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Copyright of International Journal of Professional Business Review (JPBReview) is the property of Open Access Publications LLC and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Energy consumption demand has shown successive records during recent months, primarily associated with heat waves in almost all Brazilian states. The effects of climate change induced by global warming and the increasingly frequent occurrence of extreme events, mainly regarding temperature and precipitation, are associated with this increase in demand. In this sense, the impact of meteorological variables on load demand in some substations in the northeast and southeast of Brazil was analyzed, considering the historical series of energy injected into these substations. Fifteen substations were analyzed: three in the state of São Paulo, six in Bahia, three in Pernambuco, and three in Rio Grande do Norte. Initially, essential quality control was carried out on the energy injection data. The SAMeT data sets were used for the variable temperature, and Xavier was used for precipitation and relative humidity to obtain a homogeneous data series. Daily and monthly data were used for a detailed analysis of these variables in energy demand over the northeast and southeast regions of Brazil. Some regions were observed to be sensitive to the maximum temperature variable, while others were sensitive to the average temperature. On the other hand, few cases showed the highest correlation with the precipitation and relative humidity variables, with most cases being considered slight or close to zero. A more refined analysis was based on the type of consumers associated with each substation. These results showed that where consumption is more residential, the highest correlations were associated with maximum temperature in most stations in the northeast and average temperature in the southeast. In regions where consumption is primarily rural, the correlation observed with precipitation and relative humidity was the highest despite being negative. A more detailed analysis shows that rural production is associated with irrigation in these substations, which partly explains consumption, as when rainfall occurs, the demand for irrigation decreases, and thus energy consumption is reduced. [ABSTRACT FROM AUTHOR]

As a result of the "Belt and Road" and "Going Global" policies, a growing number of Chinese power companies are expanding overseas, implementing global development strategies, and making investments in the overseas power industry. Several countries are undergoing an energy transition because of the rapid development of the world economy. This is being done to address the climate change issues that are a result of the overuse of fossil fuels. Brazil is also accelerating its pace of power transformation in its position as a major power generating country in Latin America. In addition to being the largest economy in South America, Brazil is also the country in which China has made the most investments. Additionally, Brazil is increasing its development efforts in wind power, photovoltaics, and other renewable energy sources in response to a large demand for renewable energy sources. Brazil's renewable energy sector offers a great deal of potential for investment based on solid foundations for cooperation between China and Brazil. The Grey Prediction Model was used for this research to forecast Brazil's renewable energy generation installed capacity, and the results show a positive trend in Brazil's renewable energy generation. There is a rapid growth in wind and photovoltaic power generation over the next 5 years, with growth rates reaching 50.39% and 182.99%, respectively, suggesting that there is potential for a broad range of development. Following this, the research applies factor analysis to assess investment risks associated with Brazil's renewable energy sector from 2000 to 2020. Based on the results of the study, Chinese power companies investing in Brazil's renewable energy sector face the greatest political risk, while other risks gradually decrease. To avoid political risks when investing, companies should place a high priority on preventing them. [ABSTRACT FROM AUTHOR]

Developing efficient energy conservation and strategies is relevant in the context of climate change and rising energy demands. The objective of this study is to model and predict the electrical power consumption patterns in Brazilian households, considering the thresholds for energy use. Our methodology utilizes advanced machine learning methods, such as agglomerative hierarchical clustering, k-means clustering, and self-organizing maps, to identify such patterns. Gradient boosting, chosen for its robustness and accuracy, is used as a benchmark to evaluate the performance of these methods. Our methodology reveals consumption patterns from the perspectives of both users and energy providers, assessing the corresponding effectiveness according to stakeholder needs. Consequently, the methodology provides a comprehensive empirical framework that supports strategic decision making in the management of energy consumption. Our findings demonstrate that k-means clustering outperforms other methods, offering a more precise classification of consumption patterns. This finding aids in the development of targeted energy policies and enhances resource management strategies. The present research shows the applicability of advanced analytical methods in specific contexts, showing their potential to shape future energy policies and practices. [ABSTRACT FROM AUTHOR]

Energy demand forecasting is crucial for effective resource management within the energy sector and is aligned with the objectives of Sustainable Development Goal 7 (SDG7). This study undertakes a comparative analysis of different forecasting models to predict future energy demand trends in Brazil, improve forecasting methodologies, and achieve sustainable development goals. The evaluation encompasses the following models: Seasonal Autoregressive Integrated Moving Average (SARIMA), Exogenous SARIMA (SARIMAX), Facebook Prophet (FB Prophet), Holt–Winters, Trigonometric Seasonality Box–Cox transformation, ARMA errors, Trend, and Seasonal components (TBATS), and draws attention to their respective strengths and limitations. Its findings reveal unique capabilities among the models, with SARIMA excelling in tracing seasonal patterns, FB Prophet demonstrating its potential applicability across various sectors, Holt–Winters adept at managing seasonal fluctuations, and TBATS offering flexibility albeit requiring significant data inputs. Additionally, the investigation explores the effect of external factors on energy consumption, by establishing connections through the Granger causality test and conducting correlation analyses. The accuracy of these models is assessed with and without exogenous variables, categorized as economical, industrial, and climatic. Ultimately, this investigation seeks to add to the body of knowledge on energy demand prediction, as well as to allow informed decision-making in sustainable energy planning and policymaking and, thus, make rapid progress toward SDG7 and its associated targets. This paper concludes that, although FB Prophet achieves the best accuracy, SARIMA is the most fit model, considering the residual autocorrelation, and it predicts that Brazil will demand approximately 70,000 GWh in 2033. [ABSTRACT FROM AUTHOR]

In view of the increasing demand for clean energy and the growing awareness of environmental sustainability, a bibliometric study examines the various facets of renewable natural gas (biomethane). Sustainable fuels are gaining importance as an alternative to fossil fuels because they are renewable and can reduce greenhouse gas emissions. In addition, an overview of the use of biomethane was compiled for Brazil. The country was chosen because it is the authors' home country. These emerging energy sources have the potential to play a critical role in the transition to a cleaner, more sustainable and cost-effective energy landscape, thereby reducing environmental impact and strengthening the resilience of our energy future. [ABSTRACT FROM AUTHOR]

