Modeling Bromate Formation During Ozonation

Bromate formation has been identified as a significant barrier in the application of ozone during water treatment for water sources that contain high levels of bromide. Bromate has been identified as a possible human carcinogen and bromate levels in drinking water are strictly controlled at 10 μg/L in most developed countries. Various models have been proposed to model bromate formation during ozonation based on raw water quality, ozone dose and contact time. Two main approaches for modeling have been used: an empirical regression modeling methodology and kinetic-based methodology. Currently, the benefit of the bromate models lies in their ability to show how process parameters may impact on the amount bromate formed.     

Estimating the Bubble Point Pressure and Formation Volume Factor of Oil Using Artificial Neural Networks

The phase performance of hydrocarbons is a very complicated behavior that hydrocarbons show at the time of phase change or when they remain in a particular phase. Process design is almost impossible without a good understanding of this behavior. Artificial Neural Networks have been widely utilized for engineering applications during the last two decades. Two models are presented for the prediction of the bubble point pressure and the oil formation volume factor for hydrocarbon mixtures using the Artificial Neural Networks (ANNs) approach. For this purpose, five‐layer neural networks were designed and trained using 106 experimental data points. After the training step, 9 experimental data points were also used for the model evaluation step and as a reliability check. The output of the models for both the training and predicted data are compared with the empirical equations of Standing, Glaso and Marhoun. It is concluded that the ANNs approach has an excellent capability for these purposes compared to the conventional methods.     

Survey of Seawater Intrusion in the Pearl River Basin and Modeling Bromate Formation during Ozonation of the Raw Water

Bromate formation has been identified as a significant barrier in the application of ozone during water treatment the downstream region of the Pearl River Basin that contains high levels of bromide. Seawater intrusion will increase bromide concentration in the inshore surface water. In this study, seawater intrusion in the Pearl River Basin was surveyed and modeling bromate formation during ozonation of the raw water affected by seawater intrusion was studied. Bromate formation models were developed to simulate the effects of the characteristics of water quality and the operating parameters of treatment processes on bromate formation during preozonation process and postozonation process. The results show that the downstream of the Pearl River Basin is affected seriously by seawater intrusion and the bromide mainly comes from seawater. Some empirical models were developed to estimate the concentration of bromate in ozonated surface raw water affected by seawater intrusion during the treatment process.     

Threshold Levels for Bromate Formation In Drinking Water

Ozone is a sufficiently strong oxidant to cause the oxidation of bromide ion and formation of bromate ion. In this study, bromate ion formation in a wide variety of drinking water sources was analyzed, with bromate ion formed in all sources under drinking water treatment conditions. Threshold levels for pH, bromide ion concentration, and ozone dose were found to be source-specific. Two non-linear empirical models were developed to predict bromate ion formation; these models are easy to use and require only several water quality and treatment variables. The models were tested against several literature data and a good simulation was found in other bench-scale tests, whereas the model tended to under-predict bromate ion formation in pilot-scale and full-scale programs.     

Bromate in Drinking Water A problem in Switzerland?

Ozonation of bromide-containing waters causes the formation of bromate which is considered to be potentially carcinogenic. An investigation in Switzerland on water works using ozone (85) has shown that the new drinking water standard of 10?µg/L for bromate is generally not exceeded. This is mainly due to the relatively small bromide concentrations which are typically below 25?µg/L. There is a characteristic relationship between bromate formation and the ozone exposure in a particular water type. This can be used to estimate the integral ozone exposure from the bromate formation which allows the assessment of the efficiency of the disinfection. This new concept is illustrated by means of two examples.     

人工神经网络在材料科学领域的应用

在分析神经网络基本理论的基础上,通过列举神经网络在高分子、金属、合金等材料研究中的应用,分析讨论了其在材料领域中的研究进展情况和存在的问题,展望了人工神经网络在该领域中的发展前景.     

A Survey of Bromate Ion in European Drinking Water

A one-year programme of research on the formation of bromate ion and organobrominated compounds by water ozonation was initiated recently between four French water treatment companies (C.G. Eaux, Lyonnaise des Eaux-Dumez, SAUR and SAGEP), one Spanish company (SGAB), the IARC, the KIWA, the WRc and the University of Poitiers. The programme comprises five aspects. The objective of this paper is to present the entirety of data from the following aspects: (I) inventory of the bromate ion content in distributed drinking water, and (ii) study of the evolution of bromate ion during the water treatment process.     

Bromate Surveys in French Drinking Waterworks

Two bromate surveys were made recently in order to evaluate the frequency of bromate appearance in drinking waters issued from waterworks including one or two ozonation steps. The First survey was carried out on 47 waterworks. Two sampling campaigns were analyzed in cool and warm seasons. The objective of the second survey was to follow, during 4 to 10 months, at 12 selected waterworks.

The aim of this paper is to present the data obtained and to try to model for some waterworks the bromate formation by means of some important parameters (Br, O₃/DOC, T° and pH) of water to ozonate.

