Distribution of antidepressants and their metabolites in brook trout exposed to municipal wastewaters before and after ozone treatment--evidence of biological effects

This study examined the tissues distribution of selected serotonin reuptake inhibitors (SSRIs) in brook trout exposed for 3 months to continuous flow-through primary-treated effluent before and after ozone treatment. A reliable analytical method was developed for the quantification of trace amounts of antidepressants in small tissue homogenate extracts. Levels of six antidepressants and four of their N-desmethyl metabolites were determined using liquid chromatography-tandem mass spectrometry. Significant amounts of the SSRIs were found in fish tissue-in decreasing order: liver>brain>muscle. Sertraline and its metabolite desmethylsertraline were the predominant substances observed in most tissues (0.04-10.3 ng g(-1)). However, less SSRIs (0.08-1.17 ng g(-1)) were bioaccumulated in the ozonated effluent. The early molecular effects of these SSRIs on the Na/K-dependent ATPase pump activity in brain synaptosomes where also investigated in vitro and in fish exposed to the municipal effluents. With respect to their potential biological effects, in vitro exposure to selected SSRIs induced a reduction of the brain Na/K-ATPase activity in synaptosomes in a dose-dependent manner. Results showed that Na/K-ATPase activity was readily inhibited by exposure to municipal effluent before and, to a lesser extent, after ozone treatment. Moreover, the Na/K-ATPase activity was significantly and negatively correlated with brain tissue concentrations of fluoxetine (r=-0.57; p<0.03), desmethylsertraline (r=-0.84; p<0.001), and sertraline (r=-0.82; p<0.001). The present study reveals that SSRIs are readily available in fish, biologically active and corroborates previous findings on the serotonergic properties of municipal effluents to aquatic organisms.     

Modeling transit bus fuel consumption on the basis of cycle properties

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.     

Total fuel-cycle analysis of heavy-duty vehicles using biofuels and natural gas-based alternative fuels

Heavy-duty vehicles (HDVs) present a growing energy and environmental concern worldwide. These vehicles rely almost entirely on diesel fuel for propulsion and create problems associated with local pollution, climate change, and energy security. Given these problems and the expected global expansion of HDVs in transportation sectors, industry and governments are pursuing biofuels and natural gas as potential alternative fuels for HDVs. Using recent lifecycle datasets, this paper evaluates the energy and emissions impacts of these fuels in the HDV sector by conducting a total fuel-cycle (TFC) analysis for Class 8 HDVs for six fuel pathways: (1) petroleum to ultra low sulfur diesel; (2) petroleum and soyoil to biodiesel (methyl soy ester); (3) petroleum, ethanol, and oxygenate to e-diesel; (4) petroleum and natural gas to Fischer-Tropsch diesel; (5) natural gas to compressed natural gas; and (6) natural gas to liquefied natural gas. TFC emissions are evaluated for three greenhouse gases (GHGs) (carbon dioxide, nitrous oxide, and methane) and five other pollutants (volatile organic compounds, carbon monoxide, nitrogen oxides, particulate matter, and sulfur oxides), along with estimates of total energy and petroleum consumption associated with each of the six fuel pathways. Results show definite advantages with biodiesel and compressed natural gas for most pollutants, negligible benefits for e-diesel, and increased GHG emissions for liquefied natural gas and Fischer-Tropsch diesel (from natural gas).     

Use of AERMOD to Determine a Hydrogen Sulfide Emission Factor for Swine Operations by Inverse Modeling

This study was conducted to determine both optimal settings applied to the plume dispersion model, AERMOD, and a scalable emission factor for accurately determining the spatial distribution of hydrogen sulfide concentrations in the vicinity of swine concentrated animal feeding operations (CAFOs). These operations emit hydrogen sulfide from both housing structures and waste lagoons. With ambient measurements made at 4 stations within 1 km of large swine CAFOs in Iowa, an inverse-modeling approach applied to AERMOD was used to determine hydrogen sulfide emission rates. CAFO buildings were treated as volume sources whereas nearby lagoons were modeled as area sources. The robust highest concentration (RHC), calculated for both measured and modeled concentrations, was used as the metric for adjusting the emission rate until the ratio of the two RHC levels was unity. Utilizing this approach, an average emission flux rate of 0.57 μg/m(2)-s was determined for swine CAFO lagoons. Using the average total animal weight (kg) of each CAFO, an average emission factor of 6.06 × 10(-7) μg/yr-m(2)-kg was calculated. From studies that measured either building or lagoon emission flux rates, building fluxes, on a floor area basis, were considered equal to lagoon flux rates. The emission factor was applied to all CAFOs surrounding the original 4 sites and surrounding an additional 6 sites in Iowa, producing an average modeled-to-measured RHC ratio of 1.24. When the emission factor was applied to AERMOD to simulate the spatial distribution of hydrogen sulfide around a hypothetical large swine CAFO (1M kg), concentrations 0.5 km from the CAFO were 35 ppb and dropped to 2 ppb within 6 km of the CAFO. These values compare to a level of 30 ppb that has been determined by the State of Iowa as a threshold level for ambient hydrogen sulfide levels.     

