Mercury flows in large-scale gold production and implications for Hg pollution control

Large-scale gold production(LSGP) is one of the five convention-related atmospheric mercury(Hg) emission sources in the Minamata Convention on Mercury. However, field experiments on Hg flows of the whole process of LSGP are limited. To identify the atmospheric Hg emission points and understand Hg emission characteristics of LSGP, Hg flows in two gold smelters were studied. Overall atmospheric Hg emissions accounted for 10%–17% of total Hg outputs and the Hg emission factors for all processes were 7.6–9.6 kg/ton. There were three dominant atmospheric Hg emission points in the studied gold smelters, including the exhaust gas of the roasting process, exhaust gas from the environmental fog collection stack and exhaust gas from the converter of the refining process. Atmospheric Hg emissions from the roasting process only accounted for 16%–29% of total emissions and the rest were emitted from the refining process. The overall Hg speciation profile(gaseous elemental Hg/gaseous oxidized Hg/particulate-bound Hg) for LSGP was 34.1/57.1/8.8. The dominant Hg output byproducts included waste acid, sulfuric acid and cyanide leaching residue. Total Hg outputs from these three byproducts were 80% in smelter A and 84% in smelter B. Our study indicated that previous atmospheric Hg emissions from large-scale gold production might have been overestimated.Hg emission control in LSGP is not especially urgent in China compared to other significant emission sources(e.g., cement plants). Instead, LSGP is a potential Hg release source due to the high Hg output proportions to acid and sludge.     

Relationship between physicochemical properties and dewaterability of hydrothermal sludge derived from different source

Sewage sludge (SS) and deinking sludge (DS) were used to comparatively study the hydrothermal dewatering of sludge with different components. For a better overview, an insight into the relationship between physicochemical properties and dewaterability of hydrothermal sludge was provided. Results found that not all kinds of sludge were suitably conditioned by hydrothermal treatment (HT) in term of the elevation of dewaterability. Higher hydrothermal temperature tended to enhance the dewaterability of SS rather than DS, which was supported by the variation of their physicochemical properties (including water distribution, bonding energy, extracellular polymeric substance (EPS), particles size, acid functional groups and zeta potential in this study). In addition, the changes in surface morphology suggested that the reverse effect of HT on sludge dewaterability was mainly due to their dewatering behavior. For SS, the destruction of EPS structure leaded to the release of bound water, thereby strengthening sludge dewatering. Conversely, “Bridging effect” generated by lignocellulose in DS was beneficial for sludge dewatering; however, the increasing hydrothermal temperature degraded part of lignocellulose and weakened “bridging effect”, finally resulting in worse dewaterability of DS.     

Seasonal variation and size distribution of biogenic secondary organic aerosols at urban and continental background sites of China

Size-resolved biogenic secondary organic aerosols(BSOA) derived from isoprene and monoterpene photooxidation in Qinghai Lake, Tibetan Plateau(a continental background site) and five cities of China were measured using gas chromatography/mass spectrometry(GC/MS). Concentrations of the determined BSOA are higher in the cities than in the background and are also higher in summer than in winter. Moreover, strong positive correlations(R2= 0.44–0.90) between BSOA and sulfate were found at the six sites,suggesting that anthropogenic pollution(i.e., sulfate) could enhance SOA formation,because sulfate provides a surface favorable for acid-catalyzed formation of BSOA. Size distribution measurements showed that most of the determined SOA tracers are enriched in the fine mode( 3.3 μm) except for cis-pinic and cis-pinonic acids, both presented a comparable mass in the fine and coarse( 3.3 μm) modes, respectively. Mass ratio of oxidation products derived from isoprene to those from monoterpene in the five urban regions during summer are much less than those in Qinghai Lake region. In addition, in the five urban regions relative abundances of monoterpene oxidation products to SOA are much higher than those of isoprene. Such phenomena suggest that BSOA derived from monoterpenes are more abundant than those from isoprene in Chinese urban areas.     