The main conclusion is that the bromate presence in distributed drinking waters is a reality for waterworks using ozonation steps, especially in warm period of the year. In the case of some waterworks, disinfection by sodium hypochlorite increased bromate levels in distributed water.

As shown by others on a laboratory-scale level, a multi-linear regression allows us the prediction of the bromate formation from some determining parameters, for some waterworks. However, the poor values of the linear regression lead us to have some doubts about its universal application in the real situation of an operating waterworks. A better evaluation of “C.t” will be required in the future in order to get a better prediction by the use of multi linear regression.     

Minimizing Bromate Concentration by Controlling the Ozone Reaction Time in a Full-Scale Plant

The latest European Directive 98/83/CE (5 December 1998), concerning the quality of water intended for human consumption, has set a two-stage parametric value for bromate. Bromate concentration will comply with 25 μg/L after December 25, 2003, and with 10 μg/L after December 25, 2008. Bromate formation in water is generally due to bromide oxidation during the ozonation stage. Due to higher temperatures, this latter parametric value is often exceeded in summer. Minimizing bromate levels is thus a crucial problem for drinking water producers. A bromate-minimizing strategy consists of shortening the reaction time between ozone and water. This can be done by neutralizing dissolved ozone residual with bisulfite at the exit of the ozone reactor chamber and/or by managing the introduction of ozone in different chambers depending on the water flow rate. This is only possible if, in our case, the disinfection goal for ozone is respected toward bacteria and viruses. The CT value must comply with 1.6 mg/min/L. In our plants, this value could be very large due to high contact time in and after leaving the ozone reactors.     

Inhibition of Nano-Metal Oxides on Bromate Formation during Ozonation Process

Simulation studies in pure water were conducted to investigate the effect of nano-metal oxides on bromate (BrO₃^?) formation as catalysts and the catalytic mechanism. Results indicated that compared to ozonation alone, both nano-SnO₂ and nano-TiO₂ could inhibit the formation of bromate during ozonation process. The inhibition efficiency of BrO₃^? formation by nano-TiO₂ enhanced with the increasing of ozone dosage and the decreasing of nano-TiO₂ dosage, Br^? concentrations and the pH value. Possible BrO₃^? minimization mechanism was that nano-TiO₂ accelerated the decomposition of the dissolved O₃ into OH radicals, which rapidly generated H₂O₂, and reduced HOBr/OBr^? to Br^?.     

Bromate Formation during Ozonation of Bromide Containing Drinking Water- a Pilot Scale Study

The effect of bromide ion concentration, pH, temperature, alkalinity, and hydrogen peroxide content on bromate formation was studied. Increase in pH was found to give the greatest increase in bromate formation. Also increase in the ozonation temperature, bromide ion concentration and hydrogen peroxide content increased the observed bromate concentration. Only increased alkalinity decreased the bromate formation during the ozonation experiments. Bromate formation exceeded the EU limit value for bromate ion, 10 μg/l, when the initial bromide ion concentration was around 100 μg/l, except for the alkalinity of 1.4 mmol/1, when the bromate formation was 9.4 μg/l.     

Conditions Affecting Bromate Formation During Ozonation of Bottled Water

Bromate concentration, ozone lifetime and ozone exposure (CT value) measured in bottled water in full-scale runs, were in good agreement to those measured in laboratory experiments. Ozone lifetime in bottled water was high enough to result in a CT value greater than 5 even for ozone dose as low as 0.1?mgO₃/L, at a water pH of 7.6. Bromate was gradually formed during the ozone lifetime. Bormate formation and ozone exposure were significantly influenced by pH. In full-scale runs, an ozone dose of 0.15?mgO₃/L at pH=7.6 resulted in a CT of 10.3 and a bromate concentration of 13.5?µg/L, while at pH=7.25 the values of CT and BrO₃ ^? were 12.6 and 9.6?µg/L, respectively. By decreasing further the pH to 6.8, an increase of CT value to 15.8 and a reduction of bromate to 5.5?µg BrO₃ ^?/L were observed. In addition, results in full-scale runs showed that ozone exposure and bromate concentrations were linearly related to ozone dose in the working range of 0.1 to 0.25?mgO₃/L.     

Prediction of Bromate Removal in Drinking Water Using Artificial Neural Networks

In treatment of natural water resources, bromide transforms into carcinogenic bromate, especially during the ozonation process. Adsorption was used in the experimental part of this study to remove this harmful compound from drinking water. For this purpose, technically, HCl-, NaOH-, and NH₃-modified activated carbons were used. Scanning Electron Microscopy (SEM) and Brunauer–Emmett–Teller (BET) analyses were carried out within the characterization study. Moreover, the effects of diameters and heights of adsorption columns, flowrate, and particle size of adsorbent were investigated on the removal amounts of bromate. Optimum conditions were obtained from the experiments, and regional/real samples were collected and analyzed. After the experiments, an artificial neural network (ANN) was used to predict bromate removal percentage by using the observed data. Within this context, a feed-forward back-propagation ANN was chosen in this study. Additionally, the transfer function was selected as tangent sigmoid and 3 neurons were used in the hidden layer. Particle size and amount of the activated carbon, height and diameter of the column, volumetric flowrate, and initial concentration were selected as the input variables. Bromate removal percentage was selected as the output. It was found that the model an R value of 0.988, RMSE value of 3.47 and mean absolute percentage error (MAPE) of 5.19% in the test phase.     

