High-Resolution Environmentally Extended Input-Output Model to Assess the Greenhouse Gas Impact of Electronics in South Korea.

South Korea is a global leader in electronics, but little is known about their climate change impact. Here, we estimate the direct and indirect greenhouse gas (GHG) emissions of Korean electronics by developing a new and high-resolution (∼380 sectors) environmentally extended input-output model, named KREEIO. We find that final demand for Korean electronics led to nearly 8% of national GHG emissions in 2017, mostly because of indirect emissions embodied in the electronics supply chain. Notably, the semiconductor and display sectors contributed 3.2% and 2.4% to national emissions, with capital investment accounting for 17% of the two sectors' total emissions or nearly 1% of national emissions. For other electronic products, scope 1, scope 2, and upstream scope 3 emissions on average accounted for 3%, 10%, and 87% of a sector's GHG intensity, respectively. Detailed contribution analysis suggests that reducing Korean electronics GHG emissions would benefit most from the transition to a low-carbon electricity grid, but mitigation efforts in many other sectors such as metals and chemicals are also important. Overall, our study underscores the significance of electronics GHG emissions in South Korea, especially those from semiconductors and displays, and the mitigation challenges these sectors face as demand continues to grow globally.

Characteristics of industrial hazardous waste generation in South Korea from 2008 to 2018 based on decoupling and decomposition analysis.

The industrial hazardous waste (IHW) generation to meet consumption is steadily increasing, resulting in environmental, health, and social problems around the world. To address IHW at the source, it is critical to understand the generation characteristics and key drivers on industrial hazardous waste generation (IHWG). This study analysed the generation characteristics of IHW of South Korea from 2008 to 2018 by decoupling and index decomposition analysis using Log Mean Divisia Index (LMDI) model. South Korea presented unstable decoupling of IHWG from economic growth, so more effective waste management regulations are needed to support a stable decoupling. One most critical finding was that the factors of industrial output and industrial characteristic of IHWG-to-energy were major driving factors influencing the increase of IHWG, whereas those of industrial structure and energy efficiency affect to the decrease of IHWG in most industries. In addition, the result clearly confirmed that the contribution of driving factors affecting the IHWG differs by industry. These results provide significant policy insights that the South Korean government needs institutional improvement and refinement of customised IHW management according to the characteristics of IHWG.

Fuzzy multi-objective optimization case study based on an anaerobic co-digestion process of food waste leachate and piggery wastewater.

This paper presents the development and evaluation of fuzzy multi-objective optimization for decision-making that includes the process optimization of anaerobic digestion (AD) process. The operating cost criteria which is a fundamental research gap in previous AD analysis was integrated for the case study in this research. In this study, the mixing ratio of food waste leachate (FWL) and piggery wastewater (PWW), calcium carbonate (CaCO3) and sodium chloride (NaCl) concentrations were optimized to enhance methane production while minimizing operating cost. The results indicated a maximum of 63.3% satisfaction for both methane production and operating cost under the following optimal conditions: mixing ratio (FWL: PWW) - 1.4, CaCO3 - 2970.5 mg/L and NaCl - 2.7 g/L. In multi-objective optimization, the specific methane yield (SMY) was 239.0 mL CH4/g VSadded, while 41.2% volatile solids reduction (VSR) was obtained at an operating cost of 56.9 US$/ton. In comparison with the previous optimization study that utilized the response surface methodology, the SMY, VSR and operating cost of the AD process were 310 mL/g, 54% and 83.2 US$/ton, respectively. The results from multi-objective fuzzy optimization proves to show the potential application of this technique for practical decision-making in the process optimization of AD process.

Ethanol mediated As(III) adsorption onto Zn-loaded pinecone biochar: Experimental investigation, modeling, and optimization using hybrid artificial neural network-genetic algorithm approach.

Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box-Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand-metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model-genetic algorithm (RSM-GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47µg/g) is facilitated at 30.22mg C/L of EtOH with initial As(III) concentration of 196.77µg/L at pH5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM.

