Single and binary adsorption of lead and cadmium ions from aqueous solution using the clay mineral beidellite

Beidellite, a low-cost, locally available and natural mineral was used as an adsorbent for the removal of lead and cadmium ions from aqueous solutions in batch experiments. The kinetics of adsorption process was tested for the pseudo first-order, pseudo second-order reaction and intra-particle diffusion models. The rate constants of adsorption for all these kinetic models were calculated. Comparison amongst the models showed that the sorption kinetics was best described by the pseudo second-order model. Langmuir and Freundlich isotherm models were applied to the experimental equilibrium data for different temperatures. The adsorption capacities (Q°) of beidellite for lead and cadmium ions were calculated from the Langmuir isotherm. It was found that adsorption capacity was in the range of 83.3–86.9 for lead and 42–45.6 mg/g for cadmium at different temperatures. Thermodynamic studies showed that the metal uptake reaction by beidellite was endothermic in nature. Binary metal adsorption studies were also conducted to investigate the interactions and competitive effects in binary adsorption process. Based on the optimum parameters found, beidellite can be used as adsorbent for metal removal processes.     

Estimation of Wheat/Rice Residue Burning Areas in Major Districts of Haryana,India, Using Remote Sensing Data

Haryana has emerged as an important state for Rice & Wheat production in India contributing significantly in the central pool. Mechanized combine harvesting technologies, which have become common in Rice Wheat System (RWS) in India, leave behind large quantities of straw in the field for open burning of residue. Besides causing pollution, the burning kills the useful micro flora of the soil causing soil degradation. There is no field survey (Girdawari) data available with the Government for the areas where stubble burning is taking place. The present paper describes the methodology and results of wheat and rice residue burning areas for three districts of Haryana namely Kaithal, Kurukshetra and Karnal for the year 2010 using complete enumeration approach of multi-date IRS-P6 AWiFS and LISS-III data. In season ground truth was collected using hand held GPS and used to identify area of burnt wheat/rice residues, associated crops and land features. After geo-referencing the satellite images, district images were masked-out and multi-date image data stacks were created. Normalized Difference Vegetation Index (NDVI) of each date was generated and used at the time of classification along with other spectral bands. The non-agricultural classes in the image included: forest, wasteland, water bodies, urban/settlement and permanent vegetation etc. The vector of these non-agriculture classes were extracted from the land use, imported and mask was generated. During the classification non-agriculture area was excluded by using mask of these classes. From this the agricultural area could be separated out. The area was estimated by computing pixels under the classified image mask. In season multi-date AWiFS data along with available single-date LISS-III data between third week of April to last week of May are found to be useful for estimation of wheat residue burning areas estimation. The data between second week of October to last week of November is useful for estimation of rice residue burning areas estimation at district level.     

Determination of Critical Factors in Implementing River Clean‐Up Projects: A Malaysian Case Study

Fast economic growth of a country contributes to the increase of activities that can also bring negative impacts on the rivers. Contamination of rivers, sedimentation, coastal erosion, decrease of aquatic life, and also flooding are some of these universal impacts. There are several rivers around the world, which are categorized as very polluted and require cleaning‐up operations. Several factors have been identified to be influencing factors in the success or otherwise of the implementation and operation of these projects. This study examined the factors related to the steps taken to clean‐up and rehabilitate these rivers and deduce by utilizing factor analysis the most critical success factors from the results obtained. A responsible river community is by far the most effective way to keep a river basin clean. Very often, however, cleaning‐up operations are necessary to revive and maintain the quality of the river so that it can be save to use as an important source of water for human consumption. It was found that community awareness was the most critical cluster of factors determining the success of the clean‐up work.     

Performance of real-time Precise Point Positioning using IGS real-time service

GPS Solutions - Until recently, the real-time IGS precise orbit and clock corrections were only available for the predicted part of the ultra-rapid solution. Whereas the accuracy of the ultra-rapid...     

Characterization of the Seasonal Circulation Patterns and Its Application on Oil Spill Transport in the Northwestern Continental Shelf of India

We implemented the Princeton Ocean Model to study the seasonal circulation patterns in the Gulf of Khambhat and surrounding oceans on the northwestern continental shelf of India. Simulated currents are used in General NOAA Operational Modeling Environment to track a past oil spill event in this region. The model's performance is evaluated against the Synthetic Aperture Radar (SAR) and in situ measurements. Mean currents, computed by subtracting tidal components from the simulated currents, are used together with satellite images of Chlorophyll-a to describe spatial patterns of the circulation. Mean-flow patterns inside the gulf are characterized with strong along-channel flow during southwest monsoon and spring seasons, which are weak during winter and autumn seasons. On the proximity of the gulf mouth currents are northwestward throughout the year except the southwest monsoon when the circulations are southwestward. Coastal boundary currents parallel to the 60 m isobath are prominent during the inter-monsoon and weak during the monsoon periods. Slope currents, near the shelf-break, are strong during southwest monsoon and spring periods. Numerical experiments suggest that ocean current is the main driver of the net transport of spilled oil in this region and other factors such as direct wind drift play negligible role.     

