Rabeya Sultana

Co-composting fecal sludge and organic solid waste offers a sustainable solution to waste management challenges in developing nations like Bangladesh. This study evaluates the efficacy of co-composting two waste streams- organic solid waste and fecal sludge mixed in a 75:25 ratio using fecal sludge with two different maturity periods: 14 days and 6 months. Using a bench-scale setup, critical parameters such as pH, temperature, moisture content, electrical conductivity, and the carbon-to-nitrogen (C/N) ratio were precisely monitored, while forced aeration was applied to optimize microbial activity and enhance the decomposition process. Results indicated that sludge maturity significantly influenced compost quality. Compost from sludge dried for 6 months showed superior degradation rates but had lower nutrient content than that from 14-day dried sludge. Across all reactors, pH ranged from 7.7 to 8.2, supporting microbial activity, while moisture content decreased by 20–23%, indicating effective decomposition. The 14-day sludge compost achieved higher nitrogen content (3.2%) and an ideal C/N ratio (15.34–15.55). Co-composting enhanced nutrient levels, with fecal sludge-amended compost containing up to 3.2% nitrogen, 9,855.4 ppm phosphorus, and 7,961.1 ppm potassium, outperforming organic waste alone. Pathogen reduction during the thermophilic phase met Soil Resource Development Institute (SRDI) and WHO safety standards. Overall, this study demonstrates that co-composting fecal sludge with organic solid waste can produce nutrient-rich, safe soil conditioners, reduce waste transport costs, mitigate pollution, and improve soil health, offering a decentralized and sustainable waste management strategy for urban settings.

Developing countries are facing challenges due to rapid urbanization and insufficient sanitation facilities. However, valorizing treated fecal sludge as a fuel source presents an opportunity to recover energy and mitigate environmental impacts. This experimental study aimed to produce low-cost biofuel from dried fecal sludge and enhance its energy efficiency by incorporating locally available organic matters. Various organic materials like rice husk, cow dung, sawdust, and coal were carbonized and mixed with the sludge to enhance calorific value. Eight sludge and organic matter mixtures were formed into briquettes. The blend of 50% sludge and 50% coal yielded the highest calorific value of 14618 KJ/kg and a boiling time of 14 minutes. The second-highest result was for 50% sludge and 50% cow dung, with a calorific value of 14427 KJ/kg and a boiling time of 23 minutes. The study found that blending sludge with organic materials enhances energy output. Briquettes with 50% sludge and 50% coal cost 19.87 BDT/kg, while those with 50% sludge and 50% cow dung cost 14.37 BDT/kg, proving more economical. The latter blend emerged as the most efficient and cost-effective biofuel, offering a sustainable eco-friendly solution for Bangladesh’s rural energy market.

Flood is a frequent experience for the people living in Bangladesh, especially in the south-western region. But due to its complexity and multidisciplinary nature, flood management remains a very difficult task. This research focused on finding the most vulnerable areas to flooding for each polder within the Khulna and Satkhira districts since those areas can be identified as one of the most vulnerable areas to flooding. Water level data from fourteen stations of seven rivers (Sibsa, Rupsa-Pasur, Kobadak, Bhadra, Kobadak, Ichamati (Western Border), Betna-Kholpetua, and Satkhira Khal) were analyzed to calculate water levels for 2, 5, 10, 25, and 100-year return period applying normal distribution, extreme value type-I (EV-I), and log person type-III (LP-III) distribution methods. The EV-I distribution method was showing the best fit. The study revealed that station SW243 (Rupsa-Pasur River) in the Dacope region has the most extreme water level, station SW259 (Sibsa River) has the second-highest water level, and station SW254.5 (Satkhira Khal) in Satkhira Sadar has the third-highest water level for the return period of 100 years. A flood inundation map was prepared using the EV-I method’s 10-year return period value. The Analytic Hierarchy Process (AHP) was used to demonstrate the polders’ vulnerability depending on several factors. Overall, polder15 (Ghubra, Satkhira) is the most vulnerable polder, while polder 33 and polder 32 respectively are the second and third most vulnerable polders for flooding, both located in the Dacope region.

