Determination of cyclic organic acid anhydrides in air using gas chromatography .1. A review

Gas chromatographic methods for the determination of cyclic organic acid anhydrides (OAAs) in industrial air are reviewed. The OAAs discussed are phthalic, hexahydrophthalic, methylhexahydrophthalic, tetrahydrophthalic, methyltetrahydrophthalic, trimellitic, maleic, and octenylsuccinic anhydride. Solid sorbent sampling methods, using Amberlite XAD-2 or Tenax, are used for sampling of OAA vapour. These methods are easy to use, have simple work-up procedures and sample the anhydrides as such. However, many OAAs are reactive compounds and losses during storage should be considered. Sampling of OAAs in mixed exposure of particles and vapour are performed by either bubblers or impingers with aqueous sampling solutions or by filters in series with solid sorbent tubes. It can be assumed that non-polar filter samples an OAA as such. Hence these methods are easy to use, but losses during storage must be considered. Bubblers/impingers convert the OAAs into the corresponding acids and glass-fibre filters do the same, at least in part. The acids are stable on storage but a derivatization must be performed before GC analysis. Detection methods used for the analysis are flame ionization detection (FID), electron-capture detection (ECD) and MS using electron impact or negative-ion chemical ionization. Typical detection limits for determinations of OAAs as such are 0.1 µg of OAA per sample using FID and an order of magnitude better using ECD or MS. For determination of the esters from the corresponding OAAs using MS, the detection limits are better than 0.01 µg of OAA per sample. Precisions are normally better than 10%

Thermal degradation products from plastics 2; polypropylene and polyvinyl chloride

70.00; Translated from SwedishSIGLEAvailable from British Library Document Supply Centre- DSC:9022.381(HSE-Trans--12882)T / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Estimation of Wood Fibre Length Distributions from Censored Data through an EM Algorithm

An expectation maximization (EM) algorithm is proposed to find fibre length distributions in standing trees. The available data come from cylindric wood samples (increment cores). The sample contains uncut fibres as well as fibres cut once or twice. The sample contains not only fibres, but also other cells, the so-called 'fines'. The lengths are measured by an automatic fibre-analyser, which is not able to distinguish fines from fibres and cannot tell if a cell has been cut. The data thus come from a censored version of a mixture of the fine and fibre length distributions in the tree. The parameters of the length distributions are estimated by a stochastic version of the EM algorithm, and an estimate of the corresponding covariance matrix is derived. The method is applied to data from northern Sweden. A simulation study is also presented. The method works well for sample sizes commonly obtained from increment cores. Copyright 2006 Board of the Foundation of the Scandinavian Journal of Statistics..