In the literature, it is well known that there is a bidirectional causality between economic growth and energy consumption. This is why it is crucial to forecast energy consumption. In this study, four deep learning models, i.e., Long Short-Term Memory (LSTM), stacked LSTM, bidirectional LSTM, and Gated Recurrent Unit (GRU), were used to forecast energy consumption in Brazil, Canada, and France. After a training test period, the performance evaluation criterion, i.e., R2, mean square error, root mean square error, mean absolute error, and mean absolute percentage error, was performed for the performance measure. It showed that GRU is the best model for Canada and France, while LSTM is the best model for Brazil. Therefore, the energy consumption prediction was made for the 12 months of the year 2017 using LSTM for Brazil and GRU for Canada and France. Based on the selected model, it was projected that the energy consumption in Brazil was 38 597.14–38 092.88, 63 900–4 800 000 GWh in Canada, and 50 999.72–32 747.01 GWh in France in 2017. The projected consumption in Canada was very high due to the country's higher industrialization. The results obtained in this study confirmed that the nature of energy production will impact the complexity of the deep learning model. [ABSTRACT FROM AUTHOR]

Due to climate change conditions, natural ventilation potential may reduce over the years and increase dependence on HVAC systems. Moreover, occupants' behaviour regarding natural ventilation is a significant parameter affecting the thermal-energy performance of residential buildings as people tend to occupy their homes differently depending on their life, work and cultural routines. Therefore, in this study, the thermal-energy performance of a Global South (GS) housing case study located in Brazil was assessed in a future weather context. This paper included two major steps: (1) Optimization procedure to create optimized models based on different occupancy patterns; and (2) Parametric analysis to explore the building's thermal-energy performance for a given constructive design option, occupant behaviour and weather data. The optimization procedure included a multi-objective optimization based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to minimize discomfort hours and cooling energy demand, while parametric analysis explored the occupants' behaviour varieties derived from alternative occupancy patterns, ventilation availabilities and HVAC operation modes. The obtained future context simulation results indicated an increase in discomfort hours and cooling energy demand, while the most appropriate architecture design might vary depending on the occupancy behaviour. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study explores the technical, economic, and regulatory aspects of harnessing hydroelectric spilled energy for Green Hydrogen (GH2) production. Addressing challenges such as efficiency, infrastructure, and cost, it underscores the potential of GH2 in Brazil's electrical matrix. The research identifies substantial potential for this type of GH2 production in Brazil, estimating a range between 140,669.92 and 1,406,699.17 tons during the analyzed period, with emphasis on the Southeast/Midwest and North subsystems. This represents 7.43% of Brazil's annual potential for low-carbon hydrogen production. GH2-based electricity production could reach 2,814 to 28,134 GWh, supplying significant portions of Brazil's energy consumption. Notably, GH2's surplus electricity, entirely carbon-free, could mitigate up to 22.28 million tons of C O 2 emissions, highlighting its pivotal role in maximizing renewable energy utilization and supporting global decarbonization efforts, positioning Brazil as a prominent player in this GH2 production domain. • Brazil's untapped GH2 potential via hydro spills. • Identify key GH2 hubs in Brazil regions. • GH2 offsets 22.28Mt CO2 emissions. • Hydro spills generate valuable GH2. • GH2 transforms remote Northern areas. [ABSTRACT FROM AUTHOR]

Increasingly stringent pollutant emission regulations and a customer demand for a high-fuel economy drive the modern automotive industry to hurriedly solve the problem of decarbonization and powertrain efficiency, leading R&D towards alternative powertrain solutions and fuels. Electrification, today, plays the biggest role in the topic, with Mild Hybrid Electrified Vehicles (MHEVs) being the most cost-effective architectures, displaying dominance in smaller markets such as Brazil. One of the biggest challenges for HEVs' development is the complexity of the hybrid control system, knowing when to actuate the electric machine, and the optimum power delivery, plus the gearshift schedule becomes a hard optimization problem that plays a key role in powertrain efficiency and cost savings for the customer. This paper proposes the implementation of a genetic algorithm (GA) as a machine learning-based control strategy to determine the torque split and the gear engaged for each driving condition of an MHEV operation, aiming to optimize fuel consumption. A quasi-static model of the vehicle was developed in Matlab/Simulink version 2022b, the virtual vehicle was then tested following the FTP75 and HWFET driving cycles. Simulation results indicate that the control decisions taken by the GA are qualitatively coherent for all operation conditions, and even quantitatively coherent in some cases, and that the software has the potential to be used as a control strategy outside the simulation environment, in future steps of development. [ABSTRACT FROM AUTHOR]

There is an urgent need for energy sources with lower environmental impacts to dispose of waste generated by human activities. In this context, a holistic analysis of energy use of waste from agricultural and forestry activities, animal excreta, urban solid waste and sewage, waste from the pulp and paper industry and charcoal in Brazil is presented. Based on a bibliographic review, the current Brazilian panorama is presented in figures giving, a vision of national potential for harnessing bioenergy from this theoretical and technical potential. The QGIS3.24.2 Tisler geoprocessing tool was used to generate potentiality maps from census data of microregions and municipalities available in the IBGE database (2022) and in the Geocentric Reference System for the Americas (SIRGAS 2000). The results of map analysis by micro‐regions of the primary energy from agricultural residues highlight sugar cane, corn and soybeans crops, followed by wastewater and animal excreta. They stood out amont the studied sources of biomass with technical potentials of 53.17, 15.23 and 6.81 GW, respectively. With these results, it is concluded that Brazil could enable around 75 GW installed power, reusing all biomass, potentially 12.5 PJ, without considering the 16 GW already installed from sugarcane and paper black liquor plants. [ABSTRACT FROM AUTHOR]

Open water transposition channels in hot and arid regions, like those in the São Francisco River Integration Project (PISF) in Brazil, suffer significant water losses through evaporation. This paper proposes covering these channels with photovoltaic (PV) panels to reduce evaporation while simultaneously generating clean energy. The research aims to quantify water savings and energy generation potential across all channel lengths and assess whether the generated solar power can substitute grid electricity for powering the transposition pumps during peak hours, thereby enhancing energy efficiency. This study analyzed the state-of-the-art of PV generation and calculated their solar potential. Identified the specific characteristics of PISF channels and watercourses considering the regional geography, meteorology, irradiation, and social peculiarities. And, finally, assessed the feasibility of covering the watercourses with solar panels. The results reveal that covering all current PISF channels with PV panels could save up to 25,000 cubic meters of water per day, significantly contributing to water security and improving the quality of life for the local population. Additionally, the project could generate 1200 gigawatt-hours of electricity annually, meeting the energy demands of the transposition pumps during peak hours and promoting energy efficiency within the project. This research paves the way for utilizing PV technology to address water scarcity challenges and enhance the sustainability of water infrastructure projects in arid regions worldwide. [ABSTRACT FROM AUTHOR]

