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The aim of this paper was to determine spatial variation of 6 indicator polychlorinated biphenyls (PCBs) and 18 organochlorine pesticides (OCPs) in street dust samples (n=49) collected during summer season from suburban/urban zones of Tianjin, China. Sample preparation was performed by using accelerated solvent extraction with simultaneous extraction and clean-up of PCBs and OCPs, while quantification was carried out using gas chromatography coupled with microelectro absorption detector and gas chromatography coupled with mass spectrometry. The total concentrations of studied PCBs varied from

About 10 heavy elements were determined in 90 samples of baby food collected from Spanish and Serbian market. The results indicated that iron, manganese and copper were most frequently detected. Tin was the predominant toxic element in both Spanish and Serbian samples, with occurrence frequencies of 12.5% and 10.0%, respectively. Element intake for Spanish and Serbian infants were estimated and compared with the recommended reference values, for the majority of elements being lower than one. However, iron and manganese intake through consumption of infant/follow-on formulas were assessed to be higher than the respective daily intakes. Particular attention should be paid to the exposure of infants who consume porridges made of vegetables and fish or chicken, because they may ingest certain elements, particularly arsenic and lead, at levels that exceed the reference toxicological values. Principal component analysis (PCA) was applied to classify and distinguish the different types of baby food. [ABSTRACT FROM PUBLISHER]

This paper reviews data available in the literature on biomass gasification parameters in order to elucidate the general information common for different gasification systems fueled with different biomass feedstocks by applying principal component analysis (PCA). Focus was given to the co-gasification of crude glycerol derived as by-product in biodiesel plants, with olive kernel derived from olive oil processing plants, a lignocellulosic biomass locally available in the Mediterranean region, which might be considered as an important step towards economic and sustainable biodiesel production, particularly in small and medium-scale plants. The PCA was applied for the first time on the literature-based input data sets of the thermochemical conversion processes of various biomass, aiming to: (a) characterize syngases obtained under different conditions during co-gasification of crude glycerol and olive kernel, (b) compare syngases obtained by co-gasification and co-pyrolysis of crude glycerol and olive kernel, and (c) assess general information common for different gasification systems, comparing the syngas from co-gasification of crude glycerol with olive kernel with those produced by other non-woody and woody biomass gasification processes. PCA has evidenced the strongest correlations among the variables included in the sets, which were further used to discuss the similarities among the produced gases. Some of the major conclusions derived from PCA results concern the comparability of gases produced by co-gasification of crude glycerol and olive kernel with the published data, particularly with gases produced by gasification of olive residues with intermediate to the highest H 2 contents, intermediate to low CO 2 contents and intermediate H 2 /CO ratios. Even though olive-based waste gasification may result in wide range of the gas composition, the majority of the considered syngases was separated on the PCA biplots from gases produced by gasification of woody and other non-woody biomass due to higher H 2 /CO ratios. [ABSTRACT FROM AUTHOR]

Abstract: Principal component analysis (PCA) was applied to a data set containing the levels of indicator polychlorinated biphenyls (PCBs) in human milk of mothers living in the Wielkopolska region, Poland, in order to investigate the information captured in the PCB patterns and to elucidate the relationship between PCB concentrations in milk and donor characteristics. According to the obtained PCA results milk fat content was the most influential factor affecting the PCB levels in milk of the Wielkopolska cohort. The lifestyle data collected from the questionnaire completed by the donors appeared to have no influence on PCB concentrations in breast milk. The score plots revealed the PCB contents of milk were quite low and uniform with a few outliers, without discrimination observed either between the primipareous and secundipareous females or between donors from the urban and rural areas. Comparison of the PCB levels and profiles of human milk from the Wielkopolska region and from various European and Asian locations made by PCA reflected a generally low background exposure and indicated the possible reasons for the outlying of some samples. In order to enhance the chances of observing the relationship between donor habits and PCB levels in breast milk it was suggested that the questionnaire be redesigned to gather information about vegetable product consumption and indoor air exposure. [ABSTRACT FROM AUTHOR]

