Energy scarcity is soaring due to the over exploitation of fossil fuel reserves in Bangladesh. On the contrary, a potential energy source i.e. organic municipal solid waste is creating a serious environmental hazard for municipalities ascribe to ineffective and commercially unviable waste management strategy. Therefore, the present study was performed on a dry anaerobic digestion process for biogas production from unsorted organic municipal solid waste. In batch digesters with a 5L effective capacity, the performance of the dry anaerobic digestion (DAD) process of solid waste was assessed during the period of 35 days of operation. Different factors i.e. temperature (35°C, 40°C, and 45°C), micro-nutrients (Na+, K+, Co+) and inoculum mixing ratio (Anaerobic sludge: Cow manure = 1:2, 1:3 and 2:1) were analyzed to observe the biogas production. The results show that biogas production was comparatively higher (approx. 375 mL/day) for 35°C where anaerobic sludge (AS) to cow manure (CS) ratio more than 1. The obtained gas composition was analyzed further to compare the biomethane production depending on these factors. A machine learning (ML) algorithm i.e. Random Forest Regressor was implemented to predict the biogas generation considering different parameters. The model showed performance with more than 77.8% accuracy (R-squared value). Future research can be performed by conducting experiments considering other factors which affects biogas generation and a better model can be implemented to predict the nature of biomethane production. Chemical Engineering Research Bulletin: 24 (Issue 1): 20-29
The utilization of waste material as a resource to produce polyhydroxyalkanoate (PHA) through anaerobic digestion has been identified as a cost-effective approach to the production of bioplastic. This approach involves the conversion of waste material as cost effective substate for PHA production through anaerobic digestion, which is a process that occurs in the absence of oxygen. The resulting bioplastic can be used as a sustainable alternative to traditional petroleum-based plastics. The present research investigates the feasibility of utilizing volatile fatty acids (VFAs) containing leachate, a significant component generated from municipal solid waste through anaerobic digestion, as a feedstock to produce polyhydroxyalkanoate (PHA). However, leachate contains variable concentrations of carbon and nitrogen. To evaluate the effect of enrichment history on PHA producer and production the various carbon and nitrogen levels were utilized during the accumulation phase.In this study, the possibility of mixed culture polyhydroxy alkynoate (PHA) production from waste material was assessed by studying the effects of various carbon and nitrogen levels. For this assessment, Polyhydroxyalkanoate (PHA) producing bacteria was cultured from a mixed microbial culture (MMC) using feast famine (FF) process and acetate and ammonium sulphate as nutrient source. The maximum PHA production of the enriched cultures under nutrient starvation (41%) was evaluated in batch assays. Excess substrate feeding during nutrient excess condition maximizes the PHA production. The influence of the C/N ratio on PHA accumulation capability was evaluated by supplementing the leachates. Leachate can be a promising and sustainable source for PHA production, with a C/N ratio of 3:1 resulting in a yield of 0.1g-PHA/g substrate. Chemical Engineering Research Bulletin: 24 (Issue 1): 13-19
The creation of sustainable and environmentally friendly materials has become more important in order to address concerns about the depletion of nonrenewable resources and the negative environmental impact of traditional materials. In this study, a composite material made of glass fibre, banana fibre, and chicken feathers with varying fibre content percentages (1%, 2%, and 3%) was examined. The composite material was put through tensile, flexural, microhardness, and impact tests. An SEM was used to look at the sample's surface and interior structure. FTIR analysis was performed to detect any contaminants in the sample. The impact of adding eggshell powder to the composite material to improve its qualities was investigated. It was found that the water absorption of the composite was reduced by 12%, and the tensile strength increased by 21% with the addition of eggshell powder. Furthermore, the flexural strength improved by 19%, enhancing the overall mechanical characteristics of the composite material. The addition of eggshell powder altered the interaction between the fibres and the matrix in SEM images. Furthermore, the composite material was subjected to soil exposure for a specific timeframe to evaluate its biodegradability over time. It was observed that integrating eggshell powder into composite materials has the potential to produce more ecologically friendly and sustainable products while reducing waste. This study emphasizes the potential of sustainable and environmentally friendly materials for decreasing environmental effects and ensuring long-term sustainability. Chemical Engineering Research Bulletin: 24 (Issue 1): 79-94
Plastic waste pollution poses a major threat to environmental sustainability, and the biochemical degradation of plastics through enzymatic processes offers an attractive and viable solution to this menacing problem. However, identifying suitable plastic degrading enzymes is a significant challenge. Traditional bioprospecting methods such as high-throughput enzyme screening, although identified several experimentally validated enzymes, are largely unsuccessful, time consuming, and expensive. Bioinformatics can offer a cheaper, quicker, and more successful approach to bioprospecting of novel plastic degrading enzymes. This study describes the development of an automated bioinformatics pipeline to identify proteins homologous to a query protein using a range of criteria, including sequence similarity, evolutionary relationship, and structural alignment. Using the sequences of known plastic degrading enzymes as input, the pipeline identified four homologous proteins with a high potential for plastic degrading functionality: Lipase, Lipase 1, and two uncharacterized esterases, XCC2094 and ATU5261. These proteins and the microorganisms which produce them can be tested in vitro to confirm their plastic degrading abilities, with the aim of identifying microorganisms capable of degrading all the seven types of plastics, or simply providing better plastic degrading capabilities. Chemical Engineering Research Bulletin: 24 (Issue 1): 1-12
With the continuous increment in the world population, the demand for food products has also increased noticeably. To meet this huge demand, a stable supply of food products is required to be maintained strictly. For this reason, different chemical substances such as fertilizers and pesticides are used to aid food production. But arbitrary uses of pesticides will certainly lead to various environmental and health hazards. Hence, uses of pesticides are to be strictly monitored. Models to predict the residual fate of chemicals in plants can be effectively used in pesticide design, human exposure, and environmental assessments. Often the emissions of pesticides are non- steady due to changing plant growth and transpiration. A first principle model (FPM) has been built correlating different mass transfer modes in plants. For the modelling purposes, a material balance approach was used to set up ordinary differential equations (ODEs) for four compartments of the plants, namely, root, stem, fruits/crops, and leaves. The four ODEs were then simultaneously solved in MATLAB to estimate concentrations of pesticides in plant compartments with respect to time. Chlorpyrifos (CP) and Endosulfan Sulfate (ESS) are chosen as pesticides and wheat is selected as the plant for experiment. Concentration profiles were obtained for each pesticide using different input scenarios such as spraying the pesticide in air and applying the pesticide into soil. The model results can be used to find the pre-harvest time before which pesticides should be applied and by the time of harvest the pesticide concentration will fall below the safe threshold limit. Chemical Engineering Research Bulletin: 24 (Issue 1): 47-55
