Decline in extractable antibiotics in manure-based composts during composting

A wide variety of antibiotics have been detected in natural water samples and this is of potential concern because of the adverse environmental effects of such antibiotic residues. One of the main sources of antibiotics effluence to the surrounding environment is livestock manures which often contain elevated concentrations of veterinary antibiotics (VAs) which survive digestion in the animal stomach following application in animal husbandry practices. In Korea, livestock manures are normally used for compost production indicating that there is potential for antibiotic release to the environment through compost application to agricultural lands. Therefore, reduction of the amount of VAs in composts is crucial. The purpose of this study was to understand the influence of the composting process and the components of the compost on the levels of three common classes of antibiotics (tetracyclines, sulfonamides, and macrolides). Composted materials at different stages of composting were collected from compost manufacturing plants and the variation in antibiotic concentrations was determined. Three different antibiotics, chlortetracycline (CTC), sulfamethazine (SMZ), and tylosin (TYL) at three different concentrations (2, 10, and 20 mg kg⁻¹) were also applied to a mixture of pig manure and sawdust and the mixtures incubated using a laboratory scale composting apparatus to monitor the changes in antibiotic concentrations during composting together with the physicochemical properties of the composts. During composting, in both field and lab-scale investigations, the concentrations of all three different antibiotics declined below the relevant Korean guideline values (0.8 mg kg⁻¹ for tetracyclines, 0.2 mg kg⁻¹ for sulfonamides and 1.0 mg kg⁻¹ for macrolides). The decline of tetracycline and sulfonamide concentrations was highly dependent on the presence of sawdust while there was no influence of sawdust on TYL decline.     

Application of eggshell waste for the immobilization of cadmium and lead in a contaminated soil

Liming materials have been used to immobilize heavy metals in contaminated soils. However, no studies have evaluated the use of eggshell waste as a source of calcium carbonate (CaCO₃) to immobilize both cadmium (Cd) and lead (Pb) in soils. This study was conducted to evaluate the effectiveness of eggshell waste on the immobilization of Cd and Pb and to determine the metal availability following various single extraction techniques. Incubation experiments were conducted by mixing 0–5% powdered eggshell waste and curing the soil (1,246 mg Pb kg^?1 soil and 17 mg Cd kg^?1 soil) for 30 days. Five extractants, 0.01 M calcium chloride (CaCl₂), 1 M CaCl₂, 0.1 M hydrochloric acid (HCl), 0.43 M acetic acid (CH₃COOH), and 0.05 M ethylendiaminetetraacetic acid (EDTA), were used to determine the extractability of Cd and Pb following treatments with CaCO₃ and eggshell waste. Generally, the extractability of Cd and Pb in the soils decreased in response to treatments with CaCO₃ and eggshell waste, regardless of extractant. Using CaCl₂ extraction, the lowest Cd concentration was achieved upon both CaCO₃ and eggshell waste treatments, while the lowest Pb concentration was observed using HCl extraction. The highest amount of immobilized Cd and Pb was extracted by CH₃COOH or EDTA in soils treated with CaCO₃ and eggshell waste, indicating that remobilization of Cd and Pb may occur under acidic conditions. Based on the findings obtained, eggshell waste can be used as an alternative to CaCO₃ for the immobilization of heavy metals in soils.     

Reproductive biology of the common shrimp Crangon crangon (Decapoda: Crangonidae) in the central Irish Sea

Aspects of the reproductive biology of the common shrimp Crangon crangon (L.) were studied in Port Erin Bay, Isle of Man, Irish Sea. Size at sexual maturity was determined from the proportions of ovigerous females and of females with maturing ovaries. The size at which 50% of females are mature is estimated (±95% confidence intervals) as 12.5±0.48 mm carapace length. Based on the proportions of ovigerous females and of mature females, the main breeding season was from January to June. Mean ovarian dry weights indicated two broods (winter and summer), with females bearing winter broods (WB) having higher gonad indices than those with summer broods (SB). WB females with non-eyed eggs and with eyed eggs differed in the regression of ovarian dry weight on carapace length, indicating preparation for laying a second brood. In both broods the moult stages of berried females were related to egg stage. Moulting will occur following the release of the brood. During embryonic development, mean egg length and egg volume were larger in all stages, and the mean dry weight of individual eggs of all stages heavier, in WB than in SB; there was no difference in egg number, however. Consequently, reproductive investment, the proportion of female weight devoted to egg production, was 67% higher in WB (0.20±0.04) than in SB (0.12±0.03). There is a significant effect of egg volume on brood weight, but not on egg number. In both broods, egg number was a negatively allometric function of female body size in non-eyed eggs and an isometric function of female body size in eyed eggs. Brood mortality during incubation was higher in SB (17%) than WB (10%). Differences in the reproductive variables and investment between the two broods of C. crangon are discussed in the light of reproductive strategies and life history.Communicated by J.P. Thorpe, Port Erin     

