Browsing by Subject "atmospheric pressure"

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  • Sabater, Neus; Vicent, Jorge; Alonso, Luis; Verrelst, Jochem; Middleton, Elizabeth M.; Porcar-Castell, Albert; Moreno, José (2018)
    Estimates of Sun-Induced vegetation chlorophyll Fluorescence (SIF) using remote sensing techniques are commonly determined by exploiting solar and/or telluric absorption features. When SIF is retrieved in the strong oxygen (O) absorption features, atmospheric effects must always be compensated. Whereas correction of atmospheric effects is a standard airborne or satellite data processing step, there is no consensus regarding whether it is required for SIF proximal-sensing measurements nor what is the best strategy to be followed. Thus, by using simulated data, this work provides a comprehensive analysis about how atmospheric effects impact SIF estimations on proximal sensing, regarding: (1) the sensor height above the vegetated canopy; (2) the SIF retrieval technique used, e.g., Fraunhofer Line Discriminator (FLD) family or Spectral Fitting Methods (SFM); and (3) the instrument's spectral resolution. We demonstrate that for proximal-sensing scenarios compensating for atmospheric effects by simply introducing the O transmittance function into the FLD or SFM formulations improves SIF estimations. However, these simplistic corrections still lead to inaccurate SIF estimations due to the multiplication of spectrally convolved atmospheric transfer functions with absorption features. Consequently, a more rigorous oxygen compensation strategy is proposed and assessed by following a classic airborne atmospheric correction scheme adapted to proximal sensing. This approach allows compensating for the O absorption effects and, at the same time, convolving the high spectral resolution data according to the corresponding Instrumental Spectral Response Function (ISRF) through the use of an atmospheric radiative transfer model. Finally, due to the key role of O absorption on the evaluated proximal-sensing SIF retrieval strategies, its dependency on surface pressure (p) and air temperature (T) was also assessed. As an example, we combined simulated spectral data with p and T measurements obtained for a one-year period in the Hyytiala Forestry Field Station in Finland. Of importance hereby is that seasonal dynamics in terms of T and p, if not appropriately considered as part of the retrieval strategy, can result in erroneous SIF seasonal trends that mimic those of known dynamics for temperature-dependent physiological responses of vegetation.
  • Lindfors, Pia (Helsingfors universitet, 2010)
    The most important part in bioanalysis is the sample cleanup process which is usually the most laborious and time consuming part of the analysis and very susceptible to errors. A functional bioanalysis has to be quick, easily automated, sensitive, selective and stable. It also needs to be suitable for high throughput analysis. Desorption atmospheric pressure photoionization (DAPPI) is a novel direct desorption/ionization technique for mass spectrometry that enables direct analysis of solids from surfaces or liquid samples from a suitable sample plate often without any sample preparation. The suitability of DAPPI-MS for biological samples was investigated by measuring the limits of detection for selected opioids and benzodiazepines and screening them from authentic urine samples. Limits of detection were measured for standard solutions and spiked urine. Opioids and benzodiazepines were analyzed from post mortem urine samples with an optimized DAPPI-MS method. Post mortem urine samples were analyzed with and without sample preparation. Sample preparation improved the sensitivity of the method remarkably. About 50 % of the analytes were detected without sample preparation and almost 100 % after sample cleanup. It is however difficult to estimate the suitability of DAPPI-MS as a screening method because not all analyte concentrations of the urine samples were known. Therefore we cannot be certain weither the results obtained without sample preparation are caused by the suppression of the urine matrix or if the concentrations of the analytes are below the limits of detection. The reliability of the method can further be improved by investigating the metabolites of the analytes and improving the system towards automation. On grounds of this research DAPPI-MS should be used cautiously as a screening method for urine samples without sample preparation and with only high enough analyte concentrations. DAPPI-MS shows promise as a screening method for opioids and benzodiazepines from urine when the sample cleanup is used before the analysis.