International Journal of Sustainable Energy and Environmental Research

Daily and spatial generation of palm oil mill effluent in determining volumetric capacity for bio-methane planning

2024-06-06T05:23:24-05:00

Cumulative determination of wastes generated per day and in different periods is a necessary prerequisite for planning waste recovery and averting environmental degradation. This study examined palm oil mills (small, medium and large-scaled mills) in the oil palm (Elaeis guineensis) industry at Ohaji/Egbema Local Government Area (LGA), Imo State, Nigeria for daily and periodic generation of palm oil mill effluent (POME). Survey research design was used. Eight catchment communities of the large-scaled mill, Agricultural Development Authority Palm (ADAPALM) were categorised into three strata in relation to the number of small-scaled mills in each community. In each stratum, a community was randomly sampled. Nine small-scaled mills were sampled from the three communities using proportional sampling. The lone medium and large-scaled mill in the study area represented the other scales of milling. For small and medium-scaled mills, the volume of POME generated was measured from the dimensions of the vessels where POME was stored, while that of large-scaled mill was obtained from industrial records. Independent sample T-test revealed an average of 17.574±0.408m3 POME/day and 15.509±0.465m3 POME/day in wet and the dry seasons respectively (p˂0.01). Similarly, within milling-scales, ANOVA and T-test showed that significant variations occur (p<0.01). Wilcoxon’s test revealed that there was no significant difference (p˃0.05) in the median functional small-scaled mills across seasons, hence functionality did do not influence the volume of POME generated across seasons. The findings revealed the copious volume of POME generated in the area and the required volumetric requirements to planning its collection and transformation to wealth.

Review of the environmental and human health impacts of mercury use in gold mining in the Santurban Paramo area

2024-06-06T05:33:13-05:00

Illegal mining is a problem that currently affects the vegetation cover of Colombia due to the environmental liabilities and the damage it causes to the environment in the eagerness to obtain gold in an easy way by using mercury. For this reason, this article presents a detailed bibliographical review of the environmental, social and economic problems of artisanal mining in the Santurban Paramo due to the inappropriate use of mercury and its impact on both the environment and the health of the people who perform this activity, describing first of all the importance of the Paramo in relation to the protection of its ecosystem and biodiversity; secondly, mercury as an imminent danger due to its use and the effects of the activity taking into account the policies and regulations carried out for the preservation and reduction of environmental contamination generated by the bad practices of artisanal mining and finally, the environmental and human health impacts due to direct and indirect contact with mercury. As a result of this research, although artisanal mining represents an important role for the survival of the community, it is necessary to implement continuous improvement strategies to reduce the use of mercury due to the problems caused by this dangerous metal both for the environment and the water source fundamental for the life of the Santurban Paramo and for the health of the people, where education and environmental awareness gain more strength for the protection and preservation of this natural reserve in Colombia.

A machine learning approach to forecast wind speed based on geographical location in Bangladesh

2024-06-20T00:30:34-05:00

This paper examines a learning approach to forecasting wind speed based on geographical location in Bangladesh. Most people use wind energy, a rapidly expanding renewable energy source, to produce electricity, replacing traditional fossil fuel-based electricity generation. The variable nature of wind speed necessitates an accurate estimate for planning wind power generation and grid integration. Machine learning models, based on various methods, commonly make wind speed predictions. This study implements machine learning algorithms, namely Random Forest Regression, XGBoost Regression, Multi-Layer Perceptron Regression, Ridge Regression, and Lasso Regression, to determine wind speed prediction accuracy. Firstly, we divide the dataset on wind records of Bangladesh into seven categories, each encompassing different geographical locations in Bangladesh, to account for the change in wind characteristics based on location, and then apply the algorithms to each category. The performance metrics Mean Absolute Error, Mean Squared Error, and Root Mean Square Error are utilized to draw comparisons. The findings showed that the performance of XGBoost makes it the most reliable tool for predicting wind speed in Bangladesh. The near proximity to large water bodies causes considerable variation in accuracy, i.e., it showed higher accuracy compared to the other three algorithms after applying the ensemble learning approach, which is more effective and accurate. This research will help in identifying optimal power plant locations and efficient linking methods to Bangladesh's power grid, ensuring smooth electricity access and efficient utilization of the country's energy resources.

Influence of air staging variation on agglomeration behavior of biomass fuels in fluidized bed technology

2024-08-17T05:13:47-05:00

The fluidized bed system is an effective approach widely accepted and commonly used for the thermochemical conversion of solid fuel such as biomass and agricultural residue. In most instances, there are some demerits usually associated with this approach such as development of eutectic mass, increased process of melting and bed agglomeration. This work was carried out to study the behavior of five readily available biomass fuels (Palm tree fronds, corn straw, plantain peels, sugarcane bagasse and domestic woods) in a bubbling fluidized bed (BFB) combustor. Characterization of the bed materials and ash samples were done using SEM-EDX, XRF and XRD. The effect of physical factors on the composition of obtained ash and particles from the bed was assessed. Also, the interaction between the fuel ash and bed particle was evaluated to reveal its influence on bed materials morphology. The results obtained revealed a combustion efficiency that varies between 96.2 to 99.6 % with the highest value obtained for sugarcane bagasse. The corn straw has the highest Potassium (K) content, while the domestic wood ash contained the highest Calcium (Ca) content. The XRF analysis revealed the conversion of the major potassium content of the corn straw to K2O. Meanwhile, bed agglomeration was absent when combustion was carried out with no staging-air as well as with staging air, despite high temperature above 800 oC used. Data obtained from this work revealed that agglomeration effect will be minimal issue when carrying out fluidized bed combustion of the selected biomass.

