Fluoride removal from secondary effluent of the graphite industry using electrodialysis: Optimization with response surface methodology

RSM was utilized to optimize and model influential parameters on fluoride removal. Regression models involving independent variables and main response were developed. Interactive effects and optimum of process factors were illuminated and determined. Fluoride removal efficiency of 99.69% was observed in optimal process conditions. Response surface methodology was utilized to model and optimize the operational variables for defluoridation using an electrodialysis process as the treatment of secondary effluent of the graphite industry. Experiments were conducted using a Box-Behnken surface statistical design in order to evaluate the effects and the interaction of the influential variables including the operational voltage, initial fluoride concentration and flow rate. The regression models for defluoridation and energy consumption responses were statistically validated using analysis of variance (ANOVA); high coefficient of determination values (R² = 0.9772 and R² = 0.9814; respectively) were obtained. The quadratic model exhibited high reproducibility and a good fit of the experimental data. The optimum values of the initial fluoride concentration, voltage and flow rate were found to be 13.9 mg/L, 13.4 V, 102.5 L/h, respectively. A fluoride removal efficiency of 99.69% was observed under optimum conditions for the treatment of the secondary effluent of the graphite industry.     

Wastewater-nitrogen removal using polylactic acid/starch as carbon source: Optimization of operating parameters using response surface methodology

The use of PLA/starch blends for nitrogen removal was achieved. The influence of different operating parameters on responses was verified using RSM. The conditions for desired responses were successfully optimized simultaneously. Blends material may have a promising application prospect in the future. Nitrogen removal from ammonium-containing wastewater was conducted using polylactic acid (PLA)/starch blends as carbon source and carrier for functional bacteria. The exclusive and interactive influences of operating parameters (i.e., temperature, pH, stirring rate, and PLA-to-starch ratio (PLA proportion)) on nitrification (Y₁), denitrification (Y₂), and COD release rates (Y₃) were investigated through response surface methodology. Experimental results indicated that nitrogen removal could be successfully achieved in the PLA/starch blends through simultaneous nitrification and denitrification. The carbon release rate of the blends was controllable. The sensitivity of Y₁, Y₂, and Y₃ to different operating parameters also differed. The sequence for each response was as follows: for Y₁, pH>stirring rate>PLA proportion>temperature; for Y₂, pH>PLA proportion>temperature>stirring rate; and for Y₃, stirring rate>pH>PLA proportion>temperature. In this study, the following optimum conditions were observed: temperature, 32.0°C; pH 7.7; stirring rate, 200.0 r·min^-1; and PLA proportion, 0.4. Under these conditions, Y₁, Y₂, and Y₃ were 134.0 μg-N·g-blend^-1·h^-1, 160.9 μg-N·g-blend^-1·h^-1, and 7.6 × 10³ μg-O·g-blend^-1·h^-1, respectively. These results suggested that the PLA/starch blends may be an ideal packing material for nitrogen removal.     

Optimization of methyl orange removal from aqueous solution by response surface methodology using spent tea leaves as adsorbent

The effective disposal of redundant tea waste is crucial to environmental protection and comprehensive utilization of trash resources. In this work, the removal of methyl orange （MO） from aqueous solution using spent tea leaves as the sorbent was investigated in a batch experiment. First, the effects of various parameters such as temperature, adsorption time, dose of spent tea leaves, and initial concentration of MO were investigated. Then, the response surface methodology （RSM）, based on Box- Behnken design, was employed to obtain the optimum adsorption conditions. The optimal conditions could be obtained at an initial concentration of MO of 9.75 mg·L-1, temperature of 35.3℃, contact time of 63.8 min, and an adsorbent dosage 3.90 g· L-1. Under the optimized condi- tions, the maximal removal of MO was 58.2%. The results indicate that spent tea leaves could be used as an effective and economical adsorbent in the removal of MO from aqueous solution.     

