Metabolic response under different salinity and temperature conditions for glass eel Anguilla japonica

Diadromous fish often enter freshwater directly from seawater via fish ladders or channels built in estuarine dams. The oxygen consumption rates (OCR) of glass eel, Anguilla japonica, were determined using an automatic intermittent flow respirometer under various salinity and temperature regimes to physiologically explain this direct movement. The endogenous rhythm of the OCR in wild glass eels, freshly collected from estuaries, was nearly synchronous with the tidal pattern at the estuarine collection site. When the salinity was changed from 20 psu (12°C) at a constant temperature to that of freshwater, the OCR of the glass eels decreased by 21.6±7.0% (mean ± SD) (P<0.05), showing a dampened rhythm for about 48 h. After this period of impediment, the glass eels resumed normal metabolic activity. Direct migration from seawater to freshwater under constant temperature would result in a severe physiological stress for these glass eels for about two days. When the glass eels were exposed to a cyclic change in water temperature of 2°C 26 h⁻¹, as they encounter in estuaries, and then were introduced to freshwater abruptly, the OCR rhythm corresponded to the cyclic changes in water temperature after exposure to freshwater. Under these conditions, the mean OCR of the glass eels had a small difference before and after exposure to freshwater. These data explained how glass eels can directly move from sea water into the freshwater without any apparent metabolic stress in the estuaries showing cyclic change in water temperature (Δt=2°C).     

STREAM DISCHARGE PREDICTION VIA A GRID BASED SOIL WATER ROUTING WITH PADDY FIELDS1

ABSTRACT: A grid based daily hydrologic model for a watershed with paddy fields was developed to predict the stream discharge. ASCII formatted elevation, soil, and land use data supported by the GRASS Geographic Information System are used to generate distributed results such as surface runoff and subsurface flow, soil water content, and evapotranspiration. The model uses a single flow path algorithm and simulates a water balance at each grid element. A linear reservoir assumption was used to predict subsurface runoff components. The model was applied to a 75.6 km² watershed located in the middle of South Korea, and observed stream flow hydrographs from 1995 and 1996 were compared to model predictions. The stream flow predictions of 1995 and 1996 generally agreed with the observed flow, resulting in a Nash‐Sutcliffe efficiency R² of 0.60 and 0.62, respectively. The hydraulic conductivity for percolating water through the saturated layer affected baseflow generation. The levee height of the paddy influenced the time and magnitude of the surface runoff, depending on irrigation management. The model will be used for making low flow management decisions by evaluating the role of each land use to stream flow, especially in case of paddy decrease by gradual urbanization of a watershed.     

Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO(x)), and particle mass with aerodynamic diameter below 2.5 microm (PM2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO(x), black carbon (BC), PM2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO(x) and CO fleet-average emission factors and more than 60% of PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.     

Radium isotopes in the Ulsan Bay

In order to estimate the fluxes of Ra isotopes, we measured 224Ra, 226Ra, and 228Ra activities in the Ulsan Bay mixing zone. The convex upwards curvature of the plot of Ra isotope activities versus salinity for the mixing zone suggests that Ra isotopes are supplied from particles entering the mixing zone from both the river and bottom sediments. This addition increases the estuarine flux of 226Ra and 228Ra to the outer sea by factors of 15 and 95 over the flux attributable to Ra dissolved in the riverine water alone. In order to estimate the residence time of the water in Ulsan Bay, we applied a mass balance model to the distribution of 224Ra and 226Ra activities in the Ulsan Bay mixing zone with the inflow from the Taehwa River. The obtained residence times of the waters in the Ulsan Bay were estimated to be 6.8-11.4 d. The waters in the upper part of the estuary have long residence times whereas those in the lower part, in contact with the open sea, have shorter residence times. The mean residence time of the water in the Ulsan Bay was estimated to be 9.1 d.     

