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.     

Evaluation of PCDD/Fs characterization in animal feed and feed additives

Safety control of feed and feed additives is necessary to have safe food of animal origin. Based on media reports, nine incidents regarding dioxins and/or PCBs contaminations occurred worldwide during the last decade. Korea is a country which imports feed and feed additives. In this study, various kinds of feed and feed additives were analyzed to monitor the contamination level of dioxins. The level of PCDD/Fs in fish oil was the highest with a concentration of 23.33ngkg(-1), which is equivalent to a toxicological concentration of 4.68ngWHO-TEQ/kg. Feed from animals origin such as chicken meal, animal fat, fish meal, fish oil, and shell powder showed relatively higher concentrations of PCDD/Fs. Feed from plants origin, minerals, and additives ranged from non-detects for bit pulp and ethoxyquin to 8.28ngkg(-1) for dl-methionine. From a toxicological point of view, the highest concentration in vitamins was 0.08ngWHO-TEQ/kg among the feed additives. 2,3,4,7,8-PeCDF was the dominant congener in samples of fish oil, fish meal, and shell powder. Animal fat showed that the pattern of PCDD/Fs depends on the sources of contamination. A sample of animal fat showed 1,2,3,4,7,8-HxCDF and the other sample showed 1,2,3,4,7,8-HxCDD as a primary congener. Generally, low levels of PCDDs were detected in feed additives. Patterns of PCDD/Fs in choline chloride were different with that in choline chloride from an incident in Europe in 2000.     

Impact of sample preparation on mineralogical analysis of zero-valent iron reactive barrier materials

Permeable reactive barriers (PRBs) of zero-valent iron (Fe(0)) are increasingly being used to remediate contaminated ground water. Corrosion of Fe(0) filings and the formation of precipitates can occur when the PRB material comes in contact with ground water and may reduce the lifespan and effectiveness of the barrier. At present, there are no routine procedures for preparing and analyzing the mineral precipitates from Fe(0) PRB material. These procedures are needed because mineralogical composition of corrosion products used to interpret the barrier processes can change with iron oxidation and sample preparation. The objectives of this study were (i) to investigate a method of preparing Fe(0) reactive barrier material for mineralogical analysis by X-ray diffraction (XRD), and (ii) to identify Fe mineral phases and rates of transformations induced by different mineralogical preparation techniques. Materials from an in situ Fe(0) PRB were collected by undisturbed coring and processed for XRD analysis after different times since sampling for three size fractions and by various drying treatments. We found that whole-sample preparation for analysis was necessary because mineral precipitates occurred within the PRB material in different size fractions of the samples. Green rusts quickly disappeared from acetone-dried samples and were not present in air-dried and oven-dried samples. Maghemite/magnetite content increased over time and in oven-dried samples, especially after heating to 105 degrees C. We conclude that care must be taken during sample preparation of Fe(0) PRB material, especially for detection of green rusts, to ensure accurate identification of minerals present within the barrier system.     

Monitoring of Aerial Pollutants Emitted from Swine Houses in Korea

This on-site survey study was performed to determine the concentrations and emissions of aerial contaminants in the different types of swine houses in Korea and then to present beneficial information available for Korean pig producers to manage optimal air quality in swine house. The swine houses investigated in this research were selected based on three criteria; manure removal system, ventilation mode and growth stage of swine. Mean concentrations of aerial pollutants in swine houses were 8 ppm for ammonia, 300 ppb for hydrogen sulfide, 2 mg m⁻³ for total dust, 0.6 mg m⁻³ for respirable dust, 4 log(cfu m⁻³) for total airborne bacteria and 3 log(cfu m⁻³) for total airborne fungi, respectively. Mean emissions based on pig (liveweight; 75 kg) and area (m²) were 250 and 340 mg h⁻¹ for ammonia, 40 and 50 mg h⁻¹ for hydrogen sulfide, 40 and 50 mg h⁻¹ for total dust, 10 and 15 mg h⁻¹ for respirable dust, 1.0 and 1.3 log(cfu) h⁻¹ for total airborne bacteria and 0.7 and 1.0 log(cfu) h⁻¹ for total airborne fungi, respectively. In general concentrations and emissions of gases were relatively higher in the swine houses managed with deep-pit manure system with slats and mechanical ventilation mode than the different swine housing types whereas those of particulates and bioaerosol were highest in the naturally ventilated swine houses with deep-litter bed system.     

