Finding regions of influence on SO2 and SO=4 daily concentration measurements at four sites in Spain
Abstract. Contamination by the pollutants SO2 and SO=4 was analyzed for the 1989–1992 period at four regional stations in Spain under the auspices of the EMEP-BAPMON program. The evolution of the time series of the daily pollution has also been assessed, and high mean concentrations at La Cartuja and Logroño observed, with values of 3.8 and 4.5 μg m–3 for SO2, respectively. Maximum annual concentrations were recorded in 1989, when SO2 reached values of 6.24, 5.39, 5.71, and 9.30 μg m–3 for the stations of La Cartuja, San Pablo de los Montes, Roquetas, and Logroño, respectively. This work attempts to establish a relationship between the concentrations of the pollutants – both SO2 gas and SO=4 aerosol – and the zones of emission or persistence of these long-range transported pollutants. In this way, those regions showing a greater impact on the air quality in each season have been determined. To achieve this, the trajectories of the air masses carrying away the pollution to each of the receiving stations were considered and followed by a sectorial analysis. Nonparametric statistical methods were implemented to contrast the chemical homogeneity among the different sectors. The criterion that several homogeneous sectors form a chemically homogeneous region was used. To improve this sectorial analysis, we have proposed a new technique based on the Potential-Source-Contribution Function (PSCF). Starting out from a set of specified regions, considered to be chemically homogeneous domains, it is possible to determine the likelihood that an air mass with particular characteristics (e.g., that a value of the daily concentration higher than the mean recorded at the station has been obtained) will arrive at a given station after having crossed one of the previously defined regions. Using this technique, it is possible to determine the source regions through which the air masses circulate and bring high pollution concentrations to the studied stations. Thanks to the PSCF, these statistical methods offer, through a sectorial analysis, the possibility to pass from a qualitative to a more quantitative view.
