Air pollution prediction models of particles, As, Cd, Ni and Pb in a highly industrialized area in Castellón (NE, Spain)

Abstract

The objective of this study was to elaborate a series of mathematical models with the aim of short-term prediction of TSP, PM10, As, Cd, Ni and Pb in ambient air. These pollutants depend on some known variables (meteorological variables). The reason for choosing this pollutant type is that particulate matter may present a much higher potential risk despite its low representativeness as compared with the gas pollutant group. A positive correlation between high particle concentrations and deterioration in public health has been shown in recent studies. The elements As, Cd, Ni and Pb in PM10 were also analyzed to determine the toxicity of these particles. The goal is to provide a useful instrument to alert the population facing possible episodes of high concentrations of atmospheric pollutants. The study was carried out in a highly industrialized area in the ceramic cluster of Castellón for 5 years (2001–2005). The origin of the contamination in this area is both natural and anthropogenic. The natural origin is due to the resuspension of mineral materials from the surrounding mountains and from the long-range transport of materials from North Africa. The anthropogenic contamination sources that stand out include the non-metallic mineral material industries (ceramic production), chemical industries (color, frit and enamel manufacturing), as well as vehicular traffic. Once the particle samples were collected in quartz fiber filters, the concentration levels of TSP and PM10 were determined gravimetrically. The chemical analysis of the filters was carried out by ICP-MS. Predictive models have been constructed by using multiple regression analysis together with time series models (ARIMA). The SPSS 14.0 statistical software has been employed to analyze the obtained experimental data.