Supported Pd/Sn bimetallic nanoparticles for reductive dechlorination of aqueous trichloroethylene

A Pd/Sn bimetallic nanoparticles resin (nano-Pd/Sn/resin) was successfully synthesized for reductive transformation of aqueous trichloroethylene (TCE). The physicochemical properties of the prepared resin were characterized using scanning electron microscopy, energy dispersive X-ray spectroscopy, N(2) isothermal sorption at and X-ray photospectroscopy. The surface-area-normalized rate constants (k(SA)) of Sn particles in the nanoscale range (50-100 nm) were 4.5 times larger than the k(SA) for powdered Sn (0.04 mm). After depositing 1 wt% Pd onto nano-Sn surface, k(SA) was further enhanced by about a factor of 2. Groundwater constituents such as sulfide nitrate and dissolved oxygen had significant negative effects on the rate of TCE degradation by the nano-Pd/Sn/resin. A wet-chemical method regeneration method was observed to effectively restore the reactivity of the poisoned nano-Pd/Sn/resin after dipping in sulfide solution for 2d. In all cases, less than 0.5% of the degraded TCE appeared as chlorinated byproducts including the three dichloroethene isomers. The nano-Pd/Sn/resin technique performs well in transforming TCE into nontoxic hydrocarbons, as compared with other published methods.     

A GIS-based system for allocating municipal solid waste incinerator compensatory fund

To ease the NIMBY (not in my back yard) syndrome of constructing municipal solid waste (MSW) incinerators in Taiwan, compensatory funding is widely allocated to the impacted communities to gain the acceptance and support of residents living the impacted areas. This paper presents a spatial methodology for distributing a compensatory fund more logically based on the environmental impact on each neighborhood in Taipei City. This method integrates ten impact factors, which have been proposed by a local committee, to evaluate all neighborhoods using mathematical models combined with spatial analyses in an analytic hierarchy process. The compensatory fund is distributed according to the resulting final scores. A GIS (geographic information systems)-based system has been developed to assist in assigning the final scores to the neighborhoods impacted. Results on impact factors and fund distributions are combined; they are included in an information system and displayed in spatial scales. For Taipei City, the impact of air quality during the incinerator operating period is the item of greatest concern to the surrounding residents and thus, it receives a relatively higher weight of 0.2894. As a result, high impact scores were assigned to not only those neighborhoods hosting the incinerators, but also the neighborhoods where the maximum particulate air pollutants occurred. This approach could be applicable to other MSW incinerators with similar environmental impact problems and interest in compensation schemes.     

Catalytic hydrodechlorination of 1,2-dichloroethane using copper nanoparticles under reduction conditions of sodium borohydride

1,2-Dichloroethane (1,2-DCA) is a raw material used for the manufacture of vinyl chloride monomer (VCM) and therefore has very often been detected in the groundwater nearby the VCM manufacturing plant. Zero-valent iron (ZVI) is capable of degrading a wide array of highly chlorinated contaminants; however, the reactivity of ZVI towards 1,2-DCA is very low. In this study, zero-valent copper nanoparticles have been synthesized for effective dechlorination of 1,2-DCA under reduction conditions of sodium borohydride. Copper nanoparticles consisted of mainly metallic copper (Cu(0)) with small amounts of cuprous oxide (Cu(2)O). They have surface areas of about 19.0 m(2) g(-1) and an average diameter of 15 nm. Batch experiments were conducted to test the effectiveness of copper nanoparticles for 1,2-DCA degradation using sodium borohydride as electron donors where the ORP was measured as -1100 mV. More than 80% of 1,2-DCA (30 mg L(-1)) was rapidly degraded within 2 h in the presence of both copper nanoparticles (2.5 g L(-1)) and borohydride (25 mM). No reduction of 1,2-DCA was observed when the system contained either copper nanoparticles alone or borohydride alone. The degradation intermediates included ethane and ethylene accounting for 79% and ～1.5% of the 1,2-DCA lost, respectively. Potential environmental applications can be achieved by immobilizing copper nanoparticles onto the surface of reducing metals to form a reactive bimetallic structure.     

Carbon capture of biochar produced by microwave co-pyrolysis: adsorption capacity,kinetics, and benefits

Environmental Science and Pollution Research - Microwave co-pyrolysis of sewage sludge and leucaena wood was conducted to produce biochar as an adsorbent for CO2 capture. Both microwave power level...     

Role of Geographic Information System (GIS) in Watershed Simulation By Winvast Model

The uncertainty of modeling input will increase the simulation error, and this situation always happens in a model without user-friendly interface. WinVAST model, developed by the University of Virginia in 2003, treats an entire multi-catchment by a tree-view structure. Its extra computer programs can connect geographic information system (GIS). Model users can prepare all the necessary information in ArcGIS. Extracting information from GIS interface can not only decrease the inconvenience of data input, but also lower the uncertainty due to data preparation. The Daiyuku Creek and Qupoliao Creek in the Fei-tsui reservoir watershed in Northern Taiwan provided the setting for the case study reported herein. The required information, including slope, stream length, subbasin area, soil type and land-use condition, for WinVAST model should be prepared in a Microsoft Access database, which is the project file of WinVAST with extension mdb. In ArcGIS interface, when the soil layer, land-use layer, and Digital Elevation Model (DEM) map are prepared, all the watershed information can be created as well. This study compared the simulation results from automatically generated input and manual input. The results show that the relative simulation error resulting from the rough process of data input can be around 30% in runoff simulation, and even reach 70% in non-point source pollution (NPSP) simulation. It could conclude that GIS technology is significant for predicting watershed responses by WinVAST model, because it can efficiently reduce the uncertainty induced by input errors.     

