A Step Forward to the Characterization of Secondary Effluents to Predict Membrane Fouling in a Subsequent Ultrafiltration

The intelligent prediction of membrane fouling during membrane filtration by mathematical models and artificial intelligence models

Recently, membrane separation technology has been widely utilized in filtration process intensification due to its efficient performance and unique advantages, but membrane fouling limits its development and application. Therefore, the research on membrane fouling prediction and control technology is crucial to effectively reduce membrane fouling and improve separation performance. This review first introduces the main factors (operating condition, material characteristics, and membrane structure properties) and the corresponding principles that affect membrane fouling. In addition, mathematical models (Hermia model and Tandem resistance model), artificial intelligence (AI) models (Artificial neural networks model and fuzzy control model), and AI optimization methods (genetic algorithm and particle swarm algorithm), which are widely used for the prediction of membrane fouling, are summarized and analyzed for comparison. The AI models are usually significantly better than the mathematical models in terms of prediction accuracy and applicability of membrane fouling and can monitor membrane fouling in real-time by working in concert with image processing technology, which is crucial for membrane fouling prediction and mechanism studies. Meanwhile, AI models for membrane fouling prediction in the separation process have shown good potential and are expected to be further applied in large-scale industrial applications for separation and filtration process intensification. This review will help researchers understand the challenges and future research directions in membrane fouling prediction, which is expected to provide an effective method to reduce or even solve the bottleneck problem of membrane fouling, and to promote the further application of AI modeling in environmental and food fields.

Estimation and sensitivity analysis of fouling resistance in phosphoric acid/steam heat exchanger using artificial neural networks and regression methods

One of the most frequent problem in phosphoric acid concentration plant is the heat exchanger build-up. This problem causes a reduction of the performance of this equipment and an increase of energy losses which lead to damage the apparatus. In this study, estimation of fouling resistance in a cross-flow heat exchanger was solved using a linear [Partial Least Squares (PLS)] and non linear [Artificial Neural Network (ANN)] methods. Principal Component Analysis (PCA) and Step Wise Regression (SWR) were preceded the modeling in order to determine the highest relation between operating parameters with the fouling resistance. The values of correlation coefficient (r2) and predictive ability which are equal to 0.992 and 87%, respectively showed a good prediction of the developed PLS model. In order to improve the results obtained by PLS method, an ANN model was developed. 361 experimental data points was used to design and train the network. A network containing 6 hidden neurons trained with Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm and hyperbolic tangent sigmoid transfer function for the hidden and output layers was selected to be the optimal configuration. The Garson's equation was applied to determine the sensitivity of input parameters on fouling resistance based on ANN results. Results indicated that acid inlet and outlet temperatures were the high relative important parameters on fouling resistance with importance equal to 56% and 15.4%, respectively.

Biological Oxygen-dosed Activated Carbon (BODAC) filters - A bioprocess for ultrapure water production removing organics, nutrients and micropollutants

Biological oxygen-dosed activated carbon (BODAC) filters in an Ultrapure water plant were demonstrated to have the potential to further treat secondary wastewater treatment effluent. The BODAC filters were operated for 11 years without carbon regeneration or replacement, while still functioning as pre-treatment step to reverse osmosis (RO) membranes by actively removing organic micropollutants (OMPs) and foulants. In this study, the removal of nutrients and 13 OMPs from secondary wastewater treatment effluent was investigated for 2 years and simultaneously, the granules' characterization and microbial community analysis were conducted to gain insights behind the stable long-term operation of the BODAC filters. The results showed that the BODAC granules' surface area was reduced by ∼70 % of what is in virgin carbon granules and covered by biofilm and inorganic depositions. The BODAC filters reduced the concentration of soluble organics, mainly proteins, performed as an effective nitrification system, and almost completely removed manganese. During the 2 years of observation, the filters consistently removed some OMPs such as hydrochlorothiazide, metoprolol, sotalol, and trimethoprim by at least 70 %. Finally, through microbial community analysis, we found that nitrifying and manganese-oxidizing bacteria were detected in high relative abundance on BODAC granules, supporting BODAC performance in removing OMPs and manganese as well as converting nitrogenous species in the water.

Stakeholder Expectation of Corporate Social Responsibility Practices: A Case Study of PWiK Rybnik, Poland

Practices of corporate social responsibility (CSR), especially in organizations providing key services, related to the supply of fuel, water and energy, are extremely important from the point of view of identifying stakeholders with the functioning of enterprises in line with the principles of a closed loop economy. The article discusses the origins and evolution of the concept of corporate social responsibility, with particular emphasis on the water supply and sewage industry. The research problem was the perception and expectations of stakeholders toward prosocial activities of PWiK Rybnik (Sewage and Water Supply Ltd. Rybnik). The hypothesis assumed in the study was that the external stakeholders of PWIK Rybnik positively assess the company’s involvement in the tasks carried out as part of corporate social responsibility, they notice the involvement in educational activities and additional initiatives of PWIK that improve the quality of life of its inhabitants. For the purpose of this study, a quantitative method was used. For the purpose of the survey, the authors’ questionnaire “Survey of customers’ opinions on the activities undertaken by PWiK Rybnik” was created. The surveys conducted confirmed the hypothesis that the external stakeholders of PWIK Rybnik positively assess the company’s involvement in the tasks performed as part of corporate social responsibility; they notice the involvement in educational activities and additional initiatives of PWIK that improve the quality of life of its inhabitants. The results of the research made it possible to formulate guidelines for the operation of water supply and sewage companies in accordance with corporate social responsibility in the light of the opinions of their stakeholders.