Optimization of biodiesel supply chains based on small farmers: a case study in Brazil

Biodiesel supply chain network design: a comprehensive review with qualitative and quantitative insights

The global community is actively pursuing alternative energy sources to mitigate environmental concerns and decrease dependence on fossil fuels. Biodiesel, recognized as a clean and eco-friendly fuel with advantages over petroleum-based alternatives, has been identified as a viable substitute. However, its commercialization encounters challenges due to costly production processes. Establishing a more efficient supply chain for mass production and distribution could surmount these obstacles, rendering biodiesel a cost-effective solution. Despite numerous review articles across various renewable energy supply chain domains, there remains a gap in the literature specifically addressing the biodiesel supply chain network design. This research entails a comprehensive systematic literature review (SLR) focusing on the design of biodiesel supply chain networks. The primary objective is to formulate an economically, environmentally, and socially optimized supply chain framework. The review also seeks to offer a holistic overview of pertinent technical terms and key activities involved in these supply chains. Through this SLR, a thorough examination and synthesis of existing literature will yield valuable insights into the design and optimization of biodiesel supply chains. Additionally, it will identify critical research gaps in the field, proposing the exploration of fourth-generation feedstocks, integration of multi-channel chains, and the incorporation of sustainability and resilience aspects into the supply chain network design. These proposed areas aim to address existing knowledge gaps and enhance the overall effectiveness of biodiesel supply chain networks.

Robust sustainable canola oil-based biodiesel supply chain network design under supply and demand uncertainty

The excessive consumption of fossil fuels has sparked debates and caused environmental damage, leading the global community to search for a suitable alternative. To achieve sustainable development goals and prevent harmful climate scenarios, the world needs to increase its use of renewable energy. Biodiesel, a clean and eco-friendly fuel with a high flash point and more lubrication than petroleum-based fuels, and without the emission of harmful environmental gases, has emerged as one of the fossil fuel alternatives. To promote the mass-level production of biodiesel, a sustainable supply chain (SC) that does not depend on laboratory production is necessary. For this purpose, this research proposes a multi-objective mixed-integer non-linear mathematical programming (MINLP) model to design a sustainable canola oil-based biodiesel supply chain network (CO-BSCND) under supply and demand uncertainty. This mathematical model aims to minimize the total cost (TC) and total carbon emission while maximizing the total number of job opportunities simultaneously. A scenario-based robust optimization (SBRO) approach is applied to deal with uncertainty. The proposed model is implemented in a real case study in Iran, and numerical experiments and sensitivity analysis are conducted to demonstrate its applicability. The results of this research demonstrate that designing a sustainable supply chain network for the production and distribution of biodiesel fuel is achievable. Moreover, this mathematical modeling makes mass-scale production of biodiesel fuel a possibility. In addition, the SBRO method adopted in this research enables managers and researchers to explore the design conditions of the supply chain network by controlling the uncertainties that affect it. This approach allows the chain's performance to be as close as possible to the actual conditions. As a result, the SBRO method enhances the efficiency of the supply chain network and boosts productivity toward achieving desired goals.

Income optimization of rice paddy farmers in the narrow fields during the covid-19 pandemic in South Sumatra province

This study aims to analyze the amount of income through business diversification as well as scenarios for increasing income in business diversification during the Covid-19 pandemic. The research method used is the survey method, the sampling method used is a snowball and the number of respondents is determined by purposive sampling with 100 respondents. The study results show that the amount of optimization of the income of lowland rice farmers during the Covid-19 pandemic at a business diversification of 1 Rp. 29,130,500.00, business diversification 2 Rp. 19,007,006.29, business diversification 3 Rp. 8,301,257.48, business diversification 4 Rp. 14,877,500.00. The amount of farmer's income after the scenarios for business diversification 1 is carried out with additional capital of Rp. 1,870,000 so that the optimal allocation result will be an increase in income of Rp. 2,871,644.88 or 9.86%. Business diversification 2 is carried out with additional capital of Rp. 750,000 and a reduction of the workforce by 5 JOK so that the optimal allocation result will be an increase in income of Rp. 1,472,001.57 or 7.74%. Business diversification 3, it is carried out with additional capital of Rp. 370,000 and the addition of 4 JOK workers so that the optimal allocation result will be an increase in income of Rp. 978,173.65 or 11.78%. Business diversification 4 is carried out by increasing the land area by 0.25 so that it becomes 1 hectare and increasing capital by Rp. 500,000 so that the optimal allocation of income increases by Rp. 733,061.37 or 4.93.