This paper addresses the optimization of contracted electricity demand (CD) for commercial and industrial entities, focusing on cost reduction within the Brazilian time-of-use electricity tariff scheme. Leveraging genetic algorithms (GAs), this study proposes a practical approach to determining the optimal CD profile, considering the complex dynamics of energy demand on a city-like load. The methodology is applied to a case study at the Federal University of Pará, Brazil, where energy efficiency and demand response initiatives as well as renewable energy projects are underway. The findings highlight the significance of tailored demand management strategies in achieving energy-related cost reduction for large-scale consumers, with implications for economic efficiency in energy consumption. [ABSTRACT FROM AUTHOR]

Since the 1970s, Brazil has carried out the most successful world program of commercial biomass for use and production of energy by stimulating its sugarcane industry and promoting the large-scale production of ethanol nationwide in response to the first oil shock. Today, the technologies behind ethanol production are well established. Brazil is the world's largest sugarcane supplier, producing its ethanol at a competitive price. If other sugarcane producing countries decided to join Brazil's move toward the production of this biofuel, what impacts might there be for each country's economy and employment? This is what we investigate in this paper. Prime candidates for ethanol production include Australia, China, Colombia, India, Indonesia, Mexico, Pakistan, the Philippines, Thailand, and the United States of America. We evaluated the potential socioeconomic impacts of developing this promising industry by using an input–output approach. More specifically, we adapted the Brazilian method of producing ethanol to these countries' distinct economies. We augmented the input–output table of each country, inserting a new ethanol industry based on the Brazilian ethanol production model. We also augmented their new ethanol industry's sales following a hypothetical hydrous and anhydrous ethanol consumption scenario. Thereafter, we reconcile the national accounts, concluding our analysis by quantifying and comparing the different net effects of this new industry for each of the assessed countries for the year of 2009. We demonstrate which industries would be expected to be positively or negatively impacted by this substitution in each country; and find that not all of the countries we assessed would experience positive socioeconomic results from emulating Brazil's production of ethanol. [ABSTRACT FROM AUTHOR]

Led by the emerging growth models perspective, research in comparative political economy has recently reintroduced demand drivers of economic growth into the centre of political-economic analysis. While this marks a significant advancement, current scholarship has, so far, focused mainly on explaining the endurance of existing growth models rather than the process of change. To begin addressing this gap, we identify one route to growth model change: the inclusion of organised labour into growth coalitions. Our proposed framework expands the role of growth coalitions in growth models by incorporating insights from the established literature on institutional change. Building on these insights, we distinguish between broad and narrow coalitions based on their scope, composition, and inclusive nature. With this distinction in mind, we argue that when a previously narrow coalition is broadened by incorporating organised labour, it can 'balance the scales', i.e. shift the growth model from a purely export-led model into a more balanced one. This shift occurs as labour's influence on policy promotes wage growth and redistribution which, in turn, fuel wage-based consumption. We demonstrate our theoretical framework through a comparative analysis of the primary case study of Israel and two additional cases of Brazil and Ireland. [ABSTRACT FROM AUTHOR]

Tourism serves as a crucial means of funding national development and ensuring the sustainability of local livelihoods in growing countries such as Brazil. Nevertheless, the accelerated growth of tourism in various nations might lead to significant environmental consequences due to heightened energy consumption. This surge in energy usage contributes to the exacerbation of global warming through the amplified release of carbon dioxide (CO2). In light of the increasingly evident impacts of climate change on the natural environment, a multitude of endeavors have been undertaken with the aim of attaining ecological sustainability. The objective of this study is to examine the dynamic effects of economic growth, energy consumption, and tourism on carbon emissions in Brazil by analyzing time series data spanning from 1990 to 2019. The stationarity of data was assessed through the application of unit root tests, while an autoregressive distributed lag (ARDL) approach was employed to analyze the relationship between the components, accounting for both the long-term and short-term dynamics. The empirical results indicate that a 1% rise in economic growth, energy consumption, and tourist arrivals leads to environmental deterioration by causing a respective increase in CO2 emissions of 1.37%, 1.06%, and 0.57% in the near term, and 0.72%, 0.62%, and 0.16% in the long term. This article presents policy ideas aimed at achieving carbon neutrality in Brazil by increasing the utilization of renewable energy sources, while simultaneously fostering sustainable tourism as a means to enhance the country's economy. Highlights •This study investigated the tourism-economy-energy-environment nexus in Brazil. •The econometric analysis revealed that tourism, energy use, and economic growth increase CO2 emissions. •This article offers policy suggestions to achieve sustainable tourism and carbon neutrality. [ABSTRACT FROM AUTHOR]

Coffee processing generates a large amount of organic waste, which has the potential for energy use through biogas production. Although Brazil dominates world coffee production, treating its residue with biogas technology is not a practice, especially due to this product's seasonality, which hampers continuous digester operation. The implementation of biogas production from coffee residues in a concept of industrial symbiosis could overcome this. This work evaluates the biogas energy potential from the main liquid residues of coffee processing (i.e., mucilage and wash water) and their integration with glycerin and cattle manure. Around 2773 m3 biogas day−1 would be produced (75% CH4), used as biomethane (734 thousand m3 year−1), or thermal energy (23,000,000 MJ year−1), or electricity (2718 MWh year−1), which could supply, respectively, all the liquefied petroleum gas (LPG) and diesel demands of the farm, all the thermal energy demands of the grain drying process, as well as electricity for 30 residences. Considering the short coffee season, the results have a broader context for the application of biogas production on coffee processing farms, envisaging that the Agroindustrial Eco-Park concept has the potential to integrate various agroindustrial sectors for energy production, residue exchange, and water recirculation. [ABSTRACT FROM AUTHOR]

We seek to debate the fallacy of the notion of energy transition. To this end we are based on the case study of energy production and consumption and the emission of Greenhouse Gases (GHG) in Brazil and, more particularly, the Petrobras group (Petróleo Brasileiro SA). We start from the hypothesis that the transition is a myth that covers up the real urgency of reducing global warming and exiting the economic processes of capital accumulation. Until society changes radically, the transition serves as an excuse, including for oil companies, to continue their activities of expanding production, infrastructure and oil exploration. [ABSTRACT FROM AUTHOR]