Abstract: Principal component analysis (PCA) was applied on data sets containing levels of six heavy metals (Pb, Cu, Zn, Cd, Ni, Cr) in soils from different parts of the world in order to investigate the information captured in the global heavy metal patterns. Data used in this study consisted of the heavy metal contents determined in 23 soil samples from and around the Novi Sad city area in the Vojvodina Province, northern part of Serbia, together with those from the city of Banja Luka, the second largest city in Bosnia and Herzegovina, and the ones reported previously in the relevant literature in order to evaluate heavy metal distribution pattern in soils of different land-use types, as well as spatial and temporal differences in the patterns. The chemometric analysis was applied on the following input data sets: the overall set with all data gathered in this study containing 264 samples, and two sub sets obtained after dividing the overall set in accordance to the soil metal index, SMI, calculated here, i.e. the set of unpolluted soils having SMIs<100%, and the set of polluted soils with SMIs>100%. Additionally, univariate descriptive statistics and the Spearman’s non-parametric rank correlation coefficients were calculated for these three sets. A Box–Cox transformation was used as a data pretreatment before the statistical methods applied. According to the results, it was seen that anthropogenic and background sources had different impact on the data variability in the case of polluted and unpolluted soils. The sample discrimination regarding the land-use types was more evident for the unpolluted soils than for the polluted ones. Using linear discriminant analysis, content of Cu was determined as a variable with a major discriminant capacity. The correct classification of 73.3% was achieved for predefined land-use types. Classification of the samples in accordance to the pollution level expressed as SMI was necessary in order to avoid the “masking” effect of the polluted soil patterns over the non-polluted ones. [Copyright &y& Elsevier]

In order to investigate the distribution pattern of individual organochlorine compounds in soil samples collected from the sites (Canary Island – Spain, China, Germany, India, Romania, Russia, Serbia, Swiss, UK) affected by industrial activities to the more remote areas, principal component analysis was performed on the data taken from literature. Loading plots pointed out the strong correlation among the variables. Score plots revealed similar PCB- and OCP-soil patterns for majority of the investigated sites. Nevertheless, the temporal differences of PCB-soil loads have been identified: the late 1990s and early 2000s concentrations are similar to those of the early 1940s, and they are below the levels existed in 1980. The most pronounced PCB concentrations characterized the soil from 1966. For OCPs the influence of sites location on the detected concentration has been revealed: China and India were characterized by comparably higher loads of DDX (DDT and its metabolites) and of HCH-isomers, respectively. [Copyright &y& Elsevier]

Abstract: Microelements in soft winter wheat grain samples collected from all over Serbian wheat growing regions were analyzed quantitatively by atomic absorption spectrophotometry. Microelement contents differed markedly among wheat samples harvested from various regions. The most frequently occurring pattern is Fe>Mn>Zn>Cu>Pb>As>Cd>Hg. Principal component analysis (PCA) and cluster analysis (CA) were applied to classify the samples according to their microelement contents. Four PCs, explaining 84% of total variance, correlate well with the following elements: PC1 with Cu, Mn, and Zn content; PC2 with Pb and As; PC3 with Cd; and PC4 with Hg. Iron fails to load significantly on any PCs. Physical meaning of PCs could be attributed to metabolic processes in wheat, soil type, vicinity of industrial centers and busy motorways, and application of agrochemicals. [Copyright &y& Elsevier]

In order to understand the distribution pattern of individual polycyclic aromatic hydrocarbon (PAH) compounds in soil samples collected from the sites affected by industrial activities to the more remote areas, principal component analysis and cluster analysis were performed. The score plots for the distribution pattern of individual PAH compounds differ quite considerably depending on the variations of total PAH concentration levels. The PAHs were found to be distributed in three groups mainly according to the number of rings in their structure for grossly contaminated areas. By contrast, in common contaminated areas the individual PAH compounds have been randomly spread. [Copyright &y& Elsevier]

• BTEX were measured for the first time in the smoke of locally-available biomasses. • Benzene was detected in all investigated samples except for fresh plum endocarp. • PCA and CA shown how time and temperatures profiles during combustion and pyrolysis affected levels of BTEX in smoke. • Pelleting of plum endocarp with poplar sawdust can be used as an alternative fuel. This paper reports the results of the level of benzene, toluene, ethylbenzene and p , m, o – xylenes (BTEX) compounds in smoke from combustion and pyrolysis of apricot endocarp, plum endocarp, the poplar wood pellets and sawdust of poplar clone I-214 (P. x euramericana c l. I-214 cultivated in Serbia). The total concentrations of BTEX, in the smoke produced by the combustion range from < LOD (fresh plum endocarp) to 1.74 mg kg−1 (apricot endocarp), while in the smoke produced by the pyrolysis, ranged from < LOD (poplar wood sawdust) to 1.99 mg kg−1 (apricot endocarp). Toluene, ethylbenzene and m ± p xylenes were detected during pyrolysis for all three plum endocarp samples, while during combustion only for fermented and distilled one. Additionally, this study was systematically investigated the application of cluster analysis CA and principal component analysis PCA in interpretation of origin and combustion and pyrolysis parameters; PCA and CA shown how time and temperatures profiles during combustion and pyrolysis affected levels of BTEX in smoke. The results of score plot demonstrated that PCA may be useful in discrimination between samples based on the combustion and pyrolysis properties and the emitted level of BTEX. [ABSTRACT FROM AUTHOR]