Characterization of trace organic contaminants in marine sediment from Yeongil Bay, Korea: 2. Dioxin-like and estrogenic activities

This study employed mechanism-specific in vitro bioassays to help characterize the occurrence and distribution of dioxin-like and estrogenic contaminants in sediment from Yeongil Bay, Korea. Approximately 85% of the sediments tested induced significant dioxin-like activity in the H4IIE-luc bioassay, while approximately 50% induced significant estrogenic activity in the MVLN bioassay. Instrumentally-derived estimates of 2,3,7,8-tetrachlorodibenzo-p-dioxin and 17beta-estradiol equivalents tended to underestimate the magnitude of response observed in the bioassays, suggesting that compounds detected by chemical analysis did not account for all the activity associated with Yeongil Bay sediments, or that non-additive interactions were occurring. The greatest dioxin-like and estrogenic activity was associated with the mid-polarity Florisil fractions (F2) expected to contain polycyclic aromatic hydrocarbons (PAHs) as well as chlorinated dioxins and furans. As in previous studies of Korean coastal sediment, more polar fractions (F3) generated more modest responses both in terms of magnitude and the number of samples responding.     

Compositional data analysis and geochemical modeling of CO2–water–rock interactions in three provinces of Korea

Environmental Geochemistry and Health - The CO2-rich spring water (CSW) occurring naturally in three provinces, Kangwon (KW), Chungbuk (CB), and Gyeongbuk (GB) of South Korea was classified based...     

Cadmium accumulation and elimination in tissues of juvenile olive flounder, Paralichthys olivaceus after sub-chronic cadmium exposure

Experiments were carried out to investigate the accumulation and elimination of cadmium (Cd) in tissues (gill, intestine, kidney, liver and muscle) of juvenile olive flounder, Paralichthys olivaceus, exposed to sub-chronic concentrations (0, 10, 50, 100 microg l(-1)) of Cd. Cd exposure resulted in an increased Cd accumulation in tissues of flounder with exposure periods and concentration, and Cd accumulation in gill and liver increased linearly with the exposure time. At 20 days of Cd exposure, the order of Cd accumulation in organs was gill > intestine > liver > kidney > muscle and after 30 days of exposure, those were intestine > gill > liver > kidney > muscle. An inverse relationship was observed between the accumulation factor (AF) and the exposure level, but AF showed an increase with exposure time. During the depuration periods, Cd concentration in the gill, intestine and liver decreased immediately following the end of the exposure periods. No significant difference was found Cd in concentration in the kidney and muscle during depuration periods. The order of Cd elimination rate in organs were decreased intestine > liver > gill during depuration periods.     

Chemical composition of post-harvest biomass burning aerosols in Gwangju, Korea

The main objective of this study was to investigate the chemical characteristics of post-harvest biomass burning aerosols from field burning of barley straw in late spring and rice straw in late fall in rural areas of Korea. A 12-hr integrated intensive sampling of particulate matter (PM) with an aerodynamic diameter less than or equal to 10 microm (PM10) and PM with an aerodynamic diameter less than or equal to 2.5 microm (PM2.5) biomass burning aerosols had been conducted continuously in Gwangju, Korea, during two biomass burning periods: June 4--15, 2001, and October 8--November 14, 2002. The fine and coarse particles of biomass burning aerosols were analyzed for mass and ionic, elemental, and carbonaceous species. The average fine and coarse mass concentrations of biomass burning aerosols were, respectively, 129.6 and 24.2 microg/m3 in June 2001 and 47.1 and 33.2 microg/m3 in October--November 2002. An exceptionally high PM2.5 concentration of 157.8 microg/m3 was observed during biomass burning events under stagnant atmospheric conditions. In the fine mode, chlorine and potassium were unusually rich because of the high content of semi-arid vegetation. Both organic carbon (OC) and elemental carbon increased during the biomass burning periods, with the former exhibiting a higher abundance. PM from the open field burning of agricultural waste has an adverse impact on local air quality and regional climate.     

Collective fit perceptions: A multilevel investigation of person–group fit with individual‐level and team‐level outcomes

This study describes a multilevel examination of person–group (PG) fit perceptions in a sample of 1023 individuals working in 92 teams at a private sector R&D firm. Using confirmatory factor analysis and multilevel random coefficient modeling, we provide evidence that perceptions of team‐level collective fit are unique from aggregated individual‐level PG fit perceptions at the individual and team levels. We demonstrate that collective values‐based and abilities‐based fit perceptions showed unique and positive relationships with team cohesion, team efficacy, and team performance, after accounting for aggregated individual perceptions of PG fit. Results also demonstrate that cohesion partially mediates the relationship between collective fit and team performance. Cross‐level effects were also supported, indicating that collective fit explains additional variance in individual‐level outcomes, beyond individual‐level PG fit perceptions. The usefulness of employing a multilevel approach to studying PG fit is discussed. Copyright © 2014 John Wiley & Sons, Ltd.