Fine dust filtration using a metal fiber bed

A bed-type filter composed of thin metal alloy fiber was closely examined with dust capturing in cold and hot runs. The investigation of an individual mechanism across the filter bed indicated that the aerated dust could be initially collected by depth filtration, and after a while, surface filtration dominated the overall dust collection. The present metal fiber bed was comparable to the conventional ceramic filters because of its good collection efficiency with low pressure drop. It also showed potential to be used as a prefilter in a diesel exhaust trapping system.     

Sustainable Water Resources Management in a Conflict Resolution Framework1

Abstract: A decision support system for sustainable water resources management in a water conflict resolution framework is developed to identify and evaluate a range of acceptable alternatives for the Geum River Basin in Korea and to facilitate strategies that will result in sustainable water resource management. Working with stakeholders in a “shared vision modeling” framework, sustainable management strategies are created to illustrate system tradeoffs as well as long‐term system planning. A multi‐criterion decision‐making (MCDM) approach using subjective scales is utilized to evaluate the complex water resource allocation and management tradeoffs between stakeholders and system objectives. The procedures used in this study include the development of a “shared vision model,” a simulated decision‐making support system (as a tool for sustainable water management strategies associated with water conflicts, management options, and planning criteria), and the application of MCDM techniques for evaluating alternatives provided by the model. The research results demonstrate the utility of the sustainable water resource management model in aid of MCDM techniques in facilitating flexibility during initial stages of alternative identification and evaluation in a basin suffering from severe water conflicts.     

Sources of productive efficiency: International comparison of iron and steel firms

Using a time-varying stochastic frontier model, this paper examines the technical efficiency of firms in the iron and steel industry to try to identify the factors contributing to the industry's efficiency growth. Industry observers and policymakers tend to cite most frequently three possible sources of efficiency growth: privatization; economies of scale; and vintage of equipment. Our study corroborates these factors. Based on our findings, which pertain to 52 iron and steel firms over the period of 1978–1997, privatization is likely to improve the efficiency of iron and steel firms to a great extent as evidenced in various industries. This study also provides systematic evidence that iron and steel production shows economies of scale. In addition, newer vintages of equipment are found to be closely correlated with higher levels of efficiency. This clearly indicates that investment in new plants and equipments is critical in pursuit of efficiency in the iron and steel industry.     

Nonparametric Monte Carlo Simulation for Flood Frequency Curve Derivation: An Application to a Korean Watershed1

Abstract: A mix of causative mechanisms may be responsible for flood at a site. Floods may be caused because of extreme rainfall or rain on other rainfall events. The statistical attributes of these events differ according to the watershed characteristics and the causes. Traditional methods of flood frequency analysis are only adequate for specific situations. Also, to address the uncertainty of flood frequency estimates for hydraulic structures, a series of probabilistic analyses of rainfall‐runoff and flow routing models, and their associated inputs, are used. This is a complex problem in that the probability distributions of multiple independent and derived random variables need to be estimated to evaluate the probability of floods. Therefore, the objectives of this study were to develop a flood frequency curve derivation method driven by multiple random variables and to develop a tool that can consider the uncertainties of design floods. This study focuses on developing a flood frequency curve based on nonparametric statistical methods for the estimation of probabilities of rare floods that are more appropriate in Korea. To derive the frequency curve, rainfall generation using the nonparametric kernel density estimation approach is proposed. Many flood events are simulated by nonparametric Monte Carlo simulations coupled with the center Latin hypercube sampling method to estimate the associated uncertainty. This study applies the methods described to a Korean watershed. The results provide higher physical appropriateness and reasonable estimates of design flood.     

