Drinking water treatment is not associated with an observed increase in neural tube defects in mice

Disinfection by-products (DBPs) arise when natural organic matter in source water reacts with disinfectants used in the water treatment process. Studies have suggested an association between DBPs and birth defects. Neural tube defects (NTDs) in embryos of untreated control mice were first observed in-house in May 2006 and have continued to date. The source of the NTD-inducing agent was previously determined to be a component of drinking water. Tap water samples from a variety of sources were analyzed for trihalomethanes (THMs) to determine if they were causing the malformations. NTDs were observed in CD-1 mice provided with treated and untreated surface water. Occurrence of NTDs varied by water source and treatment regimens. THMs were detected in tap water derived from surface water but not detected in tap water derived from a groundwater source. THMs were absent in untreated river water and laboratory purified waters, yet the percentage of NTDs in untreated river water were similar to the treated water counterpart. These findings indicate that THMs were not the primary cause of NTDs in the mice since the occurrence of NTDs was unrelated to drinking water disinfection.     

Toxicodynamic modeling of 137Cs to estimate white-tailed deer background levels for the Department of Energy's Savannah River Site

The U.S. Department of Energy's (USDOE) Savannah River Site (SRS) is a former nuclear weapon material production and current research facility adjacent to the Savannah River in South Carolina, USA. The purpose of this study was to determine the background radiocesium (¹³⁷Cs) body burden (e.g., from global fallout) for white-tailed deer (Odocoileus virginianus) inhabiting the SRS. To differentiate what the background burden is for the SRS versus ¹³⁷Cs obtained from SRS nuclear activities, data were analyzed spatially, temporally and compared to other off-site hunting areas near the SRS. The specific objectives of this study were: to compare SRS and offsite deer herds based on time and space; to interpret comparisons based on how data were collected as well as the effect of environmental and anthropogenic influences; to determine what the ecological half-life/decay rate is for ¹³⁷Cs in the SRS deer herd; and to give a recommendation to what should be considered the background ¹³⁷Cs level in the SRS deer herd. Based on the available information and analyses, it is recommended that the determination of what is considered background for the SRS deer herd be derived from data collected from the SRS deer herd itself and not offsite collections for a variety of reasons. Offsite data show extreme variability most likely due to environmental factors such as soil type and land-use patterns (e.g., forest, agriculture, residential activities). This can be seen from results where samples from offsite military bases (Fort Jackson and Fort Stewart) without anthropogenic ¹³⁷Cs sources were much higher than both the SRS and a nearby (Sandhills) study site. Moreover, deer from private hunting grounds have the potential to be baited with corn, thus artificially lowering their ¹³⁷Cs body burdens compared to other free-ranging deer. Additionally, sample size for offsite collections were not robust enough to calculate a temporal decay curve with an upper confidence level to determine if the herds are following predicted radioactive decay rates like the SRS or if the variability is due to those points described above. Using mean yearly values, the ecological half-life for ¹³⁷Cs body burdens for SRS white-tailed deer was determined to be 28.79 years—very close to the 30.2 years physical half-life.     

Hydrologic modelling for Lake Basaka: development and application of a conceptual water budget model

Quantification of fluxes of water into and out of terminal lakes like Basaka has fundamental challenges. This is due to the fact that accurate measurement and quantification of most of the parameters of a lake’s hydrologic cycle are difficult. Furthermore, quantitative understanding of the hydrologic systems and hence, the data-intensive modelling is difficult in developing countries like Ethiopia due to limitation of sufficient recorded data. Therefore, formulation of a conceptual water balance model is extremely important as it presents a convenient analytical tool with simplified assumptions to simulate the magnitude of unknown fluxes. In the current study, a conceptual lake water balance model was systematically formulated, solved, calibrated, and validated successfully. Then, the surface water and groundwater interaction was quantified, and a mathematical relationship developed. The overall agreement between the observed and simulated lake stage at monthly time step was confirmed based on the standard performance parameters (R ², MAE, RMSE, E _f). The result showed that hydrological water balance of the lake is dominated by the groundwater (GW) component. The net GW flux in recent period (post-2000s) accounts about 56 % of the total water inflow. Hence, GW plays a leading role in the hydrodynamics and existence of Lake Basaka and is mostly responsible for the expansion of the lake. Thus, identification of the potential sources/causes for the GW flux plays a leading role in order to limit the further expansion of the lake. Measurement of GW movement and exchange in the area is a high priority for future research.     

Feature extraction using Hough transform for solid waste bin level detection and classification

This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image’s gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.     

Metal concentrations and metallothionein levels in Mytilus galloprovincialis from Elefsis bay (Saronikos gulf, Greece)

Spatial and temporal variability of Cd, Cu, Cr, Ni, Zn, Fe and Mn and metallothionein (MT) concentrations were determined in mussels Mytilus galloprovincialis from Elefsis bay (Saronikos gulf, Greece). Higher concentrations of both metal concentrations and MTs were recorded in mussels inhabiting industrial locations (steelworks and shipyard), indicating a markedly higher metal bioavailability. However at these sites, located at the eastern part of the bay, mussel metal concentrations were not always correlated with both seawater metal concentrations and MTs possibly due to different time scales of integration of the metal sources into mussels and/or the participation of other metal regulatory mechanisms except MT induction. The pattern of the temporal variation of mussel metal concentrations and the MT levels was similar among stations with higher values during the winter–spring season and lower during the summer–autumn period. The inverse relationship of flesh condition index with mussel metal concentrations was attributed to the influence of mussel annual reproductive cycle.     

