Recently, acid precipitation is receiving global interest because it affects terrestrial and aquatic ecosystems. 1,2 Our research group has studied 3-7 the acid precipitation of Hyogo and Akita prefectures in Japan, combining a chemical analysis of the ionic substances with meteorological situations, and has analyzed pollutants by a factor analysis. [3][4][5][6][7] Furthermore, investigations for the fog on a mountain ridge showed by a factor analysis that a fog droplet had some soluble pollutants (e.g. (NH4)2SO4, seasalt, H2SO4 and HNO3), and that the uptake mechanism by a fog droplet would be different for each pollutant.It is well-known that fog/cloud water is more acidic and has a higher concentration of pollutants than rain water. 5,9-11 Nevertheless, prior attempts 15,16 to elucidate the mechanisms of fog acidification, especially the behavior of the ionic substances in the fog droplets, have not been quantitatively conclusive. There has been no investigation, moreover, concerning where the air pollutants specified by employing the oblique rotational factor analysis 3,4,6,12 are transferred.Our purpose here was threefold. First, by using an oblique rotational factor analysis, we examined the observed drop size dependence of the chemical composition during fog events at Akita Hachimantai mountain range from June to September of 1998 and 1999. Second, we evaluated the transport of some air pollutants in combination with ionic substances which were quantitatively extracted from a factor analysis developed by our research group, 3,4 with a 72 h back trajectory at the 850 hPa level and from the point of view of a synoptic weather system. Third, from the feature of chemical composition of fog or rain, which was non-ion-balanced, we tried to estimate unknown soluble chemical species. ExperimentalFog water was collected on a mountainside (39˚56′N, 140˚51′E, 1465 m, a.s.l.) of Mt. Mokkodake (1578 m, a.s.l.) in the Akita Hachimantai mountain range from June to September of 1998 and 1999 (Fig. 1) Fog and rain water samples were collected at the same time in the Akita Hachimantai mountain range in northern Japan from June to September in 1998 and 1999. The various ion concentrations in these samples were analyzed, and the fog droplet sizes were measured for each fog event. As the fog droplet size increased, the ion concentration decreased. The slope of log-log plots of the concentration versus the droplet size differed with the kind of ion. In order to characterize the air pollutant, moreover, these data were quantitatively analyzed by an oblique rotational factor analysis. We found that three factors were extracted as the air pollutant source: (NH4)2SO4, acids (HNO3 + H2SO4) and sea-salt. Combining the factor analysis with the 72 h back-trajectory at 850 hPa level, we found that the contribution of each factor varied with the transport pattern of air masses.
Using a portable near infrared (NIR) spectrometer, we discriminated flours for making Japanese noodles (Soba), not only relying on a statistical and mathematical approach, but also on a chemical interpretation of the NIR spectra. In original NIR spectra, the particle-size difference, which results in an undesired systematic variation, was extracted and interpreted as the first-principal component factor by a principal-component analysis. The discrimination of flour materials cannot be satisfied by this factor. However, after a standardized treatment for the original spectra, the particle-size effects were eliminated; alternatively, differences in the chemical contents were extracted as principal-component factors. Using these factors, flour material discrimination was achieved much better. This study suggests a novel idea of utilizing the wavelength contribution ratio spectra for interpreting the factors extracted from the principal-component analysis for the NIR spectra. This report also describes the relationship between the NIR spectra and the chemical-analysis data.
Thirty-eight beers from different producing areas and/or makers were distinguished by principal component analysis (PCA) of the near infrared (NIR) spectra acquired by a portable NIR spectrometer. Classsification of Akita beers: beers locally produced in Akita prefecture, Japan, from other famous brand beers could be successfully performed, especially when the PCA was calculated on the standard normal variate (SNV) spectra. The classification equations use information related to water and CH2 absorption that reflected the differences in chemical com position of beers due to different production processes. In addition, the compositions of total polyphenol and total nitrogen were estimated from NIR spectra by multiple linear regression (MLR). This study showed that NIR spectroscopy is promising for beer quality evaluation, both for identifying multifarious beers including Akita beers using PCA and for rapid in-line quality control and inspection for beer production using the quantitative MLR analysis.
We examined NIR spectra obtained from various plastic wastes using a portable near infrared spectrometer; herein, we discuss chemical implications of spectral characteristics. A barcode spectrum derived from the second-order derivatives spectrum provides effective alternatives to discriminate plastic types. Principal component analysis, which is applied to barcode spectra, reveals characteristics and similarity of NIR spectra among plastic samples. Chemical structure of plastic samples reflects NIR spectra. Spectral differences can be explained with reference to whether the plastic has some functional group (aromatic CH, CO and Cl) or not.
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