Isobutylene polymerization in the presence of t-BuCl/SnCl4

Summary The effect of tert-butyl chloride in the polymerizations of isobutylene carried out in the presence of SnCl₄ in dichloromethane at temperatures-20°C and-78°C was investigated. Synthesized polyisobutylene samples showed a bimodal molecular weight distribution (MWD) and it was found that the weight content of the lowermolecular weight (LMW) fraction increased with increasing t-BuCl concentration in the polymerization mixture. The effect of ageing of the initiation mixture t-BuCl/SnCl₄ in CH₂Cl₂ prepared in advance on MWD of the PIB samples was also studied. Ageing of the initiation system supports the formation of the LMW fraction and this oily PIB is the only product of the polymerization at-20°C, .     

Nitrogen dynamics during till and no-till pasture restoration sequences in Rondônia,Brazil

The clearing of tropical rain forest in the Amazon basin has created large areas of cattle pasture that are now declining in productivity. Practices adopted by ranchers to restore productivity to degraded pastures have the potential to alter soil N availability and gaseous N losses from soils. We examined how soil inorganic N pools, net N mineralization and net nitrification rates, nitrification potential and NO and N₂O emissions from soils of a degraded pasture responded to the following restoration treatments: (1) soil tillage followed by replanting of grass and fertilization, (2) no-till application of non-selective herbicide, planting of rice, harvest followed by no-till replanting of grass and fertilization, and (3) the same no-till sequence with soybeans instead of rice. Tillage increased soil NH₄⁺ and NO₃^? pools but NH₄⁺ and NO₃^? pools remained relatively constant in the control and no-till treatments. Cumulative rates of net N mineralization and net nitrification during the first 6 months after treatment varied widely but were hightest in the tilled treatment. Emissions of NO and N₂O fluxes increased with tillage and with N fertilization. There were no clear relationships among rates of N fertilizer application, net N mineralization, net nitrification, NO, N₂O and total N oxide emissions. Our results indicate that pasture restoration sequences involving tilling and fertilizing will increase emissions of N oxides, but the magnitude of the increase is likely to differ based on timing of fertilizer application relative to the presence of plants and the magnitude of plant N demand. Emissions of N oxides appear to be decreased by the use of restoration sequences that minimize reductions in pasture grass cover.     

Frying Performance of No-<Emphasis Type="Italic">trans</Emphasis>, Low-Linolenic Acid Soybean Oils

Two extruded-expelled physically refined soybean oils with reduced contents of linolenic acid, ultra-low- linolenic acid (ULL, 1.5%) and low-linolenic acid (LL, 2.6%), and a extruded-expelled physically refined control oil (control, 5.3% linolenic acid) were evaluated by frying French fries in a commercial-like setting for 6 h day⁻¹ during 23 days. The oils became darker, increased in yellow color at the beginning, and became redder and less green throughout the process. Free fatty acids levels were not different among the oils until day 14, after which, ULL was different from the control for the remainder of frying. The conjugated dienoic acid values were greatest in the control. Generally, ULL and LL oils had lower percentages of polar compounds than did the control, providing a frying life 2 days longer than the control and ~30% increase in frying time. A trained sensory panel evaluated the French fries on days 2, 5, and 6. Buttery and potato flavors decreased, and rancid and painty flavors increased over frying time for all products. Rancid flavor was highest in the fries from the control oil. Overall, the ULL and LL oils performed better than did the control oil and ULL tended to perform better than the LL.     

