Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Article number | 124839 |
---|---|
<mark>Journal publication date</mark> | 31/01/2020 |
<mark>Journal</mark> | Chemosphere |
Volume | 239 |
Number of pages | 13 |
Publication Status | Published |
Early online date | 12/09/19 |
<mark>Original language</mark> | English |
The inhalational anaesthetic agent – sevoflurane is widely employed for the induction and maintenance of surgical anaesthesia. Sevoflurane possesses a high global warming potential that imposes negative impact to the environment. The only way to resolve the issue is to remove sevoflurane from the medical waste gas before it reaches the atmosphere. A continuous adsorption study with a fixed-bed column was conducted using two commercial granular activated carbons (E-GAC and H-GAC), to selectively remove sevoflurane. The effect of bed depth (Z, 5–15 cm), gas flow rate (Q, 0.5–6.0 L/min) and inlet sevoflurane concentration (C 0, ∼55–700 mg/L) was investigated. E-GAC demonstrated ∼60% higher adsorption capacity than H-GAC under the same operating conditions. Varying the levels of Z, Q and C 0 showed significant differences in the adsorption capacities of E-GAC, whereas only changing the C 0 level had significant differences for H-GAC. Three breakthrough models (Adams-Bohart, Thomas, and Yoon-Nelson) and Bed-depth/service time (BDST) analysis were applied to predict the breakthrough characteristics of the adsorption tests and determine the characteristic parameters of the column. The Yoon-Nelson and Thomas model-predicted breakthrough curves were in good agreement with the experimental values. In the case of the Adams-Bohart model, a low correlation was observed. The predicted breakthrough time (t b) based on kinetic constant (k BDST) in BDST analysis showed satisfactory agreement with the measured values. The results suggest the possibility of designing, scaling up and optimising an adsorption system for removing sevoflurane with the aid of the models and BDST analysis.