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.     

Incorporating evolutionary processes into population viability models

We examined how ecological and evolutionary (eco‐evo) processes in population dynamics could be better integrated into population viability analysis (PVA). Complementary advances in computation and population genomics can be combined into an eco‐evo PVA to offer powerful new approaches to understand the influence of evolutionary processes on population persistence. We developed the mechanistic basis of an eco‐evo PVA using individual‐based models with individual‐level genotype tracking and dynamic genotype–phenotype mapping to model emergent population‐level effects, such as local adaptation and genetic rescue. We then outline how genomics can allow or improve parameter estimation for PVA models by providing genotypic information at large numbers of loci for neutral and functional genome regions. As climate change and other threatening processes increase in rate and scale, eco‐evo PVAs will become essential research tools to evaluate the effects of adaptive potential, evolutionary rescue, and locally adapted traits on persistence.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Optical and thermal characteristics of carbonaceous aerosols measured at an urban site in Gwangju,Korea, in the winter of 2011

Carbonaceous components (organic carbon [OC] and elemental carbon [EC]) and optical properties (light absorption and scattering) of fine particulate matter (aerodynamic diameter <2.5 μm; PM_2.5) were simultaneously measured at an urban site in Gwangju, Korea, during the winter of 2011. OC was further classified into OC1, OC2, OC3, and OC4, based on a temperature protocol using a Sunset OC/EC analyzer. The average OC and EC concentrations were 5.0 ± 2.5 and 1.7 ± 0.9 μg C m^?3, respectively. The average single-scattering albedo (SSA) at a wavelength of 550 nm was 0.58 ± 0.11, suggesting that the aerosols observed in the winter of 2011 had a local warming effect in this area. During the whole sampling period, “stagnant PM” and “long-range transport PM” events were identified. The light absorption coefficient (b_abs) was higher during the stagnant PM event than during the long-range transport PM event due to the existence of abundant light-absorbing OC during the stagnant PM event. In particular, the OC2 and OC3 concentrations were higher during the stagnant PM event than those during the long-range transport event, suggesting that OC2 and OC3 might be more related to the light-absorbing OC. The light scattering coefficient (b_scat) was similar between the events. On average, the mass absorption efficiency attributed to EC (σ_EC) was 9.6 m² g^?1, whereas the efficiency attributed to OC (σ_OC) was 1.8 m² g^?1 at λ = 550 nm. Furthermore, the σ_EC is comparable among the PM event days, but the σ_OC for the stagnant PM event was significantly higher than that for the long-range transport PM event (1.7 vs. 0.5).

Implications: Optical and thermal properties of carbonaceous aerosol were measured at Gwangju, and carbonaceous aerosol concentration and optical property varied between “stagnant PM” and “long-range transport PM” events. More abundant light absorbing OC was observed during the stagnant PM event.     

Stable isotope on the evaluation of water quality in the presence of WWTPs in rivers

Environmental Science and Pollution Research - We investigated the distribution of nitrogen compounds in Han River as well as two tributaries of Tancheon and Jungrangcheon. Particularly, we...     

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.     

Ultrasound pretreatment of filamentous algal biomass for enhanced biogas production

The filamentous alga Hydrodictyon reticulatum harvested from a bench-scale wastewater treatment pond was used to evaluate biogas production after ultrasound pretreatment. The effects of ultrasound pretreatment at a range of 10–5000 J/mL were tested with harvested H. reticulatum. Cell disruption by ultrasound was successful and showed a higher degree of disintegration at a higher applied energy. The range of 10–5000 J/mL ultrasound was able to disintegrated H. reticulatum and the soluble COD was increased from 250 mg/L to 1000 mg/L at 2500 J/mL. The disintegrated algal biomass was digested for biogas production in batch experiments. Both cumulative gas generation and volatile solids reduction data were obtained during the digestion. Cell disintegration due to ultrasound pretreatment increased the specific biogas production and degradation rates. Using the ultrasound approach, the specific methane production at a dose of 40 J/mL increased up to 384 mL/g-VS fed that was 2.3 times higher than the untreated sample. For disintegrated samples, the volatile solids reduction was greater with increased energy input, and the degradation increased slightly to 67% at a dose of 50 J/mL. The results also indicate that disintegration of the algal cells is the essential step for efficient anaerobic digestion of algal biomass.     

Effective adsorbent for arsenic removal: core/shell structural nano zero-valent iron/manganese oxide

Recently, nano zero-valent iron (nZVI) has emerged as an effective adsorbent for the removal of arsenic from aqueous solutions. However, its use in various applications has suffered from reactivity loss resulting in a decreased efficiency. Thus, the aim of this study was to develop an effective arsenic adsorbent as a core/shell structural nZVI/manganese oxide (or nZVI/Mn oxide) to minimize the reactivity loss of the nZVI. As the major result, the arsenic adsorption capacities of the nZVI/Mn oxide for As(V) and As(III) were approximately two and three times higher than that of the nZVI, respectively. In addition, the As(V) removal efficiency of the nZVI/Mn oxide was maintained through 4 cycles of regeneration whereas that of the nZVI was decreased significantly. The enhanced reactivity and reusability of the nZVI/Mn oxide can be successfully explained by the synergistic interaction of the nZVI core and manganese oxide shell, in which the manganese oxides participate in oxidation reactions with corroded Fe²⁺ and subsequently retard the release of aqueous iron providing additional surface sites for arsenic adsorption. In summary, this study reports the successful fabrication of a core/shell nZVI/Mn oxide as an effective adsorbent for the removal of arsenic from aqueous solutions.