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Committed to achieving carbon neutrality by mid-century, South America faces unique challenges in carbon mitigation due to its distinct socio-economic, technological, and institutional backgrounds compared to developed and other developing economies. Previous research on South America's carbon emissions has limited country and sector coverage and typically adopts a top-down approach that focuses on the overall emissions of an economy, neglecting individual energy sources and emission sectors. Therefore, this paper compiles a comprehensive inventory of CO 2 emissions for South American countries based on a meticulous bottom-up approach and multi-source data integration, followed by a thorough analysis of their temporal evolution patterns and the driving forces behind them. Between 2010 and 2020, South America's overall emissions peaked in 2014 at 1092.3 Mt., led by emissions from oil consumption and from the transport and electricity sectors, and dropped to 865.6 Mt. in 2020, due to the economic fluctuations and COVID-19. Specifically, Brazil was the largest emitter, Chile experienced the most significant increase in emissions, and Paraguay recorded the highest emission growth rate. Generally, expanding population was constant driver of emission growth. High energy intensity led to significant emission increases in Brazil and Ecuador, while elevated carbon intensity was the main driver in Argentina. Energy structure changes played a positive role in most countries to different extents (e.g., much more significant in Brazil than in Chile) but aggrevated emissions in Paraguay and Guyana. Therefore, carbon mitigation strategies should be tailored to each country's unique national circumstances. • During 2010–2020, South America's CO 2 emissions from fossil fuels peaked in 2014. • Transport and electricity sectors comprised over 60% of total emissions. • Brazil was the top emitter, while Chile saw the largest increase in emissions. • Emission patterns and driving factors varied significantly across countries. • Carbon reduction strategies should be tailored to local circumstances. [ABSTRACT FROM AUTHOR]

• Lifecycle benefits/harms of solar/electric ships were demystified quantitatively. • Live-Life Cycle Assessment was introduced to overcome the lack of data available. • Environmental performance of solar ships was subject to geographical conditions. • Green electric grids were suggested to contribute to net zero-emission shipping. This paper was born to introduce a novel methodology termed Live-Life Cycle Assessment using a simulation-based data generation technique that can remedy the inherent shortcomings of conventional practices of lifecycle assessment. To demonstrate its excellence, the proposed method was applied to one of the most challenging topics in the marine industry. That was to tackle the fundamental doubt of whether solar-electric propulsion ships could truly be the future energy solution of maritime transports by fulfilling new environmental conventions and goals around the world. The case study began with an existing hybrid short route ferry running on diesel and plug-in battery power. Credible PV systems for the case ship was modelled to produce ship performance data under various operational/environmental circumstances of the coastal zones across 29 countries in the platform of MATLAB/Simulink. As a key functionality of Live-Life Cycle Assessment, the produced data was directly fed, as inputs, into life cycle assessment to avoid conventional practices that heavily rely on outdated data libraries. Results of the case study clearly revealed and quantified the correlations of the performance of PV-battery systems with climate parameters such as temperature and irradiance of subject areas as well as national power production methods. For example, in terms of Global Warming Potential, the case ship with the PV system was estimated to reduce 40,812 kg CO 2 eq. per year in Brazil (average temp.: 27.4 ℃, major energy source: hydro). Interestingly, the same vessel was found to achieve greater reductions in India (average temp.: 27.5 ℃, major energy source: coal) or Australia (average temp.: 20.1 ℃, major energy source: coal) where are overly laden with coal-based power plants. Therefore, their reduction levels were estimated at 152,887 kg CO 2 eq. per year and 141,517 kg CO 2 eq. per year respectively. This paper clearly shows the excellence of the proposed method to demystify/quantify the impacts of parametric variables on the performance of the PV-electric ship. Moreover, it highly suggests the Live-Life Cycle Assessment could be a solution as a new standard to respond to strong demand to obtain general observation of lifecycle benefits/harms of new technologies across all industries, not necessarily limited to the maritime sector. [ABSTRACT FROM AUTHOR]

