Energy modelling and carbon footprint of r-NF & NF-270-400: raw results and indicators

Published: 1 August 2022| Version 1 | DOI: 10.17632/ryfb8h9rzj.1
Jorge Senan,


The following datasets compile the Membranes paper results and intermediate results of the paper submitted in Membranes Journal. -main_simulations_energy_mass.csv: (Pot_Qi: feed flow (in m3·h-1), Pot_n: number of elements, Pot_CF: Water recovery factor, Perm: permeability (in L·m2·h-1·bar-1) ; Prin: feed pressure (in bar) , SEC: specific energy consumption (in kwh·m-3); Vin: feed velocity (in m·s-1) ; Rein: Reynolds number in feed flow, Qp: product flow (in m3·h-1), Qconc: Concentrate flow (in m3·h-1) , Vconc: cncetrat3e flow velocity (in m·s-1) ; Reconc: reynolds numeber in concentrate flow; Prlosses : Pressure losses in the PV (in bar) , Pr_conc: Pressure at concentrate flow: in bar). -Years_table.csv: describes the service lifespan in which the r-NF and the NF-270 have the same CF (Pot_Qi Pot_n Pot_CF Mix `Natural gas` Solar Wind `Gravity driven`). -CF_2.csv summarises the carbon footprint results in kg CO2-eq of the main processes and energy sources. the energy processes are kg CO2-eq per kwh and membranes procesess are in kg CO2-eq per module.



Universitat de Vic - Universitat Central de Catalunya, Universitat de Girona, Fundacion IMDEA Agua


Life Cycle Assessment, Recycling, Life Cycle Thinking