Brazil is a tropical country with favorable conditions for the generation and utilization of solar energy. This energy source becomes even more attractive when considering the dry periods that impact hydroelectric power generation in the country, resulting in an increase in energy costs reflected monthly in consumers' bills through tariff flags. In order to enhance residential architectural designs and promote energy efficiency, a feasibility study of photovoltaic systems was conducted, considering key economic indicators and the current tariff flags. To accomplish this, research was conducted in collaboration with Mounting Companies for a case study located in the city of Rio de Janeiro, adopting technical assumptions commonly used for residential photovoltaic system sizing. For the graphical sizing of the case study, factors such as the environment and summer and winter solstices were taken into account, and a shadow study was conducted to assess the potential loss of power generation by the photovoltaic system throughout the year. The shadow study revealed that, during both solstices, the optimal time for power generation by photovoltaic systems is between 9 a.m. and 6 p.m. Essentially, the calculated values of NPV (Net Present Value) and IRR (Internal Rate of Return) indicate that the project is economically viable and particularly advantageous during the yellow and red tariff flags, situations in which energy costs tend to be higher for consumers. [ABSTRACT FROM AUTHOR]

The BRICS nations—Brazil, Russia, India, China, and South Africa—have grown significantly in importance over the past few decades, playing a vital role in the development and growth of the global economy. This expansion has not been without cost, either, since these countries' concern over environmental deterioration has risen sharply. Both researchers and decision-makers have focused a lot of attention on the connection between economic growth and ecological sustainability. By using nonlinear autoregressive distributed lag (NARDL) approach, the complex relationships were analyzed between important economic indicators—such as gross domestic product (GDP), ecological innovations (EI), energy consumption (ENC), institutional performance (IP), and trade openness (TOP)—and their effect on carbon emissions and nitrous oxide emissions in the BRICS countries from 1990 to 2021, this study seeks to contribute to this important dialog. Principal component analysis is formed for technological innovations and institutional performance using six (ICT service exports as a percentage of service exports, computer communications as a percentage of commercial service exports, fixed telephone subscriptions per 100 people, internet users as a percentage of the population, number of patent applications, and R&D expenditures as a percentage of GDP) and twelve (government stability, investment profile, socioeconomic conditions, internal conflict, external conflict, military in politics, control of corruption, religious tensions, ethnic tensions, law and order, bureaucracy quality, and democratic accountability) distinct indicators, respectively. The results of nonlinear autoregressive distributed lag estimation show that increase in economic growth would increase carbon dioxide and nitrous oxide emissions. The positive and negative shocks in trade openness have positive and significant impact on carbon dioxide and nitrous oxide emissions in BRICS countries. Furthermore, the positive shock energy consumptions have positive and significant effect on Brazil and India when carbon dioxide and nitrous oxide emissions are used. However, EKC exists in BRICS countries when carbon dioxide and nitrous oxide emissions are used. According to long-term estimation, energy consumption and technological innovations in the BRICS countries show a strong and adverse link with nitrous oxide and a favorable relationship with carbon dioxide emissions. In the long run, environmental indicators are seen to have a major and unfavorable impact in BRICS nations. Finally, it is proposed that BRICS nations can assure environmental sustainability if they support creative activities, enhance their institutions, and support free trade policies. [ABSTRACT FROM AUTHOR]

The Ilex paraguariensis is a species native to Brazil, Paraguay and Argentine, valued by its positive effects on human health. Mate processing consists of the following stages: pre-drying (rapid drying at high temperature, known as sapeco operation), drying, and milling. In order to verify the current process and to propose future improvements to the mate processing, thermal and mass balance analysis were applied to industrial mate processing units. Results showed that the consumption of energy in sapeco and drying operations exceeds the calorific input necessary for these operations. These results verify the need for a change in the management of temperatures in the sapeco and drying stages of mate processing in order to optimize the consumption of energy, resulting in lower costs, with positive effects on the quality of the mate products. [ABSTRACT FROM AUTHOR]

Study region: The Três Marias 396 MW power plant located on the São Francisco River in Brazil. Study focus: Hydropower generation is directly and indirectly affected by climate change. It is also a relevant source of energy for electricity generation in many countries. Thus, methodologies need to be developed to assess the impacts of future climate scenarios. This is essential for effective planning in the energy sector. Energy generation at the Três Marias power plant was estimated using the water balance of the reservoir and the future stream flow projections to the power plant, for three analysis periods: FUT1 (2011–2040); FUT2 (2041–2070); and FUT3 (2071–2100). The MGB-IPH hydrological model was used to assimilate precipitation and other climatic variables from the regional Eta climatic model, via global models HadGEM2-ES and MIROC5 for scenarios RCP4.5 and RCP8.5. New hydrological insights for the region: The results show considerable reductions in stream flows and consequently, energy generation simulations for the hydropower plant were also reduced. The average power variations for the Eta-MIROC5 model were the mildest, around 7% and 20%, while minimum variations for the Eta-HadGEM2-ES model were approximately 35%, and almost 65% in the worst-case scenario. These results reinforce the urgent need to consider climate change in strategic Brazilian energy planning. [ABSTRACT FROM AUTHOR]

Considering the negative consequences of the excessive use of non-renewable energy and the development of technologies related to photovoltaic energy, the present paper aims to analyze if the photovoltaic systems are economically viable for university hospitals. A photovoltaic system was designed in the parking lot of the University Hospital of the Federal University of São Carlos (UFSCar) and analyzed the financial viability of its installation. As a result, the photovoltaic system is financially viable, with an expected generation of 194.2 MWh in the first year and a payback of 7 years. Thus, this paper contributes to the feasibility of photovoltaic projects in university hospitals, reducing electric energy consumption, reducing its operational costs, reducing the emission of pollution, and diversification of the Brazilian energy matrix. Furthermore, the results can be used as a scientific basis for other fields, such as public and private hospitals and clinics. [ABSTRACT FROM AUTHOR]

On average, 70% of the world's freshwater is used in agriculture, with farmers transitioning to electrical irrigation systems to increase productivity, reduce climate uncertainties, and decrease water consumption. In Brazil, where agriculture is a significant part of the economy, this transition has reached record levels over the last decade, further increasing the impact of energy consumption. This paper presents a methodology that utilizes the U-Net model to detect flooded rice fields using Sentinel-2 satellite images and estimates the electrical energy consumption required to pump water for this irrigation. The proposed approach involves grouping the detected flooded areas using k-means clustering with the electricity customers' geographical coordinates, provided by the Power Distribution Company. The methodology was evaluated in a dataset of satellite images from southern Brazil, and the results demonstrate the potential of using U-Net models to identify rice fields. Furthermore, comparing the estimated electrical energy consumption required for irrigation in each cluster with the billed energy values provides valuable insights into the sustainable management of rice production systems and the electricity grid, helping to identify non-technical losses and improve irrigation efficiency. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Engenharia Agricola e Ambiental - Agriambi is the property of Revista Brasileira de Engenharia Agricola e Ambiental and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The performance of water heating systems must be evaluated considering energy consumption and efficiency in storing and distributing hot water, together with building and climate characteristics. This work aims to analyse the performance of different water heating systems compared to electric showers, which are widely used in Brazil. Systems with individual gas heaters and solar heaters with electric backup and gas backup were analysed in multi-family buildings. In addition, the influence of thermal insulation of hot water pipes was verified. The analyses were conducted using the EnergyPlus programme, considering three Brazilian cities with different climates: Curitiba, Brasília, and Belém. The results showed that solar heaters are a low primary energy consumption alternative, especially if combined with gas heaters. However, electric showers are the most efficient option for larger buildings and cold-climate cities, where thermal losses in distribution are more significant. Monthly, an electric shower can save up to 1.82 kWh/m2 of electricity compared to a solar heating system with an electric backup. The insulation has a limited influence on the performance of short-length pipes (temperature difference less than 0.3 °C in the instantaneous gas system). For longer pipes, the absence of insulation significantly reduces the shower temperature (up to 2.47 °C in solar heating systems), mainly in cold-climate locations. It is concluded that the most suitable water heating system should be determined according to the climate and characteristics of the buildings, such as the size and length of the pipe. [ABSTRACT FROM AUTHOR]