Opportunities of artificial intelligence in valorisation of biodiversity, biomass and bioresidues – towards advanced bio-economy, circular engineering, and sustainability

2024-08-17T06:32:51-05:00

Artificial intelligence (AI) has rapidly gained notoriety due to fast advances in generative AI. However, this field encompasses a broader set of already mature tools and methods. Here, we explore its broad impact on the valorization of assets directly derived from living organisms, biomass, produced in high quantities and used in non-traditional applications at an industrial scale. For this review, we have explored the trends in scientific publications as well as in patents to measure the current state of the art and the potential for commercial applications. The number of publications and patents is rapidly increasing, showing the penetration of these technologies into chemical and biochemical engineering processes. The ethical considerations of such rapid advances need to be addressed to maximize the benefits and minimize the unintentional collateral negative social impact. Considering AI’s current limitations, biases, and economic impacts will facilitate a better transition to the broad implementation of these new technologies. The valorization of biomass and bioresidues, along with the sustainable use of biodiversity, faces important challenges and obstacles that AI tools are helping to overcome, accelerating basic research and optimizing industrial processes in the development of sustainable energy, and high value-added bioproducts and biomaterials. The application of AI in these fields promises industrial innovation, enhanced efficiency, cost reduction and increased product yields for a global growing market; and thereby promotes Circular Engineering and Advanced Bioeconomy to achieve United Nations Sustainable Development goals in the near future.

Role of green financing and energy production to mitigate climate change in emerging economy like Bangladesh

2024-10-17T02:03:49-05:00

This study examines the role of green financing and energy production to mitigate climate change in emerging economies like Bangladesh. In today’s world, climate change is a significant issue that impacts humans on an environmental, social, and economic level. However, this study aims to explain how to mitigate climate change with the support of green finance and green energy in Bangladesh. The study uses mixed methods to conduct the research, such as quantitative and qualitative methods. In this particular case, the study identified several crucial factors that contribute to the effects of climate change. Two environmentally friendly tools, like green finance and green energy, are used to fight climate change. Green finance, comprising financial instruments like green bonds and loans, finances significant investments in environmental projects, particularly renewable energy, that promote the transition to a greener, low-carbon economy and ultimately help to combat climate change. Solar, wind, hydropower, biomass, and biofuels are the common green energy production technologies in Bangladesh, which can play a pivotal role in reducing climate change by reducing greenhouse gas emissions. In Bangladesh, green finance contributes to investment in green energy projects, innovation in clean energy technologies, investment risk management, and energy transitions, according to the research. The study suggests valuable implications for the Bangladesh government, policymakers, and other policymakers taking effective initiatives to protect Bangladesh from the gulf of devastating climate change.

A review on the heterogeneous catalyst for effective conversion of lignocellulosic biomass

2024-10-24T06:37:27-05:00

This study examines a review of the heterogeneous catalyst for effective conversion of lignocellulosic biomass. In light of the challenges posed by a growing global population and the depletion of natural resources, there is an urgent need for alternative solutions. One such solution is the conversion of biomass into fuel, which has the potential to be a cost-effective and widely available substitute for fossil fuels. Solid catalysis and a range of chemical conversions effectively convert biomass into value-added chemicals. A critical factor in this process is the development of a highly efficient and selective catalysis system, along with the necessary chemical reactions. This review provides a comprehensive discussion of the various sources of biomass and their essential chemical composition. It also covers the conversion of biomass into a value-added chemical and the indispensable role of catalysis in the conversion process. Additionally, the review explores various conversion techniques for transforming biomass into useful forms of energy, and highlights their potential applications. By providing a detailed analysis of this process, this review aims to contribute constructively to the ongoing search for sustainable and effective solutions to energy challenges.

Developing an energy storage systems selection methodology for peak shaving purposes in photovoltaic micro-installations

2024-11-06T00:56:06-06:00

This study investigates the selection methodology for peak shaving purposes in photovoltaic micro-installations. Due to the increasing share of photovoltaic micro-installations in the national electricity production and the consequent changes in the country's energy policy, the need for energy storage is becoming increasingly apparent. Therefore, based on data collected throughout the study of a photovoltaic installation conducted in years 2020-2024 and data on market electricity prices, the correlation between production, market electricity prices, and energy value was analyzed. The analysis established interconnections between these values and identified factors influencing their changes. It was observed that the market price of electricity is relatively low during hours of increased photovoltaic energy production. By comparing the correlations between energy production and electricity prices over different years, an increasing impact of the increasing share of photovoltaic energy production in national electricity production on the market price of electricity was noted, highlighting the importance of energy storage. For the described household, an energy storage system was selected with a view to meeting the energy demand during hours of higher market electricity prices. The selected model was Lithium-Iron-Phosphate battery with a capacity of 5 kWh. Furthermore, the cost effectiveness of household-scale energy storage systems was examined. Implementing the proposed solutions could result in increased auto-consumption and presumably improve cost-effectiveness of photovoltaic installations in the future.

Emerging energetics alternatives

2024-11-19T22:11:55-06:00

Energetics is the key to addressing climate change at scale and profitably. The current at scale and profitable climate energetics approach is renewables plus storage. This report summarizes nascent/emerging at scale and profitable energetics approaches for generation, storage, efficiency/conservation, and mitigation, the frontiers of responsible climate-related energetics. There are two weak nuclear force batteries that could provide competition for renewables and storage going forward. There are biologic approaches that could provide ultra-low-cost massive capacity biofuels, sequester massive amounts of atmospheric CO₂, and increase the planet’s albedo. Based on the learnings from renewables, profitability is the apparent key to rapid, at scale response to climate change.