Evaluation and application of a statistical model for assessment of long-range transported proportion of PM 2.5 in the United Kingdom and in Finland

Abstract

We have developed a simple statistical model for the estimation of the long-range transport (LRT) contribution to PM 2.5 concentrations. The modelling is based on linear regressions of the ‘Co-operative programme for monitoring and evaluating the long-range transmission of air pollutants in Europe’ (EMEP) background ionic components (SO 4 2−, NO 3 −, NH 4 +) with the monitored PM 2.5 concentrations. We present an evaluation and application of the model against data measured in the United Kingdom (UK) and in Finland. We have studied the correlation of ion sum values with the PM 2.5 data measured at two EMEP stations in Finland (i.e., a comparison of ionic sum and PM 2.5 at one station). The statistical correlations of the PM 2.5 concentrations with the ion sum values were very high ( R 2 varied from 0.77 to 0.83) at both of the stations considered; this provides confidence that the ion sum is a good proxy variable for the LRT PM 2.5. The comparison of different modelling options using the data measured in the UK showed that the regression model gave systematically substantially better results than the model using merely sulphate concentrations. Similarly, using the distance weighted ion sum based on data from two EMEP stations gave better correlation, compared with the option of using only one EMEP station. The evaluated average LRT contribution accounted for 35–37% of the regional air PM 2.5 concentrations in UK from 1998 to 2000. The corresponding contributions at two urban stations in London were 24–31%. We conclude that the model is a useful and simple tool for the assessment of LRT PM 2.5 that is applicable within a fairly good accuracy.