Investigation of ammonia removal from polluted waters by Clinoptilolite zeolite

Ammonia nitrogen compounds in the wastewaters and effluents have harmful effects on water resources. Ion exchange with zeolites is a separation process for ammonia removal from effluents. The objective of this research was to study the efficiency of an ammonia removal and the factor affecting to this process. The Clinoptilolite was obtained from Semnan mines at the north part of Iran. The samples were grounded and sieved based on the U.S. standard mesh number 20, 30, 40 and conditioned by ammonia sulfate and sodium chloride solutions. The characteristics of samples for ammonia removal and the selectivity sequence for adsorbing interfering cations were then determined. Results shown that the average ion exchange capacity of zeolite in batch and continuous systems were 6.65–16 and 16.31–19.5 mg NH₄ ⁺ /g zeolite weight, respectively. In study on the zeolite for selective cations showed the ranking of K⁺, NH₄ ⁺, Na⁺, Ca²⁺ and Mg²⁺ respectively. Results indicated that high level of regeneration (95–98%) might be achieved with NaCl solution. Based on the results, Clinoptilolite may be effective applied in wastewater treatment, both from technical and economical aspects.     

A novel mathematical morphology based algorithm for shoreline extraction from satellite images

Abstract

Shoreline extraction is fundamental and inevitable for several studies. Ascertaining the precise spatial location of the shoreline is crucial. Recently, the need for using remote sensing data to accomplish the complex task of automatic extraction of features, such as shoreline, has considerably increased. Automated feature extraction can drastically minimize the time and cost of data acquisition and database updating. Effective and fast approaches are essential to monitor coastline retreat and update shoreline maps. Here, we present a flexible mathematical morphology-driven approach for shoreline extraction algorithm from satellite imageries. The salient features of this work are the preservation of actual size and shape of the shorelines, run-time structuring element definition, semi-automation, faster processing, and single band adaptability. The proposed approach is tested with various sensor-driven images with low to high resolutions. Accuracy of the developed methodology has been assessed with manually prepared ground truths of the study area and compared with an existing shoreline classification approach. The proposed approach is found successful in shoreline extraction from the wide variety of satellite images based on the results drawn from visual and quantitative assessments.     

Changes in European precipitation seasonality and in drought frequencies revealed by a four-century-long tree-ring isotopic record from Brittany, western France

A new paleoclimatic reconstruction for western France is obtained from tree-ring cellulose stable isotopes. Living trees from Rennes Forest and beams from two ancient buildings in Rennes city have been combined to cover the past four centuries with a gap from 1730 to 1750. The cellulose ¹³C reflects the progressive changes in atmospheric CO₂ isotopic composition. The combined ¹³C and ¹⁸O measurements are used to propose a reconstruction of interannual fluctuations in local summer temperature and water stress. At the decadal time scale, the reconstructed water stress profile exhibits a significant similarity with the historical wine harvest dates, an indicator of warm and dry growth seasons, as well as with the summer central England and central Alps instrumental temperature records and climate model results. Combined with instrumental precipitation records from Paris, these reconstructions suggest a dramatic and widespread change in the seasonality of the precipitation at the beginning of the nineteenth century, with drier winters and wetter summers, which may have contributed to the Alpine glacier decline at the end of the Little Ice Age. The tree-ring isotope records also show a relationship with large-scale North Atlantic circulation changes and the interannual variability is modified between the nineteenth and twentieth centuries (7–8 year periodicities) and the seventeenth century (11–14 year periodicities). By classifying 20-year-long subsets of the reconstructed climatic parameters, we estimate that a decadal mean summer warming of 0.8±0.1°C induced extreme dry years to be 2.2±0.7 times more frequent.     

Time–space continuity of daily maps of fractional snow cover and albedo from MODIS

Using reflectance values from the seven MODIS “land” bands with 250 or 500 m resolution, along with a corresponding cloud product, we estimate the fraction of each 500 m pixel that snow covers, along with the albedo of that snow. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry. Rather than make users interpolate and filter these patchy daily maps without completely understanding the retrieval algorithm and instrument properties, we use the daily time series to improve the estimate of the measured snow properties for a particular day. We use a combination of noise filtering, snow/cloud discrimination, and interpolation and smoothing to produce our best estimate of the daily snow cover and albedo. We consider two modes: one is the “predictive” mode, whereby we estimate the snow-covered area and albedo on that day using only the data up to that day; the other is the “retrospective” mode, whereby we reconstruct the history of the snow properties for a previous period.     

