Estrogen equivalent concentration of 13 branched para-nonylphenols in three technical mixtures by isomer-specific determination using their synthetic standards in SIM mode with GC-MS and two new diasteromeric isomers

Thirteen isomers of branched para-nonylphenols (para-NP) in three technical mixtures were isomer-specifically determined using their synthesized standards by SIM of structurally specific ions, m/z 135, 149 or 163 with GC–MS. Of the 13 isomers, four isomers, 4-(2,4-dimethylheptan-4-yl)phenol, 4-(4-methyloctan-4-yl)phenol, 4-(3-ethyl-2-methylhexan-2-yl)phenol (3E22NP) and 4-(2,3-dimethylheptan-2-yl)phenol synthesized for their determinations were first used as standard substances. The 13 isomers in the technical mixtures individually occurred at mass percent portion of more than 2%. The total mass percent portions in the mixtures from Tokyo Chemical Industry (TCI), Aldrich, and Fluka covered with 89 ± 2%, 75 ± 4% and 77 ± 2%, respectively. The abundance of 4-(3,6-dimethylheptan-3-yl)phenol in the three mixtures was the largest with 11.1 ± 2% to 9.9 ± 0.3%, while that of 4-(2-methyloctan-2-yl)phenol was the smallest with 2.9 ± 0.3% to 3.0 ± 0.2%. Additionally, structures of four new isomers of more than 1% portion present in a technical mixture were elucidated as two pairs of diastereomeric isomers: two types of 4-(3,4-dimethylheptan-4-yl)phenol (344NP) and those of 4-(3,4-dimethylheptan-3-yl)phenol (343NP). By estrogenic assay of 13 isomers with yeast estrogen screen system, the activity of 3E22NP was the highest, while that of 4-(3-methyloctan-3-yl)phenol was the least. Their relative activities to that of 3E22NP were individually calculated. Estrogenic equivalent concentrations of the three technical mixtures were predictively evaluated. The ratio of the EEC to the conventional concentration, total mass percent portions of the 13 isomers in technical mixtures were 0.208 for TCI, 0.206 for Aldrich and 0.205 for Fluka. The predicted estrogenic activity of measured concentration of para-NP in technical mixtures was approximately 5-fold greater than the measured estrogen agonist activity.     

Concentration of bioactive compounds in mussels Mytilus galloprovincialis as an indicator of pollution

The polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organotins were analyzed in mussels Mytilus galloprovincialis from polluted and unpolluted sites from Mokpo Bay, Korea. The total PAH's concentrations (10(-3)mgkg(-1)) measured by GC-MS were in the range from 31+/-23 to 1+/-1. Among the eight PAHs the predominant ones were fluoranthene, phenanthrene and pyrene and accounted approximately 63% of the total PAHs. Among the four detected PCBs the highest content was of PCB 153, which accounted about 47% of the total PCBs. The main organotin compounds were dibutyltindichloride (DBT) and tributyltinchloride (TBT) and their composition was approximately 33% and 24%. PAHs, PCBs and organotins were found only in the mussels from polluted site. The antioxidant activity by ABTS [2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid)] test was higher in mussels from polluted than from unpolluted sites (P<0.05). It was found a correlation between the determined compounds (PAHs, PCBs and organotins) and the antioxidant activity of the mussel tissue from polluted site and the correlation coefficients were 0.96, 0.92 and 0.80, respectively. Such correlation can be explained by the properties of mussels. Since the mussel cell wall and tissues are hydrophobic, they can concentrate a number of hydrophobic pollutants like PAHs and PCBs from the marine environment by solubility rules. On the other hand, proteins are lipophilic compounds having antioxidant properties. Certain amino acid residues and thiol (-SH) groups, contained in proteins, respond to the ABTS antioxidant activity assay. Thus there may be a correlation between the total antioxidant activity of the organism and the PAH-PCB pollutants which were concentrated from its environment. The studied properties of mussels from polluted site can be used as an additional indicator of pollution.     

Effectiveness of compacted soil liner as a gas barrier layer in the landfill final cover system

A compacted soil liner (CSL) has been widely used as a single barrier layer or a part of composite barrier layer in the landfill final cover system to prevent water infiltration into solid wastes for its acceptable hydraulic permeability. This study was conducted to test whether the CSL was also effective in prohibiting landfill gas emissions. For this purpose, three different compaction methods (i.e., reduced, standard, and modified Proctor methods) were used to prepare the soil specimens, with nitrogen as gas, and with water and heptane as liquid permeants. Measured gas permeability ranged from 2.03x10(-10) to 4.96x10(-9)cm(2), which was a magnitude of two or three orders greater than hydraulic permeability (9.60x10(-13) to 1.05x10(-11)cm(2)). The difference between gas and hydraulic permeabilities can be explained by gas slippage, which makes gas more permeable, and by soil-water interaction, which impedes water flow and then makes water less permeable. This explanation was also supported by the result that a liquid permeability measured with heptane as a non-polar liquid was similar to the intrinsic gas permeability. The data demonstrate that hydraulic requirement for the CSL is not enough to control the gas emissions from a landfill.     