Sugarcane is the most traded crop in the world, with Brazil being the world's largest producer. Sugarcane processing generates up to 28% of sugarcane bagasse (SB) from the entire plant, with only 50% of it used for energy generation. SB is a lignocellulosic biomass that can be converted into biogas. However, the optimization of pretreatment process parameters is essential for its successful scaling up. This study evaluated the effect of mild alkaline pretreatment of SB using NaOH and KOH at concentrations of 1–10% and exposure time of 1–12 hours) on the biochemical methane potential (BMP) under mesophilic temperature. The central composite rotatable design (CCRD) was applied as statistical tool to generate optimal operating pretreatment conditions. The tests were performed in triplicates totalizing 84 batch bottles. The BMP of the untreated SB varied between 297–306 LN CH4 kg VS−1 while the BMP of the pretreated samples with NaOH and KOH were 19% and 20% higher. The optimized conditions were NaOH at 7.7% and KOH at 8.3% KOH for 12 hours. However, the range indicated by the statistical design with CCRD revealed that there was no statistical difference in terms of methane yield when concentrations between 4–10% NaOH and 6–10% KOH during 12 hours were applied, when compared to the specific optimized points. The optimization of the pretreatment parameters demonstrated to be a key-factor to improve the anaerobic digestion of lignocellulosic substrates, leading to a less chemically dependent and more sustainable approach, while allowing a more profitable process. [ABSTRACT FROM AUTHOR]

The search for species that produce high-quality charcoal is necessary to reduce the use of non-renewable sources of energy in the steel industry. Therefore, the present study aimed to evaluate the quality of new and non-commercial charcoal species in Brazil. Eight species of Corymbia and Eucalyptus were sampled and carbonized on a laboratory scale. The gravimetric yields of the carbonization, proximate and ultimate analysis, apparent density (AD) and energy density (ED), higher heating value (HHV), ignition (Di), and combustion (Si) indexes were determined through the curve of thermogravimetric derivative (DTG). The results suggest that C. variegata, E. longirostrata, E. major , C. henryi, and C. citriodora are competitively promising for producing charcoal for the steel industry when compared to the commercial species (E. urophylla) since they produce low reactivity charcoal (Si ∼3 × 107%2 min−2 °C−3), high energy density (>13 GJ m−3) and apparent density (>400 kg m−3). These characteristics are essential for a better energy performance, making the non-commercial species appropriate for use in Brazilian steel industry since there is a reduction on the energy consumption in the blast furnace per ton of iron produced. [ABSTRACT FROM AUTHOR]

Energy auctions are commonly used to contract energy projects and are extensively studied from the regulator's perspective. However, analyzing auctions from the stakeholders' perspective is critical to determine the impact of regulatory details on the bidder's revenues. In this study, we analyze a public energy auction in Roraima, a Brazilian state with a significant energy deficit and no grid connection, where many projects were successful in the non-intermittent Power Product category, typically unfavorable for biomass. Using Linear Programming to maximize bidders' revenues, we examine the regulatory formulas that contributed to the success of these projects and compare the optimization results to actual revenues. Our analysis shows that certain regulatory elements can benefit stakeholders by allowing them to make unconventional project design decisions. In addition, we identify a possible loophole in the formula that can have the opposite effect of the regulator's intent in the renewable Power Product category. Our findings can help bidders increase profits through optimization and regulators to change formulas if objectives are not met. This study brings the often-overlooked perspective of stakeholders to energy auctions, adding to the literature on this topic. [ABSTRACT FROM AUTHOR]

Geopolitical risk (GPR) and other social indicators have raised many somber environmental-related issues among government environmentalists, and policy analysts. To further elucidate whether or not these indicators influence the environmental quality, this study investigates the impact of GPR, corruption, and governance on environmental degradation proxies by carbon emissions (CO2) in BRICS (Brazil, Russia, India, China, and South Africa) countries, namely Brazil, Russia, India, China, and South Africa, using data over the period 1990 to 2018. The cross-sectional autoregressive distributed lag (CS-ARDL), fully modified ordinary least square (FMOLS), and dynamic ordinary least square (DOLS) methods are used for empirical analysis. First and second-generation panel unit root tests report a mixed order of integration. The empirical findings show that government effectiveness, regulatory quality, the rule of law, foreign direct investment (FDI), and innovation have a negative effect on CO2 emissions. In contrast, geopolitical risk, corruption, political stability, and energy consumption have a positive effect on CO2 emissions. Based on the empirical outcomes, the present research invites the concentration of central authorities and policymakers of these economies toward redesigning more sophisticated strategies regarding these potential variables to protect the environment. [ABSTRACT FROM AUTHOR]

Copyright of Düzce University Journal of Forestry / Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi is the property of Duzce University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study discusses the choice of dehumidification systems for high-moisture indoor environments, such as indoor swimming pools, supported by an eco-energetic performance comparison. Initially, the causes of the high relative humidity and condensation in these spaces are reported, as well as the available dehumidification technologies. Two different solutions are described: desiccant wheel dehumidification and re-cooling. The energy demand required by a refrigeration system is lower than the desiccant wheel; however, the former system requires less maintenance and does not require refrigerant fluid. An eco-energetic comparison is performed between the two systems in two countries with different energy matrices (Brazil and USA). In Brazil, the desiccant wheel is the best choice for the past 10 years, with a predicted 351,520 kgCO2 of CO2 emissions, which is 38% lower than the refrigeration system. In the USA, the best option is the refrigeration system (1,463,350 kgCO2), a 12% more efficient option than desiccant wheels. This model can be considered for energy and CO2 emissions assessment, predicting which system has better energy efficiency and lower environmental impact, depending on the refrigerant type, location and environmental conditions. [ABSTRACT FROM AUTHOR]

