An approach was developed to configure treatment scenarios for a given industrial effluent based on pollutant composition, intended end use, available technologies, as well as environmental impact assessments of the scenarios. To overcome the complexity of configuring the industrial effluent treatment chain due to the variety of contaminants and diverse available treatment technologies, a decision tree was developed based on the best available technology tailored to pollutant types. A parametric life cycle inventory was developed for the operation phase of fifteen conventional and advanced treatment technology modules to facilitate a comparative environmental impact assessment, including parametric sensitivity and uncertainty analysis. The comparative modular life cycle assessment revealed the hotspots and contributions of fifteen treatment modules to the environmental impacts of treating of 1m3 effluent, with nanofiltration, reverse osmosis, and ion-exchange having the highest overall impacts, whereas cartilage, sand filtration, and UV have the lowest environmental impacts. Sensitivity analysis unveiled high sensitivity of midpoint and endpoint environmental impacts to energy, resin and chemical consumptions. This approach offers a foundational framework for further decision tree developments as a supporting tool for treatment configuration in the effluent treatment industry, as well as sustainability assessment of treatment scenarios derived from the decision trees. Modular treatment configuration integrated into a decision tree promises more flexibility in setting up fit-for-purpose treatment scenarios and conducting modular life cycle assessments for more sustainable effluent treatment.