Search Results (22)

The development of new technologies for the production of renewable energy is fundamental to reducing greenhouse gas emissions. Therefore, the search for new energy generation methods that are environmentally responsible, socially rational, and economically viable is gaining momentum in order to mitigate carbon footprint. The aviation sector is responsible for a significant fraction of greenhouse gas emissions; for this reason, the decarbonisation of this sector must be investigated using biorefinery models. This study presents a mixed-integer linear programming (MILP) model for optimising the design and configuration of the supply chain in different states of Brazil for the production of sustainable aviation fuel (SAF) and green diesel and gasoline, using microalgae cultivated in sugarcane vinasse as the raw material. The technology of hydrothermal liquefaction was assessed in terms of its capacity to convert microalgae without need for the energy-intensive drying step. The MILP model was developed in the LINGO v.20 software using a library of physical and economic process models. We consider the selection of processes based on the object of total minimum cost, with optimal production plant scaling and regional supply chain design, including an assessment of resources and final product distribution. A case study was implemented in Brazil, considering different regions of the country and its local demands for fuels. São Paulo is the most profitable state, with a cash flow of 1071.09 and an IRR of 36.19%, far outperforming the rest. Transport emissions alone represent between 0.6 and 8.6% of emissions generated by the model. The costs of raw materials, mainly hydrogen (57%) and electricity (27%) represent the main costs evaluated in the model. The production cost (MUS$/TJ biofuel) is in the range of 0.009–0.011. Finally, changes in the cost of electricity have the greatest impact on the model. Full article

Background: In agricultural supply chains, unequal bargaining power often leads to economic inequality, particularly for farmers. The fair profit distribution (FPD) approach offers a solution by optimizing supply chain flows (materials, information, and money) to promote economic equity among members. However, our literature review highlights a gap in applying the FPD approach to the facility location-allocation problem in supply chain network design (SCND), particularly in sugarcane-derived biofuel supply chains. Methods: Consequently, we propose a multi-period optimization model based on FPD to design a sugarcane biofuel supply chain. The methodology involves four steps: constructing a conceptual model, developing a mathematical model, designing a solution strategy, and generating insights. This model considers both investment (crop development, biorefinery construction) and operational phases over a long-term planning horizon, focusing on farm location and crop allocation. Results: By comparing the FPD model to a traditional centralized planning supply chain (CSC) approach, we examine the impact of the planning horizon, number of farms, and sugarcane prices paid by biorefineries on financial performance. While the FPD model results in lower overall system profits, it fosters a fairer economic scenario for farmers. Conclusions: This study contributes to economic justice in supply chains and offers insights to promote fair trade among stakeholders. Full article

Purpose: This paper develops a high-precision yield fusion prediction model for the sugarcane industry in Chongzuo, Guangxi, based on the trend yield and meteorological yield using the long short-term memory (LSTM) model to cope with the multiple factors affecting sugarcane production. Decision support is provided to agricultural producers, policymakers, and supply chain managers so that they can plan resource allocation, market strategies, and policy directions more effectively. Methods: The paper modeled trend yield and weather yield separately to explore the complex relationship between the two in influencing sugarcane production. Trend yields were predicted using the exponential smoothing and multilayer perceptron (MLP) models, while meteorological yields were modeled using stepwise regression. The predicted yields were used again as input variables into the LSTM deep learning network to fit the nonlinear relationship between the two yields. Results: The results showed that (1) the fusion strategy of meteorological yield and MLP trend yield adopted by the model was superior to the fusion strategy of meteorological yield and exponentially smoothed trend yield, achieving a very low mean square error (MSE) of 0.011 and a goodness of fit as high as 0.979, which indicated that the model prediction was highly in agreement with the actual yield, confirming the validity of the method. (2) The prediction curve is basically consistent with the trend of actual sugarcane yield, which predicts that the sugarcane yield in Chongzuo, Guangxi, is expected to maintain a stable and small growth trend in the next eight years. (3) The fusion prediction model proposed in this study provides an accurate and practical solution for sugarcane yield prediction in Chongzuo, Guangxi, with the unique advantage of effectively analyzing and integrating the natural and socio-economic factors affecting the yield, which is of significant reference value for the prediction of sugarcane yield in the local area and even in similar ecoregions. Full article