This paper proposes an Internet-of-Things (IoT) based energy management system (EMS) for the optimal operation of unbalanced three-phase AC microgrids. The system utilizes a software architecture based on microservices, which includes a stochastic economic dispatch optimizer (EDO), a database, a web-based graphical user interface (GUI), and an application programming interface (API). The EDO uses a mixed-integer linear programming (MILP) model to ensure the day-ahead dispatch of the distributed energy resources (DERs) in the microgrid while adhering to grid constraints such as voltage, current, and power limits. Additionally, the optimization module takes into account security constraints for unplanned islanded operation, as well as stochastic scenarios of local demand and renewable generation. To assess the performance of the proposed IoT-based EMS, tests are conducted using a real-time simulator in a software-in-the-loop (SIL) experimental setup. Actual data from a microgrid located at the State University of Campinas (UNICAMP) in Brazil is utilized for the tests. The microgrid consisted of a photovoltaic (PV) system, a battery energy storage system (BESS), a thermal generation unit, and variable demands. Results indicated the effectiveness of the proposed IoT-based EMS in monitoring the operation of the microgrid and defining the optimal day-ahead dispatch of local DERs. • An IoT-based energy management system (EMS) for microgrids is presented. • A database, a web-based GUI, an API, and an optimization module comprise the EMS. • Optimal day-ahead dispatch is defined considering grid and security constraints. • Real-time simulations in a software-in-the-loop environment are implemented. • EMS is efficient in defining the dispatch and monitoring the operation of microgrids. [ABSTRACT FROM AUTHOR]

• Use of parallel pumps as turbines for power generation and energy storage. • Harnessing the structure of a lock for hybrid power generation. • Use of the grid as an intermediate means of energy storage. • Manipulation of the water without additional impact on the existing hydrology. • Spillway at adjacent plant positively influences on payback time. Waterway are one of the most efficient means for transportation. It can be applied for energy storage demonstrating the potential of using these structures with renewable energy systems, here, through an analysis of energy alternatives. This paper analyzes two different solutions for energy supply, using the Locks of the Tucuruí powerplant, in Brazil. A photovoltaic power station is compared to a hybrid system composed by photovoltaic and pumped storage. The alternatives are discussed technically and economically. The energy costs of the scenarios are calculated based on the evolution of the expenses and the related payback time are found. The water resource is exploited responsibly, keeping balanced the pumped and turbined volumes of water. The grid works as an intermediate storage and allows the operations with a single pump-turbine conversion. Its location lowers down the initial investment in favor of the hybrid system as the more viable alternative. It was found that the locks could be used to handle up to 263 kW and 387 kW of electricity in turbine and pump mode, respectively. This paper gathers crucial data on the use of hydropower in waterways locks that support the integration of renewable energies surrounding the locks. In addition, the use of pumped storage plants to store energy from intermittent sources, present themselves as an innovative opportunity to, using the own head available at facility, improve the financial return of meeting the energy demand through an economically and environmentally responsible energy system, may be useful in similar facilities around the world. [ABSTRACT FROM AUTHOR]

Stabilization at concentrations consistent with keeping global warming below 2 °C above the pre-industrial level will require drastic cuts in Greenhouse Gas (GHG) emissions during the first half of the century; net negative emissions approaching 2100 are required in the vast majority of current emission scenarios. For negative emissions, the focus has been on bioenergy with carbon capture and storage (BECCS), where carbon-neutral bioenergy would be combined with additional carbon capture thus yielding emissions lower than zero. Different BECCS technologies are considered around the world and one option that deserves special attention applies CCS to ethanol production. It is currently possible to eliminate 27.7 million tonnes (Mt) of CO 2 emissions per year through capture and storage of CO 2 released during fermentation, which is part of sugar cane-based ethanol production in Brazil. Thus, BECCS could reduce the country’s emissions from energy production by roughly 5%. Such emissions are additional to those due to the substitution of biomass-based electricity for fossil-fueled power plants. This paper assesses the potential and cost effectiveness of negative emissions in the joint production system of ethanol and electricity based on sugar cane, bagasse, and other residues in Brazil. An important benefit is that CO 2 can be captured twice along the proposed BECCS supply chain (once during fermentation and once during electricity generation). This study only considers BECCS from fermentation because capturing such CO 2 is straightforward, thus potentially representing a cost-effective mitigation option for Brazil compared to other alternatives. The assessment shows that fuel prices would increase by less than 3.5% due to the adoption of BECCS from fermentation, while increasing investors’ revenues are sufficient to compensate for the investment required. With appropriate government subsidies, or by sharing BECCS costs between all car fuels and all electricity supplied by hydro and bioelectricity, the increment in ethanol and electricity prices could be less than 1% for the final consumer. Meanwhile it would supply 77.3% of all cars’ fuel (private cars) and 17.9% of all electricity in Brazil. [ABSTRACT FROM AUTHOR]