Prediction of Ozone Concentration in Ambient Air Using Multilinear Regression and the Artificial Neural Networks Methods

ABSTRACT

This article presents the results of the statistical modeling of the ground-level ozone concentration in the air in the close vicinity of the city of Zrenjanin (Serbia). This study is aimed at defining the dependence of ozone concentration on the following predictors: SO₂, CO, H₂S, NO, NO₂, NOx, PM₁₀, benzene, toluene, m,p-Xylene, o-Xylene and ethylbenzene concentration in the air, as well as on the meteorological parameters (the wind direction, the wind speed, air pressure, air temperature, solar radiation, and RH). Multiple linear regression analysis (MLRA) and artificial neural networks (ANNs) were used as the tools for the mathematical analysis of the indicated occurrence. The results have shown that ANNs provide better estimates of ozone concentration on the monitoring site, whereas the multilinear regression model once again has proven to be less efficient in the accurate prediction of ozone concentration.     

The Influence of the Removal of Specific NOM Compounds by Anion Exchange on Ozone Demand,Disinfection Capacity,and Bromate Formation

This research on a pilot scale focuses on the reaction of ozone with natural organic matter (NOM) for three water qualities with different dissolved organic carbon (DOC) concentrations and NOM compositions, obtained after several stages of an anion exchange process. It was shown that for the same ozone dosage per DOC, the ozone demand was higher, less bromate was formed and a lower disinfection capacity was reached for water containing mainly humic substances, than for water where the humic substances were partly removed. It can be concluded that NOM composition, specifically the humic substances, influences the ozone demand, disinfection capacity and bromate formation.     

Results Of Bromide And Bromate Monitoring At Several Water Treatment Plants

The ozonation of water is a widely used technology within the water industry. Recent toxicological studies have shown that high bromate ion intake induces a high incidence of tumors in rats. Bromate ion formation from oxidation of water containing bromide ion was examined at nine treatment plants and one pilot. We found bromate ion (> 2 μg/L) in drinking water containing bromide ion when treated with ozone at pH greater than 7.0, even in the presence of ammonia. Bromate ion formation increased with the applied ozone dose. But bromate ion must be considered also as a byproduct of commercial sodium hypochlorite solutions. Under commercial conditions, chlorine dioxide and granular activated carbon had no effects on bromate levels.     

Bromate Control by Dosing Hydrogen Peroxide and Ammonia during Ozonation of the Yellow River Water

Ozonation of the downstream Yellow River water yields bromate with concentrations higher than China regulations. Bench tests demonstrated that dosing ammonia or hydrogen peroxide alone could not control the bromate concentration to below 10 μg/L. A pilot study showed that dosing hydrogen peroxide into the inherently ammonia-containing raw water at a dosage lower than 1.7 could effectively reduce the bromate concentration to below the detection limit when the ozone dosage was between 2 and 2.5 mg/L.     

基于人工神经网络的高聚物流变性能预测系统

针对影响高聚物流变性能因素的复杂性,利用VB与MATLAB混合编程将人工神经网络技术移植于应用软件,实现人工神经网络技术的各项功能,通过对采集的样本数据进行网络训练,开发了高聚物流变性能参数预测系统。经验证,系统可将预测精度误差,控制在5％以内。     

Moisture Content Prediction in the Switchgrass (Panicum virgatum) Drying Process Using Artificial Neural Networks

This article proposes two artificial neural network (ANN)-based models to characterize the switchgrass drying process: The first one models processes with constant air temperature and relative humidity and the second one models processes with variable air conditions and rainfall. The two ANN-based models proposed estimated the moisture content (MC) as a function of temperature, relative humidity, previous MC, time, and precipitation information. The first ANN-based model describes MC evolution data more accurately than six mathematical empirical equations typically proposed in the literature. The second ANN-based model estimated the MC with a correlation coefficient greater than 98.8%.     

Comparative Assessment of Bromate Control Options

Various bromate control options were assessed through an intensive pilot testing program, performed with a four-cell bubble contactor, and focused on intermediate ozonation of conventionally-treated sand-filtered water. Both acid addition and ammonia addition independently provided good bromate reduction, with their combinational addition providing no further reduction. On a CT basis, the use of a static mixer did not increase bromate formation, while staged ozonation enhanced bromate formation over single stage application.