Complex artificial intelligence models for energy sustainability in educational buildings.

Energy consumption of constructed educational facilities significantly impacts economic, social and environment sustainable development. It contributes to approximately 37% of the carbon dioxide emissions associated with energy use and procedures. This paper aims to introduce a study that investigates several artificial intelligence-based models to predict the energy consumption of the most important educational buildings; schools. These models include decision trees, K-nearest neighbors, gradient boosting, and long-term memory networks. The research also investigates the relationship between the input parameters and the yearly energy usage of educational buildings. It has been discovered that the school sizes and AC capacities are the most impact variable associated with higher energy consumption. While 'Type of School' is less direct or weaker correlation with 'Annual Consumption'. The four developed models were evaluated and compared in training and testing stages. The Decision Tree model demonstrates strong performance on the training data with an average prediction error of about 3.58%. The K-Nearest Neighbors model has significantly higher errors, with RMSE on training data as high as 38,429.4, which may be indicative of overfitting. In contrast, Gradient Boosting can almost perfectly predict the variations within the training dataset. The performance metrics suggest that some models manage this variability better than others, with Gradient Boosting and LSTM standing out in terms of their ability to handle diverse data ranges, from the minimum consumption of approximately 99,274.95 to the maximum of 683,191.8. This research underscores the importance of sustainable educational buildings not only as physical learning spaces but also as dynamic environments that contribute to informal educational processes. Sustainable buildings serve as real-world examples of environmental stewardship, teaching students about energy efficiency and sustainability through their design and operation. By incorporating advanced AI-driven tools to optimize energy consumption, educational facilities can become interactive learning hubs that encourage students to engage with concepts of sustainability in their everyday surroundings.

Whole-plant corn silage harvesting modalities: energy efficiency and operational performance.

The need for energy rationalizing in farming operations require research that optimize grain crop conduction. The operations used in the processing and production of silage have limitations in energy optimization due to the lack of studies. This paper evaluated energy efficiency of whole-plant silage operations with the objective of favor the decision making. The adopted design of the experiment was in parcels (with seven replications), consisting of three harvesting modalities: single-line forage harvester, total area forage harvester, and total area forage harvester with support transshipment. The tractors were instrumented with sensors that measured engine rotation, travel speed, and hourly fuel consumption which were used to calculate field capacity, fuel consumption per area and per harvested mass, and production capacity of the harvester-tractor set. The results went to analysis of variance and subsequently to Tukey's test. The single had a faster speed and lower hourly fuel consumption, but smaller field capacity and greater energy expenditure for the mass. The use of support transshipment set with the front harvester allowed an improvement in the operation, with an increase in the worked area, and material processing (18%), and speed (13%), without differing in fuel expenditure. The total-area forage harvester modality showed smaller costs (USD 6.7), followed by the total-area forage harvester with support transshipment set (USD 7.7) and the single-line forage harvester (USD 9.38), respectively. The use of forage harvesters with a wider working width proved to be more efficient in terms of production costs per harvested hectare, validating it's reccomendation.

A Novel Traffic Prediction Method Using Machine Learning for Energy Efficiency in Service Provider Networks.

This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to test the methodology, a case study was conducted in the telecommunications industry to address the problem of energy efficiency in data centers. The case study involved comparing four recurrent and sequential neural networks, including recurrent neural networks (RNNs), long short-term memory (LSTM), gated recurrent units (GRUs), and online sequential extreme learning machine (OS-ELM), to determine the best network in terms of prediction accuracy and computational time. The results show that OS-ELM outperformed the other networks in both accuracy and computational efficiency. The simulation was applied to real traffic data and showed potential energy savings of up to 12.2% in a single day. This highlights the importance of energy efficiency and the potential for the methodology to be applied to other industries. The methodology can be further developed as technology and data continue to advance, making it a promising solution for a wide range of prediction problems.

Vinasse as a substrate for inoculant culture and soil fertigation: Advancing the circular and green economy.