Study of the polymerization of 1-octadecene with different rnetallocene catalysts

Summary 1-Octadecene (C18) was polymerized by using different metallocene catalysts. The rac-Et(Ind)₂ZrC1₂/MAO (I) and rac-Me₂Si(Ind)₂ZrC1₂/MAO (III) presented the highest activity as compared with ra-Et(2-Me-Ind)₂ZrCl₂/MAO (II) and Ph₂C(Flu)(Cp)ZrC1₂/MAO (IV) catalysts. Catalyst IV produced polymers with highest molecular weights. The microstructure of the polymers was determined by ¹³C-NMR spectroscopy. Catalyst systems I, II and III produced isotactic polymers while catalyst IV produced polymers with mainly syndiotactic structures but with large amount of stereoregular error. Received: 21 June 2002/Revised version: 4 November 2002/ Accepted: 4 November 2002     

An Extension of the Sustainability Index Definition in Water Resources Planning and Management

The sustainability index (SI) is a relatively new concept for measuring the performance of water resource systems over long time periods. Its definition is aimed at providing an indication of the integral behaviour of the system with regards to possible undesired consequences if misbalance of available and required waters occurs. SI is initially defined as a product and later reformulated as a geometric mean of performance indicators: reliability, resilience and vulnerability. As an extension of a recently published methodology to compute and use SI, in this paper we propose introducing two more indicators of system performance: (1) reliability of annual firm (safe) water as a system yield and (2) deviation of reservoir levels from corresponding rule curves. The last indicator is of particular importance if there are multi-purpose reservoirs in the system because reservoirs are the most important and sensitive regulators of the water regime within the system. We also propose a framework for assessing system performance in a systematic manner to compute SI at various locations within the system if different operating strategies are applied and, finally, how to evaluate strategies according to the resulting SI by using multi-criteria methods. A case study example from Serbia is used to illustrate the results of measuring sustainability under alternative operating scenarios for a system with three reservoirs and two diversion structures.     

Impact of Spatial Data Availability on Climate Change Prediction in the Weyib River Basin in Ethiopia

Impact of spatial data availability on the temperature and precipitation prediction characteristics of Weyib River basin in Ethiopia has been investigated using CMIP5-CanESM2 model for the RCP8.5, RCP4.5 and RCP2.6 scenarios. The objective of the present study is to characterize how future temperatures and precipitation prediction under CMIP5-CanESM2 model output varies against diverse averaged arbitrary spatial weather stations found in the basin. The statistical downscaling model tested and verified using the observed daily data for twelve, six and three averaged arbitrary spatial weather stations as well as for a single weather station was used to predict the future climate scenarios. The results revealed that the mean annual daily maximum and minimum temperature and precipitation for twelve, six and three arbitrary spatial stations have revealed an increasing trend in the upcoming periods until the end of the century. In single station analysis, the trend itself has changed from increasing trend to decreasing trend in case of maximum and minimum temperature. In case of precipitation, no visible trend has been observed in case of single station analysis. Therefore, the variation in amount and distribution of precipitation and temperature among the four averaged spatial stations in the same study area might affect the water resources and agriculture of the basin and also instead of using a single weather station to predict future climate variables for a particular study basin, it is more reliable using averages of numerous spatial weather stations data.     

An Optimization Approach for Assessing the Reliability of Rainwater Harvesting

This study was aimed at developing an optimization approach to rainwater harvesting (RWH) considering three (3) water consumption scenarios (WCS). These scenarios which include basic water need (BWN), pour flush (PF) and full plumbing connection (FPC) corresponding to 50 litres per capita per day (lpcd), 75(lpcd) and 150(lpcd) respectively were simulated for different categories of buildings. Reliability of supply was determined by first obtaining composite surplus/deficit of rainwater followed by optimizing the redistribution of surplus rainwater harvested to deficient buildings. Results showed that when total annual rainfall intercepted by roof exceeded total demand, 100% reliability of water supply was guaranteed. Reliability was found to be a linear function of storage. When reliability of supply is possible, the optimized storage bears an inverse exponential relationship to the roof plan area per capita. The relationship between surplus/deficit and roof plan area per capita follows a one-phase decay pattern. An optimal redistribution of surplus water from self-sufficient buildings to deficient ones gave an improvement in supply reliability from 64 to 87% for basic water need, 47 to 58% for pour flush and 28 to 29% for full plumbing connection.     

