Integration of biomonitoring and instrumental techniques to assess the air quality in an industrial area located in the coastal of Central Asturias, Spain

Throughout the world, epidemiological studies were established to examine the relationship between air pollution and mortality rates and adverse respiratory health effects. However, despite the years of discussion the correlation between adverse health effects and atmospheric pollution remains controversial, partly because these studies are frequently restricted to small and well-monitored areas. Monitoring air pollution is complex due to the large spatial and temporal variations of pollution phenomena, the high costs of recording instruments, and the low sampling density of a purely instrumental approach. Therefore, together with the traditional instrumental monitoring, bioindication techniques allow for the mapping of pollution effects over wide areas with a high sampling density. In this study, instrumental and biomonitoring techniques were integrated to support an epidemiological study that will be developed in an industrial area located in Gijon in the coastal of central Asturias, Spain. Three main objectives were proposed to (i) analyze temporal patterns of PM10 concentrations in order to apportion emissions sources, (ii) investigate spatial patterns of lichen conductivity to identify the impact of the studied industrial area in air quality, and (iii) establish relationships amongst lichen conductivity with some site-specific characteristics. Samples of the epiphytic lichen Parmelia sulcata were transplanted in a grid of 18 by 20 km with an industrial area in the center. Lichens were exposed for a 5-mo period starting in April 2010. After exposure, lichen samples were soaked in 18-MΩ water aimed at determination of water electrical conductivity and, consequently, lichen vitality and cell damage. A marked decreasing gradient of lichens conductivity relative to distance from the emitting sources was observed. Transplants from a sampling site proximal to the industrial area reached values 10-fold higher than levels far from it. This finding showed that lichens reacted physiologically in the polluted industrial area as evidenced by increased conductivity correlated to contamination level. The integration of temporal PM10 measurements and analysis of wind direction corroborated the importance of this industrialized region for air quality measurements and identified the relevance of traffic for the urban area.

The impact of Sinogram-Affirmed Iterative Reconstruction on patient dose and image quality compared to filtered back projection: a narrative review

Objective: Summarize all relevant findings in published literature regarding the potential dose reduction related to image quality using Sinogram-Affirmed Iterative Reconstruction (SAFIRE) compared to Filtered Back Projection (FBP). Background: Computed Tomography (CT) is one of the most used radiographic modalities in clinical practice providing high spatial and contrast resolution. However it also delivers a relatively high radiation dose to the patient. Reconstructing raw-data using Iterative Reconstruction (IR) algorithms has the potential to iteratively reduce image noise while maintaining or improving image quality of low dose standard FBP reconstructions. Nevertheless, long reconstruction times made IR unpractical for clinical use until recently. Siemens Medical developed a new IR algorithm called SAFIRE, which uses up to 5 different strength levels, and poses an alternative to the conventional IR with a significant reconstruction time reduction. Methods: MEDLINE, ScienceDirect and CINAHL databases were used for gathering literature. Eleven articles were included in this review (from 2012 to July 2014). Discussion: This narrative review summarizes the results of eleven articles (using studies on both patients and phantoms) and describes SAFIRE strengths for noise reduction in low dose acquisitions while providing acceptable image quality. Conclusion: Even though the results differ slightly, the literature gathered for this review suggests that the dose in current CT protocols can be reduced at least 50% while maintaining or improving image quality. There is however a lack of literature concerning paediatric population (with increased radiation sensitivity). Further studies should also assess the impact of SAFIRE on diagnostic accuracy.

Assessment of the ensembles regional climate models in the representation of precipitation variability and extremes over Portugal

A new data set of daily gridded observations of precipitation, computed from over 400 stations in Portugal, is used to assess the performance of 12 regional climate models at 25 km resolution, from the ENSEMBLES set, all forced by ERA-40 boundary conditions, for the 1961-2000 period. Standard point error statistics, calculated from grid point and basin aggregated data, and precipitation related climate indices are used to analyze the performance of the different models in representing the main spatial and temporal features of the regional climate, and its extreme events. As a whole, the ENSEMBLES models are found to achieve a good representation of those features, with good spatial correlations with observations. There is a small but relevant negative bias in precipitation, especially in the driest months, leading to systematic errors in related climate indices. The underprediction of precipitation occurs in most percentiles, although this deficiency is partially corrected at the basin level. Interestingly, some of the conclusions concerning the performance of the models are different of what has been found for the contiguous territory of Spain; in particular, ENSEMBLES models appear too dry over Portugal and too wet over Spain. Finally, models behave quite differently in the simulation of some important aspects of local climate, from the mean climatology to high precipitation regimes in localized mountain ranges and in the subsequent drier regions.