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.     

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.     

超临界二氧化碳萃取－GC／MS测定土壤中的多环芳烃

本文开发了一种采用超临界二氧化碳萃取土壤中多环芳烃、不须经过纯化步骤，直接可用于ＧＣ／ＭＳ分析的简便、高效的方法。本实验中超临界革取的流体是二氧化碳，改善剂是５％的二氯甲烷／甲醇，萃取温度为１２０℃、压力为３４ＭＰａ。ＧＣ／ＭＳ分析时除了采用外标外，还加入了６种同位素ＰＡＨｓ内标以校正各段ＰＡＨｓ的响应因子。采用本方法成功地测定了我国未开垦森林土壤中的ＰＡＨｓ。     

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.     

Higher Plants As Bioindicators Of Sulphur Dioxide Emissions In Urban Environments

The evaluation of certain vascular plants that grow in the city of Madrid as biomonitors of SO₂ air pollution in urban environments has been carried out. Total concentration of sulphur in leaves of the chosen higher plants as well as other parameters in close relation to this contaminant (visible injury symptoms, chlorophyll a- and b-content and peroxidase activity) have been determined in order to study the spatial distribution and temporal changes in SO₂ deposition. Results obtained show that coniferous species such as Pinus pinea, were more sensitive to SO₂ atmospheric concentration than leafy species as Quercux ilex subspecies ballota and, in the same way, bush species, such asPyracantha coccinea and Nerium oleander, were more sensitive than wooded species, such as Cedrus deodaraandPinus pinea, respectively. There is a higher accumulation of sulphur in vegetable species located near highways and dense traffic incidence roads and near areas with high density of population. The minimum values for accumulation of SO₂ were registered in winter and spring seasons (from January to April) due to the vegetative stop; while maximum values are obtained during the summer season (from June to September), due to the stoma opening. The highest increments in sulphur concentration, calculated as the difference between two consecutive months, are obtained in May and June for all considered species except forCedrus deodara and Pyracantha coccinea, both species have few seasonal changes during the whole year. Some species are more sensitive to natural washing than others, showing a decrease in sulphur concentration after rainfall periods.     

Study of Meteorological Aspects and Urban Concentration of SO2 in Atmospheric Environment of La Plata, Argentina

This article presents and discusses SO₂ (ppbv) concentration measurements combined with meteorological data (mainly wind speed and direction) for a five-year campaign (1996 to 2000), in a site near an oil refinery plant close to the city of La Plata and surroundings (aprox. 740.000 inh.), considered one of the six most affected cities by air pollution in the country. Since there is no monitoring network in the area, the obtained results should be considered as medium term accumulated data that enables to determine trends by analyzing together gas concentrations and meteorological parameters. Preliminary characterization of the behaviour of the predominant winds of the region in relation with potential atmospheric gas pollutants from seasonal wind roses is possible to carry out from the data. These results are complemented with monthly averaged SO₂ measurements. In particular, for year 2000, pollutant roses were determined which enable predictions about contamination emission sources. As a general result we can state that there is a clear increase in annual SO₂ concentration and that the selected site should be considered as a key site for future survey monitoring network deployment. Annual SO₂ average concentration and prevailing seasonal winds determined in this work, together with the potential health impact of SO₂ reveals the need for a comprehensive and systematic study involving particulate matter an other basic pollutant gases.     

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.