Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

Dynamics of growth and seed production in the Siberian stone pine: The level and pattern of variation in characters

A statistical analysis of interannual variation in a set of vegetative and generative characters over 13 years has been performed to characterize the growth and seed production dynamics of the Siberian stone pine (Pinus sibirica Du Tour) in the southeast of the forest zone in western Siberia. The results have shown that the range of fluctuations in most of vegetative characters is ordinary and their distribution is close to normal. The range of fluctuations in many generative characters is enormous (from 0 to +∞), and the distribution of their values is usually skewed, with low values being recorded several times more frequently than high values. Most variable are the proportion of abortive cones and other characters that are determined mainly in the spring of the pollination year. These characters account for a very high level of variation in the total seed production.     

江汉平原粮食开发必须走优质高产高效的道路

分析江汉平原粮食生产的优势与问题,运用商品经济的观念,提出改革开放新形势下加快江汉平原粮食开发的设想,即依托市场,按照价值规律,科学地调整种植业比例和粮食种类结构,发展优质品种,扩大优化模式及采用高新技术等,通过优质、高产、高效,促进江汉平原粮食生产的发展。     

Toxicological Assessment of Wastewater and Runoff from the Baikal Pulp and Paper Mill

Russian Journal of Ecology -     

项目决策阶段清洁生产分析方法的研究

企业在建设项目决策时就应该按照清洁生产的原则，从源头控制污染。提出了在项目决策中，应从产品选择、工艺路线选择、主要设备选型和节能降耗4个方面进行清洁生产的分析方法，通过此分析方法的应用，可以避免项目决策中的环境失误和降低企业的环境风险。     

Geochemical characteristics of surficial sediments in a tropical estuary, south-west India

Geochemical characteristics of surficial sediments in the Panangad region of Cochin estuary, the largest brackish-water humid ecosystem in the south-west coast of India, were analysed. Temporal variations in nutrient stoichiometry, seasonal characteristics of redox elements Fe and S, and the phosphorus geochemistry were employed for the purpose. The stoichiometric analysis pointed towards autochthonous origin of organic matter, possibility of nitrogen limitation, and allochthonous modification of redox conditions. Seasonal variations were not statistically significant for all the geochemical parameters, whereas significant spatial variations were observed with lower values at sandy stations, suggesting that the texture of the sediments is the main factor influencing the sediment geochemistry. Significant inter-relations between the geochemical parameters also suggest a common control mechanism. Based on these geochemical characteristics, the study region can be effectively categorized into two distinct zones, viz. (1) erosion and transportation and (2) deposition zones.     

Deep chlorophyll maximum distribution in the central Tyrrhenian Sea described by a towed undulating vehicle

The towed undulating vehicle (TUV), named SARAGO, was used for two fine-scale surveys between the Italian and the Sardinian coasts during the Astraea 2 cruise (6-7 and 26-27 September 1995), studying the deep chlorophyll maximum distribution. SARAGO sections identify a sub-surface doming with higher chlorophyll a and primary production concentrations in the upwelling area of a cyclonic gyre region, detected by sea-surface temperature images. In the first section, the cyclone presents a double doming, in density and salinity, with shallower and concentrated patches of chlorophyll a for about 2 miles. Twenty days later, the second section shows that the gyre changes shape and extension, showing a single doming with higher primary production and chlorophyll a concentrations, distributed over a large area of about 40 nautical miles. SARAGO allows analysis of this high-variability phenomenon (cyclonic gyre) and allows concentrated patches (2 nm) to be identified, thus proving the importance of TUVs in the study of mesoscale processes.     

硫化亚铁处理含砷废水中砷的形态变化

本文对用硫化亚铁处理含砷废水时，在气相、液相和固相中砷的形态进行了研究结果表明，在气相中无ＡａＨ３，但在Ａｓ（Ｖ）废水的液相中有Ａｓ（Ｖ）和Ａｓ（Ⅲ）共同存在，在固相中有Ａｓ（０），ＦｅＡｓＯ４（ＦｅＡｓＯ３），Ａｓ２Ｓ３（Ａｓ２Ｓ５）和吸附砷，砷的形态变化表明，硫化亚铁处理含砷废水能取得良好的效果，是沉淀、沉淀转化、氧化还原、吸附共沉淀和中和五种反应共同作用的结果。     

铁铜双金属有机骨架MIL-101(Fe,Cu)活化双氧水降解染料性能

针对非均相芬顿传质效率低和Fe（Ⅲ）Fe（Ⅱ）转化慢导致活性低等问题,采用溶剂热法制备铁铜双金属有机骨架材料[MIL-101（Fe,Cu）],并研究了材料界面性质、催化降解染料（亚甲基蓝）性能以及活化催化机制.结果表明,MIL-101（Fe,Cu）晶体结构完整且呈三维八面体形状;比表面积和平均孔径分别为667.2 m² ·g^-1和1.9 nm,可充分暴露反应活性位点.MIL-101（Fe,Cu）在广谱pH范围可活化H₂ O₂高效降解亚甲基蓝.当pH=5、反应20 min,MIL-101（Fe,Cu）/H₂ O₂对20 mg ·L^-1亚甲基蓝的去除率为100%,较MIL-101（Fe）/H₂O₂和单独H₂ O₂分别提高43.1%和88.9%.自由基猝灭实验与反应前后铁和铜价态变化结果表明,羟基自由基（·OH）是MIL-101（Fe,Cu）/H₂ O₂催化降解亚甲基蓝的主要活性物种;Cu（Ⅱ）掺杂引入新的活性位点,且Cu（Ⅱ）/Cu（Ⅰ）循环和Fe（Ⅲ）/Fe（Ⅱ）循环可协同产生·OH,进而提高催化效率.MIL-101（Fe,Cu）作为新型非均相类芬顿催化剂,无需复杂pH调节即可获得良好催化效果,在工业废水处理上具有较好地应用前景.     

MnO2/Al2O3催化剂-微气泡臭氧体系催化降解喹啉及其机理

制备了纳米MnO₂,并以Al₂O₃为载体制备了掺杂型MnO₂/Al₂O₃颗粒催化剂.催化剂焙烧温度和时间分别为500℃和4 h、MnO₂质量分数为8%时,催化剂具有最高的臭氧催化氧化活性.SEM分析表明,纳米MnO₂均匀分布于Al₂O₃载体表面.MnO₂/Al₂O₃催化剂的比表面积（BET）为183.22 m²·g^-1,平均孔容为0.27 cm³·g^-1,平均孔径为4.87 nm.建立了MnO₂/Al₂O₃催化剂-微气泡臭氧催化反应体系,研究了该体系对喹啉的降解去除效果及其机理.臭氧微气泡的平均粒径为61.7 μm.微气泡臭氧投量为30 mg·L^-1时,反应60 min后喹啉去除率能达到95%以上;反应20 min后,MnO₂/Al₂O₃催化剂-微气泡臭氧体系对实际煤化工废水二级出水的TOC去除率可达到55%以上.以叔丁醇作为分子探针,证明了羟基自由基（·OH）氧化作用在臭氧微气泡催化氧化体系中对喹啉的降解起到主导作用.