مدل‌سازي انتقال جرم فرايند حذف دي‌اكسيد كربن از محيط زيست با هدف توليد متان سبز و بهينه‌سازي رشد متانوژن‌ها

Mass Transfer Modeling For CO2 Removal from Environment with the Aim of Green Biomethanation and Methanogens Growth Optimization

ﺗﺎرﯾﺦ درﯾﺎﻓﺖ: 97/12/15 ﺗﺎرﯾﺦ ﭘﺬﯾﺮش: 98/8/22 ﭼﮑﯿﺪه زﻣﯿﻨﻪ و ﻫﺪف: ﻏﻠﻈﺖ دي اﮐﺴﯿﺪﮐﺮﺑﻦ ﺑﻪ ﻋﻨﻮان ﻣﻬﻢ ﺗﺮﯾﻦ ﮔﺎز ﮔﻠﺨﺎﻧﻪ اي در اﺗﻤﺴﻔﺮ در ﺣﺎل اﻓﺰاﯾﺶ ﻣﯽ ﺑﺎﺷﺪ ﮐﻪ ﺑﻪ ﻋﻨﻮان ﯾﮑﯽ از ﻧﮕﺮاﻧﯽ ﻫﺎي ﻣﻬﻢ ﺑﺸﺮ، روش ﻫﺎي زﯾﺎدي ﺑﺮاي ﻣﻘﺎﺑﻠﻪ آن ﺑﺮرﺳﯽ ﺷﺪه اﺳﺖ. اﻣﺎ اﺳﺘﻔﺎده از آن در ﺗﻮﻟﯿﺪ ﺑﯿﻮﻣﺘﺎن اﻗﺘﺼﺎدي ﺗﺮ ﺑﻪ ﻧﻈﺮ ﻣﯽ رﺳﺪ. ﻫﺪف اﺻﻠﯽ در اﯾﻦ ﺗﺤﻘﯿﻖ ﺑﺮرﺳﯽ ﻣﺪل ﺳﺎزي ﻓﺮاﯾﻨﺪ ﺗﻮﻟﯿﺪ اﻧﺮژي ﭘﺎك ﺑﯿﻮﻣﺘﺎن و ﺣﺬف ﻫﻤﺰﻣﺎن دي اﮐﺴﯿﺪ ﮐﺮﺑﻦ از ﻣﺤﯿﻂ زﯾﺴﺖ اﺳﺖ. روش ﺑﺮرﺳﯽ: در اﯾﻦ ﻣﻘﺎﻟﻪ ﺑﺮاي ﻓﺮاﯾﻨﺪ ﺗﻮﻟﯿﺪ ﺑﯿﻮﻣﺘﺎن در ﺑﯿﻮراﮐﺘﻮر ﻧﺎﭘﯿﻮﺳﺘﻪ، ﺑﺎ ﻫﺪف اﻓﺰاﯾﺶ ﺣﺠﻢ ﺑﯿﻮﻣﺲ ﻓﻌﺎل، ﻣﺪل ﺳﺎزي اﻧﺘﻘﺎل ﺟﺮم اﻧﺠﺎم ﺷﺪ. دﻗﺖ ﻧﺘﺎﯾﺞ ﻣﺪل ﺳﺎزي ﺑﺎ ﻣﻘﺎﯾﺴﻪ ﺑﺎ داده ﻫﺎي آزﻣﺎﯾﺸﮕﺎﻫﯽ و ﺳﯿﻨﺘﯿﮑﯽ در ﻗﺎﻟﺐ ﻣﺴﺌﻠﻪ ﺻﻔﺮ ﺑﻌﺪي و ﺑﺪون ﺗﺎﺑﻌﯿﺖ ﻣﮑﺎﻧﯽ ﺑﺮرﺳﯽ ﮔﺮدﯾﺪ. ﺳﭙﺲ ﻣﻄﺎﻟﻌﻪ ﯾﮏ ﺑﻌﺪي ﺑﯿﻮراﮐﺘﻮر ﺑﻪ ﻣﻨﻈﻮر ﺑﺮرﺳﯽ ﭘﺮوﻓﺎﯾﻞ ﻏﻠﻈﺖ ﻫﯿﺪروژن و ﺑﯿﻮﻣﺲ در ﻃﻮل ﺑﯿﻮراﮐﺘﻮر و ﻣﺤﺎﺳﺒﻪ ﺣﺠﻢ ﻓﻌﺎل اﻧﺠﺎم ﺷﺪ. از روش ﭘﺎﺳﺦ ﺳﻄﺢ ﻧﯿﺰ ﺑﻪ ﻣﻨﻈﻮر ﺑﺮرﺳﯽ ﺗﺎﺛﯿﺮ ﺳﻪ ﻓﺎﮐﺘﻮر دﻣﺎ، ﻓﺸﺎر و ﺑﺮ ﺣﺠﻢ ﻓﻌﺎل ﺑﯿﻮراﮐﺘﻮر و ﯾﺎﻓﺘﻦ ﺷﺮاﯾﻂ ﺑﻬﯿﻨﻪ اﺳﺘﻔﺎده ﺷﺪ. اﯾﻦ ﺗﺤﻘﯿﻖ در ﺗﺎﺑﺴﺘﺎن 1397 اﻧﺠﺎم ﺷﺪ. ﯾﺎﻓﺘﻪ ﻫﺎ: ﻧﺘﺎﯾﺞ ﺑﺮرﺳﯽ ﺻﻔﺮ ﺑﻌﺪي ﺗﺎﯾﯿﺪ ﮐﻨﻨﺪه دﻗﺖ ﻣﺪل ﺳﺎزي ﺑﻮد. ﺑﺮرﺳﯽ ﯾﮏ ﺑﻌﺪي ﻧﺸﺎن داد ﮐﻪ ﭘﺮاﮐﻨﺪﮔﯽ رﺷﺪ ﺑﯿﻮﻣﺲ در ﻓﺎز ﻣﺎﯾﻊ ﺗﺎﺑﻊ ﭘﺮوﻓﺎﯾﻞ ﻫﯿﺪروژن اﺳﺖ ﺑﻪ ﺷﺮﻃﯽ ﮐﻪ ﺿﺮاﺋﺐ ﻧﻔﻮذ ﻫﯿﺪروژن و ﺑﯿﻮﻣﺲ در ﻣﺎﯾﻊ را ﺑﺮاﺑﺮ درﻧﻈﺮ ﮔﺮﻓﺖ و در ﺷﺮاﯾﻂ اﺳﺘﺎﻧﺪارد ﻣﺮﺗﺒﻪ ﺑﺰرﮔﯽ آن ﺑﻮد. ﻧﺘﺎﯾﺞ آﻣﺎري ﺣﺎﺻﻞ از روش ﭘﺎﺳﺦ ﺳﻄﺢ ﻧﺸﺎن داد ﮐﻪ ﻫﺮ ﺳﻪ ﻋﺎﻣﻞ دﻣﺎ، ﻓﺸﺎر و ﺗﺄﺛﯿﺮ ﻣﻌﻨﯽ داري ﺑﺮ ﻣﯿﺰان 10-9 ﺣﺠﻢ ﻓﻌﺎل ﺑﯿﻮراﮐﺘﻮر دارﻧﺪ، ﺿﻤﻦ اﯾﻦ ﮐﻪ ﺑﯿﺸﺘﺮﯾﻦ اﺛﺮ و ﻓﺸﺎر و دﻣﺎ در اوﻟﻮﯾﺖ ﺑﻌﺪي ﺗﺄﺛﯿﺮﮔﺬاري ﺑﻮدﻧﺪ. ﺑﺤﺚ و ﻧﺘﯿﺠﻪ ﮔﯿﺮي: راﮐﺘﻮر ﻧﺎﭘﯿﻮﺳﺘﻪ ﺑﺎ اﺑﻌﺎد در دﻣﺎ و ﻓﺸﺎر ﺑﺎﻻ ﺑﻬﯿﻨﻪ ﺗﺮﯾﻦ ﺷﺮاﯾﻂ را ﺑﺮاي ﺗﻮﻟﯿﺪ ﺑﯿﻮﻣﺘﺎن دارد، وﻟﯽ اﻗﺘﺼﺎد ﻓﺮاﯾﻨﺪ ﺗﻌﯿﯿﻦ ﮐﻨﻨﺪه ﻣﺤﺪوده ﻋﻤﻠﯿﺎﺗﯽ اﺳﺖ.

Background and Objective: CO2 concentration, as the main greenhouse gas, is growing in atmosphere and many alternatives have been investigated to deal with it. However, harnessing with the aim of biomethanation seems to be more economic. Method: In this study a mass transfer modeling was conducted for a biomethanation process under a batch strategy aiming at maximizing liquid active volume. The accuracy of modeling results was assessed via comparing with experimental data and kinetic results under zero-dimension study. Then one-dimensional study was conducted in order to investigate biomass and hydrogen concentration profiles within liquid phase of the bioreactor and active volume calculation. Response surface method (RSM) was also served to investigate effect of temperature, pressure and as three main factors on active volume followed by response optimization. Findings: Model accuracy was confirmed by zero-dimension study. One-dimensional study was also revealed that biomass growth dispersion within liquid phase depends on hydrogen profile concentration on condition that both hydrogen and biomass diffusion coefficients were assumed to be equal. Their degree of magnification was 10-9 in standard conditions. RSM showed that the three studied factors significantly affected on bioreactor active volume. Meanwhile, pressure and temperature influenced the most, respectively. Discussion and Conclusion: A batch bioreactor with and high pressure and temperature met optimal conditions for biomethanation; however, process economy defines operational limitations.