Defluroridation using a continuous electrocoagulation (EC) reactor

Electrocoagulation (EC) is a process of passing a steady electric current through liquid using aluminium or iron electrodes to remove impurities in water. When aluminium electrodes are used, the aluminium goes into solution at the anode and hydrogen gas is released at the cathode and dissolution of A1 anodes produces aqueous aluminium species. Experiments were undertaken to investigate the effects of the different parameters such as: current density (12.5-50 A/m2), flow rate (150-400 mL/min), initial pH (4-8), and initial fluoride concentration (5-15 mg/L) on the fluoride removal efficiency in a continuous flow electrocoagulator. The experimental results showed that for an initial fluoride concentration of 10 mg/L when flow rates varied from 150 to 300 mL/min, the residual fluoride concentration reached to less than 1 mg/L when the current densities were respectively increased from 18.75 A/m2 to 50A/m2. It appears that for higher defluoridation efficiency, the current density needs to be increased when flow rate is increased. The composition of the sludge produced was analysed using X-ray diffraction (XRD) spectrum. The strong presence of the hydroxyl-aluminium in the final pH range between 6 and 8, which maximizes the formation of fluoro-hydroxide aluminium complex, is the main reason for defluoridation by electrocoagulation. The results obtained showed that the continuous flow electrocoagulation technology is an effective process for defluoridation of potable water supplies and could also be utilized to the defluoridation of industrial wastewater

On-Site Sequencing \u27Anaerobic-Anoxic-Aerobic/Biological\u27 Process for Wastewater Reuse

The increasing scarcity of water around the world has become more evident at the beginning of this century. Management of this valuable resource is not only an environmental issue, it is also an important economic issue and its management has significant social implications. Moreover, the predicted decreases in annual rainfall around Australia, threatening the image of providing a sustainable water source for a majority of its population. The solution partly lies through the promotion of water conservation strategies involving wastewater recycling and reuse. A pilot scale 5-stage wastewater treatment system was investigated in regards to its feasibility for removing Biochemical Oxygen Demand (BOD5), Total Suspended Solids (TSS), Turbidity, Total Kjeldahl Nitrogen (TKN), Ammonia Nitrogen (NH3-N), Nitrate Nitrogen (N03-N), Organic Nitrogen (Org-N) and Total Phosphorus (TP) for the period of one year from Jan.2004 to Dec. 2004. The system readily reduced the concentration of BOD5 from average 189 mg/L to 5 mg/L (removal rate of 94%), TSS from average 216 mg/L to 3 mg/L (removal rate of 97%) and Turbidity from average 105 NTU to 2 NTU (removal rate of 96%). The removal rate for nitrogen and phosphorus was also quite satisfactory and this system was capable of reducing the Total Nitrogen (TN) from average of 41 mg/L to 5 mg/L (removal rate of 86%) and TP from average of 9 mg/L to 2 mg/L (removal rate of 81%)

Simulation of Water and Contaminant Transport Through Vadose Zone - Redistribution System

Movement of water in vadose zone, mainly focusing on infiltration and percolation that involves percolation of water under gravity from soil surface and redistribution which is the capillary rise of water movement upwards, is presented. In the global hydrologic cycle, 76% of the precipitating water enters the soil via percolation-infiltration, which leads to the downward movement of water (L’vovich 1974). The water used by natural processes, can move downwards due to infiltration and lift from groundwater table during natural redistribution process. The forecasting of water movement in unsaturated infiltration redistribution system is linked between soil hydraulic properties and hydrologic condition of natural surface water system. The understanding of water movement processes associated with infiltration and redistribution has a number of practical applications. One such application is to predict the fate and transport of materials through soil including nutrients, organic carbon and microbes under natural processes, which in turn will help in developing appropriate management plans for irrigation, fertilizer application and waste disposal on land

Investigating an innovative sea-based strategy to mitigate coastal city flood disasters and its feasibility study for brisbane, australia

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This study examines an innovative Coastal Reservoir (CR) technique as a feasible solution for flood adaptation and mitigation in the Brisbane River Estuary (BRE), Australia, which is vulnerable to coastal flooding. The study analysed the operation of a CR by using the MIKE 21 hydrodynamic modelling package. The 2D hydrodynamic model was calibrated and validated for the 2013 and 2011 flood events respectively, with a Nash-Sutcliffe coefficient (Ens) between 0.87 to 0.97 at all gauges. River right branch widening and dredging produced a 0.16 m reduction in water level at the Brisbane city gauge. The results show that by suitable gate operation of CR, the 2011 flood normal observed level of 4.46 m, with reference to the Australian Height Datum (AHD) at Brisbane city, could have been reduced to 3.88 m AHD, while under the improved management operation of the Wivenhoe Dam, the flood level could be lowered to 4 m AHD at Brisbane city, which could have been reduced with CR to 2.87 m AHD with an overall water level reduction below the maximum flood level. The results demonstrated that the innovative use of a CR could considerably decrease the overall flood peak and lessen flood severity in the coastal city of Brisbane

