A process for treatment of an effluent, which comprises an injection (3) into the effluent, of CO.sub.2 or of a mixture comprising CO.sub.2, comprising: a. a measurement of the pH (6) of the effluent is carried out upstream of the point of injection of the CO.sub.2 or of the mixture in the process; b. a curve of dose of CO.sub.2 to be injected as a function of the pH of a medium for a predetermined volume in litres or in cubic metres was determined beforehand, and this curve is entered into a regulator or automaton (4) capable of controlling the operation of the process; c. the presence of a flow of effluent to be treated is detected, and the dose of CO.sub.2 or of mixture, determined by said curve and multiplied by the flow rate of effluent to be treated, is injected.

Systems and methods to enhance the removal of inorganic contaminants, including metals, from hydrocarbon feedstocks at a refinery. One or more embodiments of such systems and methods may be used to provide a renewable hydrocarbon feedstock having a reduced amount of metal contaminants. The reduction of metal contaminants in the renewable hydrocarbon feedstock mitigates catalyst fouling and/or deactivation during downstream refinery processing of the renewable hydrocarbon feedstock.

A cooperative learning system usable for process monitoring in which a monitoring model is provided for each of plural processes arranged in chronological order at predetermined transition time period intervals. The system stores, in chronological order, first monitoring data in a first process, second monitoring data in a second process, and at least one monitoring result from the first process output from a first monitoring model using the first monitoring data as an input parameter. The system performs parent model learning processing for the first monitoring model using the first monitoring data and the monitoring result from the first monitoring model, and performs child model learning processing for a second monitoring model using a monitoring result from the first monitoring model at a first time as teacher data and using the second monitoring data at a second time shifted from the first time by a transition period as an input parameter.

This disclosure describes systems and methods for providing water to a user for consumption. Systems of the present disclosure can include a water management system including one or more a water treatment flow path for receiving source water, disinfection unit(s), additive unit(s), sensor(s) for maintaining various water conditions. Additionally, water management, treatment and/or storage systems including controller(s) and associated methods of operating are also described for dispensing water to a user.

The subject invention provides methods for improving the treatment of effluents and waste matter produced during food processing and production. In particular, the subject invention provides methods for remediating fats, oils and greases (FOG), suspended solids, proteins, and other organic matter that are discharged from plants that process, for example, meats, poultry, seafood, dairy and plant-based oils. The methods of the subject invention utilize a customized microbial cocktail comprising facultative anaerobes, in combination with one or more microbial growth by-products, e.g., enzymes and/or biosurfactants, to digest and/or liquefy food processing waste matter.

According to one or more embodiments, sulfate ions may be removed from seawater to form an injection fluid by a method including passing the seawater and formation water to a mixing tank. The seawater may comprise sulfate ions. The formation water may comprise barium ions. The seawater and formation water may be passed to the mixing tank in a ratio determined by a computerized geochemical model. The method may further include mixing the seawater and formation water to form a mixed fluid and passing the mixed fluid to a clarifier, where a barium sulfate precipitate may be formed and at least a portion of the barium sulfate precipitate may be separated from the mixed fluid. The method may further include passing the mixed fluid to a microfiltration system, where at least a portion of the barium sulfate precipitate may be removed from the mixed fluid to form an injection fluid.

The present invention relates to a system and process for treating a feedwater wherein the system includes at least one RO or nanofiltration unit that receives a feed under high pressure and produces a concentrate that is directed to and held at low pressure in a concentrate accumulator. Generally the permeate or the inlet feedwater is maintained at a constant flow rate. Periodically the system is switched from a mode 1 or normal operating process to a mode 2 where the concentrate is drained from the concentrate accumulator. However, in mode 2, the feedwater is still directed into the system and through the RO or nanofiltration unit which produces the permeate and the concentrate.

A Dielectric Barrier Discharge system controller for controlling a fluid treatment by a Dielectric Barrier Discharge system is provided. Therein, the strength of an effect caused by a discharge created by the Dielectric Barrier Discharge system is monitored, and the generation of high-voltage pulses by the high-voltage pulse generator is controlled. The controlling of the generation of the high-voltage pulses is adapted based on the received sensor data.

A water quality monitoring and maintaining system includes a water quality monitoring instrument, a process system and a water quality treating module. The water quality monitoring instrument is used for collecting a plurality of water quality data of a monitored water in a monitored environment. The process system is used for processing an error correcting operation and a storing operation for the plurality of water quality data collected by the water quality monitoring instrument, thereby establishing a water quality data model. The water quality treating module is used for adjusting the plurality of water quality data of the monitored environment according to the water quality data model.

A plant operation support system supports an operation of a plant. The plant operation support system includes a fluctuation prediction device configured to predict a fluctuation of an element which is input to the plant, and a simulation device configured to simulate a behavior of the plant using a fluctuation of the element predicted by the fluctuation prediction device and data which is obtained from the plant.