Comparison of seven indicator PCBs and three coplanar PCBs in beef, pork, and chicken fat

The risk assessment of polychlorinated biphenyls (PCBs) is difficult since complex congeners were used in many industrial applications for a long period of time and the residue monitoring in foods of animal origin and the environment were not established in comparable systems. The relationships of determined concentrations in indicator PCB congeners (mono- and di-ortho PCBs) and coplanar PCB congeners (non-ortho PCBs) in livestock products are presented in this study. The concentrations of seven indicator PCBs were compared with three coplanar PCBs in beef, pork, and chicken fat. Distributions of concentration for the indicator PCBs in three different animal species were similar except for that of PCB-118 (2,3',4,4',5-pentachlorobiphenyl) in pork fat. The congeners with the highest concentration were PCB-138 (2,2',3,4,4',5'-hexachlorobiphenyl) in beef and pork fat and PCB-28 (2,4,4'-trichlorobiphenyl) in chicken fat. The bioaccumulation and metabolism of PCBs in animal species represent different congener profiles in livestock products. The percentage of the total concentration of three coplanar PCBs was about 2% of the total concentration of the seven indicator PCBs. Relatively high concentration of mono-ortho and di-ortho PCBs in fat samples of livestock products may be calculated with the concentration of coplanar PCBs that can be usually determined on a sequential procedure with dioxin analysis. Therefore, the relationship of the amounts between seven indicator PCBs and three coplanar PCBs may be useful to derive the composition and level of contaminants in beef, pork, and chicken.     

Distribution characteristics of nonylphenols in the artificial Lake Shihwa, and surrounding creeks in Korea

Nonylphenols were determined from the water, suspended particle, and sediment samples taken from the Lake Shihwa in Korea and its surrounding creeks flowing through municipal and industrial areas, and into the lake. The nonylphenols were detected at the concentration ranges of 0.0-41.3 microg/l, 0.0-116.6 and 0.3-31.7 mg/kg in water, suspended particle and sediment samples respectively. The contamination levels of nonylphenols were increased along the down stream. Considerably high levels of nonylphenols were found at the industrial area compared to the municipal area. No remarkable differences were found between the isomer patterns of nonylphenols for the sample matrices of each sampling site, i.e. water, suspended solids and sediment. Strong correlations between water and sediment with 10(5.2) of the mean partition coefficient (Koc ) were observed. These indicate that most of nonylphenols came from industrial wastewater at high level. It is thought that the water quality of the Lake Shihwa is affected greatly by industrial environments surrounding.     

Partitioning of naphthalene to gemini surfactant-treated alumina

Partitioning of naphthalene to anionic surfactants adsorbed on alumina in the aqueous phase was studied for immobilization of the contaminant in the subsurface. Three anionic surfactants with different molecular structures were used: a conventional (sodium dodecylbenzene sulfonate, SDDBS), a gemini (dialkylated disulfonated diphenyl oxide with alkyl chain length of 12, DADS-C12), and a dianionic (monoalkylated disulfonated diphenyl oxide with alkyl chain length of 12, MADS-C12). Sorption of the surfactants onto alumina was studied in a series of batch experiments and the effectiveness of the adsorbed surfactants onto aluminum oxide as a sorptive phase for naphthalene was compared.     

Binding of dialkylated disulfonated diphenyl oxide surfactant onto alumina in the aqueous phase

Adsorption of a gemini surfactant that has two monomers and a spacer in a molecule (dialkylated disulfonated diphenyl oxide with alkyl chain lengths of twelve, DADS-C12) onto positively-charged aluminum oxide in water was studied and compared with a single-monomer anionic surfactant (sodium dodecylbenzene sulfonate, SDDBS). More mass of the gemini surfactant was adsorbed than the conventional single-monomer SDDBS. Fewer moles of the first were bound to the substrate than the second indicating that larger molecular structure of the gemini surfactant does not hinder the sorption. Both surfactants followed similar sorption mechanisms, however, stronger hydrophobic interactions were shown in the bilayer formation of the adsorbed gemini surfactant.     

Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

Two artificial neural networks (ANNs), unsupervised and supervised learning algorithms, were applied to suggest practical approaches for the analysis of ecological data. Four major aquatic insect orders (Ephemeroptera, Plecoptera, Trichoptera, and Coleoptera, i.e. EPTC), and four environmental variables (elevation, stream order, distance from the source, and water temperature) were used to implement the models. The data were collected and measured at 155 sampling sites on streams of the Adour–Garonne drainage basin (South-western France). The modelling procedure was carried out following two steps. First, a self-organizing map (SOM), an unsupervised ANN, was applied to classify sampling sites using EPTC richness. Second, a backpropagation algorithm (BP), a supervised ANN, was applied to predict EPTC richness using a set of four environmental variables. The trained SOM classified sampling sites according to a gradient of EPTC richness, and the groups obtained corresponded to geographic regions of the drainage basin and characteristics of their environmental variables. The SOM showed its convenience to analyze relationships among sampling sites, biological attributes, and environmental variables. After accounting for the relationships in data sets, the BP used to predict the EPTC richness with a set of four environmental variables showed a high accuracy (r=0.91 and r=0.61 for training and test data sets respectively). The prediction of EPTC richness is thus a valuable tool to assess disturbances in given areas: by knowing what the EPTC richness should be, we can determine the degree to which disturbances have altered it. The results suggested that methodologies successively using two different neural networks are helpful to understand ecological data through ordination first, and then to predict target variables.     

A parametric model of child body shape in seated postures

Objective: The shape of the current physical and computational surrogates of children used for restraint system assessments is based largely on standard anthropometric dimensions. These scalar dimensions provide valuable information on the overall size of the individual but do not provide good guidance on shape or posture. This study introduced the development of a parametric model that statistically predicts individual child body shapes in seated postures with a few given parameters.

Methods: Surface geometry data from a laser scanner of children ages 3 to 11 (n = 135) were standardized by a 2-level fitting method using intermediate templates. The standardized data were analyzed by principal component analysis (PCA) to efficiently describe the body shape variance. Parameters such as stature, body mass index, erect sitting height, and 2 posture variables related to torso recline and lumbar spine flexion were associated with the PCA model using regression.

Results: When the original scan data were compared with the predictions of the model using the given subject dimensions, the average root mean square error for the torso was 9.5 mm, and the 95th percentile error was 17.35 mm.

Conclusions: For the first time, a statistical model of child body shapes in seated postures is available. This parametric model allows the generation of an infinite number of virtual children spanning a wide range of body sizes and postures. The results have broad applicability in product design and safety analysis. Future work is needed to improve the representation of hands and feet and to extend the age range of the model. The model presented in this article is publicly available online through HumanShape.org.     

Solubilization of PAH mixtures by three different anionic surfactants

Solubilization of naphthalene and phenanthrene into the micelles formed by three different anionic surfactants was investigated for single, binary, and ternary mixtures including pyrene. The three surfactants were sodium dodecylbenzene sulfonate (SDDBS), monoalkylated disulfonated diphenyl oxide (MADS-C12), and dialkylated disulfonated diphenyl oxide (DADS-C12). The order of increasing solubility enhancement of naphthalene and phenanthrene was SDDBS < MADS-C12 < < DADS-C12, which indicates that the hydrophobic chains in micellar core play more important role for the solubilization of polycyclic aromatic hydrocarbons (PAHs) than the benzene rings in palisade layer of a micelle. The solubility enhancement of naphthalene was slightly changed in PAH mixtures. The solubility of phenanthrene was greatly enhanced in presence of naphthalene but reduced in presence of pyrene. The explanation for these results could be that less hydrophobic compounds can be solubilized at the interfacial region of a hydrophobic core, which reduces the interfacial tension between the core and water, and then the reduced interfacial tension can support a larger core volume for the same interfacial energy.     

Aerosol Composition Change due to Dust Storm: Measurements between 1992 and 1999 at Gosan,Korea

Aerosol composition change between dust storm and non duststorm periods is studied using the TSP (Total SuspendedParticulate) data measured at Gosan, Korea between 1992 and1999. The concentrations of elements measured between 1993and 1996 and those of ions between 1992 and 1999 duringdust storms are compared with those during non-dust stormperiods in spring (March, April, and May). Among theanalyzed ions, the concentrations of crustal species(potassium, calcium, magnesium, and chloride) andanthropogenic species (nitrate and non-sea salt (nss)-sulfate) increased when dust storm occurs while those ofammonium and sodium did not increase. Among the analyzedelements, the concentrations of crustal species (Fe, Al,Ca, Ti, and Zn) increased when dust storm occurs whilethose of anthropogenic species (Mn, V, Ni, Cu, Cd, and Cr)did not increase. The only anthropogenic element of whichconcentration increased during dust storm periods was Pb.It was found that the concentrations of nitrate and nss-sulfatewere highest during spring. Also, the ratio of theyearly average concentrations of nitrate to nss-sulfateincreases, probably due to the emission trend change innortheast Asia, especially, in China.