Sorption and biodegradation of vapor-phase organic compounds with wastewater sludge and food waste compost

To test the possible use of composted food waste and wastewater sludge as biofilters to treat gas-phase volatile organic compounds (VOCs), batch experiments were conducted with an isolated strain that could degrade aromatic compounds under aerobic conditions. A benzene and trichloroethylene (TCE) mixture was used as the gas-phase pollutant in experiments with composted food waste, sludge, and soil. Under aerobic conditions, benzene was degraded as a primary substrate and TCE was degraded cometabolically, with water contents varying from 6 to 60% (volume of water added/volume of solid). Optimal water content for VOC removal was 12% for the soil, 36% for the composted food waste, and 48% for the sludge. The extent of VOC sorption and biodegradation at the optimal water content was different for each material. With the same initial VOC concentration, more VOCs were removed by sorption onto the composted food waste and the sludge, while less VOCs were biodegraded in comparison with the results using soil. The reason the biodegradation in the soil was greater may be partly attributed to the fact that, due to less sorption, the aqueous-phase concentration of VOCs, which microorganisms could utilize as a carbon source or cometabolize, was higher. We also speculate that the distribution of microorganisms in each medium affects the rate of biodegradation. A large number of microorganisms were attached to the composted food waste and sludge. Mass transfer of VOCs and oxygen to these microorganisms, which appear to have been heterogeneously distributed in clusters, may have been limited, resulting in hindered biodegradation.     

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.     

Surface-enhanced Raman spectroscopy for emerging contaminant analysis in drinking water

● Definition of emerging contaminants in drinking water is introduced. ● SERS and standard methods for emerging contaminant analysis are compared. ● Enhancement factor and accessibility of SERS hot spots are equally important. ● SERS sensors should be tailored according to emerging contaminant properties. ● Challenges to meet drinking water regulatory guidelines are discussed. Emerging contaminants (ECs) in drinking water pose threats to public health due to their environmental prevalence and potential toxicity. The occurrence of ECs in our drinking water supplies depends on their physicochemical properties, discharging rate, and susceptibility to removal by water treatment processes. Uncertain health effects of long-term exposure to ECs justify their regular monitoring in drinking water supplies. In this review article, we will summarize the current status and future opportunities of surface-enhanced Raman spectroscopy (SERS) for EC analysis in drinking water. Working principles of SERS are first introduced and a comparison of SERS and liquid chromatography-tandem mass spectrometry in terms of cost, time, sensitivity, and availability is made. Subsequently, we discuss the strategies for designing effective SERS sensors for EC analysis based on five categories—per- and polyfluoroalkyl substances, novel pesticides, pharmaceuticals, endocrine-disrupting chemicals, and microplastics. In addition to maximizing the intrinsic enhancement factors of SERS substrates, strategies to improve hot spot accessibilities to the targeting ECs are equally important. This is a review article focusing on SERS analysis of ECs in drinking water. The discussions are not only guided by numerous endeavors to advance SERS technology but also by the drinking water regulatory policy.     

Controlling various contaminants in wastewater effluent through membranes and engineered wetland

For effective wastewater reclamation and water recovery, the treatment of natural and effluent organic matters (NOM and EfOM), toxic anions, and micropollutants was considered in this work. Two different NOM (humic acid of the Suwannee River, and NOM of US and Youngsan River, Korea), and one EfOM from the Damyang wastewater treatment plant, Korea, were selected for investigating the removal efficiencies of tight nanofiltration (NF) and ultrafiltration (UF) membranes with different properties. Nitrate, bromate, and perchlorate were selected as target toxic anions due to their well known high toxicities. Tri-(2-chloroethyl)-phosphate (TCEP), oxybenzone, and caffeine, due to their different K _ow and pK _a values, were selected as target micropollutants. As expected, the NF membranes provided high removal efficiencies in terms of all the tested contaminants, and the UF membrane provided fairly high removal efficiencies for anions (except for nitrate) and the relatively hydrophobic micropollutant, oxybenzon. Through the wetlands, nitrate was successfully removed. Therefore, a fair process of combining membranes with an engineered wetland could be proposed for sustainable wastewater reclamation and optimum control of contaminats.     

Development of a leaching assessment framework for the utilization of coal ash at South Korean mine reclamation sites

Coal-based power generates large quantities of coal ash in South Korea. However, coal ash recycling is still inactive and most wasted coal ash is buried in landfills. Recently, beneficial uses of coal ash such as in mine reclamation sites has been increasingly considered; however, as a result of legal limitations due to environmental concerns, the utilization of coal ash at mine reclamation sites has procrastinated. Consequently, to resolve this issue, the relevant environmental impact of coal ash must be considered. Therefore, a leaching assessment framework to assess the environmental impact of coal ash utilization at South Korean mine reclamation sites is presented. The framework was used to identify leaching mechanisms and support an assessment of the environmental impact of coal ash usage at mine reclamation sites in South Korea. This framework could provide guidance with regard to designing more realistic leaching procedures appropriate for all mine conditions and could support the development of regulations and protocols for future environment-friendly coal ash usage.     