Characterization of co-digestion of industrial sludges for biogas production by artificial neural network and statistical regression models.

The characteristics and impact of industrial sludges of paper, chemical, petrochemical, automobile, and food industries situated in the Ulsan Industrial Complex, Ulsan, Republic of Korea in co-digestion for biogas production were assessed by artificial neural network (ANN) and statistical regression models. The regression model was based on a simplex-centroid mixture design and the ANN was based on a resilient back-propagation algorithm (topology 5-7-1). Using connection weights and bias of the trained ANN model, the impact of each sludge of co-digestion was assessed using Garsons' algorithm. Results suggested that the modelling and predictability of ANN were superior to the regression model with accuracy (A(f)) 1.01, bias (B(f)) 1.00, root mean square error 3.56, and standard error of prediction 2.51%. Sludge from the chemical industry showed the highest impact on specific methane yield (SMY(VS)) with a relative importance of 28.59% followed by sludges from paper (20.07%), food (19.59%), petrochemical (15.92%), and automobile (15.82%) industries. The interactions between diverse industrial sludges were successfully modelled and partitioned into various synergistic and antagonistic effects on SMY(VS). Synergistic interactions between the chemical industry sludge and either petrochemical or food industry sludges on SMY(VS) were detected. However, strong negative interaction between automobile sludge and other sludges was observed. This study indicates that though the ANN model performed better in prediction and impact assessments, the regression model reveals the synergistic and antagonistic interactions among sludges.

Identifying the socioeconomic determinants of industrial hazardous waste generation: South Korea as a case study.

The South Korean government has set an ambitious target to reduce industrial hazardous waste (IHW) as part of its transition towards a circular economy. Moreover, effective management of IHW within the country has become crucial, given that IHW trade is regulated by the Basel Convention. Despite the urgent need for well-founded environmental policies, there is a lack of essential information on the characteristics and determinants of IHW generation, which hinders the effectiveness of existing IHW policies. To address this information gap, this study developed a South Korean extended IHW input-output model for 2008 and 2018 to characterize IHW generation and applied structural decomposition analysis to identify the socioeconomic determinant of change of IHW generation. The results reveal that consumption, export, and direct IHW intensity change of 'Chemical', 'Electronic and electrical equipment', 'Basic metal', and 'Other service' emerge as dominant determinants for IHW growth. Conversely, technology change, including technological structure change and direct IHW intensity change, of 'Basic metal' and 'Other service' is the key driver for IHW reduction. In addition, an intriguing aspect of the study relates to the supply chain's influence on IHW generation. The indirect growth of IHW resulting from expanding exports and consumption contributes nearly twice as much to the overall increase in IHW as direct IHW growth. These valuable insights pave the way for the South Korean government to establish holistic and customized environmental policies regarding IHW. It emphasizes the importance of considering expanded global system boundaries, technological advancements, and purchasers' consumption patterns as dominant factors in formulating these policies. Furthermore, this study not only provides crucial guidance for the government's decision-making but also suggests strengthening environmental management and monitoring practices.

Optimization of tetracycline removal from water by iron-coated pine-bark biochar.

We synthesized iron-coated pine-bark biochar (Fe-PBB) and determined the optimal conditions for removing the antibiotic tetracycline from water. The Fe-PBB was synthesized by depositing iron oxide on pyrolyzed pine-bark waste via a facile co-precipitation method. Characterization (SEM, EDX, and TGA) showed successful deposition of a mass of approximately 27% (w/w) iron on the PBB to synthesize Fe-PBB. Fe-PBB exhibited five times higher adsorption capacity (~ 10 mg/g) for tetracycline compared with PBB. The effects of initial tetracycline concentration, pH, temperature, and Fe-PBB dose on the adsorption removal of tetracycline from water were systematically investigated and optimized using a statistical experimental design and response surface methodology. The empirical relationship between the experimental factors and tetracycline removal was modeled, statistically validated through the analysis of variance, and used to predict the optimal conditions for adsorption removal of tetracycline. We found that ≥ 95% of the tetracycline can be removed at a tetracycline concentration of 1 mg/L, pH of 7, temperature of 50 °C, and a Fe-PBB dose of 2 g/L. The adsorption isotherm modeling study suggests that the adsorption of tetracycline can be attributed to the pore filling phenomenon and multilayer adsorption on the Fe-PBB. A thermodynamics study showed that the adsorption occurs spontaneously with an endothermic reaction.

