The study aimed to determine the fungal diversity in clinical waste samples from a healthcare facility in Penang Malaysia. Different fungi species were detected in 83.75 % of the 92 clinical waste samples that were screened from different sections of the healthcare facility. One hundred fifty fungal isolates comprising of 8 genera and 36 species were obtained. They were purified by using single spore isolation technique. Subsequently, the isolates were identified by phenotypic method based on morphological and culture characteristics on different culture media. Among all fungal isolates, Aspergillus spp. in section Nigri 10.2 %, Aspergillus niger 9.5 %, Aspergillus fumigatus 8.8 %, Penicillium. simplicissium 8 %, Aspergillus tubingensis 7.3 %, Aspergillus terreus var. terreus 6.6 %, Penicillium waksmanii 5.9 % and Curvularia lunata 6.5 % were the most frequent. Among five sections of the Wellness Centre, the clinical wastes collected from the diagnostic labs of haematology section had the highest numbers of fungal species (29 species). Glove wastes had the highest numbers of fungal species (19 species) among 17 types of clinical wastes screened. Among all fungal species, Aspergillus spp. exhibited higher growth at 37 °C than at 28 °C, indicating the potential of these opportunistic fungi to cause diseases in human. These results indicated the potential of hospital wastes as reservoirs for fungal species.
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 (C0, ∼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 C0 showed significant differences in the adsorption capacities of E-GAC, whereas only changing the C0 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 (tb) based on kinetic constant (kBDST) 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.