A comparison of refrigerant management policies and suggestions for improvement in South Korea

HFCs (hydrofluorocarbons) emerged as alternative refrigerants after the production of chlorofluorocarbons was banned and hydrochlorofluorocarbons were phased out, under the Montreal Protocol on Substances that Deplete the Ozone Layer. However, because the Kyoto Protocol considered HFCs as greenhouse gases, and their impact on climate change has been increasing, major developed countries have been strengthening existing regulations on the use of HFCs as refrigerants. South Korea has also passed various legislations related to refrigerant management. However, reports indicate that implementation of these regulations has been ineffective, due to the absence of a specific system for managing the production, use, and disposal phases of refrigerants. To identify and resolve these issues, this study investigates the current state of refrigerant management in South Korea for those three phases. Refrigerant management policies are compared between different legislatures, using the examples of the European Union, United States, and Japan. Based on the findings, five types of measures are suggested to reduce the production and consumption of refrigerants, and to improve refrigerant management regulations in ways that are most appropriate to the South Korean context.     

A comparison study on high-temperature water–gas shift reaction over Fe/Al/Cu and Fe/Al/Ni catalysts using simulated waste-derived synthesis gas

A comparative study on Fe/Al, Fe/Al/Cu, and Fe/Al/Ni catalysts in high-temperature water–gas shift reaction (HT–WGS) using simulated waste-derived synthesis gas has been carried out. The metal oxide (Cu and Ni) and aluminum incorporated Fe catalysts were designed to get highly active HT–WGS catalysts. Despite the high CO concentration in the simulated waste-derived synthesis gas, Fe/Al/Cu catalyst exhibited the highest CO conversion (84 %) and 100 % selectivity to CO₂ at a very high gas hourly space velocity (GHSV) of 40,057 h^?1. The outstanding catalytic performance is mainly due to easier reducibility, the synergy effect of Cu and Al, and the stability of the magnetite.     

Fate and behavior of selected heavy metals with mercury mass distribution in a fluidized bed sewage sludge incinerator

In this paper, emission and distribution behavior of six heavy metals (As, Cd, Cr, Ni, Pb, and Hg), particulate matter and mass distribution of mercury within the different streams of a fluidized bed sewage sludge incinerator are presented. At the inlet of air pollution control devices (APCDs); Cd, Cr, Ni and Pb were mainly enriched in coarse particles; comparatively As content was higher in fine particles (<PM_2.5). The concentration of heavy metals in total particulate matter and PM_2.5, at the inlet of APCDs, were in the order of Cr > Ni > Pb > As > Cd. Mercury was almost always distributed in flue gas. Metals, other than mercury, were efficiently removed in APCDs and their concentrations in bottom ash, with fly ash being higher, whereas for that in wastewater, then waste sand was lesser. Overall mercury removal efficiency of APCDs was 98.6 %. More than 83.3 % of mercury was speciated into oxidized form at the inlet of APCDs, attributed by higher chlorine content in sludge. Mercury was mainly distributed in wastewater (78.4 %), wastewater from a spray dry reactor (16.8 %), fly ash in a hopper (3.4 %) and flue gas (1.4 %). This result is one of the first for data to be obtained; more experiments are required to control emission from such sources.     

Analysis of the nitrifying bacterial community in BioCube sponge media using fluorescent in situ hybridization (FISH) and microelectrodes

There is growing interest in the development of more cost-effective and retrofit technologies for the upgrade and expansion of existing wastewater treatment plants with extreme space constraints. A free-floating sponge media (BioCube) process, using a 24L lab scale reactor, was operated to study the nitrification profiles and microbial community. The COD removal efficiencies were maintained, at an average of 95%, with the mixed liquor suspended solids (MLSS) inside the BioCube sponge media maintained at 12,688mg/L. The nitrification removal efficiencies were between 92% and 100%, with an average value of 99%. From the results of microelectrode measurements, the ammonium ion concentration was found to rapidly decrease from the surface of the BioCube sponge media to a depth of 2mm due to chemical reactions carried out by ammonia oxidizing bacteria (AOB) species. Multi-fluorescence in situ hybridization (FISH) has been used to investigate the spatial distributions of various microbial activities within reactors. Microbial communities were targeted using different oligonucleotide probes specific to AOB and nitrite oxidizing bacteria (NOB). There were a large number of AOB populations, but these were not uniformly distributed in the biofilm compared to the NOB populations.     

