Search

In the global effort to reduce CO 2 emissions, the concurrent enhancement of pollutant degradation and reductions in fossil fuel consumption are pivotal aspects of microalgae-mediated wastewater treatment. Clarifying the degradation mechanisms of bacteria and microalgae during pollutant treatment, as well as regulatory biolipid production, could enhance process sustainability. The synergistic and inhibitory relationships between microalgae and bacteria are introduced in this paper. The different stimulators that can regulate microalgal biolipid accumulation are also reviewed. Wastewater treatment technologies that utilize microalgae and bacteria in laboratories and open ponds are described to outline their application in treating heavy metal-containing wastewater, animal husbandry wastewater, pharmaceutical wastewater, and textile dye wastewater. Finally, the major requirements to scale up the cascade utilization of biomass and energy recovery are summarized to improve the development of biological wastewater treatment. [Display omitted] • The synergistic and antagonistic interactions between bacteria and microalgae are summarized. • Different stimulators that could regulate microalgal biolipid accumulation are also reviewed. • Wastewater treatment technologies that utilize microalgae and bacteria in the laboratory and open ponds are described. • The trends in microalgae-bacterial consortium in multistage energy production are proposed. [ABSTRACT FROM AUTHOR]

This paper explores the viability of utilizing agricultural biomass-based energy potential, employing mathematical, engineering, and economic modeling techniques. Moreover, the potential of a biogas-based co-digestion (CD) system, integrating its techno-economic performance and environmental sustainability in terms of electricity generation, has also been studied. In this investigation, the categorization of 25 different plant species into two groups: arable field crops (AFCs) and horticultural plants (HPs), was performed. Data was collected during the 2021‐–2022 cropping season in Bangladesh from various sources, including literature reviews, governmental, and non-governmental organizations. The findings revealed that the available agricultural biomass residues, totaling 1,02,585.75 KT, have the capacity to generate 1,33,815 million m3/year of biogas. This energy potential corresponds to 291,125.85 TJ/year or 9231.60 MW of electricity, which can fulfill 88% of the national total energy demand. In terms of levelized cost, the proposed approach is more competitive and shows a greater promise compared to other technologies. Furthermore, it demonstrates environmental friendliness by reducing CO 2 emissions by 156 tons at a cost of $7/ton while earning $1092 annually from the potential carbon-credit market. This approach presents a potential solution to address Bangladesh's energy crisis. The payback period of the system ranged from 2.93 to 3.75 years, with and without the inclusion of a slurry, respectively. The recommended methods hold significant promise for meeting national energy demands. A case study was provided as a proof-of-concept (PoC) to validate the approach. This study is the first of its kind, providing valuable insights into the renewable energy potential in Bangladesh. The results will assist policymakers in formulating sustainable energy policies. • Mathematics, engineering, economics and environmental modeling explored renewable energy. • Techno-economics and environmental sustainability validated the proposed methodology. • Bioenergy-based electricity could supply 88% of the national energy demand of Bangladesh. • A case study was provided as a proof-of-concept (PoC) to validate the approach. [ABSTRACT FROM AUTHOR]

Recent European Directives have promoted Renewable Energy Communities as pivotal drivers to achieve energy and environmental European targets. In this context, the aim of this paper is to assess the energy and environmental feasibility of a Renewable Energy Community located in Northern Italy. The analysis is conducted starting from the real electricity consumption and thermal energy requests data made available from different datasets. After the analysis and processing of input data, the size and technical characteristics of the devices installed at the Renewable Energy Community are defined. A biomass-based cogenerator, a small hydro power plant, and distributed photovoltaic systems have been selected, thereby different layouts are considered and analysed, in terms of cogenerator operating mode and photovoltaic systems peak power. The results show that, in the best scenario, the annual renewable electricity used to satisfy electric load increases by 20.3% and about 68.1% of the total thermo-electric requests are met through biomass utilization. The bi-directional interactions with power grid are reduced from 60.6% to 51.7%. The thermal and electric sharing within the community ensures a decrease of carbon dioxide emissions up to 18.5%. • Analysis of energy systems serving district heating network at Tirano municipality. • Characterization of thermal and electric loads with 1-h granularity. • Modelling and simulation of most suitable Renewable Energy Community layouts. • Definition and evaluation of energy and environmental key performance indicators. [ABSTRACT FROM AUTHOR]

This paper provides a review of negative carbon capture technologies. Based on these technologies, here it is proposed an innovative negative emissions power plant combining the generation and storage of energy from biomass, photovoltaic, and concentrated solar power, capturing and recovering CO 2 by producing H 2 or CH 4 as green energy carriers. The main features of the system are i) large-scale energy production system with negative CO 2 emissions; ii) 100% renewable system based on biomass and solar energy with the possibility of integrating other renewables; iii) synergistic integration of processes and systems; iv) recovery of O 2 generated by photovoltaic-driven electrolysis within the process of partial biomass oxycombustion and v) solar-driven limestone calcination. A detailed model of the entire plant is developed to evaluate the integration of the process. The model performance is assessed on an hourly basis throughout the whole year. The base case results show an energy consumption from 1 to 2.1 MJ/kg CO 2 to capture 60–77% of CO 2 emitted from the biomass plant and green methane production of more than 7500 tons/year. The negative emissions associated with the process are -612 kg CO 2 /MWh. It justifies the interest in the proposed negative emissions power plant. [Display omitted] • A synergetic integration of CO2 capture, energy storage and methane production is proposed. • A biomass power plant is considered, resulting in -612 kg CO2/MWh negative emissions. • Solar PV and CSP are integrated into the process to reduce the SPECCA to 1–2.1 kg CO2/MWh. • A large amount of solids storage is required to achieve 70–90% CO2 capture capacity. [ABSTRACT FROM AUTHOR]