Effects of natural organic matter type and concentration on the aggregation of citrate-stabilized gold nanoparticles

The aggregation of 12 nm citrate-stabilized gold nanoparticles (cit-AuNPs) in the presence of four different natural organic matter (NOM) isolates and a monovalent electrolyte (KCl) was evaluated using time-resolved dynamic light scattering. All four NOM isolates stabilized the cit-AuNPs with respect to aggregation. However, specific effects varied among the different NOM isolates. At pH = 6 in 80 mM KCl, low concentrations (<0.25 mg C per L) of large molecular weight Suwannee River Humic Acid (SRHA) was required to stabilize cit-AuNPs, while larger concentrations (>2 mg C per L) of smaller Suwannee River Fulvic Acid (SRFA) were necessary at the same ionic strength. Suwannee River NOM (SRNOM) which contains both SRHA and SRFA behaved in a manner intermediate between the two. Pony Lake Fulvic Acid (PLFA), an autochthonous NOM isolate, provided substantial stability at low concentrations, yet aggregation was induced at NOM concentrations > 2 mg C per L, a trend that is hypothesized to be the result of favourable hydrophobic interactions between coated particles induced at increased surface coverage. For all NOM isolates, it appears that NOM adsorption or conformational changes at the AuNP surfaces result in significant increases in the hydrodynamic diameter that aren't attributable to NP-NP aggregation.     

Utilizing pyrosequencing and quantitative PCR to characterize fungal populations among house dust samples

Molecular techniques are an alternative to culturing and counting methods in quantifying indoor fungal contamination. Pyrosequencing offers the possibility of identifying unexpected indoor fungi. In this study, 50 house dust samples were collected from homes in the Yakima Valley, WA. Each sample was analyzed by quantitative PCR (QPCR) for 36 common fungi and by fungal tag-encoded flexible (FLX) amplicon pyrosequencing (fTEFAP) for these and additional fungi. Only 24 of the samples yielded amplified results using fTEFAP but QPCR successfully amplified all 50 samples. Over 450 fungal species were detected by fTEFAP but most were rare. Twenty-two fungi were found by fTEFAP to occur with at least an average of ≥0.5% relative occurrence. Many of these fungi seem to be associated with plants, soil or human skin. Combining fTEFAP and QPCR can enhance studies of fungal contamination in homes.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Sand as a relevant fraction in geochemical studies in intertidal environments

Soil and sediment samples from several intertidal environment exposed to different types of contamination were studied to investigate the importance of grain size in relation to the capacity of the substrates to retain trace metals. The unfractionated samples (referred to as bulk samples) were separated into the following grain/size fractions: fine–coarse sand (2?0.100 mm), very fine sand (0.100?0.050 mm), silt (0.050?0.002 mm), and clay (0.002 mm). The sample into its fractions was carried out was in a glove box under high-purity N₂ atmosphere in order to minimize any alterations to the samples. The bulk samples were characterized in terms of physicochemical properties such as pH, redox potential, and grain size. The total organic carbon (TOC), total sulfur (S), iron (Fe) pyrite, Fe, and manganese (Mn), and trace metals lead (Pb), mercury (Hg), chromium (Cr), and nickel (Ni) were analyzed in the bulk samples and in each fraction. The sand fractions were also examined by scanning electron microscopy (SEM). Comparisons of the above parameters were made between fractions and between each fraction and the corresponding bulk sample. The fine–coarse sand fraction contained high levels of the primary elements of the geochemical processes that occur in marine sedimentary environments such as TOC, total Fe, Mn, and S. The net concentrations of these four elements were higher in the fine-coarse sand fraction than in the very fine sand fraction and were similar to the net concentrations in the silt and clay fractions. Detailed SEM analysis of the sand coarse fraction revealed the presence of Fe and aluminum oxyhydroxide coatings in the oxic layers, whereas the framboidal pyrites and coatings observed in the anoxic layers were Fe sulfides. The presence of the various coatings explains why the trace metal concentrations in the sand fine–coarse fraction were similar to those in the clay fraction and higher than those in the very fine sand fraction. The present results highlight the importance of the sand fraction, which is generally disregarded in geochemical and environmental studies of sedimentary layers.     

Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago

Both canonical correlation analysis (CCA) and principal component analysis (PCA) were applied to atmospheric aerosol and trace gas concentrations and meteorological data collected in Chicago during the summer months of 2002, 2003, and 2004. Concentrations of ammonium, calcium, nitrate, sulfate, and oxalate particulate matter, as well as, meteorological parameters temperature, wind speed, wind direction, and humidity were subjected to CCA and PCA. Ozone and nitrogen oxide mixing ratios were also included in the data set. The purpose of statistical analysis was to determine the extent of existing linear relationship(s), or lack thereof, between meteorological parameters and pollutant concentrations in addition to reducing dimensionality of the original data to determine sources of pollutants. In CCA, the first three canonical variate pairs derived were statistically significant at the 0.05 level. Canonical correlation between the first canonical variate pair was 0.821, while correlations of the second and third canonical variate pairs were 0.562 and 0.461, respectively. The first canonical variate pair indicated that increasing temperatures resulted in high ozone mixing ratios, while the second canonical variate pair showed wind speed and humidity’s influence on local ammonium concentrations. No new information was uncovered in the third variate pair. Canonical loadings were also interpreted for information regarding relationships between data sets. Four principal components (PCs), expressing 77.0 % of original data variance, were derived in PCA. Interpretation of PCs suggested significant production and/or transport of secondary aerosols in the region (PC1). Furthermore, photochemical production of ozone and wind speed’s influence on pollutants were expressed (PC2) along with overall measure of local meteorology (PC3). In summary, CCA and PCA results combined were successful in uncovering linear relationships between meteorology and air pollutants in Chicago and aided in determining possible pollutant sources.