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.     

Volatile pollutants emitted from selected liquid household products

BACKGROUND, AIM, AND SCOPE: To identify household products that may be potential sources of indoor air pollution, the chemical composition emitted from the products should be surveyed. Although this kind of survey has been conducted by certain research groups in Western Europe and the USA, there is still limited information in scientific literature. Moreover, chemical components and their proportions of household products are suspected to be different with different manufacturers. Consequently, the current study evaluated the emission composition for 42 liquid household products sold in Korea, focusing on five product classes (deodorizers, household cleaners, color removers, pesticides, and polishes). MATERIALS AND METHODS: The present study included two phase experiments. First, the chemical components and their proportions in household products were determined using a gas chromatograph and mass spectrometer system. For the 19 target compounds screened by the first phase of the experiment and other selection criteria, the second phase was done to identify their proportions in the purged-gas phase. RESULTS: The number of chemicals in the household products surveyed ranged from 9 to 113. Eight (product class of pesticides) to 17 (product class of cleaning products) compounds were detected in the purged-gas phase of each product class. Several compounds were identified in more than one product class. Six chemicals (acetone, ethanol, limonene, perchloroethylene (PCE), phenol, and 1-propanol) were identified in all five product classes. There were 13 analytes occurring with a frequency of more than 10% in the household products: limonene (76.2%), ethanol (71.4%), PCE (66.7%), phenol (40.5%), 1-propanol (35.7%), decane (33%), acetone (28.6%), toluene (19.0%), 2-butoxy ethanol (16.7%), o-xylene (16.7%), chlorobenzene (14.3%), ethylbenzene (11.9%), and hexane (11.9%). All of the 42 household products analyzed were found to contain one or more of the 19 compounds. DISCUSSION: The chemical composition varied broadly along with the product classes or product categories, and it was different from that reported in other studies abroad, although certain target chemicals were identified in both studies. This finding supports an assertion that chemical components emitted from household products may be different in different products and with different manufacturers. The chlorinated pollutants identified in the present study have not been reported to be components of cleaning products in papers published since the early 1990s. Limonene was identified as having the highest occurrence in the household products in the present study, although it was not detected in any of 67 household products sold in the U.S. CONCLUSIONS: The emission composition of selected household products was successfully examined by purge-and-trap analysis. Along with other exposure information such as use pattern of household products and the indoor climate, this composition data can be used to estimate personal exposure levels of building occupants. This exposure data can be employed to link environmental exposure to health risk. It is noteworthy that many liquid household products sold in Korea emitted several toxic aromatic and chlorinated organic compounds. Moreover, the current finding suggests that product types and manufacturers should be considered, when evaluating building occupants' exposure to chemical components emitted from household products. RECOMMENDATIONS AND PERSPECTIVES: The current findings can provide valuable information for the semiquantitative estimation of the population inhalation exposure to these compounds in indoor environments and for the selection of safer household products. However, although the chemical composition is known, the emissions of household products might include compounds formed during the use of the product or compounds not identified as ingredients by this study. Accordingly, further studies are required, and testing must be done to determine the actual composition being emitted. Similar to eco-labeling of shampoos, shower gels, and foam baths proposed by a previous study, eco-labeling of other household products is suggested.     

Simultaneous Measurements of Atmospheric Pollutants and Visibility with a Long-Path DOAS System in Urban Areas

In this paper, the applicability of a Long-Path Differential Optical Absorption Spectroscopy (LP-DOAS) system was checked for the feasibility of the simultaneous measurement of trace gases (such as O₃, NO₂, SO₂, and HCHO) and atmospheric visibility (light extinction by aerosols) in Asian urban areas. Field studies show that an LP-DOAS system can simultaneously measure the key pollutants (such as O₃, NO₂, SO₂, and HCHO) at detection limits in the ppb/sub-ppb range as well as the Mie extinction coefficient with an uncertainty of 0.1 km^–1 at time resolution of a few minutes. It is thus concluded that the use of LP-DOAS system is feasible for simultaneous measurement of gaseous pollutants as well as an atmospheric extinction coefficient which is tightly bound to fine particulate concentration.     

Impact of pH buffer capacity of sediment on dechlorination of atrazine using zero valent iron

This research investigated the role of the pH buffer capacity of sediment on the dechlorination of atrazine using zero valent iron (ZVI). The buffer capacity of the sediment was quantified by batch experiments and estimated to be 5.0 cmol OH(-) . pH(-1). The sediments were spiked with atrazine at 7.25-36.23 mg kg(-1) (6.21 x 10(-7)-3.09 x 10(-6) mol atrazine . g(-1) sediment) for the batch experiments. The buffer capacity of the sediment maintained the sediment suspension at neutral pH, thereby enabling continuous dechlorination until the buffer capacity of the sediment was depleted. The pseudo-first order dechlorination constants were estimated to be in the range of 1.19 x 10(-2)-7.04 x 10(-2) d(-1) for the atrazine-spiked sediments.     

Chemical characteristics of long-range transport aerosol at background sites in Korea

In this study, background concentration sites of Deokjeok and Gosan, which were deemed suitable for monitoring the impact of long-range transported air pollutants, were selected. An investigation of the source types of pollutants, their locations, and relative quantitative contributions to the particulate concentrations at both sites using appropriate methodologies to make initial estimations was conducted. Episodic measurements of PM_2.5, PM₁₀, and size distribution, along with its ion and carbon components were performed from 2005 to 2007, and a comprehensive analysis of the results was conducted utilizing back trajectory analysis. As for frequency of wind direction, it was quite apparent that the two sites are heavily influenced by air masses originating from the eastern and northern regions of China. For PM_2.5 and PM₁₀, the mass concentrations from north and east China were higher than other cases, originating from the ocean. In the northerly-wind case, meteorological properties for Deokjeok and Gosan and the influence of carbon emissions from northwest Korea resulted in a changing of air mass properties during transport. As was the case with mass concentration, the highest contribution for ionic and carbon components of PM_2.5 and PM₁₀ for both sites appeared for the westerly wind case. A specially high relative contribution, greater than 1.4 times, was apparent in the secondary aerosol case because of a large influence of long-range transported pollutants from east China. Carbon components exhibited different behaviors for the northerly and westerly wind cases compared with secondary aerosol. The major reason for this discrepancy appears to be the carbon emissions from northwest Korea.     

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.     

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.