The effect of long-range air mass transport pathways on PM sub(10) and NO sub(2) concentrations at urban and rural background sites in Ireland: Quantification using clustering techniques

• Published in: Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering Toxic/hazardous substances & environmental engineering, 2015-06, Vol.50 (7), p.647-658
• Main Authors: Donnelly, Aoife A, Broderick, Brian M, Misstear, Bruce D
• Format: Article
• Language: English
• Subjects: Air masses; Air quality; Clusters; Mathematical models; Modelling; Nitrogen dioxide; Pathways; Rural; Transport
• ISSN: 1093-4529; 1532-4117
• DOI: 10.1080/10934529.2015.1011955

The specific aims of this paper are to: (i) quantify the effects of various long range transport pathways nitrogen dioxide (NO sub(2)) and particulate matter with diameter less than 10 mu m (PM sub(10)) concentrations in Ireland and identify air mass movement corridors which may lead to incidences poor air quality for application in forecasting; (ii) compare the effects of such pathways at various sites; (iii) assess pathways associated with a period of decreased air quality in Ireland. The origin of and the regions traversed by an air mass 96h prior to reaching a receptor is modelled and k-means clustering is applied to create air-mass groups. Significant differences in air pollution levels were found between air mass cluster types at urban and rural sites. It was found that easterly or recirculated air masses lead to higher NO sub(2) and PM sub(10) levels with average NO sub(2) levels varying between 124% and 239% of the seasonal mean and average PM sub(10) levels varying between 103% and 199% of the seasonal mean at urban and rural sites. Easterly air masses are more frequent during winter months leading to higher overall concentrations. The span in relative concentrations between air mass clusters is highest at the rural site indicating that regional factors are controlling concentration levels. The methods used in this paper could be applied to assist in modelling and forecasting air quality based on long range transport pathways and forecast meteorology without the requirement for detailed emissions data over a large regional domain or the use of computationally demanding modelling techniques.