Optimization of the O3/H2O2 process with response surface methodology for pretreatment of mother liquor of gas field wastewater

• Real ML-GFW with high salinity and high organics was degraded by O₃/H₂O₂ process. • Successful optimization of operation conditions was attained using RSM based on CCD. • Single-factor experiments in advance ensured optimal experimental conditions. • The satisfactory removal efficiency of TOC was achieved in spite of high salinity. • The initial pH plays the most significant role in the degradation of ML-GFW. The present study reports the use of the O₃/H₂O₂ process in the pretreatment of the mother liquor of gas field wastewater (ML-GFW), obtained from the multi-effect distillation treatment of the gas field wastewater. The range of optimal operation conditions was obtained by single-factor experiments. Response surface methodology (RSM) based on the central composite design (CCD) was used for the optimization procedure. A regression model with Total organic carbon (TOC) removal efficiency as the response value was established (R² = 0.9865). The three key factors were arranged according to their significance as: pH>H₂O₂ dosage>ozone flow rate. The model predicted that the best operation conditions could be obtained at a pH of 10.9, an ozone flow rate of 0.8 L/min, and H₂O₂ dosage of 6.2 mL. The dosing ratio of ozone was calculated to be 9.84 mg O₃/mg TOC. The maximum removal efficiency predicted was 75.9%, while the measured value was 72.3%. The relative deviation was found to be in an acceptable range. The ozone utilization and free radical quenching experiments showed that the addition of H₂O₂ promoted the decomposition of ozone to produce hydroxyl radicals (·OH). This also improved the ozone utilization efficiency. Gas chromatography-mass spectrometry (GC-MS) analysis showed that most of the organic matters in ML-GFW were degraded, while some residuals needed further treatment. This study provided the data and the necessary technical supports for further research on the treatment of ML-GFW.     

Adsorption property of direct fast black onto acid-thermal modified sepiolite and optimization of adsorption conditions using Box-Behnken response surface methodology

The adsorption of direct fast black onto acid-thermal modified sepiolite was investigated. Batch adsorption experiments were performed to evaluate the influences of experimental parameters such as initial dye concentration, initial solution pH and adsorbent dosage on the adsorption process. The three-factor and three-level Box-Behnken response surface methodology (RSM) was utilized for modeling and optimization of the adsorption conditions for direct fast black onto the acid-thermal modified sepiolite. The raw sepiolite was converted to acid-thermal modified sepiolite, and changes in the fourier transform infrared spectrum (FTIR) adsorption bands of the sample were noted at 3435 cm^-1 and 1427 cm^-1. The zeolitic water disappeared and the purity of sepiolite was improved by acid-thermal modification. The decolorization rate of direct fast black adsorbed increased from 68.2% to 98.9% on acid-thermal modified sepiolite as the initial solution pH decreased from 10 to 2. When the adsorbent dosage reached to 2.5 g·L^-1, 2.0 g·L^-1, 1.5 g·L^-1 and 1.0 g·L^-1, the decolorization rate was 90.3%, 86.7%, 61.0% and 29.8%, respectively. When initial dye concentration increased from 25 to 200 mg·L^-1, the decolorization rate decreased from 91.9% to 60.0%. The RSM results showed that the interaction between adsorbent dosage and pH to be a significant factor. The optimum conditions were as follows: the adsorbent dosage 1.99 g·L^-1, pH 4.22, and reaction time 5.2 h. Under these conditions, the decolorization rate was 95.1%. The three dimensional fluorescence spectra of direct fast black before and after treatment showed that the direct fast black was almost all adsorbed by the acid-thermal modified sepiolite.     

响应面法优化O_3/H_2O_2/UV工艺降解1,2,4-三氯苯

研究了O3/H2O2/UV臭氧光催化工艺对水中TCB的降解效果,考察了TCB初始浓度、O3转化率、H2O2投加量及pH值对TCB降解效果的影响及其动力学分析,并通过响应面分析法对实验条件进行了优化组合.结果表明,O3/H2O2/UV对TCB的降解均遵循准一级反应动力学,其中条件优化组合后的反应动力学方程为y=0.0219x-0.0127,准一级反应速率常数为0.0219 min-1,所得线性相关系数为0.983.响应面分析结果表明,在TCB初始浓度0.3 mg.L-1、pH=10.1、H2O2投加量0.33 mmol.L-1、O3转化率99.75%的最优工艺组合条件下,TCB的3次平均去除率为94.2%,与预测值95.0%吻合度较高.     

