Environmental assessment on electrokinetic remediation of multimetal-contaminated site: a case study

In this study, an environmental assessment on an electrokinetic (EK) system for the remediation of a multimetal-contaminated real site was conducted using a green and sustainable remediation (GSR) tool. The entire EK process was classified into major four phases consisting of remedial investigations (RIs), remedial action construction (RAC), remedial action operation (RAO), and long-term monitoring (LTM) for environmental assessment. The environmental footprints, including greenhouse gas (GHG) emissions, total energy used, air emissions of criteria pollutants, such as NO_x, SO_x, and PM₁₀, and water consumption, were calculated, and the relative contribution in each phase was analyzed in the environmental assessment. In the RAC phase, the relative contribution of the GHG emissions, total energy used, and PM₁₀ emissions were 77.3, 67.6, and 70.4 %, respectively, which were higher than those of the other phases because the material consumption and equipment used for system construction were high. In the RAO phase, the relative contributions of water consumption and NO_x and SO_x emissions were 94.7, 85.2, and 91.0 %, respectively, which were higher than those of the other phases, because the water and electricity consumption required for system operation was high. In the RIs and LTM phases, the environmental footprints were negligible because the material and energy consumption was less. In conclusion, the consumable materials and electrical energy consumption might be very important for GSR in the EK remediation process, because the production of consumable materials and electrical energy consumption highly affects the GHG emissions, total energy used, and air emissions such as NO_x and SO_x.     

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.     

Decision-Tree-based data mining and rule induction for predicting and mapping soil bacterial diversity

Soilmicrobial ecology plays a significant role in global ecosystems. Nevertheless, methods of model prediction and mapping have yet to be established for soil microbial ecology. The present study was undertaken to develop an artificial-intelligence- and geographical information system (GIS)-integrated framework for predicting and mapping soil bacterial diversity using pre-existing environmental geospatial database information, and to further evaluate the applicability of soil bacterial diversity mapping for planning construction of eco-friendly roads. Using a stratified random sampling, soil bacterial diversity was measured in 196 soil samples in a forest area where construction of an eco-friendly road was planned. Model accuracy, coherence analyses, and tree analysis were systematically performed, and four-class discretized decision tree (DT) with ordinary pair-wise partitioning (OPP) was selected as the optimal model among tested five DT model variants. GIS-based simulations of the optimal DT model with varying weights assigned to soil ecological quality showed that the inclusion of soil ecology in environmental components, which are considered in environmental impact assessment, significantly affects the spatial distributions of overall environmental quality values as well as the determination of an environmentally optimized road route. This work suggests a guideline to use systematic accuracy, coherence, and tree analyses in selecting an optimal DT model from multiple candidate model variants, and demonstrates the applicability of the OPP-improved DT integrated with GIS in rule induction for mapping bacterial diversity. These findings also provide implication on the significance of soil microbial ecology in environmental impact assessment and eco-friendly construction planning.     

Using a choice experiment to measure the environmental costs of air pollution impacts in Seoul

Air pollution, a by-product of economic growth, has been incurring extensive environmental costs in Seoul, Korea. Unfortunately, air pollution impacts are not treated as a commercial item, and thus it is difficult to measure the environmental costs arising from air pollution. There is an imminent need to find a way to measure air pollution impacts so that appropriate actions can be taken to control air pollution. Therefore, this study attempts to apply a choice experiment to quantifying the environmental costs of four air pollution impacts (mortality, morbidity, soiling damage, and poor visibility), using a specific case study of Seoul. We consider the trade-offs between price and attributes of air pollution impacts for selecting a preferred alternative and derive the marginal willingness to pay (WTP) estimate for each attribute. According to the results, the households' monthly WTP for a 10% reduction in the concentrations of major pollutants in Seoul was found to be approximately 5494 Korean won (USD 4.6) and the total annual WTP for the entire population of Seoul was about 203.4 billion Korean won (USD 169.5 million). This study is expected to provide policy-makers with useful information for evaluating and planning environmental policies relating specifically to air pollution.     