Vinasse is a by-product with a key role in circular economy. In this work, we analyze sugarcane vinasse as culture medium for obtaining single and mixed inoculants. Trichoderma harzianum MT2 was cultured in single and sequential co-culture with Pseudomonas capeferrum WCS358 or Rhizobium sp. N21.2. Fungal biomass in single culture was more than three folds higher in vinasse than in a standard medium, and was higher in co-culture with Rhizobium sp. N21.2 than with P. capeferrum WCS358. Bacterial growths in vinasse, in particular P. capeferrum WCS358, were improved in co-culture with T. harzianum MT2. Residual vinasses, obtained after microbial growth, presented almost neutral pH and lower conductivities and toxicity than raw vinasse. Fertigation with residual vinasses modifies characteristics of soil evidenced in the total N, cation exchange capacity, urease and acid phosphatase, and microbial metabolic diversity, in comparison to raw vinasse. In general, soil fertigation with residual vinasse from co-culture with P. capeferrum WCS358 is more similar to irrigation with water. Treatment evaluation indicates that vinasse is suitable for the production of mixed inoculants containing T. harzianum. The co-culture with P. capeferrum WCS358 improves the characteristics of the residual vinasse allowing a fertigation with less detrimental effect in soil in comparison to Rhizobium sp. N21.2. Obtaining valuable biomass of single or mixed inoculants in vinasse with lower ecological impact is relevant for the circular and green economy.

Energy efficiency of drinking water treatment plants: A methodological approach for its ranking.

Drinking water treatment systems (DWTSs) are energy intensive facilities, and are an example of the water-energy nexus. Benchmarking energy efficiency is a valuable tool for improving the economic and environmental performance of such facilities. Data envelopment analysis (DEA) is typically used to assess efficiency, allocating flexible weights (FSW) to variables that maximise energy efficiency scores for each DWTS (DEA-FSW). It means that different conditions are applied to each DWTS. Moreover, the DEA-FSW approach has finite discriminatory power which limits cross-unit comparison of energy efficiency hindering the benchmarking of DWTSs. To overcome these limitations, our study explored the effect of estimating the energy efficiency scores of DWTSs by allocating common sets of weights (CSW) within DEA (DEA-CSW). This approach was applied empirically on a sample of 146 DWTSs. Evaluated DWTSs had poor energetic performance based on both DEA-FSW and DEA-CSW estimates (low energy efficiency scores: 0.329 and 0.163, respectively). Even in the optimistic scenario, the average energy efficiency score was low (0.220), with potential electricity savings of 78 % by DWTPs when energy efficient. Unlike DEA-FSW, DEA-CSW allowed energy efficient DWTSs to be distinguished from the 146 facilities. Significant differences in the weights allocated to electricity and pollutants removed from raw water were reported for both approaches, and contributed to diverging energy efficiency scores. In conclusion, this study demonstrated the relevance of using suitable methods to generate comparable results for water companies, allowing the energy performance of DWTSs to be objectively evaluated for benchmarking purposes.

Does energy efficiency improve environmental quality in BRICS countries? Empirical evidence using dynamic panels with heterogeneous slopes.

In a time of climate change, critically contributed by the increased global energy consumption, energy efficiency comes out as a critical factor in achieving sustainable growth for the countries. Given the fast economic advancement in the BRICS (Brazil, Russia, India, China, and South Africa) countries that have played a vital role in the global economy, energy usage, and climate governance, this study investigates the role of energy efficiency on the environmental quality of these countries. We proxy environmental quality with CO2 emissions, incorporate renewable energy in our models, and estimate the relationship with a long-panel data of 29 years (1990-2018). Our dynamic heterogeneous panel model findings confirm that energy efficiency significantly reduces CO2 emissions or improves environmental quality in the long run and the short run. Besides, we find that renewable energy has a crucial role in enhancing environmental quality in the long run with the negative impact of economic growth activities. Our findings contribute to the literature in a novel way facilitating the comprehension of the role of energy efficiency using a wide range of sophisticated techniques, thus providing robust results. For the policymakers, we humbly advocate strategies for the clean and sustainable economic transition based on our findings which has notable implications for the BRICS, other developing economies, and the world as a whole.

