Removal of organic matter and nitrogen from river water in a model floodplain

A significant improvement in river water quality cannot be expected unless nonpoint-source contaminants are treated in addition to the further treatment of point-source contaminants. If river water is sprayed over a floodplain, the consequent water filtration through the sediment profile can simultaneously remove organic matter and nitrogen in the water through aerobic and denitrifying reactions. This hypothesis was tested using lysimeters constructed from polyvinyl chloride (PVC) pipe (150 cm long, 15 cm in diameter) packed with loamy sand floodplain sediment. Water was applied to the top of the lysimeters at three different flow rates (48, 54, and 68 mm d(-1)). Concentrations of NO3 and dissolved oxygen (DO), chemical oxygen demand (COD), and redox potential (Eh) in the water were measured as functions of depth after the system reached steady states for both water flow and reactions. At the rate of 68.0 mm d(-1), a reducing condition for denitrification developed below the 5-cm depth due to the depletion of O2 by organic matter degradation in the surface oxidizing layer; Eh and DO were below 205 mV and 0.4 mg L(-1), respectively. At a depth of 70 cm, COD and NO3-N concentration decreased to 5.2 and 3.8 mg L(-1) from the respective influent concentrations of 17.1 and 6.2 mg L(-1). Most biodegradable organic matter was removed during flow and further removal of NO3 was limited by the lack of an electron donor (i.e., organic matter). These results indicate that the floodplain filtration technique has great promise for treatment of contaminated river water.     

Distribution characteristics of PCBs in the sediments of the lower Nakdong River, Korea

The objective of this study is to investigate the distribution characteristics of polychlorinated biphenyl (PCB) congeners in sediments of the lower Nakdong River of Korea. The sediments were collected using a grab sampler in May 1999. PCBs were extracted in the Soxhlet extractor and cleaned by using adsorption chromatographic techniques and concentrated sulfuric acid. A HP6890 gas chromatograph equipped with an electron capture detector was used for quantification. The results of congener specific analysis showed that the total concentration is ranged over 1.1-141 ng/g dry weight. The levels of PCB congeners are significantly correlated with the total organic carbons (TOC) in the sediments. The major fractions of PCBs in these sediments are congeners containing 4, 5 or 6 chlorine atoms per biphenyl molecule.     

Characterization of the monthly variation in (1 → 3)-β-d-glucan concentrations in university laboratories

We characterize the monthly variation in (1 → 3)-β-d-glucan concentration measured over the course of 1 year, and we evaluate the characteristics of size selection using a two-stage cyclone sampler. The (1 → 3)-β-d-glucan concentrations were measured in four bio-related laboratories. A total of 156 samples were collected using a new two-stage cyclone sampler. Analysis of (1 → 3)-β-d-glucan was performed using the kinetic Limulus amebocyte lysate assay. The study showed that airborne (1 → 3)-β-d-glucan concentrations were significantly higher in laboratory D (mean ± SD 1,105?±?1,893 pg/m³) and in the spring (5,458 pg/m³). The highest concentration of (1 → 3)-β-d-glucan occurred in the spring, particularly in May.     

Effects of NO,NO<Subscript>2</Subscript>, CO and SO<Subscript>2</Subscript> on NO oxidation over Pt/TiO<Subscript>2</Subscript> for hybrid fast SCR process

The selective catalytic reduction (SCR) rate of NO with N-containing reducing agents can be enhanced considerably by converting part of NO into NO₂. The enhanced reaction rate is more pronounced even at lower temperatures by using an equimolar mixture of NO and NO₂ (fast SCR reaction). The oxidation characteristics of NO over catalyst Pt/TiO₂ have been determined in a fixed bed reactor (8 mm-ID) with different concentrations of oxygen, nitric oxide and nitrogen dioxide in the presence of 8% water. The conversion of NO to NO₂ increases with increasing oxygen (O₂) concentration from 3 to 12%, but it levels off at higher O₂ concentrations. The NO conversion to NO₂ decreases with increasing NO concentration and it also decreases by an addition of NO₂ in the feed stream. Therefore, the oxidation of NO over Pt/TiO₂ catalyst could be auto-inhibited by the reaction product of NO₂. The effects of CO and SO₂ on NO oxidation characteristics have also been determined. In fact, the presence of SO₂ significantly suppresses oxidation of NO but due to the less stability of sulfate on anatase structure in TiO₂, it becomes less significant. On the other hand, the presence of CO increases NO oxidation significantly due to the auto-inhibition effect by CO. Moreover, the effect of SO₂/CO on NO oxidation has also been determined and it was observed that NO oxidation decreases with the increase in SO₂/CO ratio.     