Selective catalytic reduction of NO<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> using RDF char and municipal solid waste char based catalyst

Experiments were performed in order to investigate the possibility for the development of catalysts for low-temperature selective catalytic reduction (SCR) using municipal waste char and RDF byproduct. Physical and chemical activations, using water, and HCl and KOH, were employed to increase the catalytic activities. The characteristics of the activated catalysts were investigated using N₂ adsorption–desorption and FT-IR. The catalysts activated chemically using basic treatment showed higher NO _x removal efficiencies than those activated physically or chemically using acidic treatment. The de-NO _x performance of the activated catalysts was dependent on the chemical properties, such as oxygen functional groups as well as physical properties, such as specific surface area and pore volume. In order to investigate the effect of MnO _x , which has been reported to be efficient for the removal of NO _x in low-temperature SCR processes, the chemically activated catalyst was impregnated with manganese. The Mn-impregnated catalyst had the highest NO _x conversion at all of the temperatures tested in this study.     

Willingness to Pay for Improving the Residential Waste Disposal System in Korea: A Choice Experiment Study

This study attempts to apply choice experiments with regard to the residential waste disposal system (RWDS) in Korea by considering various attributes that are related to RWDS. Using data from a survey conducted on 492 households, the empirical analysis yields estimates of the willingness to pay for a clean food-waste collection facility, the collection of small items (such as obsolete mobile phones and add-ons for personal computers), and a more convenient large waste disposal system. The estimation results of multinomial logit models are quite similar to those of nested logit models. The results reveal that residents have preferences for the cleanliness of facilities and the collection of small items. In Korea, residents are required to purchase and attach stickers for the disposal of large items; they want to be able to obtain stickers at not only village offices but also supermarkets. On the other hand, the frequency of waste collection is not a significant factor in the choice of the improved waste management program.

Sonolysis of alkylphenols in aqueous solution with Fe(II) and Fe(III)

The sonolytic degradation of alkylphenols (APs), such as butylphenol, pentylphenol, octylphenol, and nonylphenol (NP), in water was investigated at a sound frequency of 200 kHz with an acoustic intensity of 6 W cm(-2) under argon, oxygen, and air atmospheres. The sonolytic degradation rate of the APs under the conditions of the present study depended upon their alkyl chain length. The decrease in the degradation rate by the radical scavenging effect was in the range of about 48-82% for APs in the presence of 3 mM 2-methyl-2-propanol. The free radicals play a significant role in the sonolytic degradation process of the APs. In the presence of Fe(II) and Fe(III), the pseudo-first-order rate constants for the sonolytic degradation of 30 microM NP as a function of the concentration of Fe(II) and Fe(III) were estimated under argon and oxygen. The maximum rate constants were observed at 50 microM Fe(II) (0.139 +/- 0.008 min(-1)) and 100 microM Fe(III) (0.103 +/- 0.001 min(-1)) under oxygen. The total organic carbon concentration (TOC) was investigated under same conditions. TOC decreased in the range of about 50-70% during the sonication in the presence of Fe(II) and Fe(III) under argon and oxygen. The sonochemical effects by the addition of Fe(II) and Fe(III) as catalyst during the sonication under the proper atmosphere result in a remarkable enhancement of degradation and mineralization.     

On-Line Adaptive and Nonlinear Process Monitoring of a Pilot-Scale Sequencing Batch Reactor

This article describes the application of on-line nonlinear monitoring of a sequencing batch reactor (SBR). Three-way batch data of SBR are unfolded batch-wisely, and then a adaptive and nonlinear multivariate monitoring method is used to capture the nonlinear characteristics of normal batches. The approach is successfully applied to an 80 L SBR for biological wastewater treatment, where the SBR poses an interesting challenge in view of process monitoring since it is characterized by nonstationary, batchwise, multistage, and nonlinear dynamics. In on-line batch monitoring, the developed adaptive and nonlinear process monitoring method can effectively capture the nonlinear relationship among process variables of a biological process in a SBR. The results of this pilot-scale SBR monitoring system using simple on-line measurements clearly demonstrated that the adaptive and nonlinear monitoring technique showed lower false alarm rate and physically meaningful, that is, robust monitoring results.