Response surface methodology (RSM) was used for modeling and optimization of operating parameters and permeate flux for hollow fiber air gap membrane distillation (AGMD-HF) desalination process with simulated 3.5% (mass) seawater as feed solution. Hot feed-in temperature

cold feed-in temperature and fluid flow rate were chosen for experiment optimization based on central composite design (CCD). A quadratic polynomial regression model for permeate flux and operating parameters was developed. Accuracy of the model was validated by analysis of variance (ANOVA)

RSM and comparison of predicted and experimental permeate flux response. Furthermore

the best optimal level of operating parameters and solar-powered verification were performed. During the experiments

permeate conductivity was constantly kept below 10 μS·cm-1

and relative ion rejection rate was above 99.99%. A R2 of 0.986

p-value smaller than 0.0001 for ANOVA were obtained

and average error of predicted and experimental permeate flux was 6.95%. Moreover

the best optimal operating parameters of 83.5℃

13.2℃ and 60.2 L·h-1 based on desirability function and solar-powered process permeate flux of 6.47 L·m-2·h-1 were presented. Consequently

modeling and optimization of operating parameters for permeate flux response could be helpful for scaling up AGMD-HF desalination process

and introduction of solar power as an alternative of conventional electric heat source could have better application prospect for AGMD-HF desalination.