Implication of the cluster analysis using greenhouse gas emissions of Asian countries to climate change mitigation

Climate change caused by excessive emission of greenhouse gases (GHGs) into the atmosphere has gained serious attention from the global community for a long time. More and more countries have decided to propose their goals such as Paris agreements, to reduce emitting these heat trapping compounds for sustainability. The Asian region houses dramatic changes with diverse religions and cultures, large populations as well as a rapidly changing socio-economic situations all of which are contributing to generating a mammoth amount of GHGs; hence, they require calls for related studies on climate change strategies. After pre-filtering of GHG emission information, 24 Asian countries have been selected as primary target countries. Hierarchical cluster analysis method using complete linkage technique was successfully applied for appropriate grouping. Six groups were categorized through GHG emission properties with major and minor emission sectors based on the GHG inventory covering energy, industrial processes, agriculture, waste, land use change, and forestry and bunker fuels. Assigning six groups using cluster analysis finally implied that the approach to establish GHG emission boundaries was meaningful to develop further mitigation strategies. Following the outcome of this study, calculating amount of reduction potential in suitable sectors as well as determining best practice, technology, and regulatory framework can be improved by policy makers, environmental scientists, and planners at the different levels. Therefore, this work on reviewing a wide range of GHG emission history and establishing boundaries of emission characteristics would provide further direction of effective climate change mitigation for sustainability and resilience in Asia.     

UPLAND SOIL EROSION SIMULATION FOR AGRICULTURAL WATERSHEDS1

ABSTRACT: A soil erosion simulation model that considered the physical conditions of agricultural watersheds and that interfaced with the modified USDAHL-74 watershed hydrology model was developed. The erosion model simulates the detachment and transport of soil particles caused by raindrop impact and overland flow from rill and interrill areas. The model considers temporal and spatial variation of plant residue, crop canopy cover, snow cover, and the moisture content of surface soil as modifying factors of the erosive forces of raindrop impact and overland flow. The hydrology model simulates overland flow and some of the physical parameters that are used in the erosion model. The simulation is executed in the time interval determined by the rainfall rate or snowmelt rate. The erosion model compares the transport capacity of the overland flow and the sediment loaded in the overland flow to determine the fate account for the free soil particles that have already been detached and are readily available to be transported by the overland flow. The model was tested with data from two small agricultural watersheds in the Palouse region of the Pacific Northwest dryland. The model was calibrated by trial-and-error to determine the coefficients of the model.     

Development of intelligent sorting system realized with the aid of laser-induced breakdown spectroscopy and hybrid preprocessing algorithm-based radial basis function neural networks for recycling black plastic wastes

Plastic recycling has been the key issue for reducing environmental problems and resolving resource depletion. To improve the recovery rate of plastics, the plastic wastes are correctly identified according to their resin type. However, the identification system, which is able to identify black plastics according to not only the type of black plastics but also the grade of resins correctly, has not been introduced. In this paper, laser-induced breakdown spectroscopy, intelligent algorithms and preprocessing algorithms are used to improve the identification of black plastics such as polypropylene, polystyrene (PS), and acrylonitrile butadiene styrene (ABS). The laser-induced breakdown spectroscopy is capable of obtaining the characteristic spectrum regardless of material’s physical state. To extract the new features which are very valuable to improving learning performance, increasing computational efficiency, and building better generalization models from the obtained spectra through laser-induced breakdown spectroscopy, the hybrid preprocessing algorithm, composed of principal component analysis and independent component analysis, is used. In addition, the intelligent algorithm named the extended radial basis function neural networks inheriting the advantages of fuzzy theory and neural networks is used to identify black plastic samples into several categories with respect to their resins. The proposed identification system, composed of three parts such as laser induced breakdown spectroscopy, hybrid preprocessing algorithms, and an efficient intelligent classification algorithm, is able to show the synergy effect on the black plastic identification problem. From several experimental results, it can be seen that the identification system based on laser-induced breakdown spectroscopy and the intelligent algorithm is used for identification of black plastics by resin type.