Reporting central tendencies of chamber measured surface emission and oxidation

Methane emissions, concentrations, and oxidation were measured on eleven MSW landfills in eleven states spanning from California to Pennsylvania during the three year study. The flux measurements were performed using a static chamber technique. Initial concentration samples were collected immediately after placement of the flux chamber. Oxidation of the emitted methane was evaluated using stable isotope techniques. When reporting overall surface emissions and percent oxidation for a landfill cover, central tendencies are typically used to report “averages” of the collected data. The objective of this study was to determine the best way to determine and report central tendencies. Results showed that 89% of the data sets of collected surface flux have lognormal distributions, 83% of the surface concentration data sets are also lognormal. Sixty seven percent (67%) of the isotope measured percent oxidation data sets are normally distributed. The distribution of data for all eleven landfills provides insight of the central tendencies of emissions, concentrations, and percent oxidation. When reporting the “average” measurement for both flux and concentration data collected at the surface of a landfill, statistical analyses provided insight supporting the use of the geometric mean. But the arithmetic mean can accurately represent the percent oxidation, as measured with the stable isotope technique. We examined correlations between surface CH₄ emissions and surface air CH₄ concentrations. Correlation of the concentration and flux values using the geometric mean proved to be a good fit (R² = 0.86), indicating that surface scans are a good way of identifying locations of high emissions.     

Combustion-derived substances in deep basins of Puget Sound: historical inputs from fossil fuel and biomass combustion

Reconstructions of 250 years historical inputs of two distinct types of black carbon (soot/graphitic black carbon (GBC) and char-BC) were conducted on sediment cores from two basins of the Puget Sound, WA. Signatures of polycyclic aromatic hydrocarbons (PAHs) were also used to support the historical reconstructions of BC to this system. Down-core maxima in GBC and combustion-derived PAHs occurred in the 1940s in the cores from the Puget Sound Main Basin, whereas in Hood Canal such peak was observed in the 1970s, showing basin-specific differences in inputs of combustion byproducts. This system showed relatively higher inputs from softwood combustion than the northeastern U.S. The historical variations in char-BC concentrations were consistent with shifts in climate indices, suggesting an influence of climate oscillations on wildfire events. Environmental loading of combustion byproducts thus appears as a complex function of urbanization, fuel usage, combustion technology, environmental policies, and climate conditions.     

The influence of socioeconomic, environmental, and demographic factors on municipality-scale land-cover change in Mexico

Land-cover change is the result of complex multi-scale interactions between socioeconomic, demographic, and environmental factors. Demographic change, in particular, is thought to be a major driver of forest change. Most studies have evaluated these interactions at the regional or the national level, but few studies have evaluated these dynamics across multiple spatial scales within a country. In this study, we evaluated the effect of demographic, environmental, and socioeconomic variables on land-cover change between 2001 and 2010 for all Mexican municipalities (n?=?2,443) as well as by biome (n?=?4). We used a land-cover classification based on 250-m MODIS data to examine the change in cover classes (i.e., woody, mixed woody, and agriculture/herbaceous vegetation). We evaluated the trends of land-cover change and identified the major factors correlated with woody vegetation change in Mexico. At the national scale, the variation in woody vegetation was best explained by environmental variables, particularly precipitation; municipalities where woody cover increased tended to be in areas with low average annual precipitation (i.e., desert and dry forest biomes). Demographic variables did not contribute much to the model at the national scale. Elevation, temperature, and population density explained the change in woody cover when municipalities were grouped by biome (i.e., moist forest, dry forest, coniferous forest, and deserts). Land-cover change at the biome level showed two main trends: (1) the tropical moist biome lost woody vegetation to agriculture and herbaceous vegetation, and (2) the desert biome increased in woody vegetation within more open-canopy shrublands.     