Optimization of low-grade coal and refuse-derived fuel blends for improved co-combustion behavior in coal-fired power plants.

This study is aimed at utilizing three waste materials, i.e., solid refuse fuel (SRF), tire derived fuel (TDF), and sludge derived fuel (SDF), as eco-friendly alternatives to coal-only combustion in co-firing power plants. The contribution of waste materials is limited to ≤5% in the composition of the mixed fuel (coal + waste materials). Statistical experimental design and response surface methodology are employed to investigate the effect of mixed fuel composition (SRF, TDF, and SDF) on gross calorific value (GCV) and ash fusion temperature (AFT). A quadratic model is developed and statistically verified to apprehend mixed fuel constituents' individual and combined effects on GCV and AFT. Constrained optimization of fuel blend, i.e., GCV >1,250 kcal/kg and AFT >1,200 °C, using the polynomial models projected the fuel-blend containing 95% coal with 3.84% SRF, 0.35% TDF, and 0.81% SDF. The observed GCV of 5,307 kcal/kg and AFT of 1225 °C for the optimized blend were within 1% of the model predicted values, thereby establishing the robustness of the models. The findings from this study can foster sustainable economic development and zero CO2 emission objectives by optimizing the utilization of waste materials without compromising the GCV and AFT of the mixed fuels in coal-fired power plants.

Production and characterization of cost-effective magnetic pine bark biochar and its application to remove tetracycline from water.

Low-cost adsorbent, pine bark biochar (PBB) from the forest residue, was produced and applied to remove tetracycline (TC) from aqueous solution via adsorption pathway. The PBB, hence obtained, was modified using aqueous ferric and ferrous ion solutions to obtain magnetic pine bark biochar (M-PBB). Batch adsorption experiments were conducted to examine the adsorption of TC by PBB and M-PBB in the variation of pH, contact time, dosage, and temperature. The adsorbents were characterized by SEM/EDX, TGA, and pHpzc. The adsorption mechanism was evaluated by fitting Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich (D-R) isotherms model. Also, the experimental data were analyzed by kinetics models (pseudo-first-order, pseudo-second-order, intra-particle diffusion, and Elovich) and thermodynamics. The maximum adsorption capacity (qm) of M-PBB was 15.3 mg/g from the experiment at pH 6. A high correlation coefficient (R2 ≈ 0.9) of Freundlich isotherm postulated multi-layer adsorption of TC on M-PBB at pH 6. The kinetic studies showed that the pseudo-first-order was more suitable for representing the adsorption of TC molecules on the surface. The thermodynamic analysis was showed that the adsorption process is favorable, spontaneous, and endothermic at studied temperatures. M-PBB demonstrated a potential for removal of TC from water as a low-cost and convenient adsorbent.

Experimental modeling and optimization for the reduction of hexavalent chromium in aqueous solutions using ascorbic acid.

In this study, we investigated the reduction of toxic Cr(VI) to less toxic Cr(III) using ascorbic acid in various aqueous solutions: deionized water, synthetic soft water, synthetic hard water, and real tap water. The experiments were performed using a statistical experimental design. Response surface methodology (RSM) was used to correlate Cr(VI) reduction (response variable) with experimental parameters such as initial Cr(VI) concentration, humic acid concentration, and ascorbic acid dosage. The empirical model obtained from the experiments was used to estimate and optimize the quantity of ascorbic acid required for the reduction of ≥ 99% Cr(VI) in water. The optimized dosages of ascorbic acid were predicted and experimentally validated for > 99.5% reduction of Cr(VI) (1, 10, 20, and 100 mg/L) in the solutions. Even a solution containing an initial Cr(VI) concentration of 100 mg/L was reduced in concentration ≥ 99.9% with optimal dosage of ascorbic acid (500 mg/L) in the presence of 20 mg/L humic acid. Moreover, the reaction kinetics (kobs-Cr(VI) = 0.71 mM-1 s-1) were sufficient to reduce the ≥ 99.9% Cr(VI) in 20 min. This study sheds new light on the effect of ascorbic acid on Cr(VI) reduction, and provides knowledge fundamental to optimize treatment of Cr(VI) contaminated water to environmentally acceptable endpoints.

