Levels and chemical composition of PM in a city near a large Cu-smelter in Spain.

A long-term series (2001-2008) of chemical analysis of atmospheric particulate matter (PM(10) and PM(2.5)) collected in the city of Huelva (SW Spain) is considered in this study. The impact of emission plumes from one of the largest Cu-smelters in the world on air quality in the city of Huelva is evidenced by the high daily and hourly levels of As, other potentially toxic elements (e.g. Cu, Zn, Cd, Se, Bi, and Pb) in particulate matter, as well as the high levels of some gaseous pollutants (NO(2) and SO(2)). Mean arsenic levels in the PM10 fraction were higher than the target value set by European Directive 2004/107/EC (6 ngAs m(-3)) for 1(st) January 2013. Hourly peak concentrations of As and other metals and elements (Zn, Cu, P and Se) analyzed by PIXE can reach maximum hourly levels as high as 326 ngAs m(-3), 506 ngZn m(-3), 345 ngCu m(-3), 778 ngP m(-3) and 12 ngSe m(-3). The contribution of Cu-smelter emissions to ambient PM is quantified on an annual basis in 2.0-6.7 µg m(-3) and 1.8-4.2 µg m(-3) for PM(10) and PM(2.5), respectively. High resolution outputs of the HYSPLIT dispersion model show the geographical distribution of the As ambient levels into the emission plume, suggesting that the working regime of the Cu-smelter factory and the sea breeze circulation are the main factors controlling the impact of the Cu-smelter on the air quality of the city. The results of this work improve our understanding of the behaviour of industrial emission plumes and their impact on air quality of a city, where the population might be exposed to very high ambient concentrations of toxic metals during a few hours.

Trends and sources vs air mass origins in a major city in South-western Europe: Implications for air quality management.

This study presents a 17-years air quality database comprised of different parameters corresponding to the largest city in the south of Spain (Seville) where atmospheric pollution is frequently attributed to traffic emissions and is directly affected by Saharan dust outbreaks. We identify the PM10 contributions from both natural and anthropogenic sources in this area associated to different air mass origins. Hourly, daily and seasonal variation of PM10 and gaseous pollutant concentrations (CO, NO2 and SO2), all of them showing negative trends during the study period, point to the traffic as one of the main sources of air pollution in Seville. Mineral dust, secondary inorganic compounds (SIC) and trace elements showed higher concentrations under North African (NAF) air mass origins than under Atlantic. We observe a decreasing trend in all chemical components of PM10 under both types of air masses, NAF and Atlantic. Principal component analysis using more frequent air masses in the area allows the identification of five PM10 sources: crustal, regional, marine, traffic and industrial. Natural sources play a more relevant role during NAF events (20.6 µg · m(-3)) than in Atlantic episodes (13.8 µg · m(-3)). The contribution of the anthropogenic sources under NAF doubles the one under Atlantic conditions (33.6 µg · m(-3) and 15.8 µg · m(-3), respectively). During Saharan dust outbreaks the frequent accumulation of local anthropogenic pollutants in the lower atmosphere results in poor air quality and an increased risk of mortality. The results are relevant when analysing the impact of anthropogenic emissions on the exposed population in large cities. The increase in potentially toxic elements during Saharan dust outbreaks should also be taken into account when discounting the number of exceedances attributable to non-anthropogenic or natural origins.

Assessment of ultrafine particles and noise measurements using fuzzy logic and data mining techniques.

This study focuses on correlations between total number concentrations, road traffic emissions and noise levels in an urban area in the southwest of Spain during the winter and summer of 2009. The high temporal correlation between sound pressure levels, traffic intensity, particle number concentrations related to traffic, black carbon and NOx concentrations suggests that noise is linked to traffic emissions as a main source of pollution in urban areas. First, the association of these different variables was studied using PreFuRGe, a computational tool based on data mining and fuzzy logic. The results showed a clear association between noise levels and road-traffic intensity for non-extremely high wind speed levels. This behaviour points, therefore, to vehicular emissions being the main source of urban noise. An analysis for estimating the total number concentration from noise levels is also proposed in the study. The high linearity observed between particle number concentrations linked to traffic and noise levels with road traffic intensity can be used to calculate traffic related particle number concentrations experimentally. At low wind speeds, there are increases in noise levels of 1 dB for every 100 vehicles in circulation. This is equivalent to 2000 cm(-3) per vehicle in winter and 500 cm(-3) in summer. At high wind speeds, wind speed could be taken into account. This methodology allows low cost sensors to be used as a proxy for total number concentration monitoring in urban air quality networks.