Optimal Absorbent Evaluation for the CO2 Separating Process by Absorption Loading,Desorption Efficiency,Cost, and Environmental Tolerance

The CO₂ absorption capacities of potassium glycinate, potassium sarcosinate (choline, proline), mono-ethanolamine (MEA), and tri-ethanolamine were evaluated to find the optimal absorbent for separating CO₂ from gaseous products by a CO₂ purification process. The absorption loading, desorption efficiency, cost, and environmental tolerance were assessed to select the optimal absorbent. MEA was found to be the optimum absorbent for separating the CO₂ and H₂ mixture in gaseous product. The maximum absorption loading rate was 0.77 mol CO₂ per mol MEA at temperature of 20°C and absorbent concentration of 2.5 mol/L, whereas desorption efficiency was 90% by heating for 3 h at 130°C. MEA was found to be an optimal absorbent for the purification process of CO₂ during gaseous production.     

Feasibility of honeycomb monolith supported sugar catalyst to produce biodiesel from palm fatty acid distillate (PFAD)

Carbon coated monolith was prepared by sucrose solution 65 wt.% via dip-coating method. Sulfonation of incomplete carbonized carbon coated monolith was carried out in order to synthesize solid acid catalyst. The textural structure characteristics of the solid acid catalyst demonstrated a low surface area and pore volume. Palm fatty acid distillate (PFAD), a by-product of palm oil refineries, was utilized as oil source in biodiesel production. The esterification reaction subjected to different reaction conditions was performed by using the sulfonated carbon coated monolith as heterogeneous catalyst. The sulfonation process had been performed by using vapour of concentrated H₂SO₄ that was much easier and efficient than liquid phase sulfonation. Total acidity value of carbon coated monolith was measured for unsulfonated sample (0.5 mmol/g) and sulfonated sample (4.2 mmol/g). The effect of methanol/oil ratio, catalyst amount and reaction time were examined. The maximum methyl ester content was 89% at the optimum condition, i.e. methanol/oil molar ratio (15:1), catalyst amount (2.5 wt.% with respect to PFAD), reaction time (240 min) and temperature 80 °C. The sugar catalyst supported on the honeycomb monolith showed comparable reactivity compared with the sugar catalyst powder. However, the catalyst reusability studies showed decrease in FFA% conversion from 95.3% to 68.8% after four cycles as well as the total acidity of catalyst dropped from the value 4.2 to 3.1 mmol/g during these cycles. This might be likely due to the leaching out of SO₃H group from the sulfonated carbon coated monolith surface. The leaching of active species reached a plateau state after fourth cycle.     

Review: recent advances in biogas purifying technologies

Biomethane production through biogas upgrading is a promising renewable energy for some industries which could be part of the equilibrium needed with fossil fuels consumption to achieve a sustainable society. This paper presents a comprehensive list of biogas upgrading technologies focused on carbon dioxide removal as well as recent advances reported by researcher with wide expertise in this topic. Additionally, an extensive costs–performance comparison among the technologies studied is discussed. Among the different alternatives, chemical scrubbing stood out to achieve high biomethane purities while cryogenic technologies proved to be effective against methane losses. Regarding the different costs, water scrubbing and membrane separation seem to be the most affordable techniques.     

Tuning the fill percentage in the hydrothermal synthesis process to increase catalyst performance for ozone decomposition

The performance of Ce-OMS-2 catalysts was improved by tuning the fill percentage in the hydrothermal synthesis process to increase the oxygen vacancy density. The Ce-OMS-2 samples were prepared with different fill percentages by means of a hydrothermal approach (i.e. 80%, 70%, 50% and 30%). Ce-OMS-2 with 80% fill percentage (Ce-OMS-2-80%) showed ozone conversion of 97%, and a lifetime experiment carried out for more than 20?days showed that the activity of the catalyst still remained satisfactorily high (91%). For Ce-OMS-2-80%, Mn ions in the framework as well as K ions in the tunnel sites were replaced by Ce⁴⁺, while for the others only Mn ions were replaced. O₂-TPD and H₂-TPR measurements proved that the Ce-OMS-2-80% catalyst possessed the greatest number of mobile surface oxygen species. XPS and XAFS showed that increasing the fill percentage can reduce the AOS of Mn and augment the amount of oxygen vacancies. The active sites, which accelerate the elimination of O₃, can be enriched by increasing the oxygen vacancies. These findings indicate that increasing ozone removal can be achieved by tuning the fill percentage in the hydrothermal synthesis process.     