Decarbonization of Vietnam's economy: decomposing the drivers for a low-carbon growth.

Vietnam has witnessed a rapid increase in national-level CO2 emissions due to rising urbanization, economic expansion, export growth, and industrial development. Moreover, to support the ambitious economic growth targets, reliance on and consumption of fossil fuels are increasing by each passing year. With this circumstance, this study aims to analyze the key drivers of CO2 emissions in Vietnam from 1990 to 2016 using the Kaya identity and decomposition method. Following this approach, CO2 emissions have been decomposed into five effect categories comprising population, affluence, energy intensity, fuel mix, and emission intensity. As per the results, CO2 emissions in Vietnam were mainly driven by rising affluence (58.5%) and changing fuel mix (33.2%) which have resulted from improved living standards, rapid industrial development, and higher fossil fuel consumption. Moreover, population (13.8%) and emission intensity (3.1%) exhibited a relatively lower impact on CO2 emissions during 1990-2016. However, energy intensity (- 8.7%) was the only negative driver which has resulted in the slowdown of carbon emissions in Vietnam. Based on the analysis of energy policy development, the share of renewable energy resources was still quite low in the national energy mix with higher reliance on traditional fossil fuels (mainly coal and petroleum). Therefore, to make a transition towards low-carbon economic growth, significant improvements in energy efficiency and emission intensity are necessary together with national energy mix restructuring for low-carbon economic growth.

Urban water infrastructure optimization to reduce environmental impacts and costs.

Urban water planning and policy have been focusing on environmentally benign and economically viable water management. The objective of this study is to develop a mathematical model to integrate and optimize urban water infrastructures for supply-side planning and policy: freshwater resources and treated wastewater are allocated to various water demand categories in order to reduce contaminants in the influents supplied for drinking water, and to reduce consumption of the water resources imported from the regions beyond a city boundary. A case study is performed to validate the proposed model. An optimal urban water system of a metropolitan city is calculated on the basis of the model and compared to the existing water system. The integration and optimization decrease (i) average concentrations of the influents supplied for drinking water, which can improve human health and hygiene; (ii) total consumption of water resources, as well as electricity, reducing overall environmental impacts; (iii) life cycle cost; and (iv) water resource dependency on other regions, improving regional water security. This model contributes to sustainable urban water planning and policy.

Methane production potential of leachate generated from Korean food waste recycling facilities: a lab-scale study.

This paper examines the applicability of food waste leachate (FWL) in bioreactor landfills or anaerobic digesters to produce methane as a sustainable solution to the persisting leachate management problem in Korea. Taking into account the climatic conditions in Korea and FWL characteristics, the effect of key parameters, viz., temperature, alkalinity and salinity on methane yield was investigated. The monthly average moisture content and the ratio of volatile solids to total solids of the FWL were found to be 84% and 91%, respectively. The biochemical methane potential experiment under standard digestion conditions showed the methane yield of FWL to be 358 and 478 ml/g VS after 10 and 28 days of digestion, respectively, with an average methane content of 70%. Elemental analysis showed the chemical composition of FWL to be C(13.02)H(23.01)O(5.93)N(1). The highest methane yield of 403 ml/g VS was obtained at 35 degrees C due to the adaptation of seed microorganisms to mesophilic atmosphere, while methane yields at 25, 45 and 55 degrees C were 370, 351 and 275 ml/g VS, respectively, at the end of 20 days. Addition of alkalinity had a favorable effect on the methane yield. Dilution of FWL with salinity of 2g/l NaCl resulted in 561 ml CH(4)/g VS at the end of 30 days. Considering its high biodegradability (82.6%) and methane production potential, anaerobic digestion of FWL in bioreactor landfills or anaerobic digesters with a preferred control of alkalinity and salinity can be considered as a sustainable solution to the present emergent problem.

