Collection of exhaled breath condensate (EBC) is a simple and noninvasive method to obtain information on the respiratory system. Different mediators can be determined in EBC. However, determinants of variability are not well described. The aim of this study was to evaluate variability of pH, volume and protein concentration of EBC between individuals and between sampling times. Therefore, EBC was collected from 20 healthy volunteers on two different days. Median pH for all samples, measured 5 min after collection without deaeration, was 6.17. Median volume was 1.70 ml and median total protein concentration was 1.02 microg/ml. Coefficients of variation were 5.17%, 21.84% and 37.93%, respectively. No intra- or interday variability could be found, except for the first collection time. Between individuals, significant differences were observed for all three mediators. Age, height and gender can explain part of this variation. In conclusion, no significant difference between sampling times on the same day or on different days was obtained for pH, volume and total protein concentration, provided that subjects are experienced in collecting EBC.
Every summer, ground level ozone concentrations rise in Belgium and cause episodes of photochemical summer smog. This phenomenon is the cause of well recognised public health distress, especially for people suffering from respiratory diseases. To warn groups of sensitive people against forthcoming smog episodes, VITO (the Flemish Institute for Technological Research) and VMM (the Flemish Environmental Agency) have joined forces to create an ozone pollution forecasting model, called SMOGSTOP (Statistical Model Of Groundlevel Short Term Ozone Pollution). SMOGSTOP is used by Belgian government agencies to issue ozone reports and warnings in the media (TV, radio, internet, etc.). Ozone pollution levels, as well as concentrations of other air pollutants, are monitored in Belgium by the telemetric air quality measuring networks of the three Belgian regions: Flanders, Wallonia and Brussels. The major meteorological variables, such as the windvector, temperature, pressure, humidity and precipitation, are also monitored by the same networks. The historical time series of those variables, generated by the networks, are the source of input data for SMOGSTOP. Photochemical ozone pollution is the result of complex non‐linear interactions between atmospheric pollutants and meteorology. As a consequence, it is extremely difficult to determine relationships between source emissions (ozone precursors) and ambient pollutant concentrations (ozone). To deal with this complexity, SMOGSTOP was constructed as an empirical model, applying a VITO tailor‐made methodology called stratified pattern matching, to link meteorological and precursor information into ozone forecasts. In this paper, an overview of the process of ozone formation in Belgium is given, followed by the definition of the explanatory variables which will be used in the model. Then the methodology behind the model is reported and finally the results of the forecasting efforts in the period of 1.5.1995 till 31.8.1995 are presented. Copyright © 2000 John Wiley & Sons, Ltd.
MC-FUME stands for median composite of fuzzy multispectral estimate. It is the name of a newly developed method for compositing individual reflective channels of the VEGETA-TION sensor onboard the SPOT-4 platform. MC-FUME is a two-step compositing methodology that uses combined angular and atmospheric corrections of reflectance measurements. The first step is an approximate BRDF correction. Considering the atmospheric influence to be stochastic, the top-of-canopy (TOC) reflectance at a reference geometry is estimated for each pixel by means of an extensive database of model-simulated top-of-atmosphere (TOA) reflectance values. The second step is compositing over a time period. This is done by taking the median of the estimated TOC reflectance values.The method is tested on simulated time series at different latitudes as well as on a time series of NOAA-AVHRR images. Tests performed on the simulated data set prove the ability of the MC-FUME algorithm to correctly reproduce TOC nadir values. Moreover, it outperforms classic compositing strategies such as the maximum-value composite of the NDVI (MVC-NDVI) [1] in this respect. Tests performed on AVHRR images show that the angular dependence of the MC-FUME algorithm is strongly reduced with respect to the classic MVC-NDVI method, as is the presence of speckle. This is especially remarkable for the individual reflective channels (RED and NIR). Thus, for individual reflective channels,MC-FUME produces speckle-free composites with reflectance values that are corrected for atmospheric and angular effects, and which therefore are independent of the observation/illumination geometry at the time of measurement.
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