Statistical analysis of air-gap membrane desalination experimental data: Hypothesis testing

• Data on membrane distillation are analyzed using methods of statistical hypothesis.
• Multiple comparison tests like F-test, Fisher's LSD, and Tukey's test are applied.
• Variance of data has dramatic effect on membrane selection process.
• Replication in membrane experimentation is of paramount importance.

Membrane distillation (MD) is a process in which the driving force for mass transfer is temperature gradient rather than conventional ones based on density, static pressure, chemical nature, affinity, and freezing point gradients. Using a porous hydrophobic membrane, MD comes into four configurations; direct contact, air gap, sweeping gas, and vacuum MD. The current technical literature shows a growing interest in experimental investigation of MD processes. In this work, a complete set of experimental data on air gap membrane distillation is analyzed using statistical methods. The experimental data involves a study of the effects of salt concentration on permeate flux for MgCl2, Na2SO4, and NaCl using three commercial membranes in AGMD unit. Hypothesis testing regarding the mean permeation flux under different salt concentrations is implemented. The objective is to gain an idea about the statistical significance of performance differences among these membranes. Several statistical techniques, i.e., F-test, Fisher's LSD test, Bonferroni and Tukey's test for multiple comparisons are applied. The F-test predicts that all three membranes handle the three salts at their low salt concentration levels in a comparable manner with no significant differences in permeate fluxes but handle the same salts differently at the higher level of salt concentrations.