响应面法建立不同经口介质中邻苯二甲酸酯生物有效性预测模型及相关因素

运用响应面法对不同消化基质下邻苯二甲酸酯(PAEs)生物有效性的相关因素进行筛选建立预测模型,并对主要因素设定值进行分析.研究表明,3种模型中因变量与自变量之间的相关性较好(土壤:R2=0.959;农作物及植物:R2=0.973;脂肪:R2=0.862),模型拟合度较高.通过多次试验模拟,初步认为在土壤消化基质中,设置人体摄入PAEs经口摄入浓度为10μg·g-1,基质质量为0.4g,pH值约为7时,生物吸收量最高.在植物源基质下,污染物浓度在10—11μg·g-1,消化时间在6—7h,基质质量为0.4g为生物吸收量最高.脂肪源中,基质质量在0.4g,污染物浓度在10μg·g-1,脂肪量在10%—11%时,PAEs生物吸收量最高.研究通过重复试验,充分体现了该模型的准确性,及设定条件的可靠性.但本研究仅考虑摄入介质相对单一,污染物化合形态等未在考虑范围内,在后期研究中将补充试验.     

Chromium recovery from solid leather waste by chemical treatment and optimisation by response surface methodology

The leather industry uses conventional tanning methods which cause environmental pollution due mainly to the presence of chromium. This study suggests a treatment for solid leather waste containing chromium as an ecological alternative to the pollution generated by tanneries. The study uses an original approach to the optimisation of chromium recovery by mathematical and statistical treatment of the experimental data. Several factors that influence recovery, such as temperature, concentration, time and solid/liquid ratio through acid and basic hydrolysis were analysed with the aid of experimental design. Tanning liquor was obtained by adjusting pH, alkalinity and concentration when hydrolysis finished. An appropriate response surface model was constructed using alkaline hydrolysis experiments with sodium hydroxide, leading to conditions for maximum recovery of Cr₂O₃. The optimal NaOH concentration (1.58%), temperature (63.7 °C), time (3 h) and solid/liquid ratio (1/70 g·mL^?1) were established. The results indicate that sodium hydroxide as an hydrolysis agent is a highly efficient means of recovering chromium from solid leather waste in order to produce tanning liquor.     

Metal removal with two biochars made from municipal organic waste: adsorptive characterization and surface complexation modeling

The adsorptive characteristics of biochar produced from garden green waste (S-char) and a mixture of food waste and garden green waste (FS-char) were investigated. Adsorption of Cu²⁺, Zn²⁺, and Mn²⁺ onto the two biochars reached equilibrium within 48 hours. The metal adsorption was effectively described by the pseudo-second-order kinetic and Freundlich isotherm models which suggest heterogeneous chemisorption. The initial solution pH influenced adsorption of Zn²⁺ and Mn²⁺ but not of Cu²⁺. Simulation via a surface complexation model showed that the fraction of XOCu⁺ adsorbed onto biochar was increased with increasing pH until it reached the adsorption maximum at pH 8.5, while the endpoint for the maximum of XOMn⁺ was higher than pH 12.     

Preparation of a permanent magnetic hypercrosslinked resin and assessment of its ability to remove organic micropollutants from drinking water

A rapid and effective method based on a novel permanent magnetic hypercrosslinked resin W150 was proposed for the removal of organic micropollutants in drinking water. W150 was prepared by suspension and post-crosslinking reaction and found to possess a high specific surface area of 1149.7 m²·g^-1, a small particle size of 50 μm to 100 μm, and a saturation magnetization as high as 8 emu·g^-1. W150 was used to eliminate nitrofurazone (NFZ) and oxytetracycline (OTC) from drinking water compared with commercial adsorbents XAD-4 and F400D. The adsorption kinetics of NFZ and OTC onto the three adsorbents well fitted the pseudo-second-order equation (r>0.972), and the adsorption isotherms were all well described by the Freundlich equation (r>0.851). Results showed that the reduction in adsorbent size and the enlargement in sorbent pores both accelerated adsorption. Moreover, the effect of particle size on adsorption was more significant than that of pore width. Given that the smallest particle size and the highest specific surface area were possessed by W150, it had the fastest adsorption kinetics and largest adsorption capacity for NFZ (180 mg·g^-1) and OTC (200 mg·g^-1). For the adsorbents with dominant micropores, the sorption of large-sized adsorbates decreased because of the inaccessible micropores. The solution pH and ionic strength also influenced adsorption.     