Development of the Spatial Rainfall Generator (SRGEN) for the Agricultural Policy/Environmental Extender Model

Accurate spatial representation of climatic patterns is often a challenge in modeling biophysical processes at the watershed scale, especially where the representation of a spatial gradient in rainfall is not sufficiently captured by the number of weather stations. The spatial rainfall generator (SRGEN) is developed as an extension of the “weather generator” (WXGEN), a component of the Agricultural Policy/Environmental eXtender (APEX) model. SRGEN generates spatially distributed daily rainfall using monthly weather statistics available at multiple locations in a watershed. The spatial rainfall generator as incorporated in APEX is tested on the Cowhouse watershed (1,178 km²) in central Texas. The watershed presented a significant spatial rainfall gradient of 2.9 mm/km in the lateral (north‐south) directions based on four rainfall gages. A comparative analysis between SRGEN and WXGEN indicates that SRGEN performs well (PBIAS = 2.40%). Good results were obtained from APEX for streamflow (NSE = 0.99, PBIAS = 8.34%) and NO₃‐N and soluble P loads (PBIAS ≈ 6.00% for each, respectively). However, APEX underpredicted sediment yield and organic N and P loads (PBIAS: 24.75‐27.90%) with SRGEN, although its uncertainty in output was lower than WXGEN results (PBIAS: ?13.02 to ?46.13%). The overall improvement achieved in rainfall generation by SRGEN is demonstrated to be effective in the improving model performance on flow and water quality output.     

Numerical simulation on multi-scale diffusion of CO2 injected in the deep ocean in a practical scenario

The direct injection of CO₂ into the deep ocean is one of the ways for the mitigation of the global warming. There is, however, a concern about its environmental impact near the injection point. To minimize its biological impact, it is necessary to make CO₂ disperse as fast as possible and it is thought that injection with pipes towed by moving-ships is effective for this purpose. Because the injection ships are planned to move in the site, the order of magnitude of which is 10² km, a mesoscale model is required to predict CO₂ fate in seawater. At the same time, it is required to predict the concentration precisely near the injection points, which move with the ships in the mesoscale domain. In this study, a multi-scale ocean model was developed to analyze the dispersion of CO₂ in the deep ocean: the model consists of a fixed mesoscale domain and 5 small-scale domains nesting in the mesoscale domain. Each small-scale domain involves 6 pipes and moves along with the trajectories of the injection ships. From the results of the present numerical simulation, the developed technique demonstrated its applicability as a tool to optimise the system to dilute CO₂ below some criterion of biological impact.     

Distribution characteristics of polychlorinated biphenyls in crucian carp (Carassius auratus) from major rivers in Korea

Polychlorinated biphenyls (PCBs) levels in crucian carp were determined at 20 locations along four major river systems, several small-scale rivers and a wetland in Korea. Twenty-eight congeners, ranging from tri- to hepta-CBs were detected. A gas chromatograph with a mass selective detector was used to quantify the individual PCB congeners. The objectives of this study were to investigate the levels of contamination of PCBs in freshwater fish and to observe the pattern of their distribution. The sampling locations were chosen among 31 sampling sites that are currently used as environmental residue checkpoints by the Korean Ministry of Environment. Concentrations of individual congeners ranged from not detectable (n.d.) to 0.75 ng g(-1) on a wet weight basis. The total concentrations of PCBs at each site ranged from n.d. to 5.41 ng g(-1) of wet weight. The most heavily contaminated site was the Nakdong estuary located near the Shinpyung-Janglim factory district. The PCB 153 and 138 were the principal congeners and penta- and hexa-chlorinated biphenyls comprised the main congener groups.     

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.     

Effects of repeated pesticide exposure on the peripheral and central nervous systems

This study was designed to compare organic farmers (comparison group) and pesticide-using farmers (pesticide group) in terms of neurobehavioral performance and sensorimotor function. The subjects were recruited in October 2004 from Chungnam Province and the neighboring Jeolla Province in western South Korea. Psychological assessment was carried out using the Wechsler Adult Intelligence Scale, the Mini-Mental State Examination, and the Bender Gestalt test. Neuroselective sensory nerve conduction threshold was measured at both left and right middle fingers by using an electrodiagnostic device to determine current perception thresholds (CPTs). Three independent CPT measurements were obtained from each test site by using sinusoidal stimuli at three frequencies. CPT testing showed no difference between the two groups. No significant differences were found in the large myelinated (2000?Hz stimulation; cutaneous touch, pressure), small myelinated (250?Hz stimulation; mechanoreceptive, pressure, temperature, fast pain) and small unmyelinated (5?Hz stimulation; polymodal nociceptive, temperature, slow pain, postganglionic sympathetic) C-fibers. Furthermore, there was no difference found between the pesticide and comparison groups in psychological variables, including intelligence quotient, orientation, memory, calculation, similarities, visual sensitivity, and psychomotor speed. In conclusion, chronic pesticide exposure has no apparent effect on either the peripheral or central nervous system in Korean farmers.     

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.