Among the analytical technique developed so far for atmospheric aerosol characterization, Fourier Transform Infrared spectroscopy (FTIR) allows to determine both organic fraction (functional groups) and some inorganic components (ammonium, nitrate, sulfate, silicates, carbonates). The FTIR analysis on particulate matter collected on filters has encountered great success since the method is basically not destructive so that the sample can be analyzed further using other techniques. It is worthy to note that the approaches used in the literature to determine the above mentioned aerosol components generally involve rinsing the sample with appropriate solvents (Maria et al., 2002; Russel et al., 2009). In this work we focus on the quantification of the inorganic components of PM (NO3-, SO42-, NH4+) by FTIR and therefore avoiding any sample pre-treatment. Of each sample was recorded in the absorption spectrum transmittance. To obtain quantitative information from the FTIR spectra, a multivariate approach based on Partial Least Squares ( PLS) has been applied. The samples themselves were used as standards for the training of the multivariate model; input data were obtained analyzing the samples with ion chromatography (Piazzalunga et al., 2013). The development of PLS models was performed on a database of 300 filters collected in several measurement campaigns carried out in Milan and Genoa between 2010 and 2012. A preliminary analysis of IC data with Principal Component Analysis (PCA) shows how the first two principal components explain 98% of the total variance. Five different PLS models were tested. The number of latent variables for each model was chosen minimizing RMSECV (error in cross validation). The models for the examined species show a good agreement with IC data, in figure 2 is reported the comparison between FTIR and IC sulphate quantification. In conclusion, coupling FTIR with PLS methods allows to quantify major ions in PM samples without pre-treatment reducing costs and time of analysis. References Piazzalunga et al., 2013, Anal. Bio. Chem. 405, 1123 - 1132 Russell et al., 2009, Atmospheric Environment, 43(38), 6100–6105 Maria et al., 2002, Atmospheric Environment, 36(33), 5185–5196

Development of a non-destructive method based on infrared analysis for quantification of ionic components in atmospheric particulate matter / A. Piazzalunga, D. Ballabio, V. Bernardoni, P. Fermo, U. Molteni, P. Prati, R. Vecchi, G. Valli. ((Intervento presentato al convegno EAC : European aerosol conference tenutosi a Prague nel 2013.

Development of a non-destructive method based on infrared analysis for quantification of ionic components in atmospheric particulate matter

V. Bernardoni;P. Fermo;R. Vecchi;G. Valli
2013

Abstract

Among the analytical technique developed so far for atmospheric aerosol characterization, Fourier Transform Infrared spectroscopy (FTIR) allows to determine both organic fraction (functional groups) and some inorganic components (ammonium, nitrate, sulfate, silicates, carbonates). The FTIR analysis on particulate matter collected on filters has encountered great success since the method is basically not destructive so that the sample can be analyzed further using other techniques. It is worthy to note that the approaches used in the literature to determine the above mentioned aerosol components generally involve rinsing the sample with appropriate solvents (Maria et al., 2002; Russel et al., 2009). In this work we focus on the quantification of the inorganic components of PM (NO3-, SO42-, NH4+) by FTIR and therefore avoiding any sample pre-treatment. Of each sample was recorded in the absorption spectrum transmittance. To obtain quantitative information from the FTIR spectra, a multivariate approach based on Partial Least Squares ( PLS) has been applied. The samples themselves were used as standards for the training of the multivariate model; input data were obtained analyzing the samples with ion chromatography (Piazzalunga et al., 2013). The development of PLS models was performed on a database of 300 filters collected in several measurement campaigns carried out in Milan and Genoa between 2010 and 2012. A preliminary analysis of IC data with Principal Component Analysis (PCA) shows how the first two principal components explain 98% of the total variance. Five different PLS models were tested. The number of latent variables for each model was chosen minimizing RMSECV (error in cross validation). The models for the examined species show a good agreement with IC data, in figure 2 is reported the comparison between FTIR and IC sulphate quantification. In conclusion, coupling FTIR with PLS methods allows to quantify major ions in PM samples without pre-treatment reducing costs and time of analysis. References Piazzalunga et al., 2013, Anal. Bio. Chem. 405, 1123 - 1132 Russell et al., 2009, Atmospheric Environment, 43(38), 6100–6105 Maria et al., 2002, Atmospheric Environment, 36(33), 5185–5196
2013
Settore CHIM/01 - Chimica Analitica
Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
Development of a non-destructive method based on infrared analysis for quantification of ionic components in atmospheric particulate matter / A. Piazzalunga, D. Ballabio, V. Bernardoni, P. Fermo, U. Molteni, P. Prati, R. Vecchi, G. Valli. ((Intervento presentato al convegno EAC : European aerosol conference tenutosi a Prague nel 2013.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/236608
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