Showing papers by "Maria C.M. Alvim-Ferraz published in 2007"

Multiple linear regression and artificial neural networks based on principal components to predict ozone concentrations

Abstract: The prediction of tropospheric ozone concentrations is very important due to the negative impacts of ozone on human health, climate and vegetation. The development of models to predict ozone concentrations is thus very useful because it can provide early warnings to the population and also reduce the number of measuring sites. The aim of this study was to predict next day hourly ozone concentrations through a new methodology based on feedforward artificial neural networks using principal components as inputs. The developed model was compared with multiple linear regression, feedforward artificial neural networks based on the original data and also with principal component regression. Results showed that the use of principal components as inputs improved both models prediction by reducing their complexity and eliminating data collinearity.

Influence of traffic emissions on the composition of atmospheric particles of different sizes – Part 1: concentrations and elemental characterization

Abstract: Epidemiological studies initially considered the impact of total solid particles on human health, but according to the acquired knowledge about the worse effect of smaller particles, those studies turned to consider the impact of PM10. However, for the last decade PM2.5 began to be more important, once as they are smaller they can penetrate deeper in the lungs, being possible their trapping in alveoli and worse effects on human health. Therefore, more information on PM2.5 should be provided namely concerning the levels and elemental composition. Considering the relevance of traffic on the emission of particles of small sizes, this work included the detailed characterization of PM10 and PM2.5, sampled at two sites directly influenced by traffic, as well as at two reference sites, aiming a further evaluation of the influence of PM10 and PM2.5 on public health. The specific objectives were to study the influence of traffic emission on PM10 and PM2.5 characteristics, considering concentration, size distribution and elemental composition. PM10 and PM2.5 samples were collected using low-volume samplers; the element analyses were performed by particle induced X-ray emission (PIXE). At the sites influenced by traffic emissions PM10 and PM2.5 concentrations were 7–9 and 6–7 times higher than at the background sites. The presence of 17 elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn and Pb) was determined in both PM fractions; particle metal contents were 3–44 and 3–27 times higher for PM10 and PM2.5, respectively, than at the backgrounds sites. The elements originated mostly from anthropogenic activities (S, K, V, Mn, Ni, Zn and Pb) were predominantly present in PM2.5, while the elements mostly originated from crust (Mg, Al, Si and Ca) predominantly occurred in PM2.5–10. The results also showed that in coastal areas sea salt spray is an important source of particles, influencing PM concentration and distributions (PM10 increased by 46%, PM2.5/PM10 decreased by 26%), as well as PM compositions (Cl in PM10 was 11 times higher).

Air Quality Improvements Using European Environment Policies: A Case Study of SO2 in a Coastal Region in Portugal

Abstract: The European Union (EU) has defined several efforts for preventing and controlling air pollution that have led to a generalized reduction of health risks and environmental effects. One example of these efforts was the establishment of legislation that imposed a reduction of sulfur content in fuels, switching to cleaner fuels for industry and motor vehicles (Auto-Oil Directives). The goal of this study was to evaluate the first trends in the air quality of Oporto Metropolitan Area (Oporto-MA) related to implementation of these directives in Portugal since 2000. Therefore, sulfur dioxide (SO2) concentration data from air quality monitoring sites were analyzed for the period 1999 through 2003. It was observed that daily SO2 concentrations in the industrial area are much higher than those of the urban and rural areas, reflecting the influence of the industrial sector. The annual SO2 concentrations for the consecutive years of analysis decreased considerably for all the monitoring sites. A considerable decreas...

Influence Of Traffic On The ElementalComposition Of PM10 And PM2.5 InOporto Region

Abstract: The aim of this work was to study the influence of traffic emissions on the physical and chemical characteristics of PM10 and PM2.5, namely considering: concentration, size distribution and elemental composition. Four monitoring sites in the north of Portugal were selected: two sites directly influenced by traffic emissions and two rural background sites. PM10 and PM2.5 samples were collected using low-volume samplers; the element analyses were performed by particle induced X-ray emission (PIXE). At the sites influenced by traffic emissions PM10 and PM2.5 concentrations were 7-9 and 6-7 times higher than at the background sites. The presence of 17 elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn and Pb) was determined in both PM fractions; particle metal contents were 3-44 and 3-27 times higher for PM10 and PM2.5, respectively, than at the backgrounds sites. The results also showed that in coastal areas sea salt sprays are important sources of particles, influencing PM concentration and distributions (PM10 increased by 46%, PM2.5/PM10 decreased by 26%), as well as PM compositions (Cl in PM10 was 11 times higher).