The mushroom market has seen accelerated growth in today's world. Despite advances in technology, harvesting is a more artisanal procedure. Countries such as Portugal and Brazil are not self-sufficient in mushroom production. Among the difficulties in the production of mushrooms is the question of acclimatization using temperature and relative humidity control. An experimental study was conducted. Energy analyzers were placed in the lighting, acclimatization, and water pumping system to produce 2200 kg of mushrooms in an acclimatized shed with an area of 100 m2. Energy consumptions of 48 kWh for lighting, 1575 kWh for air conditioning, and 9 kWh for pumping water were determined. A TEWI index of 0.7515 kWh/kg of Paris-type mushroom (Agaricus bisporus) was found. With equipment using R-454 B as a refrigerant, the estimated TEWI using the proposed HVAC equipment model was 0.537 kWh/kg, and CO2 emissions were reduced from 18,219 to 5324.81, a reduction of 70%. Thus, the proposed HVAC equipment model can potentially decrease greenhouse gas emissions and energy consumption in mushroom production, making a step towards achieving sustainability and mitigating climate change. [ABSTRACT FROM AUTHOR]

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 tCO2eq 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. [ABSTRACT FROM AUTHOR]

In this study, we analyzed the energy and reproductive cycles of female and male Gymnodactylus geckoides in the Caatinga area of northeast Brazil. We investigated whether these proxies of body condition, such as reproductive cells maturation and cellular structures changed in response to variation in abiotic and biotic factors (i.e., humidity, temperature, seasonality, body temperature, growing rate and gonad volume), using individuals stored under scientific conditions collected between September 2018 and December 2021. The condition factor showed an isometric growth pattern in the population studied. Meanwhile, the lipid, hepatic, and gonad factors correlated with body growth and showed monthly and seasonal variations, as well as reproductive cell maturation and cellular structure morphology. The cycles displayed constant replacement of energy reserves and mature reproductive cells, indicating constant and acyclic reproduction in G. geckoides. Energy reserves appear to be used for many reproductive activities, including meeting, gestation, and egg laying that occur at different frequencies during different periods in the dry and rainy seasons. Therefore, the reproductive cycle is likely to be strongly controlled by biotic factors, which are modeled using abiotic factors and environmental conditions (environmental patterns which proportionate greater resource availability). Our study is the first to investigate energy cycles and reproductive strategies in G. geckoides. It has shown that this species stores greater amounts of energy during the rainy season and then depletes these reserves during the dry period, since the rainy season correspond to the increase in energy consumption, mainly because of gestation and egg laying. [ABSTRACT FROM AUTHOR]

Brazil's agriculture and livestock annually generates enormous amounts of biomass, which varies in its biochemical composition. Many studies have pointed out the benefits of using this biomass as a substrate for biogas production through anaerobic digestion (AD), mostly via the co‐digestion (co‐AD) pathway. The agriculture and livestock of southeastern Brazil – sugarcane, orange, corn, soybean, coffee, cattle, swine, and poultry – have together demonstrated their potential for producing biomass that can be used for maximizing methane production. Filter cake, vinasse, straws, bagasse, mucilage, pulp, washing water, thin stillage, and manures also have specific organic matter and nutrient content that can be evaluated from an economic perspective as co‐products of biorefineries. Some are costless but others have acquisition costs in the agricultural market. Comparing the recent biochemical compositions cited in scientific literature (technical parameter) and to know the costs (valuation parameter) is crucial for farmers and investors make decisions in large‐scale. This study conducted a bibliographical survey of biomass generated in Brazilian agroindustry as a co‐substrate for energy production. The analysis summarized two tables: 1‐ a compilation of biochemical composition of the main co‐substrates, and 2‐ the acquisition or opportunity costs, discussing innovative aspects in the context of biogas production. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Copyright of Sustainability in Debate / Sustentabilidade em Debate is the property of University of Brasilia, Center for Sustainable Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study aims to determine the factors that affect the forest products footprint (FPF) in Brazil during the period 1965–2018 by proposing a new cointegration test which augments the Engle-Granger cointegration test with a Fourier function (Fourier Engle-Granger) and allows multiple structural breaks in the long-run relationship. Since the results of the unit root tests show that all variables are nonstationary, we applied the Fourier Engle-Granger cointegration test and revealed that there was a long-term relationship between the forest products' footprint, energy consumption, gross domestic product, and trade openness. Although energy consumption was found to have a decreasing effect on FPF, the remaining variables were found to have a healing effect on FPF. Policymakers in Brazil should consider shifting energy consumption to clean energy sources and sustain international trade and economic growth in the current form to consider the FPF. [ABSTRACT FROM AUTHOR]

Seas and oceans offer great potential as a widely available source of clean and renewable energy near high energy consumption centers. This source of energy is a valuable option in the energy transition and in energy matrix decarbonization. Wave energy and an oscillating water column (OWC) device stand out as the types of ocean energy with the most potential. An onshore OWC requires locations with rocky outcrops and steeper slopes as the device needs to be physically installed and has lower energy dissipation due to friction with the seabed. However, Brazil has approximately 7490 km of coastlines, with various shoreline geometries and geomorphologies, some of which are very suitable for OWC implementation. Some authors have estimated that the Brazilian coast has a total potential of 114 GW, distributed between wave and tidal energy, with a great possibility of contributing to global decarbonization efforts. This study aimed to identify and quantify the potential of locations suitable for implementing wave energy farms equipped with onshore OWC. For this, a prospect was carried out using the georeferencing software QGIS, resulting in a georeferenced map with a dataset of 319 locations, and determining a power capacity of exploitation of 9.84 GW and an estimated energy of 83,689 GWh/year in ten of the seventeen coastal states. This energy corresponds to twice the energy consumption of the state of Rio de Janeiro, which has a population of approximately 17.5 million people. If the same amount of wave energy as gas-fired thermal generation energy were to be consumed, the use of wave energy would reduce emissions by approximately 44.52 million tons of CO2 annually. This result suggests that wave energy generation should be included in future studies on the expansion of Brazilian electric systems as an accelerating factor in the energy transition. [ABSTRACT FROM AUTHOR]

