Long-term variations in individual particle types in the aerosol of Phoenix, Arizona, as determined using automated electron microprobe analysis and multivariate statistical techniques

1993 ◽  
Vol 51 ◽  
pp. 742-743
Author(s):  
Karen A. Katrinak ◽  
James R. Anderson ◽  
Peter R. Buseck
Keyword(s):  
Electron Microprobe ◽  
Fine Fraction ◽  
Coarse Fraction ◽  
Motor Vehicles ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
X Ray ◽  
Mineral Particles ◽  
Anthropogenic Air Pollutants

Aerosol samples were collected in Phoenix, Arizona on eleven dates between July 1989 and April 1990. Elemental compositions were determined for approximately 1000 particles per sample using an electron microprobe with an energy-dispersive x-ray spectrometer. Fine-fraction samples (particle cut size of 1 to 2 μm) were analyzed for each date; coarse-fraction samples were also analyzed for four of the dates.The data were reduced using multivariate statistical methods. Cluster analysis was first used to define 35 particle types. 81% of all fine-fraction particles and 84% of the coarse-fraction particles were assigned to these types, which include mineral, metal-rich, sulfur-rich, and salt categories. "Zero-count" particles, consisting entirely of elements lighter than Na, constitute an additional category and dominate the fine fraction, reflecting the importance of anthropogenic air pollutants such as those emitted by motor vehicles. Si- and Ca-rich mineral particles dominate the coarse fraction and are also numerous in the fine fraction.

Classification of mineral particles by non-linear mapping of electron microprobe energy dispersive X-ray spectra

The Analyst ◽  
1994 ◽  
Vol 119 (5) ◽  
pp. 971 ◽  
Author(s):  
Boris Treiger ◽  
Igor Bondarenko ◽  
Piet Van Espen ◽  
Ren� Van Grieken ◽  
Fred Adams
Keyword(s):  
Electron Microprobe ◽  
Linear Mapping ◽  
Energy Dispersive ◽  
X Ray ◽  
Mineral Particles ◽  
Non Linear

Soil spatial patterns analysis at the ancient city of Ibida (Dobrogea, SE Romania), via portable X-ray fluorescence spectrometry and multivariate statistical methods

CATENA ◽  
2020 ◽  
Vol 189 ◽  
pp. 104506 ◽  
Author(s):  
Radu Gabriel Pîrnău ◽  
Cristian Valeriu Patriche ◽  
Bogdan Roşca ◽  
Ionuţ Vasiliniuc ◽  
Nicoleta Vornicu ◽  
...  
Keyword(s):  
Statistical Methods ◽  
Spatial Patterns ◽  
Fluorescence Spectrometry ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
X Ray ◽  
Ancient City

scholarly journals Geochemical characterization of the Sutlegen bauxite deposit, SW Antalya

2021 ◽  
Vol 15 (3) ◽  
pp. 108-121
Author(s):  
Ozge Ozer Atakoglu ◽  
Mustafa Gurhan Yalcin
Keyword(s):  
Geochemical Characteristics ◽  
X Ray Diffraction ◽  
Bauxite Deposit ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
X Ray ◽  
Icp Ms ◽  
Plasma Mass Spectrometry ◽  
Practical Implications

Purpose.The purpose is to determine geological and geochemical characteristics of the Sutlegen (Antalya, Turkey) bauxites, to identify the elements that played a major role in their formation. Methods. X-ray diffraction (XRD) mineral phase analysis, X-ray fluorescence (XRF) elemental analysis, plasma-mass spectrometry (ICP-MS), the petrographic and mineralogical analyses, and multivariate statistical methods were used. Findings. The major element content of the ore was determined as Al2O3 (60-35.2 wt%), SiO2 (39.5-0.2 wt%), Fe2O3 (48.4-19.5 wt%), TiO2 (36.9-16 wt%), and P2O5 (0.5-0.1 wt%). The Sutlegen region, which shows epirogenetic action with the uplift of the earth's crust, is generally rich in neritic carbonates. It was revealed that the bauxite ores have undergone moderate and strong laterization as a result of the deferruginization in the environment, and they were classified into four groups as lateritic, ferritic, kaolinitic, and bauxite. The increase in the aluminosilicate minerals, which were formed during the formation of bauxite in the environment was found to be directly proportional to the laterization processes. In this context, it was considered that the lateritic material that was firstly formed in the environment filled the cavities and pores of the karst-type limestones and sedimentary units in the region by superficial transfer phenomena. The bivariate diagrams of Log Cr vs. Log Ni revealed that the bauxite that formed in the region had an ultrabasic source. Originality. In literature, no scientific studies have been found on bauxite mineralization in the Sutlegen deposits that have been operated for a long period. Practical implications. In this context, the geochemical characteristics of bauxites revealed that the source of the laterization process in the region was the ultrabasic igneous rocks. The lateritic material moved by superficial transfer was accumulated on sandstone, claystone, siltstone, and limestone and in karstic cavities; then, it formed karstic bauxite (kaolinitic and bauxite) of different classifications due to the effect of metamorphism.