Optimization of an artificial neural network for identifying fishing set positions from VMS data: An example from the Peruvian anchovy purse seine fishery

The spatial behavior of numerous fishing fleets is nowadays well documented thanks to satellite Vessel Monitoring Systems (VMS). Vessel positions are recorded on a frequent and regular basis which opens promising perspectives for improving fishing effort estimation and management. However, no specific information is provided on whether the vessel is fishing or not. To answer that question, existing works on VMS data usually apply simple criteria (e.g. threshold on speed). Those simple criteria generally focus in detecting true positives (a true fishing set detected as a fishing set); conversely, estimation errors are given no attention. For our case study, the Peruvian anchovy fishery, those criteria overestimate the total number of fishing sets by 182%. To overcome this problem an artificial neural network (ANN) approach is presented here. In order to set both the optimal parameterization and use “rules” for this ANN, we perform an extensive sensitivity analysis on the optimization of (1) the internal structure and training algorithm of the ANN and (2) the “rules” used for choosing both the relative size and the composition of the databases (DBs) used for training and inferring with the ANN. The “optimized” ANN greatly improves the estimates of the number and location of fishing events. For our case study, ANN reduces the total estimation error on the number of fishing sets to 1% (in average) and obtains 76% of true positives. This spatially explicit information on effort, provided with error estimation, should greatly reduce misleading interpretations of catch per unit effort and thus significantly improve the adaptive management of fisheries. While fitted on Peruvian anchovy fishery data, this type of neural network approach has wider potential and could be implemented in any fishery relying on both VMS and at-sea observer data. In order to increase the accuracy of the ANN results, we also suggest some criteria for improving sampling design by at-sea observers and VMS data.     

Modelling spatial distribution of hard bottom benthic communities and their functional response to environmental parameters

In this study we analyzed and modelled spatial distribution of hard bottom benthic communities in the Lagoon of Venice, and used the model to derive functional response of these communities to changing environmental conditions.     

溶藻菌对受污染水源水除藻及脱氮特性研究

针对我国水源地藻类污染日趋严重等问题,利用前期分离获得的溶藻菌Streptomyces sp.HJC-D1研究固定化微生物技术强化污染水源水除藻以及脱氮性能。结果表明,对照组和试验组的水体叶绿素a平均去除率分别为（71.66±5.35）%和（80.94±4.36）%,NH4＋—N的平均去除率为（77.76±2.83）%和（72.36±3.18）%,而高锰酸盐指数（CODMn）平均去除率为（24.99±1.52）%和（18.74±1.38）%;不同曝气条件的影响研究发现,曝气/停曝时间比2：4、曝气量60 L.h-1工况下,系统CODMn和NH4＋—N去除率均有所提高,相比对照组NO3-—N积累更为明显;水力停留时间（HRT）变化对系统NH4＋—N、CODMn等的去除影响不大,但缩短HRT时叶绿素a去除率有所降低;分析反应器内填料表面微生物相发现,试验组填料表面有溶藻菌富集,推测对照组除藻主要通过填料对藻类的吸附去除,而试验组则是藻类吸附在填料表面后通过溶藻微生物实现藻类去除。     

The application of artificial neural networks to flow and phosphorus dynamics in small streams on the Boreal Plain,with emphasis on the role of wetlands

Historically, management strategies in Canada's boreal forest have focused on forest polygons and terrestrial biodiversity to address ecological considerations in forest management. The Forest Watershed and Riparian Disturbance (FORWARD) project examines the problem from a watershed perspective rather than a forest polygon viewpoint. The main objective of this study was to devise an artificial neural network (ANN) modeling tool that can predict flow and total phosphorus (TP) concentration for ungauged watersheds (where daily flow is not monitored). This dictates that all inputs should be easily accessed via a public domain database, like the Environment Canada weather database, without the need to install flow gauges in each modeled watershed. Daily flow and TP concentration for two of the project watersheds were modeled using ANNs. The two watersheds (1A Creek, 5.1 km² and Willow Creek, 15.6 km²) were chosen to reflect variations in wetland area and composition in the study area. Flow was modeled with a feed-forward multilayer perceptron ANN trained with the error back-propagation algorithm. Simulated values for flow were then used, as inputs, to model TP concentration using the same neural networks algorithm. One hidden layer with three slabs; each operating with a different activation function was utilized to simulate the conceptual differences between base flow, snowmelt, and storm events. Time domain analysis was conducted to identify possible model time-lagged inputs reflecting the time dependency of the modeled variables. Spectral analysis was used to address data hystereses. Our results highlight the capabilities of ANN in modeling complex ecosystems and highly correlated variables. Results also indicated that more research towards the phosphorus dynamics in wetlands is required to better represent the impact of wetland area and composition on the water-phase phosphorus in ANN modeling.     