Assessment of energy efficiency and performance in a two-phase anaerobic process for organic matter removal.

Energy efficiency (EE) depends mainly on the lower heating values (LHVs) of hydrogen and methane selected from the thermodynamics tables under ideal conditions. However, for practical applications, the heating value should be calculated by considering some environmental factors under real conditions. Accordingly, this study compared EE using the ideal LHV with the EE using the real LHV in a two-phase anaerobic digestion reactor treating synthetic wastewater. Additionally, the process performance and the stability were studied. The results showed that the EE value calculated using LHVideal was, on average, 35% higher than that evaluated using LHVreal; these differences are relevant to the estimation of real energy and also for practical applications. At the same time, the index buffer intermediate alkalinity/partial alkalinity was shown to be more accurate than the pH value to analyze the stability of the process. With regards to chemical oxygen demand, the removal efficiency in the methanogenic phase decreased drastically when utilizing 100% of the acidogenic phase. Future considerations for the optimization of each phase are highlighted.

A causal link between renewable energy, energy efficiency, property rights, and CO2 emissions in developed countries: A road map for environmental sustainability.

CO2 emissions are the leading causes of deterioration in air quality and global warming. Likewise, it has been shown that clean energy reduces air pollution, so this would be a way out of environmental pollution. Some previous studies have focused on knowing the determinants of environmental pollution; however, they have omitted the State's role. Thus, this study explores the long-term nexus between CO2 emissions and renewable energy, energy efficiency, fossil fuels, GDP, property rights from 1995 to 2019 in nine developed countries. The results reveal a long-term equilibrium relationship in developed European countries, but not in developed non-European countries. The main results show that renewable energy and energy efficiency are negatively correlated with CO2 emissions. In developed European countries, a 1% increase in renewable energy consumption represents a 0.03% decrease in CO2 emissions. Finally, some policy measures are suggested to achieve environmental sustainability.

C-offset and crop energy efficiency increase due industrial poultry waste use in long-term no-till soil minimizing environmental pollution.

Brazil is one of the major global poultry producers, and the organic waste generated by the chicken slaughterhouses can potentially be used as a biofertilizer in agriculture. This study was designed to test the hypothesis that continuous use of biofertilizer to the crops, substituting the use of mineral fertilizer promote C-offset for the soil and generate crop energy efficiency for the production system. Thus, the objectives of this study were to evaluate the effects of biofertilizer use alone or in combination with mineral fertilizer on soil organic carbon (SOC) stock, carbon dioxide (CO2) mitigation, C-offset, crop energy efficiency and productivity, and alleviation of environmental pollution. The experiment was established in southern Brazil on a soil under 15 years of continuous no-till (NT). Experimental treatments were as follows: i) Control with no fertilizer application, ii) 100% use of industrial mineral fertilizer (Min-F); iii) 100% use of organic waste originated from poultry slaughterhouses and hereinafter designated biofertilizer (Bio-F), and iv) Mixed fertilizer equivalent to the use of 50% mineral fertilizer + 50% of biofertilizer (Mix-F). Effects of experimental treatments were assessed for the crop sequence based on bean (Phaseolus vulgaris), soybean (Glycine max) and corn (Zea mays) in the summer and wheat (Triticum aestivum) and black oat (Avena strigosaSchreb) in the winter composing two crops per year, as follow: bean/wheat-soybean/black oat-corn/wheat-soybean/black oat-corn/wheat-bean. The continuous use of Bio-F treatment significantly increased the index of crop energy efficiency. It was higher than that of control, and increased it by 25.4 Mg CO2eq ha-1 over that of Min-F treatment because of higher inputs of crop biomass-C into the system. Further, continuous use of Bio-F resulted in a significantly higher CO2eq stock and offset than those for Min-F treatment. A positive relationship between the C-offset and the crop energy efficiency (R2 = 0.71, p < 0.001) indicated that the increase of C-offset was associated with the increase of energy balance and the amount of SOC sequestered. The higher energy efficiency and C-offset by application of Bio-F indicated that the practice of crop bio fertilization with poultry slaughterhouse waste is a viable alternative for recycling and minimizing the environmental impacts.