A Flood Forecasting Model that Considers the Impact of Hydraulic Projects by the Simulations of the Aggregate reservoir’s Retaining and Discharging

The hydraulic projects, such as reservoirs, ponds, and paddy fields, have a marked influence on the generation of floods, causing a number of difficulties where hydrological forecasting is concerned. To consider the influence of the hydraulic projects in hydrological forecasting, a modified TOPMODEL is presented in the paper, based on the simulation rules of the aggregate reservoir’s retaining and discharging (ARRD). In the new purposed model, termed as ARRD-TOPMODEL, the hydraulic projects are first aggregated as an equivalent reservoir, then the simulation rules of the aggregate reservoir’s retaining and discharging are determined, finally, the simulation rules are combined with an original TOPMODEL model calibrated using the floods not influenced by the hydraulic projects for flood forecasting. The ARRD-TOPMODEL was tested on the upstream of Wudaogou station basin in Northeast China. The results show that compared to the original model, the qualified rate (i.e., the ratio of the number of floods that meet acceptable criteria and the total number of floods) of runoff forecasting was increased from 73% to 100%. The problems that the overestimation of the runoff at beginning of flood season and after a long drought, as well as that the underestimation of the large flood in middle flood season are both solved, and the flood processes predicted by the new model are more consistent with the observed ones. All of these demonstrate that the newly developed model is superior to the original one and the simulation rules of the aggregate reservoir’s retaining and discharging are capable of accurately accounting for the influence of the hydraulic projects on the floods.     

Water Bloom Precursor Analysis Based on Two Direction S-Rough Set

In the field of water quality management, it is vital to determine the main precursory anomalies from the precursor of intricate water bloom in the context of a given area. In this paper, a water bloom precursor analysis method, based on two direction singular rough set, was proposed. This approach was produced on the basis of the different sections and pre-water bloom of water bloom precursor anomalies and characteristic of elements transferred in singular rough set. For testing the validity of two direction singular rough set application in water bloom precursor analysis, Xiangxi River, which is one of the typical tributaries of Three Gorges Reservoir in China, was selected as study area. The result showed that compared with other indexes, pH and dissolved oxygen (DO) are the most valuable indicators of water bloom in the precursory anomalies. Furthermore, regarding with water bloom precursory anomalies in Xiangxi River, most of the nutrient loading and biological community are the key indicators. Hence, this method can determine the main precursory anomaly for water bloom in the study area, which provides powerful knowledge support to water quality specialists for them to comprehensively analyze precursory anomaly so as to find out its relationship with occurrence law of water bloom.     

An Estimation of the Suspended Sediment Load Using Adaptive Network Based Fuzzy Inference System,Support Vector Machine and Artificial Neural Network Models

Sediment transport in streams and rivers takes two forms as suspended load and bed load. Suspended load comprises sand + silt + clay-sized particles that are held in suspension due to the turbulence and will only settle when the stream velocity decreases, such as when the streambed becomes flatter, or the streamflow into a pond or lake. The sources of the suspended sediments are the sediments transported from the river basin by runoff or wind and the eroded sediments of the river bed and banks. Suspended-sediment load is a key indicator for assessing the effect of land use changes, water quality studies and engineering practices in watercourses. Measuring suspended sediment in streams is real sampling and the collection process is both complex and expensive. In recent years, artificial intelligence methods have been used as a predictor for hydrological phenomenon namely to estimate the amount of suspended sediment. In this paper the abilities of Support Vector Machine (SVM), Artificial Neural Networks (ANNs) and Adaptive Network Based Fuzzy Inference System (ANFIS) models among the artificial intelligence methods have been investigated to estimate the suspended sediment load (SSL) in Ispir Bridge gauging station on Coruh River (station number: 2316). Coruh River is located in the northern east part of Turkey and it is one of the world”s the fastest, the deepest and the largest rivers of the Coruh Basin. In this study, in order to estimate the suspended sediment load, different combinations of the streamflow and the SSL were used as the model inputs. Its results accuracy was compared with the results of conventional correlation coefficient analysis between input and output variables and the best combination was identified. Finally, in order to predict SSL, the SVM, ANFIS and various ANNs models were used. The reliability of SVM, ANFIS and ANN models were determined based on performance criteria such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Efficiency Coefficient (EC) and Determination Coefficient (R²).