新乡市地表水中多环芳烃的分布特征及生态风险

利用GC-MS测定了新乡市地表水中15种多环芳烃(PAHs)的含量,分析了其组成特征,并通过安全阈值(MOS10)法评价了新乡市地表水中PAHs的生态风险.结果表明,新乡市地表水中PAHs的含量为369—4248 ng·L,与国内其他河流相比,污染水平较高.PAHs的组成以3环和4环为主,分别占总量的41.3%和40.3%.新乡市地表水中单种PAHs对水生生物的生态风险大小依次为蒽(Ant)菲(Phe)芘(Pyr)苯并[a]芘(Ba P)荧蒽(Flua)芴(Flu)苊(Ace),其中Ant和Phe的暴露浓度超过影响10%水生生物的概率分别为30.2%和10.4%,具有潜在生态风险;Ace、Flu、Flua、Pyr和Ba P的暴露浓度超过影响10%的水生生物的概率分别为0.85%、1.96%、4.26%、6.71%和5.69%,生态风险较低.联合生态风险评价结果表明,新乡市地表水中∑PAH7等效浓度超过影响10%水生生物的概率为43.7%,大于任何单种PAHs对水生生物的生态风险,主要河流的生态风险从大到小依次为金堤河(56.6%)共产主义渠(43.0%)天然文岩渠(16.4%).     

森林新近凋落叶溶出DOM的性质及其对菲增溶作用的影响

凋落叶作为森林凋落物的主要组成部分,其溶出的大量有机质也是森林土壤可溶性有机质（DOM）的主要来源之一。研究森林凋落叶溶出DOM对PAHs增溶作用的影响有利于合理预测及评价森林土壤中PAHs的环境行为和生态风险。本研究采集了南亚热带常绿阔叶人工林的4种常见树种--尾叶桉（Eucalyptus urophylla）、木荷（Schima superba）、大叶相思（Acacia auriculiformis）和湿地松（Pinus elliottii）的新近凋落叶为试验材料,研究其DOM含量、组成与性质,对比分析了不同凋落叶DOM对菲的増溶作用及其与DOM性质的相关关系。结果表明,4种凋落叶的可溶性有机碳（DOC）质量分数在C 11.61~36.25 mg·g-1之间,其中尾叶桉的含量最大,湿地松最小。尾叶桉和木荷DOM的主要组分是可溶性糖（SS）和可溶性酚（SP）,两者总C量占DOC的比例超过47%,而大叶相思和湿地松中SS和SP两者总量所占比例均低于30%。另外,4种凋落叶DOM的质量分数（以C计）与其电导率的线性关系图中有明显转折点,说明它们均具有表面活性剂的性质。凋落叶DOM在临界胶束浓度（CMC）之上对菲具有不同程度的増溶作用,其与菲的结合系数（logKDOC）的大小顺序为尾叶桉（3.05 L·kg-1）＞木荷（3.02 L·kg-1）＞大叶相思（2.79 L·kg-1）＞湿地松（2.54 L·kg-1）,这表明尾叶桉和木荷DOM的增溶作用明显高于大叶相思和湿地松DOM。经分析表明,logKDOC与各DOM在254、280 nm处的特征紫外吸光度值（SUV-A254、SUV-A280）及其SS、SP的相对含量均呈显著正相关（p＜0.01）,与A240/A420、A254/A400比值呈显著负相关（p＜0.01）,说明DOM的芳香化程度越高,分子量越大, SS与SP所占比例越高,其对菲的増溶效果越明显。     

Loss of organic matter and nutrients from a coastal dune heath in Northwest Denmark caused by fire

The loss of organic matter and nutrients due to a natural fire in a Danish coastal dune heath system (175 ha) was studied for three heath types: dryEmpetrum nigrum heath, moistE. nigrum-Vaccinium uliginosum heath, and wetErica tetralix-Molinia coerulea heath. The highest loss of organic matter, as well as N, P and K, was found in the moist heath (67%, 68%, 20% and 25% respectively). The lowest loss was found in the wet heath (35%, 28%, 14%, and 11% respectively). The loss in the dry heath was intermediate. For the burnt heath in total, loss of organic matter, N, P and K of about 13000, 192, 10 and 6 tons respectively, was estimated. Processes of nutrient loss by fire and regeneration of nutrients are discussed.     