PM<Subscript>2.5</Subscript> particulates and metallic elements (Ni,Cu, Zn,Cd and Pb) study in a mixed area of summer season in Shalu,Taiwan

PM_2.5 has become an important environmental issue in Taiwan during the past few years. Moreover, electricity increased significantly during the summertime and TTPP generated by coal burning base is the main electricity provider in central Taiwan. Therefore, summer season has become the main research target in this study. The ambient air concentrations of particulate matter PM_2.5 and PM₁₀ collected by using VAPS at a mixed characteristic sampling site were studied in central Taiwan. The results indicated that the average daytime PM_2.5 and PM₁₀ particulate concentrations were occurred in May and they were 44.75 and 57.77 µg/m³ in this study. The results also indicated that the average nighttime PM_2.5 and PM₁₀ particulate concentrations were occurred in June and they were 38.19 and 45.79 µg/m³ in this study. The average PM_2.5/PM₁₀ ratios were 0.7 for daytime, nighttime and 24-h sampling periods in the summer for this study. This value was ranked as the lowest ratios when compared to the other seasons in previous study. Noteworthy, the results further indicated that the metallic element Pb has the mean highest concentrations for 24-h, daytime and nighttime sampling periods when compared to those of the other metallic elements (Ni, Cu, Zn and Cd). The average mean highest metallic Pb concentrations in PM10 were 110.7, 203.0 and 207.2 ng/m³ for 24-h, daytime and nighttime sampling periods in this study. And there were 59.53, 105.2 and 106.6 ng/m³ for Pb in PM2.5 for 24-h, daytime and nighttime sampling periods, respectively. Moreover, the results further indicated that mean metallic element Pb concentrations on PM_2.5 and PM₁₀ were all higher than those of the other elements for 24 h, day and nighttime.     

Sensitivity of Simulated Conservation Practice Effectiveness to Representation of Field and In-Stream Processes in the Little River Watershed

Evaluating the effectiveness of conservation practices (CPs) is an important step to achieving efficient and successful water quality management. Watershed-scale simulation models can provide useful and convenient tools for this evaluation, but simulated conservation practice effectiveness should be responsive to parameter values used to represent the practices in the modeling. The objectives of this study were to (1) assess the impacts of a set of conservation practices on hydrology and water quality of a watershed and (2) evaluate the sensitivity of Soil and Water Assessment Tool (SWAT) modeling outputs and simulated conservation practice effectiveness to parameters. The modeling study was conducted in an agricultural watershed, the subwatershed K (16.9 km²) of the Little River Experimental watershed located in the South Atlantic Coastal Plain of the USA. Sensitivity analysis showed that hydrologic response unit (HRU) and watershed-scale simulations for water quality were most sensitive to CN and FILTERW parameters. Load reduction rates as a function of increased aerial coverage of the conservation practices were greatest for total phosphorus (TP), followed by sediment and total nitrogen (TN). The results indicated that conservation practices would have a limited impact on stream flow volume but could have a significant impact on sediment and TP loads within this region. Watershed-scale TN and TP loads were also sensitive to an in-stream nutrient transformation process represented using the QUAL2E algorithm in SWAT. The study clearly demonstrated the most sensitive model parameters and the optimal conservation practices for this watershed.     

Characterization and prediction of meandering channel migration in the GIS environment: A case study of the Sabine River in the USA

This study focused on the prediction of a 22 km meandering channel migration of the Sabine River between the states of Texas and Louisiana. The meander characteristics of 12 bends, identified from seven orthophotos taken between 1974 and 2004, were acquired in a GIS environment. Based on that earlier years' data acquisition, channel prediction was performed for the two years 1996 and 2004 using least squares estimation and linear extrapolations, yielding a satisfactory agreement with the observations (the median predicted and observed migration rates were 3.1 and 3.6 [m/year], respectively). The best-predicted migration rate was found to be associated with the longest orthophoto-recorded interval. The study confirmed that channel migration is strongly correlated with bend curvature and that the maximum migration rate of the bend corresponded to a radius of curvature [bend radius (R(C))/channel width (W(C))] of 2.5. In tight bends of a smaller radius of curvature than 1.6, secondary flow scouring near the bend apex increases bend curvature. The stability index of the dimensionless bend radius was determined to be 2.45. Overall, this study proves the effectiveness of least squares estimation with historical orthophotography for characterization of meandering channel migration.     

An automated monitoring of atmospheric mixing height from routine radiosonde profiles over South Korea using a web-based data transfer method

This study describes an effort to estimate atmospheric mixing height using vertical profiles of thermodynamic variables measured operationally at radiosonde sites in South Korea. We focus on mixing height at 06UTC (15LST) when vigorous daytime convection is expected with clear skies. For this purpose, we developed a simple numerical algorithm using a new data transfer tool, known as cURL, to determine mixing height and applied it to radiosonde data at Osan and Gwangju for 2010. Emphasis was placed on automating as much as possible the process of determining mixing height. According to the preliminary results, the estimation algorithm performed successfully for most cases with clear sky conditions and was useful in diagnosing and monitoring daytime mixing heights more effectively on a near-real-time basis. With the developed algorithm, it is possible to estimate mixing heights from radiosonde data within a few hours of the development of the convective boundary layer. Application to radiosonde sites in other countries is straightforward and continued modifications of the algorithm are anticipated in the near future.     

Food waste impact on municipal solid waste angle of internal friction

The impact of food waste content on the municipal solid waste (MSW) friction angle was studied. Using reconstituted fresh MSW specimens with different food waste content (0%, 40%, 58%, and 80%), 48 small-scale (100-mm-diameter) direct shear tests and 12 large-scale (430 mm × 430 mm) direct shear tests were performed. A stress-controlled large-scale direct shear test device allowing approximately 170-mm sample horizontal displacement was designed and used. At both testing scales, the mobilized internal friction angle of MSW decreased considerably as food waste content increased. As food waste content increased from 0% to 40% and from 40% to 80%, the mobilized internal friction angles (estimated using the mobilized peak (ultimate) shear strengths of the small-scale direct shear tests) decreased from 39° to 31° and from 31° to 7°, respectively, while those of large-scale tests decreased from 36° to 26° and from 26° to 15°, respectively. Most friction angle measurements produced in this study fell within the range of those previously reported for MSW.