Optimization of membrane-based CO2-removal from natural gas using simple models considering both pressure and temperature effects

Simple models for permeability and selectivity variations of the CO₂/CH₄ system in 6FDA-2,6-DAT membrane have been derived that include both temperature and pressure effects simultaneously in a single equation. The proposed models were used in MATLAB, for a membrane-based CO₂-removal process design for natural gas sweetening. The effects of the following factors on design parameters were examined: feed temperature, feed pressure and permeate pressure. The effect of permeate pressure was found to be very significant in the optimization process. In order to reduce hydrocarbon losses to below 2%, a two-stage membrane process was modeled and simulated in MATLAB, and the extent of desired hydrocarbon recovery was shown to be crucial in the optimization process. It has also been shown that there exist minima for the total required area of the two-stage membrane-based process, and as the CO₂ load increases in the feed, the position of these minima shift to higher values of methane loss.     

Development and evaluation of air pollution–linked quality of life (AP-QOL) questionnaire: insight from two different cohorts

Environmental Science and Pollution Research - In this study, the air pollution–related quality of life (AP-QOL) questionnaire was carried out in two geographically and economically different...     

CLIMATE CHANGE IMPACTS ON NEW YORK CITY'S WATER SUPPLY SYSTEM1

ABSTRACT: It has been well established that the greenhouse gas loading of the atmosphere has been increasing since the mid 19th century. Consequently, shifts in the earth's radiative balance are expected with accompanying alterations to the earth's climate. With these anticipated, and perhaps already observable, changes in both global and regional climate, managers of regional water resources seek insight to the possible impacts climate change may have on their present and future water supplies. The types and degrees of impacts that climate change may have on New York City's water supply system were assessed in a study of a watershed at Allaben, New York. Hypothetical scenarios of future climate and climate change projections from three General Circulation Models (GCMs) were used in conjunction with the WatBal hydrological model and the Palmer Drought Severity Index (PDSI) to ascertain how runoff and soil moisture from this watershed may change in a warmer climate. For the worst case predictions, the results indicate that within the century of the 2000s, the watershed's air temperature may increase up to about 11°F, while its precipitation and runoff may decrease by about 13 and 30 percent, respectively. If this watershed is typical of the others within the New York City water supply system, the system's managers should consider implementing mitigation and adaptation strategies in preparation for the worst of these possible future conditions.     

Experimental investigation,intelligent modeling and multi-characteristics optimization of dry WEDM process of Al–SiC metal matrix composite

Dry wire electrical discharge machining (WEDM) is an environmentally friendly modification of the oil WEDM process in which liquid dielectric is replaced by a gaseous medium. In the present work, parametric analysis has been fulfilled while dry WEDM of Al–SiC metal matrix composite. Experiments were designed and conducted based on L₂₇ Taguchi's orthogonal array to study the effect of pulse on time, pulse off time, gap voltage, discharge current, wire tension and wire feed on cutting velocity (CV) and surface roughness (SR). Firstly, a series of exploratory experiments has been conducted to identify appropriate gas and wire material based on the values of cutting velocity. After selection of best gas and best wire, they were used for later stage of experiments. Analysis of variances (ANOVA) has been performed to identify significant factors. In order to correlate relationship between process inputs and responses, an adaptive neuro-fuzzy inference system (ANFIS) has been employed to predict the process characteristics based on experimental observation. At the end, an artificial bee colony (ABC) algorithm has been associated with ANFIS models to maximize CV and minimize SR, simultaneously. Then the optimal solutions that obtained through ANFIS-ABC technique have been compared with numbers of confirmatory experiments. Results indicated that oxygen gas and brass wire guarantee superior cutting velocity. Also, according to ANOVA, pulse on time and discharge current were found to have significant effect on CV and SR. In modeling of CV and SR by ANFIS, it was resulted that the proposed method has superiority in prediction of them in the ranges of factors beyond the training condition. Also, association of ANFIS with ABC can find the optimal combination of process parameters accurately according to the confirmatory experiments.     

The effect of weather data on the spread of COVID-19 in Jordan

Environmental Science and Pollution Research - This study aims to analyze the correlation between the daily confirmed COVID-19 cases in Jordan and metrological parameters including the average...     

Bio-indicators in cadmium toxicity: Role of HSP27 and HSP70

Environmental Science and Pollution Research - Heat shock proteins (HSPs) are a family of proteins that are expressed by cells in reply to stressors. The changes in concentration of HSPs could be...     

Removal of dinitrotoluenes from water via reduction with iron and peroxidase-catalyzed oxidative polymerization: a comparison between Arthromyces ramosus peroxidase and soybean peroxidase

A two-step process for the removal of dinitrotoluene from water is presented: zero-valent iron reduction is coupled with peroxidase-catalyzed polymerization of the resulting diaminotoluenes (DAT). The effect of pH was examined in the reduction step: at pH 6 the reaction occurred much more rapidly than at pH 8. In the second step, optimal pH and substrate ratio, minimal enzyme concentration and effect of polyethylene glycol (PEG) as an additive for greater than 95% conversion of DAT, over a 3h reaction period were determined using high performance liquid chromatography. Two enzymes were investigated and compared: Arthromyces ramosus peroxidase (ARP) and soybean peroxidase (SBP). The optimal pH values were 5.4 and 5.2 for ARP and SBP, respectively, but SBP was more resistant to mild acid whereas ARP was more stable in neutral solutions. SBP was found to have a greater hydrogen peroxide demand (optimal peroxide/DAT molar ratio for SBP: 2.0 and 3.0 for 2,4-diaminotoluene (2,4-DAT) and 2,6-diaminotoluene (2,6-DAT), respectively; for ARP: 1.5 and 2.75 for 2,4-DAT and 2,6-DAT, respectively) but required significantly less enzyme (0.01 and 0.1 U ml(-1) for 2,4-DAT and 2,6-DAT, respectively) to convert the DAT than ARP (0.4 and 1.5 U ml(-1) for 2,4-DAT and 2,6-DAT, respectively). PEG was shown to have no effect upon the degree of substrate conversion for either enzyme.     

Flow injection spectrophotometric determination of methamidophos using online hydrolysis

A new protocol for the online spectrophotometric determination of methamidophos has been developed. The method is based on online hydrolysis of methamidophos, and the resulting hydrolyzed product is reacted with sodium nitroproside to form a colored complex. The calibration curve is linear over the concentration range of 0.5–20 μgml^?–?1, with a molar absorptivity of 2.5×10⁴ L mol^?1 cm^?1. The method is fast and reproducible with a sample throughput of 90 samples/h. The method is successfully applied to formulations and real samples.