Modeling and optimization of Nile blue sulfate mineralization by heterogeneous fenton oxidation

Artificial neural network and response surface methodology have been used to develop a model for simulation and optimization of the removal of Nile blue sulfate by heterogeneous Fenton oxidation. Experimental data were used to train an artificial neural network model with linear transfer function at the output layer and a tangent sigmoid transfer function at the hidden layer. A Box–Behnken design was employed to assess the effects of input process parameters on the total organic carbon removal. First order kinetics and lumped kinetics models were used to describe the reaction; a high regression coefficient indicated that the latter fitted best. The formation of non-oxidizable compounds was shown by liquid chromatography–mass spectrometry.     

Ecological and health risks of DDTs and HCHs in surface water from the upper reaches of the Huaihe River

Based on the available toxicity data and the concentrations of DDTs and HCHs in surface water from the upper reaches of the Huaihe River, overlapping areas of probability density and margin of safety (MOS₁₀) were used to estimate the risk levels of DDTs and HCHs to aquatic organisms. The overlapping areas of α-HCH, γ-HCH, p,p′-DDE, p,p′-DDD, and p,p′-DDT were found to be 9.3 × 10^?5, 4.6 × 10^?3, 4.3 × 10^?2, 2.2 × 10^?2, and 4.2 × 10^?2, respectively. The risks from DDTs were higher than those from HCHs, the risk from α-HCH being the smallest. The MOS₁₀ values of α-HCH, γ-HCH, p,p′-DDE, p,p′-DDD, and p,p′-DDT were 2.6 × 10³, 97, 5.9, 15, and 8.6, respectively, i.e. greater than 1.0, indicating limited overlaps between the distributions of exposure concentrations and of toxicity data, and thus minimal ecological risk. Health risk calculations based on incremental lifetime risks for HCHs and DDTs were conducted to evaluate human cancer risk and non-carcinogenic hazard. The total cancer risks from organochlorine pesticides (OCPs) in the studied area were in the range of 10^?8–10^?7, lower than the baseline value of acceptable risk (10^?6). Non-carcinogenic hazard indices of OCPs ranging from 10^?6 to 10^?5 were much lower than the threshold values (1.0). These results suggest that the water from the upper reaches of the Huaihe River does not pose any health risk for local residents using river water as a source for drinking water.     

Review and comparison of methods to study the contribution of variables in artificial neural network models

Convinced by the predictive quality of artificial neural network (ANN) models in ecology, we have turned our interests to their explanatory capacities. Seven methods which can give the relative contribution and/or the contribution profile of the input factors were compared: (i) the ‘PaD’ (for Partial Derivatives) method consists in a calculation of the partial derivatives of the output according to the input variables; (ii) the ‘Weights’ method is a computation using the connection weights; (iii) the ‘Perturb’ method corresponds to a perturbation of the input variables; (iv) the ‘Profile’ method is a successive variation of one input variable while the others are kept constant at a fixed value; (v) the ‘classical stepwise’ method is an observation of the change in the error value when an adding (forward) or an elimination (backward) step of the input variables is operated; (vi) ‘Improved stepwise a’ uses the same principle as the classical stepwise, but the elimination of the input occurs when the network is trained, the connection weights corresponding to the input variable studied is also eliminated; (vii) ‘Improved stepwise b’ involves the network being trained and fixed step by step, one input variable at its mean value to note the consequences on the error. The data tested in this study concerns the prediction of the density of brown trout spawning redds using habitat characteristics. The PaD method was found to be the most useful as it gave the most complete results, followed by the Profile method that gave the contribution profile of the input variables. The Perturb method allowed a good classification of the input parameters as well as the Weights method that has been simplified but these two methods lack stability. Next came the two improved stepwise methods (a and b) that both gave exactly the same result but the contributions were not sufficiently expressed. Finally, the classical stepwise methods gave the poorest results.