This paper presents an economic outlook of the ethanol industry in Brazil considering different biomass feedstocks and different industrial processing options. A spreadsheet model was designed to account for different feedstocks and industrial processes, and expected trends in biomass yield, sugar- and fibre content, industrial scale and efficiency. Sugarcane and energycane cultivation costs may be reduced from 35 US$ 2010 /TC in 2010 to 27 US$ 2010 /TC and 22 US$ 2010 /TC in 2030 respectively. Eucalyptus and elephant grass cultivation costs could be reduced from 32 to 23 US$ 2010 /tonne wet and 38 to 26 US$ 2010 /tonne wet for eucalyptus and elephant grass. Total ethanol production costs of first generation processing may decrease from 700 US$ 2010 /m 3 in 2010, to 432 US$ 2010 /m 3 in 2030. First generation ethanol production costs may decrease by reduced feedstock costs, increase in sugar content, utilization of cane trash, and use of sweet sorghum. Furthermore, the improvement in industrial efficiency of the first generation process, increasing industrial scale and change to an improved technology are other measures. For second generation technology utilizing eucalyptus, the total ethanol production costs could be strongly reduced to 424 US$ 2010 /m 3 in 2030. Costs reduction measures for second generation industrial processing include reduced feedstock costs, increasing industrial efficiency and scale, and a change to more advanced industrial process. Overall, biomass yield, increase in sugar content of sugarcane, and improved industrial efficiency are important parameters in total ethanol production costs. Ongoing RD&D effort and commercialization of second generation industrial processing may result in the lowest ethanol production costs for second generation processing in the future. [ABSTRACT FROM AUTHOR]

In the early 2000s high expectations existed regarding the potential contribution of biofuels to the reduction of greenhouse gas emissions and substitution of fossil fuels in transport. In recent years sobering judgments prevailed. The major barriers for a further expansion of biofuels are their high costs (compared to fossil fuels), moderate ecological performances, limited feedstocks for biofuel production and their competition with food production. The objective of this paper is to investigate the market prospects of biofuels up to the year 2030. It focuses on the three currently most important regions for biofuels production and use: the US, EU and Brazil which in 2010 accounted together for almost three-quarters of global biofuel supply. Our method of approach is based on a dynamic economic framework considering the major cost components of biofuels and corresponding technological learning with respect to capital costs. Moreover, for the analysis of the competitiveness of biofuels with fossil fuels also taxes are considered. The most important result is that under existing tax policies biofuels are cost-effective today and also for the next decades in the regions investigated. However, their potentials are restricted especially due to limited crops areas, and their environmental performance is currently rather modest. The major final conclusions are: (i) To reveal the real future market value of biofuels, a CO 2 based tax system should be implemented for all types of fuels providing a neutral environmental incentive for competition between all types of fossil and renewable fuels; (ii) Moreover, the research and development for all types of biofuels, but especially for second generation biofuels, has to be intensified. [ABSTRACT FROM AUTHOR]