Biological oxidation of hydrogen sulfide under steady and transient state conditions in an immobilized cell biofilter.

The removal of hydrogen sulfide (H(2)S) was investigated in a lab scale biofilter packed with biomedia, encapsulated by sodium alginate and polyvinyl alcohol (PVA). The main H(2)S oxidation products were SO(4)(2-), SO(3)(2-), S(2-) and S(0). The immobilized cell biofilter required no separate acclimatization period and showed high removal efficiencies (RE) within the first few days of experiments. The removal efficiencies in the biofilter were consistently greater than 99% even when H(2)S loading was 6 g m(-3)h(-1). The maximum elimination capacity achieved in this study is 8 g H(2)Sm(-3)h(-1) at a loading rate of 13 g H(2)Sm(-3) h(-1). The response of the immobilized cells to fluctuations in inlet concentration and flow rate was determined by subjecting the biofilter to inlet loads of up to 10 g H(2)Sm(-3)h(-1). The biofilter responded effectively to these shock loading conditions and convalesced rapidly within 4-8h. Pressure drop values were consistently less throughout the operational period. The results from this study suggest that an immobilized cell biofilter is effective in treating H(2)S under steady and transient operating conditions.

Effect of COD/N ratio and salinity on the performance of sequencing batch reactors.

The effects of COD/N ratio (3-6) and salt concentration (0.5-2%) on organics and nitrogen removal efficiencies in three bench top sequencing batch reactors (SBRs) with synthetic wastewater and one SBR with fish market wastewater were investigated under different operating schedules. The solids retention time (SRT, 20-100 days) and aeration time (4-10h) was also varied to monitor the performance. For synthetic wastewater, chemical oxygen demand (COD) removal efficiencies were consistently greater than 95%, irrespective of changes in COD/N ratio, aeration time and salt concentrations. Increasing the salt concentrations decreased the nitrification efficiency, while high COD/N ratio's favored better nitrogen removal (>90%). The treatment of real saline wastewater ( approximately 3.2%) from a fish market showed high COD (>80%) and nitrogen (>40%) removal efficiencies despite high loading rate and COD/N fluctuations, which is due to the acclimatization of the biomass within the SBR.

Adsorption equilibrium and kinetics of polyvinyl alcohol from aqueous solution on powdered activated carbon.

In this study, powdered activated carbon (PAC) was used to remove polyvinyl alcohol (PVA) from the aqueous PVA solution. The adsorption kinetics has been studied pertaining to various initial PVA concentration and PAC dosage. The rates of adsorption were found to conform to the second-order kinetics with good correlation. Boyd plot confirmed that external mass transfer was the rate-limiting step in the sorption process. The adsorption isotherm obtained resembled with H-type of isotherm, which indicated a high affinity of the solute for the sorption sites. The Freundlich model appeared to fit the isotherm data better than the Langmuir model. The thermodynamic parameters such as Delta H degrees , Delta S degrees and Delta G degrees were evaluated from the slope and intercept of linear plot of log Kc against (1/T) x 1000. The change in entropy (DeltaS degrees ) and heat of adsorption (Delta H degrees ) of PAC was estimated as 1.45 kJ mol(-1)K(-1) and 365 kJ mol(-1), respectively. The free energy of the adsorption at all temperatures was negative indicating a spontaneous process. The maximum PVA removal of 92% was obtained at a pH of 6.3 and contact time of 30 min for an adsorbent dose of 5 g/L.

Ammonium and potassium removal for anaerobically digested wastewater using natural clinoptilolite followed by membrane pretreatment.