Healthcare students are clinicians-in-training likely to come into contact with COVID-19 as much as other frontline healthcare professionals. It is therefore necessary to prioritize vaccinations for this group. We conducted a global systematic assessment of COVID-19 vaccine acceptance rates and related factors among healthcare students using the PubMed, Scopus, and Web of Science databases and keyword searches in March of 2022. We found 1779 articles with relevant information and 31 articles that matched our inclusion criteria. We performed a random-effects meta-analysis and quality assessment using the eight-item Joanna Briggs Institute Critical Appraisal test for cross-sectional studies. A total of 30,272 individuals from 16 countries were studied. Most of the studies were carried out in the U.S. (n = 6), China (n = 5), Poland (n = 5), India (n = 2), Italy (n = 2), and Israel (n = 2). The prevalence of the COVID-19 vaccine acceptance rate was 68.8% (95% confidence interval [CI]: 60.8–76.3, I² = 100%), and the prevalence of the vaccine hesitancy rate was 25.8% (95% CI: 18.5–33.8, I² = 99%). In country-specific analyses, Romania showed the highest acceptance rate (88.0%, 95% CI: 44.5–100%), while Iraq showed the lowest acceptance rate (66.2%, 95% CI: 35.5–90.8%). In time-trend analyses, we found that acceptance rates among healthcare students decreased over time. Students concerned about potentially serious side effects of the vaccine were less willing to accept the vaccine. National and international interventions should be adopted to reduce COVID-19 vaccination hesitancy rates among these important frontline workers.

Vaccination is undoubtedly one of the most effective strategies to halt the COVID-19 pandemic. The current study aimed to investigate the acceptance of COVID-19 vaccination and its associated factors using two health behavior change frameworks: the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). A total of 639 Bangladeshi adults (mean age: 24 years) participated in a cross-sectional online study between July and August 2021. The questionnaire covered questions regarding vaccine intentions, sociodemographic features, health status, perceived trust in/satisfaction with health authorities, reasons for vaccine hesitancy, and factors related to the health behavior change frameworks. Hierarchical logistic regression was employed to determine associations between these predictors and vaccine acceptance. The intention to get a COVID-19 vaccination was expressed among 85% of the participants. In fully adjusted models, students and respondents with more normal body weights reported higher intentions to get vaccinated. Respondents were also more likely to seek vaccination if they reported greater levels of perceived susceptibility, benefits, and cues to action, as well as lower levels of barriers and self-efficacy. Fear of future vaccine side effects was the most common reason for COVID-19 vaccine hesitancy and was expressed by 94% of the vaccine-hesitant respondents. These factors should be considered by health authorities in Bangladesh and perhaps other countries when addressing the plateauing COVID-19 vaccination rates in many populations.

Wetland ecosystems provide a wide range of ecosystem services that are often neglected in the decision-making process, resulting in the overexploitation of resources. Quantification of the services generated by this dynamic landscape is critical to developing appropriate conservation priorities for wetland management. The biggest challenge is the lack of adequate knowledge on the economic value of wetland services and proper understanding of potential revenue opportunities associated with it. This chapter introduces an application of an open source tool for estimating the value of freshwater wetland ecosystem services. The Semi-Automatic Classification Plugin (SCP) integrated into the management infrastructure of Quantum Geographic Information Systems (QGIS) can facilitate the supervised classification of multi-spectral satellite images. Thus, a case study of Beel Dakatia, a freshwater wetland of southwest coastal Bangladesh, has been demonstrated to quantify the ecosystem services value (ESV) using the “value transfer method.” This study estimated the total ESV of the wetland by combining Landsat-8 images using land use land cover (LULC) datasets of the year 2020 with its previously published global value coefficients. The LULC was prepared using SCP of QGIS. The study estimated a total ESV of US$42.16 million for Beel Dakatia. The study also found that the more natural ecosystems, e.g., water body and vegetation, contributed the highest (96%) amount of ESV. Regarding ecosystem functions, water regulation contributed the highest (56.13%) ESV, followed by water supply (21.85%) and waste treatment (7.21%). These findings will help policymakers to adopt a sustainable conservation policy for the coastal freshwater wetlands of Bangladesh.