This study investigates the time–frequency nexus of carbon dioxide (CO2) emissions with economic growth, nonrenewable (i.e., coal, natural gas, and oil), and renewable (i.e., hydro and geothermal) energy consumption. In this context, BRICS countries (namely, Brazil, Russian Federation, India, China, and South Africa), which are leading emerging countries, are included, and quarterly data from 1990/Q1 to 2019/Q4 is used. The study employs the wavelet coherence (WC) approach to explore the co-movement between the variables at different frequencies. The empirical results show that (i) there is a strong and positive co-movement between CO2 emission and economic growth; however, it is weak for Russia and South Africa in the medium and long-term; (ii) coal energy consumption is strongly and positively co-moved with CO2 emission for all BRICS countries; (iii) natural gas energy consumption is strongly and positively co-moved with CO2 emissions in Brazil, India, and China; however, it is weakly and positively co-moved in Russia and South Africa; (iv) oil energy consumption is strongly and positively co-moved with CO2 emissions in Brazil, India, and China; however, it changes a bit for Russia and South Africa; (v) hydro energy consumption is weakly and positively co-moved with CO2 emissions in general, whereas country-based results vary; (vi) geothermal energy consumption is also similar to hydro energy consumption. Thus, the WC results highlight the strong co-movement of economic growth and nonrenewable energy consumption with CO2 emissions, whereas renewable energy consumption has a relatively lower co-movement. Based on the results, policy implications are also discussed for BRICS countries. [ABSTRACT FROM AUTHOR]

The use of renewable energy, notably solar and wind energy, has grown exponentially in Brazil. Consumers can generate their energy using renewable sources, whether interconnected to the distribution system (on-grid) or not (off-grid). In this paper, a fuzzy method is developed for the recommendation of solar and wind sources, for any location in the Brazilian territory. In many aspects, it can be viewed as a representation of human decision-making using sets and inference rules and also can be with vagueness and uncertainty, being very useful to idealize recommendation systems. Georeferenced and historical data were obtained from 2003 to 2019 on solar irradiation and wind speed, and electricity consumption until 2021. With the energy generation data from photovoltaic panels and wind turbines, this method allows us to propose installed areas by each technology and obtain the membership of fuzzy recommendation between solar, wind, both solar and wind, unfeasible or hybrid. In addition, a long short-term memory neural network and the seasonal autoregressive integrated moving average model were used to predict consumption for more than 30 months ahead, allowing the recalculation of fuzzy memberships and updating the installation area by respective technologies. As a result, the recommendation is given as the installed area (m2) of each technology per km2 of consumer units, as a function of the regional consumption density (MWh/km2). It can be concluded that it is possible to plan the viability of the type of renewable energy used, according to regional characteristics for smaller consumer units (farms, cooperatives, industries, consortiums), given the diversity of these factors in the huge Brazilian territory. This methodology is in line with the Brazilian Normative Resolution that authorizes the generation of energy by landowners. [ABSTRACT FROM AUTHOR]

In this paper, the effects of economic growth and four different types of energy consumption (oil, natural gas, hydroelectricity, and renewable energy) on environmental quality in terms of carbon dioxide (CO2) emissions were examined within the framework of the Environmental Kuznets Curve (EKC) for three Latin American countries, namely, Argentina, Brazil, and Chile, from 1975 to 2018. The autoregressive distributed lag (ARDL) in the form of Error Correction Mechanism (ECM) was used to verify the validity of the EKC hypothesis and the impacts of the variables in the short and the long run alike. Furthermore, the Toda-Yamamoto Granger causality test was carried out to identify the direction of causality between the variables. From ARDL-ECM estimation, the EKC was confirmed (inverted U-shaped curve between income growth and CO2 emissions) only in Argentina in the long run but not in Brazil and Chile. Based on the findings, renewable energy can have a great potential in reducing CO2 emissions in the future, but this advantage has not been fully exploited yet since a significant negative impact on CO2 emissions was only found in Chile. Also, the use of other less carbon-intensive energy sources such as natural gas and hydropower if they could be combined with renewable energy would be of great benefit and contribute to enhancing environmental quality and energy security in the short and the medium term and to successful low-carbon energy transition in the long run in Argentina, Brazil, and Chile. [ABSTRACT FROM AUTHOR]

Improvements in modelling energy systems of populous emerging economies are highly decisive for a successful global energy transition. The models used–increasingly open source–still need more appropriate open data. As an illustrative example, we take the Brazilian energy system, which has great potential for renewable energy resources but still relies heavily on fossil fuels. We provide a comprehensive open dataset for scenario analyses, which can be directly used with the popular open energy system model PyPSA and other modelling frameworks. It includes three categories: (1) time series data of variable renewable potentials, electricity load profiles, inflows for the hydropower plants, and cross-border electricity exchanges; (2) geospatial data on the administrative division of the Brazilian federal states; (3) tabular data, which contains power plant data with installed and planned generation capacities, aggregated grid network topology, biomass thermal plant potential, as well as scenarios of energy demand. Our dataset could enable further global or country-specific energy system studies based on open data relevant to decarbonizing Brazil's energy system. [ABSTRACT FROM AUTHOR]

Purpose: Energy consumption and renewable energy sources are included in the goals for the 2030 Sustainable Development Goal 7 (SDG7) agenda, and target buildings are the biggest electricity consumers. In turn, Netzero energy buildings (NZEB) contribute to achieve SDG7 goals. This paper aims to identify which Brazilian higher education institutions (HEIs) practices contribute to developing the NZEB concept. Design/methodology/approach: Case studies were selected to identify which implanted practices applied by HEIs in Brazil, listed in the UI GreenMetric 2020 Ranking, are related to the NZEB concept. The implemented sustainable practices were also analyzed to evaluate the connections and impact between universities and the local community. Findings: Results show the lighting and air conditioning retrofit were among the most common practices related to energy efficiency to reduce consumption. For renewable energy generation, photovoltaic solar energy is the most common practice used by HEIs. Research limitations/implications: Only Brazilian HEIs listed in the UI Green Metric Ranking were analyzed. No standard regulation or formal reports support the wide dissemination of the strategies adopted by HEIs in Brazil. Practical implications: The strategies adopted by HEIs related to Netzero buildings can reduce emissions, optimize operating costs and improve building comfort conditions, which connect all SDGs. Social implications: HEIs can promote awareness related to energy use and clean energy generation within the local community. Originality/value: This paper presents the most common strategies adopted by Brazilian HEIs. However, limitations related to lack of strategies, data transparency and specific Netzero energy regulation were also found. These issues can hinder other HEIs to adopt similar strategies and contribute to the promotion of SDG7 in Brazil. [ABSTRACT FROM AUTHOR]