scholarly journals Differentiation of Particulate Matter Sources Based on the Chemical Composition of PM10 in Functional Urban Areas

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 583 ◽  
Author(s):  
Dusan Jandacka ◽  
Daniela Durcanska
Keyword(s):  
Particulate Matter ◽  
Urban Areas ◽  
Road Traffic ◽  
Chemical Elements ◽  
Winter Season ◽  
Fine Fraction ◽  
Gravimetric Method ◽  
Coarse Fraction ◽  
Multivariate Statistical ◽  
The City

Urban air quality is continuing to deteriorate. If we want to do something about this problem, we need to know the cause of the pollution. The big problem, not only in Europe, is the high concentrations of particulate matter (PM) in the urban environment. The origin of these particles can be different, including combustion, transport, industry, natural resources, etc. Particulate matter includes a large amount of the finest PM fractions, which can remain in the air for a long time, easily enter respiratory tracks, and damage human health. Particulate matter is also produced by the abrasion of different parts of roads and vehicle fleets and from resuspension road dust, which concerns matter with larger aerodynamic diameters. For this reason, we carried out a series of measurements at various measuring stations in Žilina, Slovakia, during different measuring seasons. The main objective was to find out the diversity of particulate matter sources in Žilina. The search for the particulate matter origin was carried out by particulate matter measurements, determination of the particulate matter fraction concentrations (PM10, PM2.5, and PM1), an investigation on the effect of secondary factors on the particulate matter concentrations, chemical analyses, and multivariate statistical analyses. Varied behavior of the particulate matter with respect to the measurement station and the measurement season was found. Differences in the concentrations of investigated chemical elements contained in the PM were found. Significant changes in the concentrations of particulate matter are caused not only by primary sources (e.g., road traffic in the city of Žilina), but mainly by the negative events (combination of air pollution sources and meteorological conditions). Maximum concentrations of particulate matter PM10 were measured during the winter season at the measuring station on Komenského Street: PM10 126.2 µg/m3, PM2.5 97.7 µg/m3, and PM1 90.4 µg/m3 were obtained using the gravimetric method. The coarse fraction PM2.5-10 was mainly represented by the chemical elements Mg, Al, Si, Ca, Cr, Fe, and Ba, and the fine fraction PM2.5 was represented by the chemical elements K, S, Cd, Pb, Ni, and Zn. Road transport as a dominant source of PM10 was identified from all measurements in the city of Žilina by using the multivariate statistical methods of principal component analysis (PCA) and factor analysis (FA).

Carbon stability in a texture contrast soil in response to depth and long-term phosphorus fertilisation of grazed pasture

Soil Research ◽  
2020 ◽  
Vol 58 (1) ◽  
pp. 21 ◽  
Author(s):  
Elizabeth C. Coonan ◽  
Alan E. Richardson ◽  
Clive A. Kirkby ◽  
Lynne M. Macdonald ◽  
Martin R. Amidy ◽  
...  
Keyword(s):  
Plant Material ◽  
Fine Fraction ◽  
Coarse Fraction ◽  
Metabolic Quotient ◽  
Microbial Decomposition ◽  
Soil C ◽  
Soil Fractions ◽  
The Stability ◽  
Phosphorus Fertilisation

It is important to understand the stability of soil organic matter (SOM) sequestered through land management changes. In this study we assessed differences in carbon (C) stability of pasture soils that had high and low C content (2.35% vs 1.73% whole soil C in the 0–10 cm layer) resulting from long-term phosphorus fertilisation. We used soil size fractionation (fine fraction, coarse fraction and winnowing) to assess the amount of stable C and indicators of microbial decomposition capacity (catabolic profiles, metabolic quotient) to assess C stability. As a main effect throughout the 60-cm profile, C concentrations were higher in the fine fraction soil in the high (excess P fertiliser; P2) than low (no P fertiliser; P0) treatments, demonstrating a larger stable C fraction. For both P2 and P0, there was a strong correlation between C measured in the fine fraction and winnowed fraction in the 0–30 cm layer (R = 0.985, P < 0.001), but no correlation was observed for the 30–60 cm layer (R = 0.121, P > 0.05). In addition, we conducted two incubation experiments to assess C stability in the treatments with depth and to assess C stability in the physical soil fractions. For the surface soils (0–10 cm), the highest respiration occurred in fractions containing plant material, including roots (coarse fraction, 0.65 g CO2-C kg–1 soil; whole soil, 1.48 g CO2-C kg–1 soil), which shows that the plant material was less stable than the fine and winnowed soil fractions (0.43 and 0.40 g CO2-C kg–1 soil respectively). Soil respiration, microbial metabolic quotient and substrate utilisation were similar in P0 and P2. Collectively, the data show that the increased C in P2 was associated with increased C concentrations in the more stable fine soil fraction, but with no change in the stability of the C within the fractions.