Immobilized Fe (III)-doped titanium dioxide for photodegradation of dissolved organic compounds in water

Photocatalytic degradation of dissolved organic carbon (DOC) by utilizing Fe(III)-doped TiO₂ at the visible radiation range is hereby reported. The photocatalyst was immobilized on sintered glass frits with the coating done by wet method, calcinated at 500 °C and then applied in a photodegradation reactor. The addition of a transition metal dopant, Fe(III), initiated the red shift which was confirmed by UV–Vis spectroscopy, and the photocatalyst was activated by visible radiation. X-ray diffraction patterns showed that Fe(III) doping had an effect on the crystallinity of the photocatalysts. Mixtures of DOC and associated coloured solutions were degraded in first-order kinetics, showing that the degradation process was not dependent on intermediates or other species in solution. A reactor with a catalyst coating area of 12.57 cm² was able to degrade 0.623 mg of the dissolved material per minute. Exposure of the reactor to hostile acidic conditions and repeated use did not compromise its efficiency. It was observed that the reactor regenerates itself in the presence of visible light, and therefore, it can be re-used for more than 100 runs before the performance dropped to <95 %. The results obtained indicate that the photocatalyst reactor has a great potential of application for use in tandem with biosorbent cartridges to complement water purification methods for domestic consumption.     

A new hypothesis concerning the nature of small pelagic fish clusters: An individual-based modelling study of Sardinella aurita dynamics off West Africa

Coastal populations of small pelagic fish display nested aggregation levels. Above the level of the school structure, clusters are observed the nature of which has not been definitively determined. We hypothesized that these clusters corresponded to a materialisation of the microcohorts originating from successive spawnings of fish populations in their vital domain.A candidate individual-based model was developed to investigate this hypothesis. This model is based on pattern-oriented modelling of a concrete documented case: the dynamics of the round sardinella (Sardinella aurita) population living off the West African coasts and subject to environmental fluctuations caused by seasonal upwelling. The simulated agents were round sardinella microcohorts situated and moving in a discretised physical environment. The combined effects of environmental forcing (temperature, wind, retention) and inner biological dynamics (reproduction, growth and mortality, competition) condition the dynamics of this population.The modelled behaviour generated realistic dynamic patterns (population distribution, spawning zones, periods and plasticity, biomass fluctuations), which were obtained simultaneously and successfully compared with observations. The steady-state number of microcohorts obtained after simulation convergence was similar to the number of clusters observed in situ in this area for this population.The realism and diversity of the patterns simultaneously simulated suggested the cluster-microcohort equivalence hypothesis as a candidate framework accounting for the origin of the clusters observed in situ. Within this preliminary exploration, we discuss the consistency of the hypothesis and the accuracy of the model. If the correspondence between clusters and microcohorts proves to be real, it may be transient and progressively modified by other environmental factors. If stable over time, as simulated in the model, the number of observed clusters should be related to the number of spawning events in the species’ lifetime.     

No evidence for genetic differentiation between Antarctic limpet Nacella concinna morphotypes

The extent to which genetic divergence can occur in the absence of physical barriers to gene flow is currently one of the most controversial topics in evolutionary biology, with implications for our understanding of speciation, phenotypic plasticity and adaptive potential. This is illustrated by a recent study reporting a surprising pattern of genetic differentiation between intertidal and subtidal morphotypes of the broadcast-spawning Antarctic limpet Nacella concinna. To explore this further, we collected almost 400 Antarctic limpets from four depths (intertidal, 6, 15 and 25 m) at Adelaide island, Antarctica, and conducted a combined morphometric and genetic analysis using 168 polymorphic amplified fragment length polymorphism (AFLP) loci. Morphological analysis revealed not only pronounced differences between the two morphotypes, but also a continuous cline in shell shape from the intertidal zone down to 25 m depth, suggesting that the distinction between the morphotypes may be artificial. Moreover, genetic analysis using both F _st and a Bayesian analogue found no evidence for differentiation either between the two morphotypes or by depth, and a Bayesian cluster analysis did not detect any cryptic genetic structure. Our findings lend support to the notion that limpets can be phenotypically highly plastic, although further studies are required to determine unequivocally whether there is any genetic basis to the observed variation in shell morphology.