Purpose: There is a great interest in developing eco-friendly operations as alternative uses of resources in the university campus, making the employment of technologies more sustainable. Practices such as energy management and efficiency initiatives have been encouraged to meet these sustainability goals. The purpose of this paper is to describe and discuss the main features of the GENIIOT project, a system of energy management using Internet of Things applied in a Brazilian university campus to support energy education practices and to promote lasting energy efficiency measures. The focus of the study is directed at the energy consumption of the air-conditioning system, which is responsible for 40% of the total electricity consumption. In addition, this project also scrutinizes processes such as the building occupants' comfort demands, lighting levels and energy waste control. Design/methodology/approach: A case study at the Unicamp campus was conducted to illustrate the design procedures through qualitative description. This study comprises an overview of the physical plant, hardware and software development, energy data monitoring, management process and energy education. Findings: The GENIIOT project enables energy efficiency actions by concerning the use of air-conditioning equipment based on monitored data, different types of monitored rooms, user's behaviors and their feedback. This initiative requires the engagement, awareness and actions from users combined with investment in energy efficiency to achieve an efficient use of this type of equipment. The proposed approach can be applied in the future to similar situations, inside the Unicamp campus and at other university campuses. In addition, this project can contribute to building efficiency analysis by using the hardware structure developed to monitor facilities and carry out evaluations, providing valuable information for strategic initiatives in energy efficiency projects and research and development programs based on practical experience and promoting a discussion about sustainability aspects in the context of the university campus for energy efficiency. Originality/value: The GENIIOT project is aligned with some of the sustainable development goals, among which sustainability and responsible consumption are identified. Considering the sustainability issues, the economic dimension can be evaluated through a cost–benefit analysis of energy efficiency projects with prudent investment, while the social attractiveness of the project is ensured by education and awareness practices for the community that interacts with the system and learns about a more efficient way of using resources in the campus. Furthermore, there is a more conscious use of natural resources by minimizing waste from the use of electricity and reducing carbon dioxide emissions. GENIIOT is part of Sustainable Campus Project, a living laboratory which aims at developing energy-efficiency-related research activities in the university campus to reduce costs in higher and federal institutions of education in Brazil. [ABSTRACT FROM AUTHOR]

Energy demand has increased worldwide, and biomass burning is one of the solutions most used by industries, especially in countries that have a great potential in agriculture, such as Brazil. However, these energy sources generate pollutants, consisting of particulate matter (PM) with a complex chemical composition, such as sugarcane bagasse (SB) burning. Controlling these emissions is necessary; therefore, the aim was to evaluate PM collection using a rectangular Venturi scrubber (RVS), and its effects on the composition of the PM emitted. Considering the appropriate use of biomass as an industrial fuel and the emerging need for a technique capable of efficiently removing pollutants from biomass burning, this study shows the control of emissions as an innovation in a situation such as the industrial one with the use of a Venturi scrubber in fine particle collection, in addition to using portable and representative isokinetic sampling equipment of these particles. The pilot-scale simulation of the biomass burning process, the representative sampling of fine particles and obtaining parameters to control pollutant emissions for a Venturi scrubber, meets the current situation of concern about air quality. The average collection efficiency values were 96.6% for PM> 2.5, 85.5% for PM1.0–2.5, and 66.9% for PM< 1.0. The ionic analysis for PM< 1.0 filters showed potassium, chloride, nitrate, and nitrite at concentrations ranging from 20.12 to 36.5 μg/m3. As the ethanol and sugar plants will continue to generate electricity with sugarcane bagasse burning, emission control technologies and cost-effective and efficient portable samplers are needed to monitor particulate materials and improve current gas cleaning equipment projects. [ABSTRACT FROM AUTHOR]

The present paper explored the effect of renewable energy, financial development, and technological innovation on the ecological footprint in Brazil using a yearly dataset stretching between 1990 and 2018. The research leverage dynamic autoregressive distributed lag, Bayern and Hank cointegration, and frequency domain causality to explore these interrelationships. The ARDL bounds test outcome confirms a long-run connection between ecological footprint and its drivers. Besides, we employed the Bayern and Hank cointegration, and the outcome resonated with the ARDL bounds test result. Moreover, the dynamic ARDL outcomes disclosed that economic progress worsens the ecosystem whilst renewable energy, trade globalization, and technological innovation lessen the ecological footprint. In addition, no significant interrelationship was found between financial development and ecological footprint. Moreover, with the exemption of financial development, all the exogenous variables can forecast the ecological footprint in Brazil. The study proposes that policymakers in Brazil should undertake investments in research and development in order to achieve technological innovation. Furthermore, since technological innovation has been shown to contribute significantly to lowering the ecological footprint, it is possible to assume that enhancing current technology is the ultimate remedy to Brazil's ecological problems. • Dynamic ARDL applied to Brazil's time series data. • Renewable energy and Technology innovation improve environmental quality. • Trade and globalization also reduce Ecological Footprints (EF). • Economic Growth contributes to higher EF. [ABSTRACT FROM AUTHOR]

Energy demand, especially in developing countries, is partly supplied by firewood and charcoal from natural forests. However, there are not always previous studies of energy quality, with implications for forest management. This study aimed to characterize the energy potential of the wood of six shrub-tree species from the Caatinga and the influence of the circumference class on their chemical properties and energy potential to subsidize forest management. Thus, Anadenanthera colubrina var. cebil (Angico), Cenostigma bracteosum (Catingueira), Cnidoscolus quercifolius (Faveleira), Mimosa ophthalmocentra (Jurema branca), Mimosa tenuiflora (Jurema preta) and Aspidosperma pyrifolium (Pereiro) from an area of Dry Forest (Caatinga) in Floresta, Pernambuco state, Brazil, were analyzed. Each species had three individuals sampled in five circumference classes (I a V) at 1.30 m from the ground. Carbon, hydrogen, nitrogen, insoluble lignin, and ash contents, as well as higher and lower calorific values, apparent and energetic densities and energy production were evaluated. Then, a completely randomized design in a factorial arrangement (species x circumference classes) with three replications, and comparison of means (Tukey’s test, p < 0.05) were considered in the statistical analysis. A Cluster analysis was also performed aiming at joint analysis of variables. The results showed that the biomass of M. ophthalmocentra and M. tenuiflora have the highest energy density and amount of energy per unit of mass. C. quercifolius and A. pyrifolium were lower when compared to the other species. In addition, M. ophthalmocentra, M. tenuiflora, A. colubrina and C. bracteosum stood out for energy generation. Classes IV and V can be indicated as biomass for combustion, while class I has disadvantages due to higher nitrogen content and lower upper and lower calorific values. [ABSTRACT FROM AUTHOR]