Source Apportionment of Urban Background Particulate Matter in Birmingham, United Kingdom Using a Mass Closure Model

Abstract

Particulate matter (PM) collected during the summer period of 2011 at the urban background of Elms Road Observatory Site (EROS) in Birmingham, United Kingdom was studied and apportioned using the mass closure model. Particulate matter samples were analysed for Cu, Zn, Fe, Ni, Mn, Cl -, NO 3 -, SO 4 2-, PO 4 3-, C 2 O 4 2-, Na + , NH 4 + , K + , Ca 2+ , OC and EC using the standard procedures. Results showed mean mass concentrations of 5.42 ± 1.7 µg m -3 for PM 2.5 and 5.41 ± 0.27 µg m -3 for PM 10-2.5 . Organic carbon (OC, 26%) formed the major component of PM 2.5 followed by sulphate (25%) and ammonium (12%). In the coarse PM fraction, ammonium, chloride and OC constituted 17, 15 and 14%, respectively of mass concentration. Metal concentrations in both PM fractions were less than 2% of the observed mass. The mass closure model applied to apportion PM 2.5 and PM 10-2.5 chemical species was able to identify four components namely: carbonaceous (45 and 19%, respectively), sea salt (7 and 25%), secondary aerosol (48 and 13%) and minerals (13 and 12%). The mass closure model was unable to explain all the chemical components in the coarse PM category leaving the unidentified mass as 31%. On the other hand, the model overestimated the mass of PM 2.5 by 14%. The study showed secondary aerosol and carbonaceous species as the dominating sources of PM pollution in the study area.

How Aeolian Dust Deteriorate Ambient Particulate Air Quality along an Expansive River Valley in Southern Taiwan? A Case Study of Typhoon Doksuri

“…Nevertheless, aeolian dust contributed to 17.8-20.5% of PM 10 on the right bank and 12.3-14.3% on the left bank of the Kaoping River after the ADE (Stage II). The results indicated that a small amount of finer aeolian dust emitted from the bare lands could be still suspended in the ambient air during the period of Stage II (Lin et al, 2007;Kuo et al, 2010;Taiwo et al, 2016). Additionally, the mass percentages of sea salts obtained from sites KA and PD were always higher than other sites during the ADE.…”

“…Previous studies reported that source identification and apportioning of PM had been recognized as one of the curial measures to quantify the major contributors of PM to improve the poor particulate air quality (Cao et al, 2009;Nayebare et al, 2016;Taiwo et al, 2016). Studies have used several measures to assess the comparative performance of various source apportionment techniques namely, CMB receptor modelling, positive matrix factorization, principal component analysis (PCA), absolute principal component analysis, and targeted factor analysis (Hopke et al, 2006;Brook et al, 2007;Nayebare et al, 2016).…”

“…Many source apportionment studies have attempted to develop and implement air pollution control strategies for urban areas (Li et al, 2013a;Ni et al, 2013;Taiwo et al, 2016). Receptor models have been widely used to estimate the contribution from various types of sources, except for aeolian dust, to ambient air quality.…”

Upgrading the Estimation of Daily PM10 Concentrations Utilizing Prediction Variables Reflecting Atmospheric Processes

“…Thus, sources and factors influencing aerosol levels must be well analyzed and controlled. Particle composition in Birmingham, clearly revealed an urban aerosol profile made up by combustion generated carbonaceous particles, secondary sulphates and nitrates from regional transport and predominantly coarse (PM COARSE = PM 10 -PM 2.5 ) dusts (Harrison et al, 2004;Taiwo, 2016). Non-exhaust particles derived from tire wear and break friction, also constitute an important source of PM in Birmingham, according to Pant et al (2015); Taiwo et al (2014) and Harrison et al (2003).…”

Accuracy of Advanced and Traditional Three-Way Factor Analysis Models for Determining Source Contributions to Particulate Matter

“…However, individual contributions of each source category to PM cannot be measured directly (Shen et al, 2014). Therefore, various source apportionment methods have been developed and applied (Zheng et al, 2011;Shen et al, 2014;Taiwo, 2016;Vu et al, 2016).…”