rural and coastal PM 2.5 in Canada (Dabek-Zlotorzynska et al, 2011). For the BORTAS-B study a new PMC woodsmoke enrichment factor was calculated.…”

Section: Receptor Modelsmentioning

confidence: 99%

A comparison of four receptor models used to quantify the boreal wildfire smoke contribution to surface PM2.5 in Halifax, Nova Scotia during the BORTAS-B experiment

et al. 2015

View full text Add to dashboard Cite

Abstract. This paper presents a quantitative comparison of the four most commonly used receptor models, namely absolute principal component scores (APCS), pragmatic mass closure (PMC), chemical mass balance (CMB) and positive matrix factorization (PMF). The models were used to predict the contributions of a wide variety of sources to PM 2.5 mass in Halifax, Nova Scotia during the experiment to quantify the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BOR-TAS). However, particular emphasis was placed on the capacity of the models to predict the boreal wildfire smoke contributions during the BORTAS experiment. The performance of the four receptor models was assessed on their ability to predict the observed PM 2.5 with an R 2 close to 1, an intercept close to zero, a low bias and low RSME. Using PMF, a new woodsmoke enrichment factor of 52 was estimated for use in the PMC receptor model. The results indicate that the APCS and PMC receptor models were not able to accurately resolve total PM 2.5 mass concentrations below 2 µg m −3 . CMB was better able to resolve these low PM 2.5 concentrations, but it could not be run on 9 of the 45 days of PM 2.5 samples. PMF was found to be the most robust of the four models since it was able to resolve PM 2.5 mass below 2 µg m −3 , predict PM 2.5 mass on all 45 days and utilise an unambiguous woodsmoke chemical tracer. The median woodsmoke relative contributions to PM 2.5 estimated using PMC, APCS, CMB and PMF were found to be 0.08, 0.09, 3.59 and 0.14 µg m −3 respectively. The contribution predicted by the CMB model seemed to be clearly too high based on other observations. The use of levoglucosan as a tracer for woodsmoke was found to be vital for identifying this source.

show abstract

“…8 Determination of carbonaceous species was based on a reflectance method, 9 which assumed elemental carbon (EC) to be the principal light-absorbing particulate species present in ambient air. 10 A Sunset Laboratory Carbon Analyzer (Model 4L) was used to determine the relative concentrations of elemental and organic carbon (OC).…”

Section: Sampling and Analysismentioning

confidence: 99%

Influence of intensive agriculture on dry deposition of aerosol nutrients

Allen

Cardoso

Wiatr

et al. 2010

J. Braz. Chem. Soc.

View full text Add to dashboard Cite

É apresentado um modelo para quantificação de fontes e deposição de espécies nutrientes que contribuem com a formação e concentração do aerossol atmosférico. Para este procedimento foram utilizadas ferramentas estatísticas como: a análise de componentes principais (PCA) e análise de regressão linear múltipla (MLRA) associadas a modelos de deposição de partículas segregadas por tamanho. Em região rural do sudeste do Brasil, a queima de biomassa, produtos de reações secundárias, e re-suspensão de poeira do solo possibilitaram explicar 43%, 31% e 21% da massa do MP 2.5 , respectivamente. A re-suspensão de poeira e a queima de biomassa contribuíram com 22% e 19%, respectivamente, da massa do MP 10 . A re-suspensão possibilitou explicar cerca da metade da massa das partículas grossas. Cerca de 40% de NO 3 --N, 20% de fósforo e 55% de potássio depositados tem origem nas emissões relacionadas com a agricultura. Atualmente a deposição sobre a floresta tropical é aumentada pelos fatores de 12.2 (N), 6.2 (P) e 2.6 (K) com relação a aqueles que existiam nas condições naturais do passado.A procedure is presented for quantification of sources contributing to atmospheric aerosol chemical nutrient concentrations and dry deposition fluxes. Source apportionment using principal component analysis (PCA) and multiple linear regression analysis (MLRA) was followed by application of a size-segregated particle dry deposition model. In a rural region of southeast Brazil, biomass burning, products of secondary reactions, and soil dust re-suspension explained 43%, 31% and 21% of PM 2.5 mass, respectively. Re-suspension and biomass burning contributed 22% and 19%, respectively, to PM 10 mass, and re-suspension accounted for approximately half of the mass of coarse particles. At least 40% of NO 3 --N, 20% of phosphorus and 55% of potassium deposited originated from agriculture-related emissions. Deposition to tropical forest is currently higher than the minimum under natural conditions by factors of 12.2 (N), 6.2 (P) and 2.6 (K).

show abstract

Major component composition of urban PM10 and PM2.5 in Ireland

Cited by 74 publications

References 34 publications

Source apportionment of PM<sub>2.5</sub> in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

Source apportionment of PM<sub>2.5</sub> in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

A comparison of four receptor models used to quantify the boreal wildfire smoke contribution to surface PM<sub>2.5</sub> in Halifax, Nova Scotia during the BORTAS-B experiment

Influence of intensive agriculture on dry deposition of aerosol nutrients

Contact Info

Product

Resources

About

Major component composition of urban PM10 and PM2.5 in Ireland

Cited by 74 publications

References 34 publications

Source apportionment of PM&lt;sub&gt;2.5&lt;/sub&gt; in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

Source apportionment of PM&lt;sub&gt;2.5&lt;/sub&gt; in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

A comparison of four receptor models used to quantify the boreal wildfire smoke contribution to surface PM&lt;sub&gt;2.5&lt;/sub&gt; in Halifax, Nova Scotia during the BORTAS-B experiment

Influence of intensive agriculture on dry deposition of aerosol nutrients

Contact Info

Product

Resources

About

Source apportionment of PM<sub>2.5</sub> in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

Source apportionment of PM<sub>2.5</sub> in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

A comparison of four receptor models used to quantify the boreal wildfire smoke contribution to surface PM<sub>2.5</sub> in Halifax, Nova Scotia during the BORTAS-B experiment