Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated Carbons
Increasing environmental concerns, stricter legal requirements, and a wide range of industrial applications have led to growing demand for activated carbon worldwide. The energy-intensive production of fresh activated carbon causes significant CO<sub>2</sub> emissions and contributes to...
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MDPI AG
2023-12-01
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| Online Access: | https://www.mdpi.com/2311-5629/9/4/115 |
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| author | Karthik Rathinam Volker Mauer Christian Bläker Christoph Pasel Lucas Landwehrkamp Dieter Bathen Stefan Panglisch |
| author_facet | Karthik Rathinam Volker Mauer Christian Bläker Christoph Pasel Lucas Landwehrkamp Dieter Bathen Stefan Panglisch |
| author_sort | Karthik Rathinam |
| collection | DOAJ |
| description | Increasing environmental concerns, stricter legal requirements, and a wide range of industrial applications have led to growing demand for activated carbon worldwide. The energy-intensive production of fresh activated carbon causes significant CO<sub>2</sub> emissions and contributes to global competition for renewable carbon-based raw materials. Although (thermal) reactivation of spent activated carbon can drastically reduce the demand for fresh material, the reactivation process itself is still mostly based on experience and empirical knowledge locked into activated carbon companies. Despite the vast number of papers published in the field, practically relevant, systematic, and quantitative knowledge on the thermal reactivation process is barely available. This paper presents a simple and robust methodology for the development of a predictive model for the production of reactivated carbon with a defined product quality under energetically optimized conditions. An exhausted activated carbon sample was subjected to 26 reactivation experiments in a specially designed laboratory rotary kiln, whereas the experiments were planned and evaluated with statistical design of experiments. The influence of the reactivation conditions (heating rate, heating time, H<sub>2</sub>O/N<sub>2</sub> volume ratio, and CO<sub>2</sub>/N<sub>2</sub> volume ratio) on the specific surface area, energy consumption, yield, and adsorption capacity for diatrizoic acid were evaluated. The BET surface of the reactivated carbons ranged between 590 m<sup>2</sup>/g and 769 m<sup>2</sup>/g, whereas the respective fresh carbon had a BET surface of 843 m<sup>2</sup>/g. The adsorption capacity for diatrizoic acid measured as the maximum solid phase concentration q<sub>m</sub> derived from the Langmuir equation varied between 24.4 g/kg and 69.7 g/kg (fresh carbon: 59.6 g/kg). It was possible to describe the dependency of the quality criteria on different reactivation parameters using mathematical expressions, whereas the response surface methodology with nonlinear regression was applied to build the models. A reactivation experiment under statistically optimized conditions resulted in energy savings up to 65%, whereas the properties of the reactivated sample were close to the predicted values. |
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| institution | Directory Open Access Journal |
| issn | 2311-5629 |
| language | English |
| last_indexed | 2024-03-08T20:54:25Z |
| publishDate | 2023-12-01 |
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| spelling | doaj.art-17b8e330f83f4c608ac80ae624fc544e2023-12-22T13:59:17ZengMDPI AGC2311-56292023-12-019411510.3390/c9040115Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated CarbonsKarthik Rathinam0Volker Mauer1Christian Bläker2Christoph Pasel3Lucas Landwehrkamp4Dieter Bathen5Stefan Panglisch6Chair for Mechanical Process Engineering and Water Technology, University of Duisburg-Essen, 47057 Duisburg, GermanyChair for Thermal Process Engineering, University of Duisburg-Essen, 47057 Duisburg, GermanyChair for Thermal Process Engineering, University of Duisburg-Essen, 47057 Duisburg, GermanyChair for Thermal Process Engineering, University of Duisburg-Essen, 47057 Duisburg, GermanyChair for Mechanical Process Engineering and Water Technology, University of Duisburg-Essen, 47057 Duisburg, GermanyChair for Thermal Process Engineering, University of Duisburg-Essen, 47057 Duisburg, GermanyChair for Mechanical Process Engineering and Water Technology, University of Duisburg-Essen, 47057 Duisburg, GermanyIncreasing environmental concerns, stricter legal requirements, and a wide range of industrial applications have led to growing demand for activated carbon worldwide. The energy-intensive production of fresh activated carbon causes significant CO<sub>2</sub> emissions and contributes to global competition for renewable carbon-based raw materials. Although (thermal) reactivation of spent activated carbon can drastically reduce the demand for fresh material, the reactivation process itself is still mostly based on experience and empirical knowledge locked into activated carbon companies. Despite the vast number of papers published in the field, practically relevant, systematic, and quantitative knowledge on the thermal reactivation process is barely available. This paper presents a simple and robust methodology for the development of a predictive model for the production of reactivated carbon with a defined product quality under energetically optimized conditions. An exhausted activated carbon sample was subjected to 26 reactivation experiments in a specially designed laboratory rotary kiln, whereas the experiments were planned and evaluated with statistical design of experiments. The influence of the reactivation conditions (heating rate, heating time, H<sub>2</sub>O/N<sub>2</sub> volume ratio, and CO<sub>2</sub>/N<sub>2</sub> volume ratio) on the specific surface area, energy consumption, yield, and adsorption capacity for diatrizoic acid were evaluated. The BET surface of the reactivated carbons ranged between 590 m<sup>2</sup>/g and 769 m<sup>2</sup>/g, whereas the respective fresh carbon had a BET surface of 843 m<sup>2</sup>/g. The adsorption capacity for diatrizoic acid measured as the maximum solid phase concentration q<sub>m</sub> derived from the Langmuir equation varied between 24.4 g/kg and 69.7 g/kg (fresh carbon: 59.6 g/kg). It was possible to describe the dependency of the quality criteria on different reactivation parameters using mathematical expressions, whereas the response surface methodology with nonlinear regression was applied to build the models. A reactivation experiment under statistically optimized conditions resulted in energy savings up to 65%, whereas the properties of the reactivated sample were close to the predicted values.https://www.mdpi.com/2311-5629/9/4/115water treatmentactivated carbon reactivationCO<sub>2</sub> savingmodelingresponse surface methodologydesign of experiments |
| spellingShingle | Karthik Rathinam Volker Mauer Christian Bläker Christoph Pasel Lucas Landwehrkamp Dieter Bathen Stefan Panglisch Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated Carbons C water treatment activated carbon reactivation CO<sub>2</sub> saving modeling response surface methodology design of experiments |
| title | Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated Carbons |
| title_full | Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated Carbons |
| title_fullStr | Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated Carbons |
| title_full_unstemmed | Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated Carbons |
| title_short | Eliminating Luck and Chance in the Reactivation Process: A Systematic and Quantitative Study of the Thermal Reactivation of Activated Carbons |
| title_sort | eliminating luck and chance in the reactivation process a systematic and quantitative study of the thermal reactivation of activated carbons |
| topic | water treatment activated carbon reactivation CO<sub>2</sub> saving modeling response surface methodology design of experiments |
| url | https://www.mdpi.com/2311-5629/9/4/115 |
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