Prediction of the effluent from a domestic wastewater treatment plant of CASP using gray model and neural network

When a domestic wastewater treatment plant (DWWTP) is put into operation, variations of the wastewater quantity and quality must be predicted using mathematical models to assist in operating the wastewater treatment plant such that the treated effluent will be controlled and meet discharge standards. In this study, three types of gray model (GM) including GM (1, N), GM (1, 1), and rolling GM (1, 1) were used to predict the effluent biochemical oxygen demand (BOD), chemical oxygen demand (COD), and suspended solids (SS) from the DWWTP of conventional activated sludge process. The predicted results were compared with those obtained using backpropagation neural network (BPNN). The simulation results indicated that the minimum mean absolute percentage errors of 43.79%, 16.21%, and 30.11% for BOD, COD, and SS could be achieved. The fitness was higher when using BPNN for prediction of BOD (34.77%), but it required a large quantity of data for constructing model. Contrarily, GM only required a small amount of data (at least four data) and the prediction results were analogous to those of BPNN, even lower than that of BPNN when predicting COD (16.21%) and SS (30.11%). According to the prediction, results suggested that GM could predict the domestic effluent variation when its effluent data were insufficient.     

Chemically coupled microwave and ultrasonic pre-hydrolysis of pulp and paper mill waste-activated sludge: effect on sludge solubilisation and anaerobic digestion

The effects of alkali-enhanced microwave (MW; 50–175 °C) and ultrasonic (US) (0.75 W/mL, 15–60 min) pretreatments, on solubilisation and subsequent anaerobic digestion efficiency of pulp and paper mill waste-activated sludge, were investigated. Improvements in total chemical oxygen demand and volatile suspended solids (VSS) solubilisation were limited to 33 and 39 % in MW pretreatment only (175 °C). It reached 78 and 66 % in combined MW–alkali pretreatment (pH 12?+?175 °C), respectively. Similarly, chemical oxygen demand and VSS solubilisation were 58 and 37 % in US pretreatment alone (60 min) and it improved by 66 and 49 % after US–alkali pretreatment (pH 12?+?60 min), respectively. The biogas yield for US 60 min–alkali (pH 12)-pretreated sludge was significantly improved by 47 and 20 % over the control and US 60 reactors, respectively. The biogas generation for MW (150 °C)–alkali (pH 12)-pretreated sludge was only 6.3 % higher than control; however, it was 8.3 % lower than the MW (150 °C) reactor, which was due to the inhibition of anaerobic activity under harsh thermal–alkali treatment condition.     

Uncertainty in watershed response predictions induced by spatial variability of precipitation

Negligence to consider the spatial variability of rainfall could result in serious errors in model outputs. The objective of this study was to examine the uncertainty of both runoff and pollutant transport predictions due to the input errors of rainfall. This study used synthetic data to represent the “true” rainfall pattern, instead of interpolated precipitation. It was conducted on a synthetic case area having a total area of 20 km² with ten subbasins. Each subbasin has one rainfall gauge with synthetic precipitation records. Six rainfall storms with varied spatial distribution were generated. The average rainfall was obtained from all of the ten gauges by the arithmetic average method. The input errors of rainfall were induced by the difference between the actual rainfall pattern and estimated average rainfall. The results show that spatial variability of rainfall can cause uncertainty in modeling outputs of hydrologic, which would be transport to pollutant export predictions, when uniformity of rainfall is assumed. Since rainfall is essential information for predicting watershed responses, it is important to consider the properties of rainfall, particularly spatial rainfall variability, in the application of hydrologic and water quality models.     

A Generalized Water Quality Index for Taiwan

By exploring the behavior and limitations of conventional methods for quality evaluation, a better overall index for water quality in Taiwan and its application in Keya River are proposed. The thirteen variables are employed for the quality assessment. Numerical scales relating to the degree of quality are established for each variable to assess variations in quality and to convey findings in a comprehensive manner to others. The employed variables are categorized into three aspects referred to the principal components analysis, which are 'organics', 'particulates' and 'microorganisms'. The overall index consists of the geometric mean for the three defined aspects and multiplying by three coefficients, which reflect quality degrees of temperature, pH and toxicity, respectively. Besides, the arithmetic mean is addressed among the variables associated in the same aspect. Finally, a fresh, mixed aggregation function is developed for ensuring that the index score tells us something useful and does not hide important information. A case study of the Keya River is made to illustrate the application of this new index system. The new proposed index provides comprehensive information for water quality assessment, than the existing index used in Taiwan does.     

The Parameter Optimization in the Inverse Distance Method by Genetic Algorithm for Estimating Precipitation

This study aimed to analyze long-term urban land use (LU) change and its negative implications on the coastal environment of Iskenderun, Turkey. Information on urban LU change for the 144-year period between 1858 and 2002 was extracted from a historic city plan, black-white monoscopic aerial photographs, and Landsat ETM+ imagery. According to the results, areal extent of urban areas has increased approximately 40 times during the past 144 years. The population growth as a result of industrial developments and permanent migration was main driving force to the urbanization. Environmental problems that resulted from rapid development in the region such as air, water and soil pollution were highlighted and some recommendations were made in the light of qualitative and quantitative information on the urbanization and its negative consequences.