Low-carbon ammonia production is crucial for sustainable development. Brazil, a top ethanol producer, can boost competitiveness and cut emissions by integrating ammonia and ethanol production. However, optimal location and production strategy identification is challenging due to existing possibilities and uncertainties. For that, a new MILP superstructure with robust optimisation was developed and used to analyse low-carbon ammonia production integration in the ethanol industry in São Paulo state by ethanol and biomethane routes, in two different scenarios. As for the results, in scenario 1, biomethane and ethanol investments were USD 3.846 M and USD 314 M. In scenario 2, the investments were USD 316 M for biomethane and USD 259 M for ethanol. Despite the higher investment, the biomethane route results in lower hydrogen production cost (USD 1880/tonne) due to raw material prices; however, ethanol displays a higher hydrogen potential, consuming just 8% of total production against 54% of vinasse availability, which is used for biodigestion and biomethane production. In conclusion, the results suggest that the northern region of São Paulo has greater potential for ammonia facilities due to resource availability. These findings can inform and support more comprehensive studies and public incentive policies. Full article

This study mapped the bioenergy production from sugarcane vinasse according to the mesoregions of the State of São Paulo (SP), Brazil, assessing the magnitude of biogas-derived electricity and biomethane production and estimating the greenhouse gas (GHG) emissions. SP holds 45% of the Brazilian ethanol-producing plants, in which 1.4 million m³ of carbon-rich vinasse are generated daily. The electricity generated from vinasse has the potential to fully supply the residential consumption (ca. 6.5 million inhabitants) in the main sugarcane-producing mesoregions of the state (Ribeirão Preto, São José do Rio Preto, Bauru, Araçatuba and Presidente Prudente). In another approach, biomethane could displace almost 3.5 billion liters of diesel, which represents a 26% abatement in the annual state diesel consumption. Energetically exploiting biogas is mandatory to prevent GHG-related drawbacks, as the eventual emission of methane produced under controlled conditions (261.2 × 10⁶ kg-CO₂eq d⁻¹) is ca. 7-fold higher than the total emissions estimated for the entire ethanol production chain. Meanwhile, replacing diesel with biomethane can avoid the emission of 45.4 × 10⁶ kg-CO₂eq d⁻¹. Implementing an efficient model of energy recovery from vinasse in SP has great potential to serve as a basis for expanding the utilization of this wastewater in Brazil. Full article

The aeronautical sector faces challenges in meeting its net-zero ambition by 2050. To achieve this target, much effort has been devoted to exploring sustainable aviation fuels (SAF). Accordingly, we evaluated the technical performance of potential SAF production in an integrated first- and second-generation sugarcane biorefinery focusing on Brazil. The CO₂ equivalent and the renewability exergy indexes were used to assess environmental performance and impact throughout the supply chain. In addition, exergy efficiency (η_B) and average unitary exergy costs (AUEC) were used as complementary metrics to carry out a multi-criteria approach to determine the overall performance of the biorefinery pathways. The production capacity assumed for this analysis covers 10% of the fuel demand in 2020 at the international Brazilian airports of São Paulo and Rio de Janeiro, leading to a base capacity of 210 kt jet fuel/y. The process design includes sugarcane bagasse and straw as the feedstock of the biochemical processes, including diverse pre-treatment methods to convert lignocellulosic resources to biojet fuel, and lignin upgrade alternatives (cogeneration, fast pyrolysis, and gasification Fischer-Tropsch). The environmental analysis for all scenarios shows a GHG reduction potential due to a decrease of up to 30% in the CO₂ equivalent exergy base emissions compared to fossil-based jet fuel. Full article

The sugarcane crop has great socioeconomic relevance because of its use in the production of sugar, bioelectricity, and ethanol. Mainly cultivated in tropical and subtropical countries, such as Brazil, India, and China, this crop presented a global harvested area of 17.4 million hectares (Mha) in 2021. Thus, decision making in this activity needs reliable information. Obtaining accurate sugarcane yield estimates is challenging, and in this sense, it is important to reduce uncertainties. Currently, it can be estimated by empirical or mechanistic approaches. However, the model’s peculiarities vary according to the availability of data and the spatial scale. Here, we present a systematic review to discuss state-of-the-art sugarcane yield estimation approaches using remote sensing and crop simulation models. We consulted 1398 papers, and we focused on 72 of them, published between January 2017 and June 2023 in the main scientific databases (e.g., AGORA-FAO, Google Scholar, Nature, MDPI, among others), using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. We observed how the models vary in space and time, presenting the potential, challenges, limitations, and outlooks for enhancing decision making in the sugarcane crop supply chain. We concluded that remote sensing data assimilation both in mechanistic and empirical models is promising and will be enhanced in the coming years, due to the increasing availability of free Earth observation data. Full article

