Eco-friendly complementary biosorption process of methylene blue using micro-sized dried biosorbents of two macro-algal species (Ulva fasciata and Sargassum dentifolium): Full factorial design, equilibrium, and kinetic studies.


National Research Centre (NRC), Water Pollution Research Department, Dokki, Cairo 12622, Egypt. Electronic address: [Email]


Finding green effective methods for dye removal from wastewater created an important interest in comparison to conventional methods. The aim of the present work was directed to study micro grinded dried biomass of two macro-algal species, Ulva fasciata and Sargassum dentifolium as complementary biosorbent materials for effective methylene blue (MB) removal from waste water. The two macro-algal species were collected, dried, and grinded by ball mill to get the micro size. After that, the biosorbent materials were characterized by FT-IR, TEM, and DLS. Furthermore, Full Factorial Design was applied to determine the optimum conditions that maximize the MB adsorption efficiency. Ulva fasciata biosorbent material was achieved the highest MB adsorption capacity, 97% of 328 mg/l MB with a maximum adsorption capacity (qmax) of 244 mg/g in comparison to the Sargassum dentifolium, 85.6% of 26 mg/l MB with (qmax) of 66.6 mg/g. Based on Factorial Design data the main effects of the Ulva biosorbent exhibited that both time & biosorbent dose had a positive effect on biosorption and both pH & MB concentrations have a negative effect, on the other hand, no temperature effect on both biosorbents. Point of zero charge (pHpzc) was recorded at pH 6.7 and 9 for Ulva and Sargassum biosorbents, respectively. The obtained results suggested that the two macro-algal species can be used in a complementary consecutive process where Ulva fasciata started first and followed by Sargassum dentifolium. The complementary treatment process achieved efficiency of 99.2% adsorption of 300 mg/l MB concentration. Moreover, the kinetic data suggested that the adsorption of MB follows the pseudo-second order model.