Integrated life cycle sustainability assessment of the electricity generation sector in Bangladesh: Towards sustainable electricity generation

The electricity sector of Bangladesh has experienced a drastic expansion over the last decade, which will continue in the future. However, the country is not attaining optimal benefit from the sector due to discrepancies among its different components. Increased generation capacity based on fossil fuel sources is not only causing negative environmental impacts but also raising future energy security concerns. Stakeholders are unable to address these interconnected issues due to lack of adequate knowledge, which is leading to policy inconsistencies. This paper aims to evaluate the integrated sustainability of Bangladesh’s electricity generation, considering environmental, economic and social aspects using a life cycle approach. Eighteen sustainability indicators have been assessed for five electricity generation technologies currently in operation. Applying a multi-criteria decision analysis, all the technologies have been ranked considering equal as well as differing preferences for the three aspects. Solar power followed by hydropower is the most sustainable option when all aspects are given equal importance and priority is given to economic and social aspects. However, hydropower becomes the most sustainable option when the environmental aspect is prioritized. Among fossil sources, gas is the best and oil power is found as the least sustainable option in all preferences except the environmental aspect when coal becomes the worst. By identifying the disputes between different indicators, this study demonstrates the variations in the results of the integrated sustainability assessment that can be considered while planning improved energy policies for sustainable future electricity generation

Assessment of Physicochemical Properties and Comparative Pollution Status of the Dhaleshwari River in Bangladesh

The Dhaleshwari river which flows near Dhaka, the capital of Bangladesh, is currently under threat due to the recent relocation of the Hazaribagh tannery to the Savar area. This study investigated the physicochemical parameters of water quality along with the heavy metal levels in the Dhaleshwari river and performed a comparative analysis among the peripheral rivers around Dhaka City. Surface water quality parameters such as total dissolved solids (TDS), biochemical oxygen demand (BOD5), and chemical oxygen demand (COD) obtained for the Dhaleshwari river deviated by as much as 90% from World Health Organization (WHO) standards in certain instances due to direct discharge from untreated point sources. Concentrations of toxic metals such as chromium (Cr), cadmium (Cd), and nickel (Ni) were above the Food and Agriculture Organization (FAO) standards for heavy metals in surface waters. Strong correlations among the heavy metals indicated significant linear dependences. Based on the physicochemical and toxicity-based characterization, the river system in Dhaka city can be termed as severely polluted with respect to organic and solids discharge, while ecological risk indices (ERI) indicated disastrously high risk in the Dhaleshwari and Buriganga rivers. The study outcomes emphasize the necessity of frequent investigation while controlling the point and nonpoint urban pollution sources discharging into the peripheral rivers of Dhaka city

Identification of Functionally Relevant Populations in Enhanced Biological Phosphorus Removal Processes Based On Intracellular Polymers Profiles and Insights into the Metabolic Diversity and Heterogeneity

This study proposed and demonstrated the application of a new Raman microscopy-based method for metabolic state-based identification and quantification of functionally relevant populations, namely polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs), in enhanced biological phosphorus removal (EBPR) system via simultaneous detection of multiple intracellular polymers including polyphosphate (polyP), glycogen, and polyhydroxybutyrate (PHB). The unique Raman spectrum of different combinations of intracellular polymers within a cell at a given stage of the EBPR cycle allowed for its identification as PAO, GAO, or neither. The abundance of total PAOs and GAOs determined by Raman method were consistent with those obtained with polyP staining and fluorescence in situ hybridization (FISH). Different combinations and quantities of intracellular polymer inclusions observed in single cells revealed the distribution of different sub-PAOs groups among the total PAO populations, which exhibit phenotypic and metabolic heterogeneity and diversity. These results also provided evidence for the hypothesis that different PAOs may employ different extents of combination of glycolysis and TCA cycle pathways for anaerobic reducing power and energy generation and it is possible that some PAOs may rely on TCA cycle solely without glycolysis. Sum of cellular level quantification of the internal polymers associated with different population groups showed differentiated and distributed trends of glycogen and PHB level between PAOs and GAOs, which could not be elucidated before with conventional bulk measurements of EBPR mixed cultures

Heterogeneity of Intracellular Polymer Storage States in Enhanced Biological Phosphorus Removal (EBPR) – Observation and Modeling

A number of agent-based models (ABMs) for biological wastewater treatment processes have been developed, but their skill in predicting heterogeneity of intracellular storage states has not been tested against observations due to the lack of analytical methods for measuring single-cell intracellular properties. Further, several mechanisms can produce and maintain heterogeneity (e.g., different histories, uneven division) and their relative importance has not been explored. This article presents an ABM for the enhanced biological phosphorus removal (EBPR) treatment process that resolves heterogeneity in three intracellular polymer storage compounds (i.e., polyphosphate, polyhydroxybutyrate, and glycogen) in three functional microbial populations (i.e., polyphosphate-accumulating, glycogen-accumulating, and ordinary heterotrophic organisms). Model predicted distributions were compared to those based on single-cell estimates obtained using a Raman microscopy method for a laboratory-scale sequencing batch reactor (SBR) system. The model can reproduce many features of the observed heterogeneity. Two methods for introducing heterogeneity were evaluated. First, biological variability in individual cell behavior was simulated by randomizing model parameters (e.g., maximum acetate uptake rate) at division. This method produced the best fit to the data. An optimization algorithm was used to determine the best variability (i.e., coefficient of variance) for each parameter, which suggests large variability in acetate uptake. Second, biological variability in individual cell states was simulated by randomizing state variables (e.g., internal nutrient) at division, which was not able to maintain heterogeneity because the memory in the internal states is too short. These results demonstrate the ability of ABM to predict heterogeneity and provide insights into the factors that contribute to it. Comparison of the ABM with an equivalent population-level model illustrates the effect of accounting for the heterogeneity in models