Pressure-induced cation exchange in bentonite/laponite mixtures

Clay Minerals ◽  
1991 ◽  
Vol 26 (3) ◽  
pp. 371-375 ◽  
Author(s):  
E. Paterson ◽  
D. R. Clark
Keyword(s):  
Cation Exchange ◽  
Microprobe Analysis ◽  
Adsorbed Water ◽  
Exchangeable Cation ◽  
X Ray Diffraction ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
X Ray ◽  
Physical Mixtures ◽  
Mechanism Of The Reaction

AbstractExchangeable cation associations in physical mixtures of bentonite and laponite have been examined using X-ray diffraction and a combination of electron microprobe analysis and multivariate statistical methods. The results suggest that cation exchange can occur in air-dry mixtures when pressure (∼64 kbar) is applied. Although no attempt is made to describe the mechanism of the reaction it appears to require the presence of adsorbed water.

scholarly journals The use of a combined portable X ray fluorescence and multivariate statistical methods to assess a validated macroscopic rock samples classification in an ore exploration survey

Talanta ◽  
2011 ◽  
Vol 85 (5) ◽  
pp. 2307-2315 ◽  
Author(s):  
J. Figueroa-Cisterna ◽  
M.G. Bagur-González ◽  
S. Morales-Ruano ◽  
J. Carrillo-Rosúa ◽  
F. Martín-Peinado
Keyword(s):  
Statistical Methods ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
X Ray ◽  
Rock Samples ◽  
Ore Exploration

scholarly journals Corporate rating forecasting using Artificial Intelligence statistical techniques

2019 ◽  
Vol 16 (2) ◽  
pp. 295-312 ◽  
Author(s):  
Daniel Caridad ◽  
Jana Hančlová ◽  
Hosn el Woujoud Bousselmi ◽  
Lorena Caridad y López del Río
Keyword(s):  
Artificial Intelligence ◽  
Credit Rating ◽  
Financial Health ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Rating Agencies ◽  
Large Samples ◽  
Public Data ◽  
High Level

Forecasting companies long-term financial health is provided by Credit Rating Agencies (CRA) such as S&P, Moody’s, Fitch and others. Estimates of rates are based on publicly available data, and on the so-called ‘qualitative information’. Nowadays, it is possible to produce quite precise forecasts for these ratings using economic and financial information that is available in financial databases, utilizing statistical models or, alternatively, Artificial Intelligence techniques. Several approaches, both cross section and dynamic are proposed, using different methods. Artificial Neural Networks (ANN) provide better results than multivariate statistical methods and are used to estimate ratings within all the range provided by the CRAs, obtaining more desegregated results than several proposed models available for intervals of ratings. Two large samples of companies ‘public data’ obtained from Bloomberg are used to obtain forecasts of S&P and Moody’s ratings directly from these data with high level of accuracy. This also permits to check the published rating’s reliability provided by different CRAs.

scholarly journals Provenance Study of Archaeological Ceramics from Syria Using XRF Multivariate Statistical Analysis and Thermoluminescence Dating

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Elias Hanna Bakraji ◽  
Rana Abboud ◽  
Haissm Issa
Keyword(s):  
Bronze Age ◽  
Fluorescence Analysis ◽  
Archaeological Site ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Archaeological Ceramics ◽  
X Ray ◽  
Thermoluminescence Dating ◽  
Three Samples ◽  
Middle Bronze Age

Thermoluminescence (TL) dating and multivariate statistical methods based on radioisotope X-ray fluorescence analysis have been utilized to date and classify Syrian archaeological ceramics fragment from Tel Jamous site. 54 samples were analyzed by radioisotope X-ray fluorescence; 51 of them come from Tel Jamous archaeological site in Sahel Akkar region, Syria, which fairly represent ceramics belonging to the Middle Bronze Age (2150 to 1600 B.C.) and the remaining three samples come from Mar-Takla archaeological site fairly representative of the Byzantine ceramics. We have selected four fragments from Tel Jamous site to determinate their age using thermoluminescence (TL) method; the results revealed that the date assigned by archaeologists was good. An annular 109Cd radioactive source was used to irradiate the samples in order to determine their chemical composition and the results were treated statistically using two methods, cluster and factor analysis. This treatment revealed two main groups; the first one contains only the three samples M52, M53, and M54 from Mar-Takla site, and the second one contains samples that belong to Tel Jamous site (local).

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