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

Logistics and Supply Chain Modelling for the Biobased Economy: A Systematic Literature Review and Research Agenda

One way to mitigate the negative impacts of climate change, is for society to move towards a biobased economy, where fossil resources are replaced by biobased ones. This replacement requires the development of biobased supply chains that differ significantly from the conventional supply chain. For example, seasonality and variability of the feedstocks create specific challenges for biobased systems and call for customized solutions for the design and operation of biobased chains. As a result, the modelling efforts to support decision-making processes for biobased logistics and supply chains have some different requirements. This paper presents a systematic literature review on logistics and supply chain modelling studies for the biobased economy published in a period of 2011–2020. The literature analysis shows that most modelling studies for the biobased economy are strategic optimization models aiming to minimize economic impact. As biomass source, forest and agricultural residues are mostly used, and fuel and energy are the most common biobased applications. Modelling strategies, biomass sources and applications are however diversifying, which is what we encourage for future research. Also, not only focusing on economic optimization but also optimizing social and environmental performance is an important future research direction, to deal with the sustainability challenges the world is facing.

An overview to process design, simulation and sustainability evaluation of biodiesel production

The overwhelming concerns due to over exploitation of fossil resources necessitate the utilization of alternative energy resources. Biodiesel has been considered as one of the most adaptable alternative to fossil-derived diesel with similar properties and numerous environmental benefits. Although there are various approaches for biodiesel production, development of cost-effective and robust catalyst with efficient production methods and utilization of a variety of feedstock could be the optimum solution to bring down the production cost. Considering the complexity of biodiesel production processes, process design, quantitative evaluation and optimization of the biodiesel from whole systems perspectives is essential for unlocking the complexity and enhancing the system performances. Process systems engineering offers an efficient approach to design and optimize biodiesel manufacturing systems by using a variety of tools. This review reflects state-of-the-art biodiesel research in the field of process systems engineering with a particular focus on biodiesel production including process design and simulation, sustainability evaluation, optimization and supply chain management. This review also highlights the challenges and opportunities for the development of potentially sustainable and eco-friendly enzymatic biodiesel technology.

Optimizing Resource Utilization in Biomass Supply Chains by Creating Integrated Biomass Logistics Centers

Bio-based supply chains are by nature complex to optimize. The new logistic concept of integrated biomass logistical center (IBLC) provides us the opportunity to make full use of the idle capacity for a food/feed plant to produce biobased products so that the entire chain efficiency can be improved. Although research has been conducted to analyze the IBLC concept, is yet to be an optimization model that can optimally arrange the activities in the supply chain where an IBLC stands in the middle. To fill the knowledge gap in the literature, this paper makes the first step to develop a MILP model that enables biobased supply chain optimization with the IBLC concept, which supports logistic and processing decisions in the chain. The model is applied in a case study for a feed and fodder plant in Spain where managerial insights have been derived for transferring the plant to a profitable IBLC.

Life cycle assessment of biodiesel production in China

This study aims to evaluate energy, economic, and environmental performances of seven categories of biodiesel feedstocks by using the mixed-unit input-output life cycle assessment method. Various feedstocks have different environmental performances, indicating potential environmental problem-shift. Jatropha seed, castor seed, waste cooking oil, and waste extraction oil are preferred feedstocks for biodiesel production in the short term. Positive net energy yields and positive net economic benefits of biodiesel from these four feedstocks are 2.3-52.0% of their life cycle energy demands and 74.1-448.4% of their economic costs, respectively. Algae are preferred in the long term mainly due to their less arable land demands. Special attention should be paid to potential environmental problems accompanying feedstock choice: freshwater use, ecotoxicity potentials, photochemical oxidation potential, acidification potential and eutrophication potential. Moreover, key processes are identified by sensitivity analysis to direct future technology improvements. Finally, supporting measures are proposed to optimize China's biodiesel development.

Development of a Saccharomyces cerevisiae strain for increasing the accumulation of triacylglycerol as a microbial oil feedstock for biodiesel production using glycerol as a substrate

Triacylglycerol (TAG) is a microbial oil feedstock for biodiesel production that uses an inexpensive substrate, such as glycerol. Here, we demonstrated the overproduction of TAG from glycerol in engineered Saccharomyces cerevisiae via the glycerol-3-phosphate (G3P) pathway by overexpressing the major TAG synthesis. The G3P accumulation was increased 2.4-fold with the increased glycerol utilization gained by the overexpression of glycerol kinase (GUT1). By overexpressing diacylglycerol acyltransferase (DGA1) and phospholipid diacylglycerol acyltransferase (LRO1), the engineered YPH499 (pGutDgaLro1) strain produced 23.0 mg/L lipids, whereas the YPH499 (pESC-TRP) strain produced 6.2 mg/L total lipids and showed a lipid content that was increased 1.4-fold compared with 3.6% for the wild-type strain after 96 h of cultivation. After 96 h of cultivation using glycerol, the overall content of TAG in the engineered strain, YPH499 (pGutDgaLro1), yielded 8.2% TAG, representing a 2.3-fold improvement, compared with 3.6% for the wild-type strain. The results should allow a reduction of costs and a more sustainable production of biodiesel.