On the basis of the wastewater characteristic of anaerobically digested wastewater, this work studied the individual and simultaneous adsorption of ammonium and potassium ions by the natural clinoptilolite. Langmuir, Freundlich, Langmuir-Freundlich, and Toth model were employed to fit the experimental isotherm data and the fitting performances of different models were compared. Both the individual and simultaneous adsorption kinetics of ammonium and potassium were studied at various pHs and temperatures. The individual adsorption of ammonium was very fast and potassium uptake was even faster than that of ammonium. The adsorption approached equilibrium within 1h in most cases. Five models, including pseudo-first-order, pseudo-second-order, Vermeulen's model, squared driving force model and Elovich equation were used to fit the individual and simultaneous adsorption kinetics of ammonium and potassium. The validities of the fittings for the ammonium and potassium adsorption kinetics were also evaluated.

An analysis of synergistic and antagonistic behavior during BTEX removal in batch system using response surface methodology.

The removal of benzene, toluene, ethylbenzene and xylene (BTEX) as quaternary mixtures were studied in batch systems using a well-defined mixed microbial culture. The synergistic and antagonistic effects of total BTEX removal (BTEXT-RE) due to the presence of mixed substrate was evaluated through experiments designed by response surface methodology (RSM). The low and high concentrations of individual BTEX were 15 and 75 mg l(-1), respectively. The results showed that, increasing the concentration of xylene increased the cumulative BTEX removal (BTEXT-RE), however the reverse occurred when benzene concentrations were increased from low to high levels. A mixed response of increasing and decreasing trend in the BTEXT-RE value was observed when either of toluene or ethylbenzene concentration was increased. When the concentrations of individual BTEX compounds were 30 mg l(-1), the BTEXT-RE was about 58%. Complete BTEXT-RE was achieved at optimal BTEX concentrations of 48.1, 45.6, 49.3 and 56.6 mg l(-1). The RSM approach was found efficient in explaining the main, squared and interaction effects among individual BTEX concentrations on the BTEXT-RE in a more statistically meaningful way.

Effect of organic and metal ion concentration on the simultaneous biological removal of NH4+ and NO3- under anaerobic condition.

A bacterial strain of Pseudomonas aeruginosa AE-1-3, isolated from soil was used to remove NH4+ and NO3- simultaneously in an anaerobic environment containing 0.1% NH4NO3 and 3% glucose in the medium. After preliminary screening, eight isolates were obtained, which were evaluated for their potential to decompose NH4+ and NO3-. Each experimental investigation was carried out for 15 days under controlled laboratory conditions by varying the concentrations of glucose (0-3%). The bacterial strain, AE-1-3 showed 100% removal of both NH4+ and NO3-. The effect of metal ions in combinations of Cu2+, Zn2+, Sn2+ were also studied to ascertain the performance. The results revealed that NO3- could be removed completely in 9 days at 3 microM concentrations of the three metal ions, while 33% of NH4+ remained in 0.1% NH4NO3 medium with 0.5% glucose in the absence of these three ions.

Mechanism of removal of arsenic by bead cellulose loaded with iron oxyhydroxide (beta-FeOOH): EXAFS study.

Bead cellulose loaded with iron oxyhydroxide (BCF) with 47 mass% Fe content was prepared and was successfully applied to the elimination of arsenic from aqueous solutions. A clearer understanding of the arsenic removal mechanism will provide accurate prediction of the arsenic adsorptive properties of the new adsorbent. To study the mechanism of the adsorption process, we measured the extended X-ray absorption fine structure (EXAFS) spectra of arsenite and arsenate sorbed onto the adsorbent with different surface coverages. Both arsenite and arsenate were strongly and specifically adsorbed by akaganéite adsorptive centers on BCF by an inner-sphere mechanism. There was no change in oxidation state following interaction between the arsenic species and the BCF surface. The dominant complex of arsenic species adsorbed on akaganéite was bidentate binuclear corner-sharing ((2)C) between As(V) tetrahedra (or As(III) pyramids) and adjacent edge-sharing FeO(6) octahedra. On the basis of the results from EXAFS spectra, the adsorptive characteristics of arsenic, such as the effects of pH and competing anions, were satisfactorily interpreted.