基于环境温度传感的节水调节器设计研究

传统节水调节器使用半自动机械控制,能够实现部分水资源节约,但在新疆等温度交替变化明显地区,无法根据温度变化情况实现自动控制节水调节,从而造成部分水资源浪费。为此提出基于环境温度传感的节水调节器设计。采用concise结构设计,在阻挠蝶板上增加环境温度传感装置,依托沿程阻力系数判定温度传感器节水调节系数ξ,通过不同ξ值的反馈,针对性的采取相应调节措施;使用调节Accurate检验机制,对温度变化幅度k进行测定,确定调节幅度有效取值,完成节水调节器的自动调节控制,实现基于环境温度传感的节水调节器设计。     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Microbiological characteristics in a zero-valent iron reactive barrier

Zero-valent iron (Fe⁰)-based permeable reactive barriertreatment has been generating great interest for passivegroundwater remediation, yet few studies have paid particularattention to the microbial activity and characteristics withinand in the vicinity of the Fe⁰-barrier matrix. The presentstudy was undertaken to evaluate the microbial population andcommunity composition in the reducing zone of influence byFe⁰ corrosion in the barrier at the Oak Ridge Y-12 Plantsite. Both phospholipid fatty acids and DNA analyses were usedto determine the total microbial population and microbialfunctional groups, including sulfate-reducing bacteria,denitrifying bacteria, and methanogens, in groundwater andsoil/iron core samples. A diverse microbial community wasidentified in the strongly reducing Fe⁰ environment despitea relatively high pH condition within the Fe⁰ barrier (up topH 10). In comparison with those found in the backgroundsoil/groundwater samples, the enhanced microbial populationranged from 1 to 3 orders of magnitude and appeared to increase from upgradient of the barrier to downgradient soil. Inaddition, microbial community composition appeared to change overtime, and the bacterial types of microorganismsincreased consistently as the barrier aged. DNA analysisindicated the presence of sulfate-reducing and denitrifyingbacteria in the barrier and its surrounding soil. However, theactivity of methanogens was found to be relatively low,presumably as a result of the competition by sulfate/metal-reducing bacteria and denitrifying bacteria because of the unlimited availability of sulfate and nitrate in the site groundwater. Results of this study provide evidenceof a diverse microbial population within and in the vicinity ofthe iron barrier, although the important roles of microbial activity, either beneficially or detrimentally, on the longevityand enduring efficiency of the Fe⁰ barriers are yet to be evaluated.     

螯合树脂在线富集——火焰原子吸收光度法测定水中微量Cu,Pb,Zn,Cd

对螯合树脂在线富集，火焰原子吸收光度法进行了条件试验。试验证实方法对Ｃｕ、Ｐｂ、Ｚｎ、Ｃｄ４个元素检出浓度可达μｇ／Ｌ级，校准曲线性、样品重现性及准确度可满足测定要求。     

Reduction of SO2 emissions by ammonia gas during unstaged combustion

The reduction of SO₂ by the addition of ammonia gas has been studied in a 2 m high fluidized bed combustor having a 30 cm static bed height and a freeboard height of 170 cm. Ammonia gas was injected at 52 cm above the distributor where the temperature is ca. 700° C by an uncooled stainless steel tube injector. Experiments were carried out to investigate the effects of amminia gas injection on sulphur dioxide emissions at unstaged conditions of: (i) excess air level, (ii) NH₃:SO₂ molar ratio, (iii) fluidizing velocity and (iv) bed height.A maximum reduction of 75% in SO₂ emissions was found at 40% excess air, at an NH₃:SO₂ molar ratio of 5.4. The onset of SO₂ reduction occurred at an NH₃:SO₂ ratio of 1.5 However, the most effective ratio was found to be between 3 and 5. Fluidizing velocity and bed height were also found to have significant influence on SO₂ reduction.It is difficult to determine how the SO₂ reduction varied with operating conditions. When ammonia is added in the main combustor zone, the temperature is much higher than that required for the occurrence of sulphur dioxide-ammonia and sulphur trioxide-ammonia reactions. However, this paper points out the significance of ammonia addition in the reduction of sulphur dioxide.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Modeling photocatalytic destruction of the organic contaminants in continuous stir flow reactor

Thin-film technique is becoming an industry standard for the preparation of TiO₂-based photocatalyst for organic destruction. The catalyst provides several advantages over the conventional powder TiO₂ in the treatment of wastewater and groundwater. In this study, a continuous stir flow reactor model is developed capable of describing the photocatalytic process. The model incorporates the following fundamental mechanisms: adsorption, diffusion, liquid-film transfer, UV attenuation, and photocatalytic reaction. All of the simulation results indicate that there exists a highly nonlinear relation between each of these parameters and the destruction rate. Various incident light intensities also are incorporated to simulate the energy efficiency. The simulations illustrate that the photocatalytic model can be used to elucidate the effect of process variables. It is also possible to “custom-design” a catalyst for the treatment of a particular waste stream.