Inverse Analysis of Deep Excavation Using Differential Evolution Algorithm

This paper presents the applications of the differential evolution (DE) algorithm in back analysis of soil parameters for deep excavation problems. A computer code, named Python‐based DE, is developed and incorporated into the commercial finite element software ABAQUS, with a parallel computing technique to run an FE analysis for all trail vectors of one generation in DE in multiple cores of a cluster, which dramatically reduces the computational time. A synthetic case and a well‐instrumented real case, that is, the Taipei National Enterprise Center (TNEC) project, are used to demonstrate the capability of the proposed back‐analysis procedure. Results show that multiple soil parameters are well identified by back analysis using a DE optimization algorithm for highly nonlinear problems. For the synthetic excavation case, the back‐analyzed parameters are basically identical to the input parameters that are used to generate synthetic response of wall deflection. For the TNEC case with a total of nine parameters to be back analyzed, the relative errors of wall deflection for the last three stages are 2.2, 1.1, and 1.0%, respectively. Robustness of the back‐estimated parameters is further illustrated by a forward prediction. The wall deflection in the subsequent stages can be satisfactorily predicted using the back‐analyzed soil parameters at early stages. Copyright © 2014 John Wiley & Sons, Ltd.     

An Improved Approach for Parameterizing Surface-Layer Turbulent Transfer Coefficients in Numerical Models

Based on classic iterative computation results, new equations to calculate the surface turbulent transfer coefficients are proposed, which allow for large ratios of the momentum and heat roughness lengths. Compared to the Launiainen scheme, our proposed scheme generates results closer to classical iterative computations. Under unstable stratification, the relative error in the Launiainen scheme increases linearly with increasing instability, even exceeding 15%, while the relative error of the present scheme is always less than 8.5%. Under stable stratification, the Launiainen scheme uses two equations, one for 0 < Ri _B ≤ 0.08 and another for 0.08 < Ri _B ≤ 0.2, and does not consider the condition that Ri _B > 0.2, while its relative errors in the region 0 < Ri _B ≤ 0.2 exceed 31 and 24% for momentum and heat transfer coefficients, respectively. In contrast, the present scheme uses only one equation for 0 < Ri _B ≤ 0.2 and another equation for Ri _B > 0.2, and the relative error of the present scheme is always less than 14%.     

Radio Emission of Flares and Coronal Mass Ejections

We review recent progress on our understanding of radio emission from solar flares and coronal mass ejections (CMEs) with emphasis on those aspects of the subject that help us address questions about energy release and its properties, the configuration of flare?–?CME source regions, coronal shocks, particle acceleration and transport, and the origin of solar energetic particle (SEP) events. Radio emission from electron beams can provide information about the electron acceleration process, the location of injection of electrons in the corona, and the properties of the ambient coronal structures. Mildly relativistic electrons gyrating in the magnetic fields of flaring loops produce radio emission via the gyrosynchrotron mechanism, which provides constraints on the magnetic field and the properties of energetic electrons. CME detection at radio wavelengths tracks the eruption from its early phase and reveals the participation of a multitude of loops of widely differing scale. Both flares and CMEs can ignite shock waves and radio observations offer the most robust tool to study them. The incorporation of radio data into the study of SEP events reveals that a clear-cut distinction between flare-related and CME-related SEP events is difficult to establish.     

THE BEGINNING OF THE USING OF ZINC IN CHINA.

In my work, Lapidarium Sinicum, the chapter on brass is speciallydevoted to this inquiry. Recently Dr. Read of the U. S. Bureau of Mineswrote to Dr. Ting, suggesting the question whether "The knowledge ofzinc-smelting in India is previous to that developed in China." Therefore     

School vulnerability to disaster: examination of school closure,demographic, and exposure factors in Hurricane Ike’s wind swath

Damage and destruction to schools from climate-related disasters can have significant and lasting impacts on curriculum and educational programs, educational attainment, and future income-earning potential of affected students. As such, assessing the potential impact of hazards is crucial to the ability of individuals, households, and communities to respond to natural disasters, extreme events, and economic crises. Yet, few studies have focused on assessing the vulnerability of schools in coastal regions of the USA. Using Hurricane Ike’s tropical storm wind swath in the State of Texas as our study area, we: (1) assessed the spatial distribution patterns of school closures and (2) tested the relationship between school closure and vulnerability factors (namely physical exposure and school demographics) using zero-inflated negative binomial regression models. The regression results show that higher probabilities of hurricane strikes, more urbanized school districts, and school districts located in coastal counties on the right side of Ike’s path have significant positive associations with an increase in the number of school closure days. Socioeconomic characteristics were not significantly associated with the number of days closed, with the exception of proportion of Hispanic youth in schools, a result which is not supported by the social vulnerability literature. At a practical level, understanding how hurricanes may adversely impact schools is important for developing appropriate preparedness, mitigation, recovery, and adaptation strategies. For example, school districts on the right side of the hurricane track can plan in advance for potential damage and destruction. The ability of a community to respond to future natural disasters, extreme events, and economic crises depends in part on mitigating these adverse effects.