Effect of TiO2 nanoparticle aggregation on marine microalgae Isochrysis galbana

TiO_2 nanoparticles(NPs) could adversely impact aquatic ecosystems. However, the aggregation of these NPs could attenuate this effect. In this work, the biological effects of TiO_2 NPs on a marine microalgae Isochrysis galbana were investigated. The aggregation kinetics of TiO_2 NPs under different conditions was also investigated to determine and understand these effects. Results showed that, though TiO_2 NPs had no obvious impact on the size and reproducibility of algal cells under testing conditions, they caused a negative effect on algal chlorophyll, which led to a reduction in photosynthesis. Furthermore, fast aggregation of TiO_2 NPs occurred under all conditions, especially at the pH close to the p Hzpc. Increasing ionic strength and NP concentration also enhanced the aggregation rate.The aggregation and the following sedimentation of TiO_2 NPs reduced their adverse effects on I. galbana.     

螯合树脂在线富集——火焰原子吸收光度法测定水中微量Cu,Pb,Zn,Cd

对螯合树脂在线富集，火焰原子吸收光度法进行了条件试验。试验证实方法对Ｃｕ、Ｐｂ、Ｚｎ、Ｃｄ４个元素检出浓度可达μｇ／Ｌ级，校准曲线性、样品重现性及准确度可满足测定要求。     

火焰原子吸收分光光度法测定鱼内脏及河流底泥中的铜

采用火焰原子吸收分光光度法测定鱼内脏及河流底泥中的铜。鱼内脏经组织捣碎机捣成匀浆后，加硝酸消解；底泥则经氢氟酸和高氯酸消化。该方法具有灵敏度高，精密度和回收率较好等特点。     

Photocatalytic degradation of phenol

In this study photocatalytic degradation of phenol in thepresence of UV irradiated TiO₂ catalyst andH₂O₂was investigated. Effects of TiO₂ andH₂O₂concentrations and pH on photocatalytic degradation were examined. The rate constants for photocatalytic degradation wereevaluated as a function of TiO₂ and H₂O₂ concentrations and pH of the solution. It was found thatphotodegradation is an effective method for the removal of phenoland disappearance of phenol obeyed first order kinetics. The amount of CO₂h produced during photocatalytic degradation wascorresponding to the complete mineralization. Photodegradationcan be an alternative method for the treatment of phenol containing wastewaters.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Comparison of Two Manual Methods of Nitrogen Dioxide Determination in Ambient Air

Sodium arsenite (modified Jacobs and Hochheiser method; hereafter referred as SA), the most widely used manual monitoring method for determination of nitrogen dioxide (NO₂) in ambient air, particularly in developing countries has been evaluated and compared with US EPA recommended equivalent method of TGS-ANSA (hereafter referred as ANSA). NO₂ concentrations generated from laboratory test atmosphere were analyzed by these two methods and were compared statistically. Laboratory evaluations showed that SA method has high sensitivity to different sampling conditions, which normally vary during actual field monitoring. Hence, correction factors for absorption efficiency were estimated for SA and ANSA methods. Absorption efficiency of NO₂ in SA method was found to be much lower (64%) as against the reported value of 82% at the method recommended sampling conditions, whereas for ANSA method, it was found 1.0 as against the reported value of 0.93. After applying derived correction factors, both the methods produced almost similar concentration values of NO₂.