The sugarcane supply chain is one of the main contributors to economic development in many countries. However, it is necessary to consider the relationship of this supply chain with the environment in order to reduce/mitigate adverse environmental impacts. Life cycle assessment (LCA) supports improving the relationship between production systems and the environment, increasing process efficiency, and reducing costs. The main objective of this research was to identify the extent to which the sugarcane supply chain impacts environmental and human health aspects as well as the use of resources through LCA. This analysis focused on a supply chain in Brazil’s Midwest region, considering the stages of cultivation, transportation, and production. The results indicated that using fertilizers and pesticides and burning crops during harvest severely threaten the sustainability of this supply chain. Also, using crude oil, natural gas, coal, and other chemical products in ethanol production is a critical threat to the sustainability of the sugarcane supply chain. The obtained results cooperate with the decarbonization goals assumed by Brazil at the United Nations Climate Change Conference 2015 (COP 21). A multidimensional approach is necessary to assess the sugarcane production chain results, and the LCA method is appropriate for performing this analysis. Full article

Ethanol, a common renewable energy resource, can reduce greenhouse gas (GHG) emissions to resolve the problem of global warming worldwide. Various feedstocks such as corn, sugarcane, maize stover, and wheat straw can be utilized for ethanol production. They determine production operations and relevant costs. Although there are monetary incentives and government policies in different countries to increase ethanal use, it is still challenging to make its sales price competitive due to the inefficient supply chain of ethanol. Unlike fossil fuels such as coal, oil, and natural gas using a well-designed supply chain in the long history of mankind, additional efforts are needed to organize and stabilize the supply chain of ethanol efficiently. The goal of this study is to investigate how simulation modeling techniques can be applied to various supply chain management issues of ethanol. Particularly, application cases of three major simulation paradigms such as discrete-event simulation, system dynamics, and agent-based simulation are investigated by conducting a scientific literature review. The findings of this study will contribute to the expansion of simulation use in the field of biofuel supply chain management. Full article

Background: This study aims to explore how domestic entrepreneurs can benefit from the thriving global agribusiness by establishing themselves in agro-industrial segments that can best remunerate capital and labour. The ways in which domestic entrepreneurs in Brazil enter different segments of the agribusiness industry were assessed with specific attention to implications for the development of local agro-industrial capabilities. Methods: We assessed the current market share of domestic companies in relation to foreign multinationals in various segments of the sugar and ethanol supply chain in Brazil. Results: Foreign multinationals are market leaders in the fertilizers, machinery and trading segments (domestic companies market share is 20.3%, 33.3% and 42.9% in those segments respectively). However, Brazilian companies have achieved higher market share in segments such as plant breeding, sugarcane processing and farming (domestic market share is 93.2%, 67.4% and 75.5% respectively). Plant breeding, farming and trading benefit from governmental support in research, subsidized credits and market policies respectively. Conclusions: By investing in agro-industrial sectors developing countries can benefit from agribusiness expansion for their economic growth. Investments in science and technology and domestic regulatory actions can help to build country capabilities, although the impacts are sometimes limited to the agro-industrial sectors where domestic companies are more competitive. These lessons can help other developing countries to assess their opportunities and challenges for agro-industrial development. Full article

This article reviews the current scenario and the main uncertainties and challenges associated with implementing Sustainable Aviation Fuel (SAF) in Colombia, from which it determines the possible certified technologies under the ASTM D 7566 standard as well as co-processing technologies contemplated within the ASTM D 1655 standard, more suitable for the implementation of SAF production. Likewise, through the PESTEL tool (Political, Economic, Social, Technological, Environmental, and Legal), a diagnosis is made in order to obtain an updated overview of the implementation of SAF in Colombia. Based on the above, it provides recommendations to mitigate the uncertainties identified, and it is complemented by the ECOCANVAS tool, which applies to businesses related to the circular economy, and also include the net production potential of SAF in Colombia, considering the production of feedstock, in agricultural residue of sugarcane, oil palm, corn, and coffee. This study concludes with some policy recommendations that can make SAF implementation viable and allow responsible institutions to organize themselves for better strategic action and identify the fields of research and the need for investment in R + D + i to strengthen the supply chain. Full article

