Transesterification of Caesalpinia eriostachys seed oil using heterogeneous and homogeneous basic catalysts

Caesalpinea eriostachys seed oil, as a source of triglycerides with potential application for biodiesel production in Mexico is introduced. Its lipid profile obtained by Gas Chromatography-Mass Spectrometry (GC-MS) revealed saturated and unsaturated glycerol esters as the constituents. Therefore, heterogeneous and homogeneous catalyzed transesterification reactions were assayed employing ZnAl hydrotalcites and KOH, as the catalysts, respectively. The transesterification reactions yielded 59% for Zn/Al(2), 79% for Zn/Al(4), and 90% for KOH, depicting typical behavior, as in biodiesel production data from literature, where Zn-Al hydrotalcites or KOH were assayed. The caloric, density, viscosity values, and fatty acid methyl esters profile from reaction products were concordant to EN 14214, suggesting C. eriostachys as a promising feedstock for biodiesel production.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Mineralization of integrated gasification combined-cycle power-station wastewater effluent by a photo-fenton process

The aim of this work was to study the mineralization of wastewater effluent from an integrated-gasification combined-cycle (IGCC) power station sited in Spain to meet the requirements of future environmental legislation. This study was done in a pilot plant using a homogeneous photo-Fenton oxidation process with continuous addition of H₂O₂ and air to the system.The mineralization process was found to follow pseudo-first-order kinetics. Experimental kinetic constants were fitted using neural networks (NNs). The NNs model reproduced the experimental data to within a 90% confidence level and allowed the simulation of the process for any values of the parameters within the experimental range studied. At the optimum conditions (H₂O₂ flow rate = 120 mL/h, [Fe(II)] = 7.6 mg/L, pH = 3.75 and air flow rate = 1 m³/h), a 90% mineralization was achieved in 150 min.Determination of the hydrogen peroxide consumed and remaining in the water revealed that 1.2 mol of H₂O₂ was consumed per each mol of total organic carbon removed from solution. This result confirmed that an excess of dissolved H₂O₂ was needed to achieve high mineralization rates, so continuous addition of peroxide is recommended for industrial application of this process.Air flow slightly improved the mineralization rate due to the formation of peroxo-organic radicals which enhanced the oxidation process.     

Analyzing the Social Factors That Influence Willingness to Pay for Invasive Alien Species Management Under Two Different Strategies: Eradication and Prevention

Biological invasions occur worldwide, and have been the object of ecological and socio-economic research for decades. However, the manner in which different stakeholder groups identify the problems associated with invasive species and confront invasive species management under different policies remains poorly understood. In this study, we conducted an econometric analysis of the social factors influencing willingness to pay for invasive alien species management under two different regimes: eradication and prevention in the Doñana Natural Protected Area (SW Spain). Controlling for the participation of local residents, tourists and conservationists, email and face-to-face questionnaires were conducted. Results indicated that respondents were more willing to pay for eradication than prevention; and public support for invasive alien species management was influenced by an individual’s knowledge and perception of invasive alien species, active interest in nature, and socio-demographic attributes. We concluded that invasive alien species management research should confront the challenges to engage stakeholders and accept any tradeoffs necessary to modify different conservation policies to ensure effective management is implemented. Finally, our willingness to pay estimates suggest the Department of Environment of Andalusian Government has suitable social support to meet the budgetary expenditures required for invasive alien species plans and adequate resources to justify an increase in the invasive alien species management budget.     

Characterization and Properties of Hydrophilic Cellulose Acetate Propionate Derivative

The chemical modification of Acrylamidomethyl Cellulose Acetate Propionate (AMCAP) was carried out by radical addition of acrylic acid. The structural modification was confirmed with the aid of FTIR, MS and NMR techniques. Thermal properties of hydrophilic cellulose derivative (AMCAP–H₂O₂) such as glass transition (T_g 153 °C) and thermal stability (372.7 °C) were determined by DSC and TGA techniques, respectively. These thermal properties confirmed the introduction of carboxylic groups into AMCAP structure, which causes an impact in their properties. The AMCAP–H₂O₂ shows minor contact angle compared to AMCAP, giving a more hydrophilic characteristic, due to acrylic acid addition into the side chains of AMCAP polymer.