Modeling daily reference evapotranspiration (ET0) in the north of Algeria using generalized regression neural networks (GRNN) and radial basis function neural networks (RBFNN): a comparative study

Estimation of reference evapotranspiration (ET₀) is needed to support irrigation design and scheduling, and watershed hydrology studies. There are many available methods to estimate evapotranspiration from a water surface, comprising both direct and indirect methods. In the first part of this study, the generalized regression neural networks model (GRNN) and radial basis function neural network (RBFNN) are developed and compared in order to estimate the reference ET₀ for the first time in Algeria. Various daily climatic data, that is, daily mean relative humidity, sunshine duration, maximum, minimum and mean air temperature, and wind speed from Dar El Beida, Algiers, Algeria, are used as inputs to the GRNN and RBFNN models to estimate the ET₀ obtained using the FAO-56 Penman-Monteith equation (PM56). The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. In the second part of the study, the empirical Hargreaves-Samani (HG) and Priestley-Taylor (PT) equations are also considered for the comparison. Based on the comparisons, the GRNN was found to perform better than the RBFNN, Priestley-Taylor and Hargreaves-Samani models. The RBFNN model is ranked as the second best model.     

基于Photomod 3.11制作数字正射影像

介绍了俄罗斯的数字摄影测量系统Photomod 3.11,分析了采用比例尺为1∶20 000的航片制作数字正射影像的流程,试验表明其能满足1∶5 000地形图的精度要求.     

Invasion of anthropogenic CO<Subscript>2</Subscript> recorded in planktonic foraminifera from the northern Gulf of Aqaba

The stable carbon isotopic composition of the planktonic foraminifera Globigerinoides sacculifer and G. ruber (white) and sedimentary organic matter from the northern Gulf of Aqaba have been investigated to estimate changes in ¹³C_DIC in surface waters during the last 1,000 years. The high sedimentation rates at the core sites (about 54 cm/Kyear) provide high temporal resolution (~10 years). Recent sediments at the top of the cores reflect conditions younger than 1950. The ¹³C records of the planktonic foraminifera from three multicores display similar trends, showing a uniform and consistent pattern before the 1750s, and a gradual decrease of approximately 0.63 over the last two centuries. This decrease seems to track the decrease of ¹³C_DIC in surface waters, which is mainly caused by the increase of anthropogenic input of ¹³C-depleted CO₂ into the atmosphere. Similarly, a trend towards lighter values of the carbon isotopic composition of sedimentary organic matter (¹³C_org) during the last 200 years supports the interpretation obtained from the planktonic foraminiferal ¹³C. Furthermore, direct measurements of seawater show that ¹³C of the dissolved inorganic carbon (DIC) in the northern Gulf of Aqaba has decreased by about 0.44 during the period 1979–2000. The average annual decrease is 0.021, which is similar to that observed globally. The ¹³C values of planktonic foraminifera combined with organic matter ¹³C from marine sediments are good indicators for reconstructing past changes in atmospheric CO₂ concentrations from the northern Gulf of Aqaba.     

Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India

This study examines the consistency between the AVHRR and MODIS normalized difference vegetation index (NDVI) datasets in estimating net primary productivity (NPP) and net ecosystem productivity (NEP) over India during 2001–2006 in a terrestrial ecosystem model. Harmonic analysis is employed to estimate seasonal components of the time series. The stationary components (representing long-term mean) of the respective NDVI time series are highly coherent and exhibit inherent natural vegetation characteristics with high values over the forest, moderate over the cropland, and small over the grassland. Both data exhibit strong semi-annual oscillations over the cropland dominated Indo-Gangetic plains while annual oscillations are strong over most parts of the country. MODIS has larger annual amplitude than that of the AVHRR. The similar variability exists on the estimates of NPP and NEP across India. In an annual scale, MODIS-based NPP budget is 1.78 PgC, which is 27% higher than the AVHRR- based estimate. It revealed that the Indian terrestrial ecosystem remained the sink of atmospheric CO ₂ during the study period with 42 TgC y ^?1 NEP budget associated with MODIS-based estimate against 18 TgC y ^?1 for the AVHRR-based estimate.