三种偶氮染料降解历程在紫外-可见光谱上的表现

本文对基本结构相似的三种偶氮染料橙黄Ⅱ、活性艳红Ｘ－３Ｂ和活性黑Ｋ－ＢＲ水溶液在铁粉还原－光氧化两步法处理中的紫外－可见光谱图作对比分析,依据其结构与特征吸收的关系,初步推测还原铁粉－光氧化法降解染料的历程。     

Chemical defense of the mint plant, Teucrium marum (Labiatae)

Summary. The mint plant, Teucrium marum (family Labiatae), sometimes called cat thyme, contains two methylcyclopentanoid monoterpenes, dolichodial and teucrein. The former compound is potently anti-insectan. It is repellent to ants (Monomorium pharaonis) and induces preening reflexes in flies (Phormia regina) and cockroaches (Periplaneta americana). Evidence is presented suggesting that dolichodial, which is presumed to be the plant's chief defensive agent, is stored in the tiny epidermal capsules that beset the leaves. It is only when the leaves are injured (and the capsules ruptured) that the leaves become repellent. Teucrein, in contrast, has no anti-insectan potency. It is present predominantly in the leaf buds, unlike dolichodial, which is present mostly in mature leaves. It is argued that teucrein is the storage compound from which dolichodial is generated during leaf development.     

施用污泥堆肥对作物和土壤的影响

污泥中的有机质、营养成分可为农业生产提供重要的有机肥源,但污泥中的重金属是制约污泥农用的重要因素,为检验污泥堆肥施用后对作物及土壤的影响,文章对污泥与稻草或木屑堆肥的产品进行了盆栽试验研究。结果表明,污泥与稻草或木屑的堆肥作为肥料施用于萝卜(Brassicacampestris)和菜心(Brassicaparachinensis),产量明显提高,部分堆肥产品增产效果优于化肥,且后效明显。堆肥施用使土壤中有机质、各养分含量增加,微生物活动增强、数量增加,然而作物和土壤中的重金属含量也有不同程度的提高。     

高含盐废水脱盐处理技术研究进展

综述了几种常见的高含盐废水脱盐处理技术的发展历程、工艺原理、优缺点及目前的研究进展,分析了热分离、膜分离、电渗析、离子交换、电吸附、微生物脱盐等方法的优缺点,展望了未来废水脱盐工艺的发展方向。指出：脱盐方法将根据各类水体的水质特点更加精细化;多种脱盐技术联合应用也是今后废水脱盐的发展方向。     

Comparative study on performances of a heat-pipe PV/T system and a heat-pipe solar water heating system

The heat-pipe solar water heating (HP-SWH) system and the heat-pipe photovoltaic/thermal (HP-PV/T) system are two practical solar systems, both of which use heat pipes to transfer heat. By selecting appropriate working fluid of the heat-pipes, these systems can be used in the cold region without being frozen. However, performances of these two solar systems are different because the HP-PV/T system can simultaneously provide electricity and heat, whereas the HP-SWH system provides heat only. In order to understand these two systems, this work presents a mathematical model for each system to study their one-day and annual performances. One-day simulation results showed that the HP-SWH system obtained more thermal energy and total energy than the HP-PV/T system while the HP-PV/T system achieved higher exergy efficiency than the HP-SWH system. Annual simulation results indicated that the HP-SWH system can heat the water to the available temperature (45°C) solely by solar energy for more than 121 days per year in typical climate regions of China, Hong Kong, Lhasa, and Beijing, while the HP-PV/T system can only work for not more than 102 days. The HP-PV/T system, however, can provide an additional electricity output of 73.019 kWh/m², 129.472 kWh/m², and 90.309 kWh/m² per unit collector area in the three regions, respectively.     

The determination and matching analysis of pinch point temperature difference in evaporator and condenser of organic rankine cycle for mixed working fluid

Exergo-economic analysis of the pinch point temperature difference (PPTD) in both evaporator and condenser of sub-critical organic Rankine cycle system (ORCs) are performed based on the first and second laws of thermodynamics. Taking mixture R13I1/R601a as a working fluid and the annual total cost per net output power Z as exergo-economic performance evaluation criterion, the effects of PPTD in evaporator ΔT_e, and the PPTD ratio of condenser to evaporator y, on the exergo-economic performance of ORCs are analyzed. Moreover, how some other parameters influence the optimal PPTD in evaporator ΔT_e,opt and the optimal PPTD ratio of condenser to evaporator y_opt are also discussed. It has been found that the exergo-economic performance of ORCs is remarkably influenced by ΔT_e and y, and there exists ΔT_e,opt and y_opt. In addition, ΔT_e,opt and y_opt are affected by heat transfer coefficient ratio of condenser to evaporator ß, the temperature of working fluid at dew point in condenser T_1a, and composition of R13I1/R601a: larger ß and T_1a lead to lower ΔT_e,opt and y_opt; by contraries, larger mass fraction of R13I1 makes ΔT_e,opt and y_opt increase, and y_opt increases linearly. The effects of the temperature of working fluid at bubble point in evaporator T_3a, mass flow rate of exhaust flue gas m_g, and inlet temperature of exhaust flue gas T_gi on ΔT_e,opt and y_opt are very slight. For comparison, three additional working fluids, namely R601a, R245fa, and 0.32R245fa/0.68R601a, are also taken into account.     

The fractionation and geochemical characteristics of rare earth elements measured in ambient size-resolved PM in an integrated iron and steelmaking industry zone

Environmental Science and Pollution Research - Improved understanding of the fractionation and geochemical characteristic of rare earth elements (REEs) from steel plant emissions is important due...     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.