This study investigated the relationship among biomass energy consumption, economic growth and carbon emissions in West Africa during 1980–2010. This nexus was explored by integrating the pollution production function and energy demand function with an augmented endogenous growth model. Moreover, this paper employed a simultaneous equation model estimated with three stage least squares (3SLS). Analysis was conducted for individual West African countries and panel of the countries. The overall results show that a complete significant interactive relationship (feedback effects) exists among GDP, biomass consumption and carbon emission in five West Africa countries (Nigeria, Burkina Faso, The Gambia, Mali and Togo). There are partial significant links among the variables in the remaining West African countries. A complete significant nexus among the variables was also discovered for panel of the countries. Based on the results, some policy implications were drawn for West African countries. There is need to reduce the prevailing high energy intensity of output in West Africa through the adoption of energy-efficient technologies. It is also imperative to find clean energy alternatives (or complementary) to biomass use so as to reduce the resulting high carbon emissions which may hinder the attainment of high and sustainable growth in the nearest future. [ABSTRACT FROM AUTHOR]

Biofuel manufacturing from renewable biomass through a smart manufacturing system is an important alternative to fossil fuels, which helps to decrease dependability on conventional fuel and decrease carbon emanations. By utilizing efficient labors, smart machines, and minimized energy utilization, the conventional biofuel manufacturing framework can be converted into a smart sustainable manufacturing framework. The existing conventional fuel demand can be replaced by biofuel. This study efforts to make pure biofuel with less amount of carbon emanations and energy utilization through a smart multi-type biofuel manufacturing framework, where the demand of the biofuel is selling price dependent. The different energy costs including air handling cost, lighting cost are calculated in this work-in-process inventory. The carbon emissions cost is included in every stage of this model. A variable demand has introduced for the maximization of profit. To reduce energy consumption and carbon emissions, a two-stage inspection cost with a variable manufacturing rate is taken to make the manufacturing process flexible such that the amount of impure biofuel is minimized. Although a random manufacturing rate is applied through a smart manufacturing system, still impure biofuel is manufactured. The impure biofuel is remanufactured again through refining just after the well-planned manufacturing ends. In this model, the multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to market places at predetermined intervals at the time of delivery frame. The classical optimization technique is used for continuous and differentiable variables and the mixed integer programming technique is utilized for discrete variables to maximize the total profit globally. To validate the model's usefulness, four numerical observations are studied. It is shown that by utilizing the said procedure, the percentage of impure biofuel can be decreased truly through the minimized energy consumption. The graphical representation and the sensitivity experiment show the impact of every parameter with the whole cost of the research paper. Numerical results assist to get the maximum profit and the optimum selling price of biofuel globally in a sustainable smart multi-type biofuel manufacturing system. [Display omitted] [ABSTRACT FROM AUTHOR]

Increasing energy demand and the rising levels of greenhouse gas emissions have increased the necessity of bioenergy and sustainable energy generation. The sustainable bioenergy supply chain is the key to produce sustainable biofuel. This paper points to render an optimization model for planning a versatile and dependable biomass-to-bioenergy sustainable supply chain network in which crop residuals from several agricultural sectors, multi-transportation disruption modes, multi-biorefineries, multi-biogas plants, and multi-market centers are investigated for two bioenergy sources, namely biofuel and biogas. For this reason, supply chain cost optimization, emissions of feedstock transport, processing, and distributing end biofuel to respective markets are utilized. The multi-setup-multi-delivery (MSMD) concept is incorporated and lead time crashing cost is applied to minimize the lead time in this model. The carbon emission costs at all steps and the variable production rate for the production of bioenergy are included within the model. Finally, one small-scale data and another large-scale data of six agricultural areas, four biorefineries, four biogas plants, and six markets are considered to validate the model's usefulness. The model's goal is to show bioenergy's effect to make a sustainable supply chain of biofuel and biogas. The numerical results reveal that the cost of bioenergy production contributed 54.12%, a major extent of the whole cost in biorefinery and biogas plants. The transportation segment is the preeminent initiator of carbon emissions with 83.33% in the entire carbon emission within the whole supply chain. Although, transportation cost contributed 33.09% of the total cost, the multi setup-delivery-multi-delivery policy minimized the whole supply chain cost. The results provide a systematic guideline for developing a sustainable biofuel supply-chain by minimizing cost, various aspects of transportation logistics, and multi-model alternatives under reduced energy effects. • Energy demand and two approaches of biofuel and biogas production are evaluated. • Reduction of the supply chain network's total cost. • Optimizing allocation of the appropriate quantity of residual biomass and biofuel. • Reducing energy consumption by using variable production rate. • An intelligent logistics system with multi-disruption is addressed. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the causal relationship among renewable energy technologies, biomass energy consumption, per capita GDP, and CO 2 emissions for Germany. We constructed an innovative algorithm, the Quantum model, and applied it with Machine Learning experiments – through a software capable of emulating a quantum system – to data over the period of 1990–2018. This process is possible after eliminating the "irreversibility" of classical computations (unitary transformations) by making the process "reversible". The empirical findings support the powerful role of biomass energy in reducing carbon dioxide emissions, although the effect of renewable energy technology displays a much stronger magnitude. Moreover, income remains an important determinant of environmental pollution in Germany. • An innovative Machine Learning algorithm (the Quantum model) has been constructed and applied. • The empirical findings support the powerful role of biomass energy in reducing CO 2 emissions. • GDP represents an important determinant of environmental pollution in Germany. [ABSTRACT FROM AUTHOR]