A geochemical equilibrium modeling approach to assessing soil acidification impacts due to depositions of industrial air emissions

Soil acidification impacts arising from depositions of industrial air emissions may become a serious environmental concern. Currently, in the literature quantitative mechanistic modeling and the experimental acid neutralizing capacity (ANC) approach and a qualitative evaluation approach classifying soils into various levels of sensitivity to acid additions have been reported to assess the long-term soil acidification impacts due to industrial air emissions. Another alternative quantitative approach proposed by this study is the geochemical modeling approach that can be used to similate an ANC curve based on relevant soil chemistry data by calculating the equilibrium distributions of chemical species in the soil solution according to the specified geochemical processes. The purpose of this syudy was essentially to illustrate the potential applications and practical utility of the proposed geochemical modeling approach to assessing soil acidification impacts due to industrial air emissions. The application of the geochemical modeling approach was illustrated by comparisons of the experimental and simulated ANC curves for a calcareous and a noncalcareous soil representing insensitive and sensitive soil cases, respectively. Results obtained from these comparisons reveal that, in terms of producing the ANC curve for the soil solution, the geochemical modeling approach seems to perform well and produce more reliable results for calcareous soil than for noncalcareous soil. However, the approach can also be used for noncalcareous soils when the air emission rates are low and may need further testing with additional measured data for a wide range of soils other than those presented in this study

Reduction of Dendrite Formations to Improve the Appearance of the Powder Cured Films for Automotive Industry

The appearance of powder-coated films is dependent upon powder chemistry and spraying parameters. One of the most important physical factors controlling the powder film appearance is the microdeposition of the powder particles on the grounded substrate. During the electrostatic deposition of powder, the formation of dendrites and agglomerates was observed; these formations have an adverse effect on the final film appearance and their elimination may result in smoother and glossier films. Dendrites are generated due to bipolar charging and inter-particulate electrostatic attractive forces. The corona charging technique is mostly used in industrial powder coating applications. At low corona voltages (- 40 to - 60 kV) a greater degree of bipolar charging was observed compared to that at higher voltages (- 80 to - 100 kV). At the higher voltages, the increase n number of ions produces a more unipolar charging and higher charge-to-mass ratios. As the film builds up, the powder transfer efficiency decreases as the repulsion forces between oncoming charged particles and the already deposited powder layer increase. By controlling the deposition patterns, the final film appearance can be improved. The smoothest films were obtained when the voltage was ramped from - 60 to - 100 kV. Another method to reduce dendrite formations was to deposit powder particles charged unipolarly by first separating them from the oppositely charged ones by using a charge separator

Electrostatic Microencapsulation of Composite Particulate Materials for Manufacturing and Environmental Applications

Electrostatic microencapsulation is a dry coating process where two powders, one containing the fines and the other relatively larger particles, are separately dispersed in air and pre-charged with opposite polarity, using corona charging for electrostatic coagulation. These oppositely charged core and guest particles experience attractive electrostatic forces and generate composite particles. Preliminary experiments of electrostatic microencapsulation were performed using Anionic Exchange Resin (AG 1-X8) as the host particle and Red Toner (Omega 4000) as the guest particles. An electrostatic microencapsulation tower has been designed for generation of composite particles using particles of different particle size distribution

Twenty-First Century Research Needs in Electrostatic Processes Applied to Industry and Medicine

From the early century Nobel Prize winning (1923) experiments with charged oil droplets, resulting in the discovery of the elementary electronic charge by Robert Millikan, to the early 21st century Nobel Prize (2002) awarded to John Fenn for his invention of electrospray ionization mass spectroscopy and its applications to proteomics, electrostatic processes have been successfully applied to many areas of industry and medicine. Generation, transport, deposition, separation, analysis, and control of charged particles involved in the four states of matter: solid, liquid, gas, and plasma are of interest in many industrial and biomedical processes. In this paper, we briefly discuss some of the applications and research needs involving charged particles in industrial and medical applications including: (1) Generation and deposition of unipolarly charged dry powder without the presence of ions or excessive ozone, (2) Control of tribocharging process for consistent and reliable charging, (3) Thin film (less than 25 micrometers) powder coating and Powder coating on insulative surfaces, (4) Fluidization and dispersion of fine powders, (5) Mitigation of Mars dust, (6) Effect of particle charge on the lung deposition of inhaled medical aerosols, (7) Nanoparticle deposition, and (8) Plasma/Corona discharge processes. A brief discussion on the measurements of charged particles and suggestions for research needs are also included

Evaluation studies of a sensing technique for electrostatic charge polarity of pharmaceutical particulates

Electrostatic charge due to inter-particle and particle-wall contacts may generate significant hazards during the processing of particulates within the pharmaceutical industry. Although charge behaviour of particulates is erratic and not easy to predict, it would be desirable to characterise the tendency of tribocharging prior to manufacturing. The work reported in this paper concentrates on a new and novel techniques for the detection of the active ingredient and excipient in a bipolar material. Three different case studies are presented for demonstration of the applicability of the method in different practical situations. Work confirmed through an experimental rig set-up indicates that materials that accumulate opposite charge via contact and rubbing can be detected from their charge sign as well as their relative magnitude. The results reported clearly demonstrated that the developed method for charge characterisation is a useful tool to understand how the charges are distributed in a population of particles showing a number of advantages over conventional methods

Neural network models as a management tool in lakes

A research was made on the potential use of neural network based models in eutrophication modelling. As a result, an algorithm was developed to handle the practical aspects of designing, implementing and assessing the results of a neural network based model as a lake management tool. To illustrate the advantages and limitations of the neural network model, a case study was carried out to estimate the chlorophyll-a concentration in Keban Dam Reservoir as a function of sampled water quality parameters (PO4 phosphorus, NO3 nitrogen, alkalinity, suspended solids concentration, pH, water temperature, electrical conductivity, dissolved oxygen concentration and Secchi depth) by a neural network based model. Alternatively, the same system was solved with a linear multiple regression model in order to compare the performances of the proposed neural network based model and the traditional linear multiple regression model. For both of the models, the linear correlation coefficients between the logarithms of observed and calculated chlorophyll-a concentrations were calculated. The correlation coefficient R, the best linear fit between the observed and calculated values, was evaluated to assess the performances of the two models. R values of 0.74 and 0.71 were obtained for the neural network based model and the linear multiple regression model, respectively. The study showed that the neural network based model can be used to estimate chlorophyll-a with a performance similar to that of the traditional linear multiple regression method. However, for cases where the input and the output variables are not linearly correlated, neural network based models are expected to show a better performance

Development of water quality management strategies for the proposed Isikli reservoir

A two-dimensional laterally averaged hydrodynamic and water quality model (CE-QUAL-WS) is used to simulate the water quality behavior in the proposed Isikli Reservoir of the Ankara Water Supply System to determine appropriate strategies for the management of water quality

ASSESSMENT OF SOIL ACIDIFICATION - A CASE-STUDY

The Menemen-Aliaga-Foca region on the northwestern Aegean coast of Turkey near Izmir, is under the influence of air emissions originating from various industrial establishments. In this article, the long-term acidification impacts of these industrial emissions on the agricultural and forest soils of the region were studied by using qualitative and quantitative soil acidification assessment approaches. The relevant characteristics of the regional soils were determined experimentally and the number of years required to reach certain critical soil pH levels were estimated. Predictions were also made regarding the improvements expected in the future when the existing industries comply with the emission standards stipulated by the currently effective legislation