In Northeast Brazil, the use of biomass for energy generation is settled on traditional productive arrangements, such as a sugarcane production system in the humid Atlantic coastal area and firewood extraction from native tropical dry forests in the west. In parallel, substantial amounts of other biomass sources, such as residues from agricultural or urban processes, are still little used or wholly wasted, fudging the opportunity to generate new value chains based on these biomass sources. We hypothesize that using these non-traditional biomass sources to produce biofuels would significantly increase the regional bioenergy supply. In this context, this article discusses the potential for the production and use of biofuels and bioenergy in Northeast Brazil and its effects on regional development, which may be useful for both private actors and policymakers in the energy sector. The use of biomass sources for energy in the region is significant, reaching approximately 8.8 million tons of oil equivalent (toe) per year, emphasizing the already consolidated production of sugarcane and its derivatives. The use of all biomass resources in the Northeast region could supply around 4% of the Brazilian national electrical energy demand, with an environmental footprint of 0.055 tCO_2eq per toe, which would contribute to reducing emissions from the Brazilian energy matrix generation. Regarding the spatial distribution of biomass sources, sugarcane prevails on the coast, firewood and livestock manure in the dryland area towards the west, and municipal solid waste is distributed throughout the region within urban areas. Different from what we expected, the potential energy recovery from municipal waste and animal manure would increase by only 17% the current bioenergy supply. In the future, since the majority of the region presents a semi-arid climate with limited rainfall, to increase the use of biomass as an energy source, there is a need to increase the supply of biomass sources with high efficiency in water use and good yields in drylands. For this, the cultivation and use of cacti and agave, for example, could contribute to making biorefineries viable in the region. Above all, public policies for harnessing bioenergy in NE Brazil must seek opportunities associated with the carbon/decarbonization economy, with studies being needed to assess the technical, economic, social, and environmental viability of future productive arrangements. Full article

Climate change and the COVID-19 pandemic have disrupted the food supply chain across the globe and adversely affected food security. Early estimation of staple crops can assist relevant government agencies to take timely actions for ensuring food security. Reliable crop type maps can play an essential role in monitoring crops, estimating yields, and maintaining smooth food supplies. However, these maps are not available for developing countries until crops have matured and are about to be harvested. The use of remote sensing for accurate crop-type mapping in the first few weeks of sowing remains challenging. Smallholder farming systems and diverse crop types further complicate the challenge. For this study, a ground-based survey is carried out to map fields by recording the coordinates and planted crops in respective fields. The time-series images of the mapped fields are acquired from the Sentinel-2 satellite. A deep learning-based long short-term memory network is used for the accurate mapping of crops at an early growth stage. Results show that staple crops, including rice, wheat, and sugarcane, are classified with 93.77% accuracy as early as the first four weeks of sowing. The proposed method can be applied on a large scale to effectively map crop types for smallholder farms at an early stage, allowing the authorities to plan a seamless availability of food. Full article

This paper presents an optimization modeling approach to support strategic planning for designing hydrogen supply chain (HSC) networks. The energy source for hydrogen production is proposed to be electricity generated at Mexican sugar factories. This study considers the utilization of existing infrastructure in strategic areas of the country, which brings several advantages in terms of possible solutions. This study aims to evaluate the economic and environmental implications of using biomass wastes for energy generation, and its integration to the national energy grid, where the problem is addressed as a mixed-integer linear program (MILP), adopting maximization of annual profit, and minimization of greenhouse gas emissions as optimization criteria. Input data is provided by sugar companies and the national transport and energy information platform, and were represented by probability distributions to consider variability in key parameters. Independent solutions show similarities in terms of resource utilization, while also significant differences regarding economic and environmental indicators. Multi-objective optimization was performed by a genetic algorithm (GA). The optimal HSC network configuration is selected using a multi-criteria decision technique, i.e., TOPSIS. An uncertainty analysis is performed, and main economic indicators are estimated by investment assessment. Main results show the trade-off interactions between the HSC elements and optimization criteria. The average internal rate of return (IRR) is estimated to be 21.5% and average payback period is 5.02 years. Full article

The dairy industry generates large volumes of liquid waste that can be used to produce biopolymers, potentially employable for the creation of milk biodegradable bottles. In that regard, this paper aims to explore the consumers’ intention to purchase sustainable packages, as well as to assess the willingness to pay for it considering renewable packages made using organic waste feedstocks from the dairy industry (e.g., whey) and plant-based material (e.g., corn, sugarcane, etc.). To reach the stated objectives, we collected individual-level information (e.g., age, gender, education, income) from a convenient sample of 260 Italian consumers and a modified version of the Theory of Planned Behavior estimated using a structural equation model. Findings show that attitudes and perceived behavioral control are the most important drivers of the consumers’ intention to purchase sustainable packages. Finally, statistics show that respondents slightly prefer to purchase products packaged using plant-based biodegradable material, as well as most of the respondents show a low willingness to pay for milk offered in biodegradable packaging, regardless of the raw material used. Then, policymakers and companies should invest in educational/informational campaigns pointing out the beneficial effects on the environment from the purchase of foods in sustainable packaging. This may potentially increase the consumers’ intention to purchase, as well as their willingness to pay for plant-based and dairy whey-based packages by increasing the sustainability of the dairy supply chain. Full article