Isolation and Characterization of <Emphasis Type="Italic">Bacillus cereus</Emphasis> Bacteriophages from Foods and Soil

The aim of this study was to isolate and characterize Bacillus cereus bacteriophages of various origins. Twenty-seven bacteriophages against B. cereus were isolated from various Korean traditional fermented foods and soils. Plaque size, transmission electron microscopy, virulence profile, and in vitro lytic activity of bacteriophage isolates were examined. Transmission electron microscopy confirmed B. cereus bacteriophages belonging to the family Siphoviridae. Among B. cereus bacteriophages with broad host range, 18 isolates (66.7%) did not harbor any B. cereus virulence factors. Among them, bacteriophage strain CAU150036, CAU150038, CAU150058, CAU150064, CAU150065, and CAU150066 effectively inhibited B. cereus in vitro within 1 h. Therefore, they are considered potential candidates for controlling the contamination of B. cereus in food or other applications.     

Re-emergence of a GII.4 Norovirus Sydney 2012 Variant Equipped with GII.P16 RdRp and Its Predominance over Novel Variants of GII.17 in South Korea in 2016

Noroviruses are major causative pathogen of nonbacterial acute gastroenteritis worldwide. Of the seven genogroups of noroviruses suggested recently, genogroup II genotype 4 (GII.4) had been the most common genotype identified in hospitalized patients in the last few decades. However, since the latter half of 2014, new variants of GII.17 have been reported as the main causes of outbreaks over GII.4 in East Asia and have also occurred in America and Europe. In this study, we monitored norovirus GII in coastal streams at South Gyeongsang province and South Jeolla province of South Korea from March 2015 to May 2016. Norovirus GII.17 capsid sequences were predominantly detected until September 2015 in water samples. However, we found that the number of positive cases of the norovirus GII.4 Sydney 2012 capsid sequence has been increasing since December 2015, overtaking that of GII.17 in 2016. The RdRp genotype of this predominant GII.4 variant in 2016 was identified as GII.P16. The emergence and predominance of the GII.4 pandemic capsid sequence harboring a different RdRp genotype suggested the potential for a future pandemic.     

Emission of particulate and gaseous pollutants from household laser processing machine

Indoor air quality (IAQ) directly affects the health of occupants. Household manufacturing equipment (HME) used for hobbies or educational purposes is a new and unexplored source of air pollution. In this study, we evaluated the characteristics of particulate and gaseous pollutants produced by a household laser processing equipment (HLPE). Various target materials were tested using a commercial HLPE under various operating conditions of laser power and sheath air flow rate. The mode diameters of the emitted particles gradually decreased as laser power increased, while the particle number concentration (PNC) and particle emission rate (PER) increased. In addition, as the sheath air flow rate quadrupled from 10 to 40 L/min, the mode diameter of the emitted particles decreased by nearly 25%, but the effect on the PNC was insignificant. When the laser induced the target materials at 53 mW, the mode diameters of particles were <150 nm, and PNCs were >2.0 × 10⁴ particles/cm³. Particularly, analyses of sampled aerosols indicated that harmful substances such as sulfur and barium were present in particles emitted from leather. The carcinogenic gaseous pollutants such as acrylonitrile, acetaldehyde, 1,3-butadiene, benzene, and C₈ aromatics (ethylbenzene) were emitted from all target materials. In an actual indoor environment, the PNC of inhalable ultrafine particles (UFPs) was >5 × 10⁴ particles/cm³ during 30 min of HLPE operation. Our results suggest that more meticulous control methods are needed, including the use of less harmful target materials along with filters or adsorbents that prevent emission of pollutants.     

Effect of biochar amendment on tylosin adsorption-desorption and transport in two different soils

The role of biochar as a soil amendment on the adsorption-desorption and transport of tylosin, a macrolide class of veterinary antibiotic, is little known. In this study, batch and column experiments were conducted to investigate the adsorption kinetics and transport of tylosin in forest and agricultural corn field soils amended with hardwood and softwood biochars. Tylosin adsorption was rapid at initial stages, followed by slow and continued adsorption. Amounts of adsorption increased as the biochar amendment rate increased from 1 to 10%. For soils with the hardwood biochar, tylosin adsorption was 10 to 18% higher than that when using the softwood biochar. Adsorption kinetics was well described by Elovich equation ( ≥ 0.921). As the percent of biochar was increased, the rates of initial reactions were generally increased, as indicated by increasing α value at low initial tylosin concentration, whereas the rates during extended reaction times were generally increased, as indicated by decreasing β value at high initial tylosin concentration. A considerably higher amount of tylosin remained after desorption in the corn field soil than in the forest soil regardless of the rate of biochar amendment, which was attributed to the high pH and silt content of the former. The breakthrough curves of tylosin showed that the two soils with biochar amendment had much greater retardation than those of soils without biochar. The CXTFIT model for the miscible displacement column study described well the peak arrival time as well as the maximum concentration of tylosin breakthrough curves but showed some underestimation at advanced stages of tylosin leaching, especially in the corn field soil. Overall, the results indicate that biochar amendments enhance the retention and reduce the transport of tylosin in soils.     