• An innovative framework for energy benchmarking of buildings is proposed. • Entropy and cluster analysis reduced uncertainty in setting parameters of archetypes. • The machine learning technique used as a benchmarking tool showed high performance. • The benchmarking applied in actual buildings showed a high inefficiency ratio. Energy benchmarking of buildings has an important role in improving energy performance by establishing a reference for the energy efficiency of the building stock. The simulation of archetypes followed by a generalisation model has been widely used to obtain benchmarks. However, even though archetypes summarise the main features of the building stock, the uncertainties must be accounted for in the modelling process. Moreover, testing the response of the benchmarking model using the actual building stock data supports the reliability of the method. This paper aims to propose an innovative framework to reduce the uncertainty of archetypes for benchmarking buildings. A standard framework for data compiling is proposed and an assessment of the uncertainty of variables using entropy and cluster analysis allowed to obtain representative archetypes. An Artificial Neural Network (ANN) was used as a predictive tool, and it was applied to benchmark a sample of actual buildings. Also, the simulation outcomes were used to determine energy end-uses according to the climatic zones. The framework proposition is presented alongside with a practical application. The result is an unprecedented benchmarking model: the archetype considers more variation in parameters of the building stock with higher uncertainties. Additionally, the modelling process showed to be robust for combining different datasets, and the ANN achieved high-performance metrics. Conclusion indicates the potential of using the framework for other typologies. Moreover, the framework demonstration is used for a school stock in Brazil, showing a trend to the inefficiency while a specific case study was explored, showing the potential of the method to find faults in the building energy use. [ABSTRACT FROM AUTHOR]

• General framework for the optimal net present value of smart appliance investment. • A Tree Algorithm with Interior Point speedup the framework in days. • Forty important economic cities in Brazil taken as case studies using real data. • Payback and return on investment measures are not enough for economic analysis. • Full set of results available online. Smart homes allow optimized energy usage, allowing households to reduce electricity bills or even make profits. By 2020, 20% of all households in Europe will be expected to become smart homes. Although smart homes seem to be the future for homes, many customers have the perception that a transition from current homes to smart ones is unprofitable. Adopting a smart home concept requires investments for which the households desire a positive return. A question in this context is the following: for a given household, when and/or what set of home appliances/technologies should be acquired so that the investment made by householder has a positive financial return? The available tool to answer that question can be time-consuming from a practical perspective. Based on our previous work, this paper proposes a framework to help the transition from current houses to smart homes considering customized electricity usage and economic measures. A tree algorithm is developed to decrease the time needed by an economic analysis of each possible acquisition combination of smart appliances or equipment for a given user. The proposed framework is tested on 40 cases covering all Brazilian capital cities, whose results are available online and may be used directly as an approximation for economic analyses. An example of one case is described in detail. Results show that the proposed tree algorithm is able to reduce days of CPU time to solve the problem and Net Present Value should be used as an economic measure to answer the aforementioned question. [ABSTRACT FROM AUTHOR]

• Modeling interdependency between production and investment decisions is critical. • Investment in anaerobic digestion for vinasse treatment is advisable. • Second-generation ethanol via hydrolysis of surplus bagasse is still uncompetitive. • Long-term electricity contracting could hedge the risks accrued from investment. The past decades have seen a diversification of the sugarcane industry with the emergence of new technology to produce bioenergy from by-product and waste process streams. Given Brazil's ambitious goal of reducing green-house gas emissions by over 40% below 2005 levels by 2030, it is of paramount importance to develop reliable decision-making systems in order to stimulate investment in these low-carbon technologies. This paper seeks to develop a more accurate optimization model to inform risk-conscious investment decisions for bioenergy generation capacity in sugarcane mills. The main objective is for the model to enable a better understanding of how Brazilian government policies, such as the electricity price in the regulated market, may impact these investments, by taking into account the uncertainty in sugar, ethanol and spot electricity markets and the interdependency between production and investment decisions in terms of saleable product mix. The proposed methodology combines portfolio optimization theory with superstructure process modeling and it relies on simple surrogates derived from a detailed sugarcane plant simulator to retain computational tractability and enable scenario analysis. The case study of an existing sugarcane plant is used to demonstrate the methodology and illustrate how the model can assist decision-makers. In all of the scenarios assessed, the model recommends investment in extra bioelectricity capacity via the anaerobic digestion of vinasse but advises against investment in second-generation ethanol production via the hydrolysis of surplus bagasse. Furthermore, the decision to upgrade the cogeneration system with a condensation turbine is highly sensitive to the electricity price practiced in the regulated market, capacity constraints on the sugar-ethanol mix, and the accepted level of risk. Another key insight drawn from the case study is that recent market conditions have favored a production focused on the sugar business, making it challenging for policy-makers to create attractive scenarios for biofuels. Long-term electricity contracting appears to be the main hedging strategy for de-risking other products and investments in the sugarcane business, provided it is priced adequately. [ABSTRACT FROM AUTHOR]