Copper recovery is the core of waste printed circuit boards (WPCBs) treatment. In this study, we proposed a feasible and efficient way to recover copper from WPCBs concentrated metal scraps by direct electrolysis and factors that affect copper recovery rate and purity, mainly CuSO4·5H2O concentration, NaCl concentration, H2SO4 concentration and current density, were discussed in detail. The results indicated that copper recovery rate increased first with the increase of CuSO4·5H2O, NaCl, H2SO4 and current density and then decreased with further increasing these conditions. NaCl, H2SO4 and current density also showed a similar impact on copper purity, which also increased first and then decreased. Copper purity increased with the increase of CuSO4·5H2O. When the concentration of CuSO4·5H2O, NaCl and H2SO4 was respectively 90, 40 and 118 g/L and current density was 80 mA/cm2, copper recovery rate and purity was up to 97.32% and 99.86%, respectively. Thus, electrolysis proposes a feasible and prospective approach for waste printed circuit boards recycle, even for e-waste, though more researches are needed for industrial application.
The relationship between the improvement of sludge dewaterability and variation of organic matters has been studied in the process of sludge pre-conditioning with modified cinder, especially for extracellular polymeric substances (EPS) in the sludge. During the conditioning process, the decreases of total organic carbon (TOC) and soluble chemical oxygen demand (SCOD) were obviously in the supernatant especially for the acid modified cinder (ACMC), which could be attributed to the processes of adsorption and sweeping. The reduction of polysaccharide and protein in supernatant indicated that ACMC might adsorb EPS so that the tightly bound EPS (TB-EPS) decreased in sludge. In the case of ACMC addition with 24 g·L–1, SRF of the sludge decreased from 7.85 × 1012 m·kg–1 to 2.06 × 1012 m·kg–1, and the filter cake moisture decreased from 85% to 60%. The reconstruction of “floc mass” was confirmed as the main sludge conditioning mechanism. ACMC promoted the dewatering performance through the charge neutralization and adsorption bridging with the negative EPS, and provided firm and dense structure for sludge floc as skeleton builder. The passages for water quick transmitting were built to avoid collapsing during the high-pressure process.
A biofilm membrane bioreactor (BF-MBR) and a conventional membrane bioreactor (MBR) were parallelly operated for treating digested piggery wastewater. The removal performance of COD, TN, NH4+-N, TP as well as antibiotics were simultaneously studied when the hydraulic retention time (HRT) was gradually shortened from 9 d to 1 d and when the ratio of influent COD to TN was changed. The results showed that the effluent quality in both reactors was poor and unstable at an influent COD/TN ratio of 1.0±0.2. The effluent quality was significantly improved as the influent COD/TN ratio was increased to 2.3±0.5. The averaged removal rates of COD, NH4+-N, TN and TP were 92.1%, 97.1%, 35.6% and 54.2%, respectively, in the BF-MBR, significantly higher than the corresponding values of 91.7%, 90.9%, 17.4% and 31.9% in the MBR. Analysis of 11 typical veterinary antibiotics (from the tetracycline, sulfonamide, quinolone, and macrolide families) revealed that the BF-MBR removed more antibiotics than the MBR. Although the antibiotics removal decreased with a shortened HRT, high antibiotics removals of 86.8%, 80.2% and 45.3% were observed in the BF-MBR at HRTof 5–4 d, 3–2 d and 1 d, respectively, while the corresponding values were only 83.8%, 57.0% and 25.5% in the MBR. Moreover, the BF-MBR showed a 15% higher retention rate of antibiotics and consumed 40% less alkalinity than the MBR. Results above suggest that the BF-MBR was more suitable for digested piggery wastewater treatment.
This paper studied the biofilm properties and corrosion behavior of sulfate reducing bacteria (SRB) on stainless steel 316L (SS316L) surface in circulating cooling water system with and without additives including hydroxy ethyl fork phosphonic acid (HEDP), dodecyl dimethyl benzyl ammonium chlotide (1227) and NaClO. Biochemical technique, electrochemical technology, X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM) were used. The results show that the extracellular polymeric substance (EPS) in biofilm attached on the SS316L surface mainly contain proteins and polysaccharides, the contents are 98 ug·cm-2 and 635ug·cm-2, respectively. The polysaccharides were cut by 1227 about 80%, while 55% by NaClO. The proteins were reduced by NaClO about 53%, while only 30% by 1227. The potentiodynamic polarization shows that the corrosion potential of SS316L was enhanced from -0.495 V to -0.390 V by the chemical additives, delaying the occurrence of the corrosion. And the corrosion rate was also reduced from 5.19 × 10-3 mm·a-1 to 2.42 × 10-3 mm·a-1. But NaClO still caused pitting corrosion after sterilizing the bacteria, while 1227 can form a protective film on the surface of SS316L. Though HEDP contribute to the bacteria activity, it can enhance the breakdown potential. XPS results confirmed that 1227 can change the value of C:O in the biofilm attached on metal surface, and NaClO can eliminate the existence of amidogen. This study would provide some recommendations for the selection of chemical additives in the thermal power plant.
Observed effects of metal mixtures on animals and plants often differ from the estimates, which are commonly calculated by adding up the biological responses of individual metals. This difference from additivity is commonly referred to as being a consequence of specific interactions between metals. The science of how to quantify metal interactions and whether to include them in risk assessment models is in its infancy. This review summarizes the existing predictive tools for evaluating the combined toxicity of metals present in mixtures and indicates the advantages and disadvantages of each method. We intend to provide eco-toxicologists with background information on how to make good use of the tools and how to advance the methods for assessing toxicity of metal mixtures. It is concluded that statistically significant deviations from additivity are not necessarily biologically relevant. Incorporation of interactions between metals in a model does not on forehand mean that the model is more accurate than a model developed based on additivity only. It is recommended to first use a relatively simple method for effect prediction of uninvestigated metal mixtures. To improve the reliability of toxicity modeling for metal mixtures, further efforts should focus on balancing the relationship between the significance of statistics and the biological meaning, and unraveling the toxicity mechanisms of metals and their mixtures.
