A further closure of the water circuit in paper mills with a relative high optimization of their water network is limited by the increase of contamination in the water and runnability problems of the paper machine. Therefore, new strategies for saving water must be focussed on the treatment of final effluents of the paper mill, aiming to obtain high quality water that may replace fresh water use in some applications. An appropriate treatment train performed at pilot scale, consisting on a previous clarification stage followed by anaerobic and aerobic treatments, ultrafiltration, and reverse osmosis, made possible producing the highest water quality from the final effluent of the mill. Anaerobic pre-treatment showed very good performance assisting the aerobic stage on removing organics and sulphates, besides it produced enough biogas for being considered as cost-effective. Permeate recovery depended on the silica content of the paper mill effluent, and it was limited to a 50-60%. The reject of the membranes fully met the legislation requirements imposed to effluents arriving to municipal wastewater treatment plants.
Papermaking is an industrial process that is becoming more competitive nowadays. In this process there are numerous techniques and measurements to indicate paper quality. To increase competitiveness a good control of paper quality is needed through paper properties predictions from different process measurements. However, complex physico-chemical processes take place during papermaking, and thus, paper property predictions are not easy to obtain, especially in the wet-end area. In the wet end flocculation takes place, which will determine the floc properties during the formation of the sheet, and therefore, it will influence retention, drainage and formation. These strongly affect the runnability of the machine and the properties of the final product, and thus, using wet-end measurements for the predictions implies advanced data treatment. Artificial neural networks have been used in this article to predict newsprint paper properties from wet-end parameters. Results show that formation and strength properties can be robustly predicted from pulp properties at the headbox, flocculation parameters and machine speed.
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