Distribution of uranium contamination in weathered fractured saprolite/shale and ground water

The objective of this study was to determine how structure, stratigraphy, and weathering influence fate and transport of contaminants (particularly U) in the ground water and geologic material at the Department of Energy (DOE) Environmental Remediation Sciences Department (ERSD) Field Research Center (FRC). Several cores were collected near four former unlined adjoining waste disposal ponds. The cores were collected, described, analyzed for U, and compared with ground water geochemistry from surrounding multilevel wells. At some locations, acidic U-contaminated ground water was found to preferentially flow in small remnant fractures weathering the surrounding shale (nitric acid extractable U [U(NA)] usually < 50 mg kg(-1)) into thin (<25 cm) Fe oxide-rich clayey seams that retain U (U(NA) 239 to 375 mg kg(-1)). However, greatest contaminant transport occurs in a 2 to 3 m thick more permeable stratigraphic transition zone located between two less permeable, and generally less contaminated zones consisting of (i) overlying unconsolidated saprolite (U(NA) < 0.01 to 200 mg kg(-1)) and (ii) underlying less-weathered bedrock (U(NA) generally < 0.01 to 7 mg kg(-1)). In this transition zone, acidic (pH < 4) U-enriched ground water (U of 38 mg L(-1)) has weathered away calcite veins resulting in greater porosity, higher hydraulic conductivity, and higher U contamination (U(NA) 106 to 745 mg kg(-1)) of the weathered interbedded shale and sandstone. These characteristics of the transition zone produce an interval with a high flux of contaminants that could be targeted for remediation.     

Interfacial solar steam generation by wood-based devices to produce drinking water: a review

Environmental Chemistry Letters - Freshwater supply is declining in the context of climate change, pollution, and soil salinization, calling for sustainable methods to produce drinking water. For...     

Identification of black plastics realized with the aid of Raman spectroscopy and fuzzy radial basis function neural networks classifier

To accomplish the effective classifier and secure the accurate classification capabilities of black plastics, a comprehensive design methodology of fuzzy radial basis function neural networks is developed with the aid of principal component analysis and particle swarm optimization. Plastics recycling is the competitive method which can deal with the shortage of natural resource. To recycle and reuse the waste plastics, this study is given as the key issue to identify and classify waste plastics by resin type such as polyethylene terephthalate, polypropylene, polystyrene, etc. To complement the weak points of recognition and classification of the near-infrared radiation equipment, Raman spectroscopy is used to obtain qualitative as well as quantitative analysis of black plastics. To improve the identification performance of black plastics, an intelligent computing algorithm such as fuzzy radial basis function neural networks classifier and preprocessing algorithm as principal component analysis are applied to analyze and classify the obtained spectrum of black plastics. Finally, to optimize the structure as well as parameters of fuzzy radial basis function neural networks, particle swarm optimization technique is used. The obtained experimental results show that the proposed network architecture exhibits high classification capabilities in practical applications.     

Daily intakes of naturally occurring radioisotopes in typical Korean foods

The concentrations of naturally occurring radioisotopes ((232)Th, (228)Th, (230)Th, (228)Ra, (226)Ra, and (40)K) in typical Korean foods were evaluated. The daily intakes of these radioisotopes were calculated by comparing concentrations in typical Korean foods and the daily consumption rates of these foods. Daily intakes were as follows: (232)Th, 0.00-0.23; (228)Th, 0.00-2.04; (230)Th, 0.00-0.26; (228)Ra, 0.02-2.73; (226)Ra, 0.01-4.37 mBq/day; and (40)K, 0.01-5.71 Bq/day. The total daily intake of the naturally occurring radioisotopes measured in this study from food was 39.46 Bq/day. The total annual internal dose resulting from ingestion of radioisotopes in food was 109.83 muSv/y, and the radioisotope with the highest daily intake was (40)K. These values were same level compiled in other countries.     

NO removal by reducing agents and additives in the selective non-catalytic reduction (SNCR) process

The effect of the additives on the selective non-catalytic reduction (SNCR) reaction has been determined in a three-stage laboratory scale reactor. The optimum reaction temperature is lowered and the reaction temperature window is widened with increasing concentrations of the gas additives (CO, CH4). The optimum reaction temperature is lowered and the maximum NO removal efficiency decreases with increasing the concentration of alcohol additives (CH3OH, C2H5OH). The addition of phenol lowers the optimum reaction temperature about 100-150 degrees C similar to that of the toluene addition. The volatile organic compounds (VOCs: C6H5OH, C7H8) can be utilized in the SNCR process to enhance NO reduction and removed at the same time. A previously proposed simple kinetic model can successfully apply the NO reduction by NH3 and the present additives.