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Industrial Wastewater Reuse & ZLD

1,350 m³/d Pickling Wastewater Metals & Hardness Removal

This 1,350 m³/d steel pickling wastewater project combines iron-removal and softening pretreatment, tubular membrane separation, nanofiltration salt separation, reverse osmosis concentration, and evaporation and crystallization for water reuse and salt resource recovery.

Project scale
1,350 m³/d
Feed / process stream
Steel pickling wastewater
Main process stages
Iron-removal and softening pretreatment → PEK tubular membranes → nanofiltration salt separation → reverse osmosis concentration → evaporation and crystallization
1,350 m³/d steel pickling wastewater tubular membrane system
Project-related system image. Customer identity and operating-performance data are not published.

01 · Engineering task

What the project needed to resolve

This 1,350 m³/d steel pickling wastewater project combines iron-removal and softening pretreatment, tubular membrane separation, nanofiltration salt separation, reverse osmosis concentration, and evaporation and crystallization for water reuse and salt resource recovery.

02 · Main process stages

The overall project process route

Iron-removal and softening pretreatment → PEK tubular membranes → nanofiltration salt separation → reverse osmosis concentration → evaporation and crystallization

Configuration, operating windows, and guarantees are not transferred automatically to a new duty.

03 · Plum scope

Plum’s full-process scope of supply

Plum supplied the full-process treatment systems for this project, covering pretreatment, PEK tubular membranes, nanofiltration salt separation, reverse osmosis concentration, and evaporation and crystallization.

04 · Public project facts

Facts available for preliminary comparison

The project treats steel pickling wastewater at a scale of 1,350 m³/d. The overall process includes iron-removal and softening pretreatment, PEK tubular membranes, nanofiltration salt separation, reverse osmosis concentration, and evaporation and crystallization. Customer identity and operating-performance data are not published.