Road Dust Emission Sources and Assessment of Street Washing Effect

Although previous studies report on the effect of street washing on ambient particulate matter levels, there is a lack of studies investigating the results of street washing on the emission strength of road dust. A sampling campaign was conducted in Madrid urban area during July 2009 where road dust samples were collected in two sites, namely Reference site (where the road surface was not washed) and Pelayo site (where street washing was performed daily during night). Following the chemical characterization of the road dust particles the emission sources were resolved by means of Positive Matrix Factorization, PMF (Multilinear Engine scripting) and the mass contribution of each source was calculated for the two sites. Mineral dust, brake wear, tire wear, carbonaceous emissions and construction dust were the main sources of road dust with mineral and construction dust being the major contributors to inhalable road dust load. To evaluate the effectiveness of street washing on the emission sources, the sources mass contributions between the two sites were compared. Although brake wear and tire wear had lower concentrations at the site where street washing was performed, these mass differences were not statistically significant and the temporal variation did not show the expected build-up after dust removal. It was concluded that the washing activities resulted merely in a road dust moistening, without effective removal and that mobilization of particles took place in a few hours between washing and sampling. The results also indicated that it is worth paying attention to the dust dispersed from the construction sites as they affect the emission strength in nearby streets.

Efecto de la adición de una turba comercial en la asimilabilidad de cobre, zinc, hierro, manganeso de un suelo en el que se ha cultivado trigo

Se ha estudiado el efecto de la adición de diferentes cantidades de una turba comercial (con un 80 % de turba rubia y un 20% de turba negra) en la asimilabilidad de los elementos nutritivos en un suelo calcáreo en el que se cultivó trigo. Para ello se determinaron los contenidos en N, P y K, así como las concentraciones totales y potencialmente asimilables para las plantas de los micronutrientes Cu, Zn, Fe y Mn. También se determinó el rendimiento en grano y el índice de cosecha del cultivo de trigo realizado en función del tratamiento de turba aplicado. Los resultados estadísticos no mostraron diferencias significativas entre tratamientos en cuanto a la concentración total de N, K, Cu, Zn, Fe y Mn en el suelo de la rizosfera del cultivo. Sin embargo sí se obtuvieron diferencias significativas (P < 0,05) en las concentraciones de Cu, Zn, Fe y Mn potencialmente disponibles en el suelo, aumentando en general, dichas concentraciones con los incrementos de la dosis de turba. El aumento de la dosis de turba también afectó al valor de pH del suelo, disminuyendo el valor del mismo a medida que aumenta dicha dosis. El mayor rendimiento en grano del cultivo de trigo se obtuvo con el tratamiento con turba que consiguió en el suelo un contenido en materia orgánica del 2,5 %.

Star dust memories, or how to detect allergen traces in powder foods

Allergies and food intolerances are at the forefront of institutional interest (European Regulation No 1169/2011) for their impact on consumer health. Allergies to peanuts and other nuts and gluten intolerance, makes production processes involving mixtures of powders a great concern for the industry, given the need to indicate the existence of traces of any of them. The food industry requires non-destructive and non-invasive methods of quantification that meet sensitivity requirements but also specificity levels. Optical methods such as NIR spectrophotometry or hyper-spectral image are currently some of the technologies that show potential success. This is the context of this paper that evaluates how to use NIR spectroscopy (900-1600nm) to detect traces of 15 different kinds of nuts and 20 other flours.

Dust effects on PV array performance: in-field observations with non-uniform patterns

This paper presents the impact of non-homogeneous deposits of dust on the performance of a PV array. The observations have been made in a 2-MW PV park in the southeast region of Spain. The results are that inhomogeneous dust leads to more significant consequences than the mere short-circuit current reduction resulting from transmittance losses. In particular, when the affected PV modules are part of a string together with other cleaned (or less dusty) ones, operation voltage losses arise. These voltage losses can be several times larger than the short-circuit ones, leading to power losses that can be much larger than what measurements suggest when the PV modules are considered separately. Significant hot-spot phenomena can also arise leading to cells exhibiting temperature differences of more than 20 degrees and thus representing a threat to the PV modules' lifetime.

Implementation of road dust resuspension in air quality simulations of particulate matter in Madrid (Spain)

An evaluation of the concentration levels of Particulate Matter (PM) was carried out in Madrid (Spain) by introducing the emissions from road dust resuspension. Road dust resuspension emission factors (EF) for different types of vehicles were calculated from EPA-AP42, a global resuspension factor of 0.097 g veh−1km−1 as described in Amato et al. (2010) and a rain-dependent correction factor. With these resuspension EFs, a simulation at street canyon level was performed with the OSPM model without rainfall. Subsequently, a simulation using the CMAQ model was implemented adding resuspension emissions affected by the rain. These data were compared with monitored data obtained from air quality stations. OSPM model simulations with resuspension EFs but without the effect of rainfall improve the PM estimates in about 20gm−3μ compared to the simulation with default EFs. Total emissions were calculated by adding the emissions estimated with resuspension EFs to the default PM emissions to be used by CMAQ. For the study in the Madrid Area, resuspension emissions are approximately of the same order of magnitude as inventoried emissions. On a monthly scale, rain effects are negligible for resuspension emissions due to the dry weather conditions of Spain. With the exception of April and May, the decrease in resuspension emissions is not >3%. The predicted PM10 concentration increases up to 9μ gm−3 on annual average for each station compared to the same scenario without resuspension. However, in both cases, PM 10 estimates with resuspension are still underestimating observations. It should be noted that although that accounting for resuspension improves the quality of model predictions, other PM sources (e.g., Saharan dust) were not considered in this study.