Prediction of nutrient concentrations in urban storm water

Excessive quantities of nutrients in urban storm-water runoff can lead to problems such as eutrophication in receiving water bodies. Accurate process based models are difficult to construct due to the vast array of complex phenomena affecting nutrient concentrations. Furthermore, it is often impossible to successfully apply process based models to catchments with limited or no sampling. This has created the need for simple models capable of predicting nutrient concentrations at unmonitored catchments. In this study, simple statistical models were constructed to predict six different types of nutrients present in urban storm-water runoff: ammonia (NH3), nitrogen oxides (NOx), total Kjeldahl nitrogen, total nitrogen, dissolved phosphorus, and total phosphorus. Models were constructed using data from the United States, collected as a part of the Nationwide Urban Stormwater Program more than two decades ago. Comparison between the models revealed that regression models were generally more applicable than the simple estimates of mean concentration from homogeneous subsets, separated based upon land use or the metropolitan area. Regression models were generally more accurate and provided valuable insight into the most important processes influencing nutrient concentrations in urban storm-water runoff

Techniques for predicting total phosphorus in urban stormwater runoff at unmonitored catchments

This paper investigates the applicability of using artificial neural network (ANN) and multilinear regression models to predict urban stormwater quality at unmonitored catchments. Models were constructed using logarithmically transformed environmental data. Violation of the assumption of data independence lead to the inclusion of insignificant variables when a straightforward stepwise regression was applied. To overcome this problem, cross validation was used to determine when to stop adding variables. Regression models calibrated using event mean concentration (EMC) as the dependent variable were more accurate than those using event load. Regression models developed on a regional subset of data were more accurate than the models developed on the entire data set. Even though regression and ANN models yielded similar predictions, regression modelling was considered to be a more applicable approach. Compared to ANN models, regression models were faster to construct and apply, more transparent and less likely to overfit the limited data

Prediction of long-term urban stormwater loads at single sites

Long-term total phosphorus loads from 17 urban catchments in the USA were predicted using five different measures of central tendency defining site mean concentration (arithmetic mean, geometric mean, median, harmonic mean and flow-weighted mean). Overall, the flow-weighted mean concentration produced the most accurate predictions of long-term loads. The geometric mean produced the second most accurate predictions. Along with the median and harmonic mean, the geometric mean predicted long-term load relatively well at most catchments exhibiting negative correlations between event mean concentration and total event runoff depth. However, they significantly underestimated long-term load at catchments exhibiting a positive correlation between these variables. Better estimates of long-term load at these two catchments were produced using the flow-weighted mean and arithmetic mean. However, the arithmetic mean tended to overestimate long-term load at the remainder of catchments

Dairy shed wastewater treatment by anaerobic digestion technology

Continued growth and consolidation of the livestock industry such as dairy industry has generated large-quantities and high-strength manure, which has long been identified as a major contributor to diffuse source pollution in Australia. However, conventional dairy shed wastewater treatment practices in Australia such as two pond systems still do not provide sufficient treatment. In addition, relevant laws and regulations in terms of nutrient management plans and manure solids disposal require new waste management approaches. Anaerobic digestion (AD) is an efficient, small footprint, cost effective and sustainable technology that should be applied in Australian dairy farms, and has the potential not only to minimise the environmental impacts but also to maximise resource recovery especially generation of useful renewable bio-fuel (methane) including wastewater reuse. In order to be able to design and operate efficiently anaerobic digestion systems, appropriate mathematical models need to be developed to observe and analyse the anaerobic process dynamics and accordingly optimize anaerobic digestion applications before investment of construction and installation. The present paper critically reviews AD technology in the context of dairy shed wastes and AD modelling. The necessity of AD application on Australian dairy farming is discussed, based on conventional dairy waste management practices and relevant laws and regulations. Also the advantages of AD technology are illustrated by comparing traditional and integrated dairy waste management practices. The unique characteristics of Australian dairy shed wastes, the knowledge gap and future trends of AD technology have been identified. As a result, it is known that AD technology should be extended to Australian dairy farming

Electrocoagulation (EC) technology for nitrate removal

High nitrate contamination in drinking water is a serious environmental pollutant, as it is generally a problem associated with anthropogenic activities. Sources of nitrate pollution include discharge of chemical fertilizers, human and animal wastes. Excessive application of agricultural fertilizers has been known to cause penetration of large quantities of nitrates into underground and surface waters. Nitrate is a stable and highly soluble ion with low potential for precipitation or adsorption. These properties make it difficult to remove using conventional water treatment method. Several methods have been proposed in the literature for the removal of nitrate. In this project, a laboratory batch electrocoagulation (EC) reactor was designed to investigate the effects of the different parameters, such as: electrolysis time, current value, and the pH of the solution on the nitrate removal efficiency. The influence of process parameters on denitrification was achieved using “synthetic” water. The results showed that at an operating current of 2.5A, the nitrate removal efficiency was 90% when initial nitrate concentration and electrolysis time respectively were kept at 45 mg/L -N and 90 min. The denitrification process is more efficient for pH ranging from 9 to 11. Further it is shown that a linear relationship exists between the electrolysis time for total nitrate removal and the initial nitrate concentration. It is concluded that the electrocoagulation technology for denitrification can be an effective process provided that the ammonia byproduct can be removed effectively

A general review of applications of artificial neural network to water industry

This paper presents case studies of applications of artificial neural network (ANN) to water industry including water treatment, water quality and water consumption. Overall, ANN was found to be superior to time series and multiple regression analysis for most applications. At the same time, however, ANN is a data driven model, so care has to be taken in preparing data for ANN models. Limitations of the current ANN study to coagulant dosages in water treatment plants are presented and further ANN improvements in this field are in progress