Modeling of road traffic noise and estimated human exposure in Fulton County, Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN?. After analyzing noise levels with raster, vector and fa?ade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N=870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.     

Evaluation of Dynamically Dimensioned Search Algorithm for Optimizing SWAT by Altering Sampling Distributions and Searching Range

The primary advantage of Dynamically Dimensioned Search (DDS) algorithm is that it outperforms other optimization techniques in both convergence speed and searching ability for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation factor) in the optimization process. Conventionally, a default value of 0.2 is used as the perturbation factor, where a normal distribution is applied with mean sampling distribution of zero and variance of one. However, the perturbation factor sensitivity to the performance of DDS for watershed modeling is still unknown. The fixed‐form sampling distribution may result in finding parameters at the local scale rather than global in the sampling space. In this study, the efficiency of DDS was evaluated by altering the perturbation factor (from 0.05 to 1.00) and the selection of sampling distribution (normal and uniform) on hydrologic and water quality predictions in a lowland agricultural watershed in Texas, United States. Results show that the use of altered perturbation factor may cause variations in convergence speed or the ability to find better solutions. In addition, DDS results were found to be very sensitive to sampling distribution selections, where DDS‐N (normal distribution) outperformed DDS‐U (uniform distribution) in all case scenarios. The choice of sampling distributions could be the potential major factor to be attributed for the performance of auto‐calibration techniques for watershed simulation models.     

Diurnal vertical migration of Cochlodinium polykrikoides during the red tide in Korean coastal sea waters

The diurnal vertical migration of Cochlodinium polykrikoides (C. polykrikoides), which caused a red tide in the Korean coastal waters of the East Sea/Sea of Japan in September 2003, was examined by determining the time-dependent changes in the density of living cells in relation to the depth of the water column. The ascent of this species into the surface layer (depth of water 2 m) occurred during 1400-1500. The descent started at 1600 and a high distribution rate (86%) at 15-20 m was observed at 0300. During the ascent, the cells were widely distributed at each depth level from 0600 hr and at 0800-1100, the cells were primarily distributed in the middle layer (0-6 m). The concentration of dissolved inorganic nitrogen was generally < or = 2.86 micromol l(-1), but at 1400-1500, the concentration in the surface layer reduced to < or = 0.14 micromol l(-1). Moreover, the concentration gradually increased as the depth increased to > or = 5 m. These results showed that the nutrient-consumption rate associated with the proliferation of C. polykrikoides during a red tide is more influenced by the inorganic-nitrogen resources ratherthan the inorganic-phosphorus compounds.     

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 (R²), 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.     

Influence of various reaction parameters on 2,4-D removal in photo/ferrioxalate/H(2)O(2) process

The influence of various reaction parameters on herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) removal were examined in the photo/ferrioxalate/H(2)O(2) system, with regard to: (1) sulfate, phosphate, and z.rad;OH scavenger, as solution constituent; and (2) light intensity, ferrioxalate, H(2)O(2), and oxalate concentration, as operating parameter. In terms of 2,4-D removal, the photo/ferrioxalate/H(2)O(2) system has always been superior to the photo/Ferric ion/H(2)O(2) system, despite the high presence of anions (sulfate 100 mM, phosphate 1 mM) or z.rad;OH scavenger. Not only the rate of 2,4-D removal, but also the decomposition rate of H(2)O(2) and oxalate proportionally increase with light intensity. The ferrioxalate concentration determines the light absorption fraction, and thus, controls the rates of 2,4-D removal, and the decomposition of H(2)O(2) and oxalate, are predicted from kinetic formulations. The optimal concentration of H(2)O(2) and oxalate, according to the extent of the z.rad;OH scavenging reaction with these reagents, has been demonstrated for 2,4-D removal. It was found that an increasing oxalate concentration, which bears the burden of increased dissolved organic carbon (DOC), does not occur. This is because its decomposition, as a result of the photochemical reduction of the ferric oxalate complex, results in a decrease of the equivalent DOC. The importance of the key reaction factors to be considered, when applying this system to real wastewater treatment, is also discussed.