Social media and disasters: a functional framework for social media use in disaster planning,response, and research

A comprehensive review of online, official, and scientific literature was carried out in 2012–13 to develop a framework of disaster social media. This framework can be used to facilitate the creation of disaster social media tools, the formulation of disaster social media implementation processes, and the scientific study of disaster social media effects. Disaster social media users in the framework include communities, government, individuals, organisations, and media outlets. Fifteen distinct disaster social media uses were identified, ranging from preparing and receiving disaster preparedness information and warnings and signalling and detecting disasters prior to an event to (re)connecting community members following a disaster. The framework illustrates that a variety of entities may utilise and produce disaster social media content. Consequently, disaster social media use can be conceptualised as occurring at a number of levels, even within the same disaster. Suggestions are provided on how the proposed framework can inform future disaster social media development and research.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Arsenic concentration in porewater of an alkaline coal ash disposal site: Roles of siderite precipitation/dissolution and soil cover

The geochemical behavior of As in porewaters of an alkaline coal ash disposal site was investigated using multilevel samplers. The disposal site was in operation from 1983 until 1994 and was covered with 0.3–0.5 m thick soils in 2001 when this study was initiated. Sequential extraction analyses and batch leaching experiments were also performed using the coal ash samples collected from the disposal site. The results suggest the important roles of siderite (FeCO₃) precipitation/dissolution and soil cover, which have been ignored previously. Arsenic levels in the porewater were very low (average of 10 μg L⁻¹) when the site was covered with soil due to coprecipitation with siderite. The soil cover enabled the creation of anoxic conditions, which raised the Fe concentration by the reductive dissolution of Fe-(hydr)oxides. Because of the high alkalinity generated from the alkaline coal ash, even a small increase in the Fe concentration (0.66 mg L⁻¹ on average) could cause siderite precipitation. When the soil cover was removed, however, an oxidizing condition was created and triggered the precipitation of dissolved Fe as (hydr)oxides. As a result, the dissolution of previously precipitated As-rich siderite caused higher As concentration in the porewater (average of 345 μg L⁻¹).     

Heterogeneous uptake of octamethylcyclotetrasiloxane (D4) and decamethylcyclopentasiloxane (D5) onto mineral dust aerosol under variable RH conditions

We have carried out kinetic studies to characterize the heterogeneous decay of octamethylcyclotetrasiloxane (D₄) and decamethylcyclopentasiloxane (D₅) in the presence of representative mineral dust aerosol in order to obtain a better understanding of the atmospheric fate of these siloxanes. The heterogeneous chemistry of D₄ and D₅ with various mineral dusts was studied in an environmental aerosol reaction chamber using FTIR absorption spectroscopy to monitor the reaction. The apparent heterogeneous uptake coefficient, γ_app, for D₄ and D₅ with various mineral dusts was measured under dry conditions and as a function of relative humidity (RH). In addition, the effect of initial D₄ and D₅ concentration on the rate and yield of the reaction was examined. The uptake coefficient, γ_app, for D₄ and D₅ was similar for the most reactive aerosols tested, with kaolinite ≈hematite > silica. Limited uptake onto carbon black and calcite surfaces was observed for either siloxane. Reaction with hematite and kaolinite resulted in multilayer coverages, suggesting extensive polymerization of D₄ and D₅ on the aerosol surface.     

Comparison of summer and winter California central valley aerosol distributions from lidar and MODIS measurements

Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2007. While the ground PM_2.5 (particulate matter with diameter ≤ 2.5 μm) concentration was highest in the winter, the aerosol optical depth (AOD) measured from the MODIS and lidar instruments was highest in the summer. A multiyear seasonal comparison shows that PM_2.5 in the winter can exceed summer PM_2.5 by 68%, while summer AOD from MODIS exceeds winter AOD by 29%. Warmer temperatures and wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not necessarily by surface particulate matter monitors. Temperature inversions, especially during the winter, contribute to higher PM_2.5 measurements at the surface. Measurements of the mixing layer height from lidar instruments provide valuable information needed to understand the correlation between satellite measurements of AOD and in situ measurements of PM_2.5. Lidar measurements also reflect the ammonium nitrate chemistry observed in the San Joaquin Valley, which may explain the discrepancy between the MODIS AOD and PM_2.5 measurements.