Air pollution sources of PM10 in Buenos Aires City

To elucidate the sources of PM(10) air pollution from the experimental information collected in a local air quality monitoring campaign we have applied two methods, effective variance and genetic algorithms, in the solution of the chemical mass balance. The comparison of these two mathematical approaches show that the identification of the possible sources and the evaluation of its contributions are quite independent of them. The role of possible different sources for major and trace elements and the significance of standardizing available data is also addressed. We also present a simple method for identifying the number of candidate sources, a key element defining the dimension of the search space.     

A combined analysis to identify airborne PM10 sources

A two step procedure that combines an air dispersion model with a receptor model was used to identify the key sources that contribute to air levels of suspended particulate matter. The contribution to PM(10) concentrations measured at four monitoring sites in San Nicolas, Argentina, of the following sources, a thermal power plant, an integrated steel mill, motor vehicle exhaust fumes, and finally dust from paved and unpaved roads, have been analysed. Moreover, an air dispersion model was used to estimate the contribution of the thermal power plant, emissions of which have been described in depth by means of hourly fuel consumption and specific emission factors. The ratio "apportionment coefficient" was introduced to relate the contribution of this source to the measured 24 h PM(10) concentrations by analysing the frequency of occurrence of connecting winds between the power plant and each monitoring site. In San Nicolas 70% of the PM(10) sampled at three of the four monitoring sites could be attributed to the power plant in those scenarios where winds connected the facility's tall point sources with the sampling locations. The contribution to the measured PM(10) levels of the rest of the sources that are present in the analysed area was confirmed by way of receptor models. For this purpose, the multielemental composition of 41 samples was determined by Wavelength Dispersive X-ray Fluorescence analysis. In order to ascertain the underlying correlations between PM(10) samples and potential sources, Principal Component Analysis was performed on the standard matrix of composition profiles, which comprises the measured PM(10) samples being enlarged with the composition profiles of the potential contributing sources. The diagonalization of the covariance matrix was used as a screening procedure to differentiate the most likely contributing sources from those that were not significant.     

Saharan dust contribution to PM₁₀, PM₂.₅ and PM₁ in urban and suburban areas of Rome: a comparison between single-particle SEM-EDS analysis and whole-sample PIXE analysis

From February 15th to April 15th 2009, a period characterised by two episodes of Saharan dust outbreaks in Italy, particulate matter (PM) samples were collected at two stations (urban and suburban) in Rome. Some samples were selected and analysed using the SEM-EDS technique to characterise PM, focussing especially on the mineral contribution. Samples were representative both of days affected by Saharan dust episodes and days without this contribution. Cluster analysis allowed the attribution of each of about 67,000 analysed particles to one of the seven main statistical groups based on their composition. Characteristics of the particulate components identified using SEM-EDS analysis were verified by PIXE analysis carried out on filters collected in a suburban area. Ultimately, the contribution of crustal particles was revealed to be consistently high, highlighting the importance of local and regional mineral contributions, as well as those of Saharan origin. Therefore, quantifying all mineral contributions to resuspended particulate could lead to significant reductions of the PM level also on days not influenced by Saharan dust, thus limiting conditions when PM?? daily limit value (DLV) established by European legislation is exceeded.     

Multilevel approach to organizational and group safety climate and safety performance: Co-workers as the missing link

The aim of this study is to test a model on the relationships between organizational and group safety climate and safety performance, that highlights the importance of co-workers as a safety climate agent side by side supervisors at group level. The idea is to consider the co-workers’ safety climate as a necessary part of a multilevel model of safety climates’ framework associated to safety performance. Firstly, the assessment of the safety climates’ framework which consider organizational safety climate and at group level supervisor’s and co-workers’ safety climate was performed. Then, the mediating role of co-workers’ safety climate between organizational and supervisor’s safety climate, and worker’s safety behaviours was explored. From the literature, the importance to study safety climate in a multilevel perspective by a theoretical and methodological point of view is known. For these reasons the proposed models were tested with multilevel structural equation modelling. We used a two-level design which considered the individual level and the work-group level. Data collection involved 991 blue-collars, belonging to 91 work groups, from five Italian manufacturing companies. The research highlighted the importance of considering at group level not only climate referred to supervisor, but also climate referred to co-workers. Furthermore, results confirmed the mediating role of co-workers’ safety climate and revealed that co-workers’ safety climate had a stronger influence on safety behaviours, and in particular on safety participation, than supervisor’s safety climate, at individual level as well at group level.     

Factors driving sediment compositional change in the distal area of the Ria de Vigo (NW Spain): oceanographic processes vs. paleopollution

Environmental Science and Pollution Research - We analyze potential Late Holocene metal contamination along a sediment core collected in the distal zone of Ria de Vigo (North Spain). Statistical...     

Rose Bengal‐sensitized photooxygenation of chlorohydroxyaromatic contaminants in water: A kinetic study

A kinetic study of the RB‐sensitized photooxygenation of a series of chlorohydroxyaromatic (ClArOH) water contaminants (phenolic and dihydroxybenzene derivatives) has been carried out. In addition, an exhaustive study on the possible interactions of RB electronically excited triplet and singlet states with ClArOH was also developed. The determination of relative rates of oxygen uptake upon sensitized irradiation, employing auxiliar selective quenchers of oxygen active species, indicate the contribution of both singlet molecular oxygen (ca. 71%) and Superoxide ion (ca. 26%) as the reactive pathways for ClArOH degradation. The substitution by chlorine atoms in position meta greatly decrease the photooxygenation rate of the phenolic derivatives. For the dihydroxybenzene series, increase in nuclear chlorination parallels a decrease in the photodegradation rate.

Outdoors sensitized solar irradiation experiments on different ClArOH mixtures leads to measurable levels of oxygen after a few minutes exposure. From the environmental point of view, and ruling out the possibility of direct‐irradiation photoreactions, sensitized photooxygenation appears as an alternative pathway for ClArOH degradation, in competence with other naturally‐occurring photoprocesses involving reactive transient species.     

Non-parametric analysis of infrared spectra for recognition of glass and glass ceramic fragments in recycling plants

Glass ceramic detection in glass recycling plants represents a still unsolved problem, as glass ceramic material looks like normal glass and is usually detected only by specialized personnel. The presence of glass-like contaminants inside waste glass products, resulting from both industrial and differentiated urban waste collection, increases process production costs and reduces final product quality. In this paper an innovative approach for glass ceramic recognition, based on the non-parametric analysis of infrared spectra, is proposed and investigated. The work was specifically addressed to the spectral classification of glass and glass ceramic fragments collected in an actual recycling plant from three different production lines: flat glass, colored container-glass and white container-glass. The analyses, carried out in the near and mid-infrared (NIR-MIR) spectral field (1280-4480 nm), show that glass ceramic and glass fragments can be recognized by applying a wavelet transform, with a small classification error. Moreover, a method for selecting only a small subset of relevant wavelength ratios is suggested, allowing the conduct of a fast recognition of the two classes of materials. The results show how the proposed approach can be utilized to develop a classification engine to be integrated inside a hardware and software sorting architecture for fast "on-line" ceramic glass recognition and separation.