Distribution characteristics of nonylphenolic chemicals in Masan Bay environments, Korea

To understand the distribution characteristics of nonylphenolics and sterols, samples such as in creek water, sea surface water, waste water treatment plant (WWTP) effluent water, sediment and mussel were collected and analyzed. The principal analytes are nonylphenol (NP), nonylphenol monoethoxylate (NP1EO), nonylphenol diethoxylate (NP2EO), coprostanol (5beta) and cholestanol (5alpha). All these target pollutants showed 100% detection frequency in all of the samples analyzed. Total concentration of nonylphenolic compounds ranged from 334 to 3628ngl(-1) (average: 1331ngl(-1)) in creek water, from 15 to 36400ngl(-1) (average: 1013ngl(-1)) in sea surface water, from 131 to 2811ngg(-1) dry weight (average: 581ngg(-1) dry weight) in sediment and from 50.5 to 289ngg(-1) dry weight (average: 139ngg(-1) dry weight) in mussel. For water samples, levels of nonylphenolics determined in summer season were higher than those in spring season. Among them, nonylphenol and NP1EO was dominant in creek water and seawater, respectively. The highest concentration was recorded in sediment near a WWTP effluent outlet. And high levels of nonylphenolics and sterols were found in about 3km area surrounding WWTP effluent outlet. Coefficient of linear regression (R(2)) for NP in mussel and in sediment was 0.90. Similarly good correlation (R(2)=0.98) was obtained between concentration in water and in mussel indicating that a steady state has been reached in this bay. The calculated bio concentration factor (BCF=2990) for NP in Masan Bay agrees well with reported values in the literature.     

Characterizing hydrochemical properties of springs in Taiwan based on their geological origins

This study was performed to characterize hydrochemical properties of springs based on their geological origins in Taiwan. Stepwise discriminant analysis (DA) was used to establish a linear classification model of springs using hydrochemical parameters. Two hydrochemical datasets—ion concentrations and relative proportions of equivalents per liter of major ions—were included to perform prediction of the geological origins of springs. Analyzed results reveal that DA using relative proportions of equivalents per liter of major ions yields a 95.6% right assignation, which is superior to DA using ion concentrations. This result indicates that relative proportions of equivalents of major hydrochemical parameters in spring water are more highly associated with the geological origins than ion concentrations do. Low percentages of Na⁺ equivalents are common properties of springs emerging from acid-sulfate and neutral-sulfate igneous rock. Springs emerging from metamorphic rock show low percentages of Cl⁻ equivalents and high percentages of HCO₃^-_{3}^{-} equivalents, and springs emerging from sedimentary rock exhibit high Cl⁻/SO₄^2-_{4}^{2-} ratios.     

Modelling and Prediction of Diesel Engine Performance using Relevance Vector Machine

Diesel engines are being increasingly adopted by many car manufacturers today, yet no exact mathematical diesel engine model exists due to its highly nonlinear nature. In the current literature, black-box identification has been widely used for diesel engine modelling and many artificial neural network (ANN) based models have been developed. However, ANN has many drawbacks such as multiple local minima, user burden on selection of optimal network structure, large training data size, and over-fitting risk. To overcome these drawbacks, this article proposes to apply an emerging machine learning technique, relevance vector machine (RVM), to model and predict the diesel engine performance. The property of global optimal solution of RVM allows the model to be trained using only a few experimental data sets. In this study, the inputs of the model are engine speed, load, and cooling water temperature, while the output parameters are the brake-specific fuel consumption and the amount of exhaust emissions like nitrogen oxides and carbon dioxide. Experimental results show that the model accuracy is satisfactory even the training data is scarce. Moreover, the model accuracy is compared with that using typical ANN. Evaluation results also show that RVM is superior to typical ANN approach.     

Source attribution for mercury deposition with an updated atmospheric mercury emission inventory in the Pearl River Delta Region,China

Estimated anthropogenic Hg emission was 11.9 tons in Pearl River Delta for 2014. Quantifying contributions of emission sources helps to provide control strategies. More attentions should be paid to Hg deposition around the large point sources. Power plant, industrial source and waste incinerator were priorities for control. A coordinated regional Hg emission control was important for controlling pollution. We used CMAQ-Hg to simulate mercury pollution and identify main sources in the Pearl River Delta (PRD) with updated local emission inventory and latest regional and global emissions. The total anthropogenic mercury emissions in the PRD for 2014 were 11,939.6 kg. Power plants and industrial boilers were dominant sectors, responsible for 29.4 and 22.7%. We first compared model predictions and observations and the results showed a good performance. Then five scenarios with power plants (PP), municipal solid waste incineration (MSWI), industrial point sources (IP), natural sources (NAT), and boundary conditions (BCs) zeroed out separately were simulated and compared with the base case. BCs was responsible for over 30% of annual average mercury concentration and total deposition while NAT contributed around 15%. Among the anthropogenic sources, IP (22.9%) was dominant with a contribution over 20.0% and PP (18.9%) and MSWI (11.2%) ranked second and third. Results also showed that power plants were the most important emission sources in the central PRD, where the ultra-low emission for thermal power units need to be strengthened. In the northern and western PRD, cement and metal productions were priorities for mercury control. The fast growth of municipal solid waste incineration were also a key factor in the core areas. In addition, a coordinated regional mercury emission control was important for effectively controlling pollution. In the future, mercury emissions will decrease as control measures are strengthened, more attention should be paid to mercury deposition around the large point sources as high levels of pollution are observed.