Sustainability Indicators System Based on Multicriteria Analysis: A Tool for the Management of the Sustainability of Offshore Oil and Gas Production Units.

The increasing production of oil and gas in the marine environment and the growing participation of companies of different nationalities and sizes require the use of tools to support the sustainable management of offshore oil and gas production units. This paper presents the results of the application of a sustainability indicator system, developed from the identification of the economic, environmental, social, and operational impacts of the activities of these production units. The sustainability performances of 3 oil and gas production units operating in the Brazilian marine environment were compared to the performance of one considered ideal, through the application of the PROMETHEE II and ordinal COPELAND multicriteria methods. The indicator system applied favored the analysis of the sustainability management of offshore oil and gas production activity in a multidimensional approach, considering the points of view of experts from various areas of knowledge, and proved to be a reliable tool to support the sustainable management of these offshore production units. Integr Environ Assess Manag 2021;17:614-625. © 2020 SETAC.

Trilemma assessment of energy intensity, efficiency, and environmental index: evidence from BRICS countries.

This paper provides an assessment of energy density and energy efficiency and creates an important indicator of environmental performance. This article applied two mathematical models and econometric techniques to obtain detailed and specific results. The DEA and the non-normative account aggregation mean a collective aggregation to form a mathematical aggregation tool to create an environmental index for the BRICS countries (Brazil, Russia, India, China, and South Africa) based on available data from 2011 to 2016. The advantage of the proposed approach is to manage the irregularities of the data and follow the desired properties of the index number. The current paper is relevant for the broad scope of construction, the environmental index, and the evolution of the rankings of countries based on multiple indicators. Our results indicate that Brazil and Russia have the highest values of the Environmental Performance Index, which range between 67.44 and 60.70, respectively. India has a minimum value of 30.57 of the environmental index. The analysis shows that Brazil, Russia, and South Africa have the best scores and that these countries have the best results, while China and India also have the best results. This study can help form a valuable political tool for the development and development of the country's politics.

Traffic impact studies committed to sustainability: The case of Rio de Janeiro.

This article investigates whether the traditional approaches to Traffic Impact Studies (TISs) have evolved to meet the current needs of a society increasingly concerned with sustainability, especially in Brazil. For this purpose, we conducted a comprehensive literature review to identify the main sustainability aspects that should be covered by these studies, including the most suitable analytic techniques for this purpose, in particular for traffic simulation. We then prepared a proposal for classifying traffic impact studies and applied it in a specific case, in the city of Rio de Janeiro, the study of the Porto Maravilha port district revitalization project. This enabled understanding the current state of the practice of these studies in the country, indicating they are in general very poor, justifying the need for improvements.

Economic growth and energy consumption in Brazil: cointegration and causality analysis.

Energy is a crucial part of any economy and holds a central position in enhancing social development in the world. Energy consumption and the economy in Brazil have both increased in the past decade. In this paper, time series statistics from 1980 to 2017 will be used to analyze the relationship between real GDP per capita and energy consumption to will examine how energy use in the country affects economic growth using causality models. This is established through testing for stationarity using Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test for trend stationarity. A cointegration relationship is found between the two variables.

Techno-economic and environmental assessment of biogas production from banana peel (Musa paradisiaca) in a biorefinery concept.

Two scenarios for the biogas production using Banana Peel as raw material were evaluated. The first scenario involves the stand-alone production of biogas and the second scenario includes the biogas production together with other products under biorefinery concept. In both scenarios, the influence of the production scale on the process economy was assessed and feasibility limits were defined. For this purpose, the mass and energy balances were established using the software Aspen Plus along with kinetic models reported in the literature. The economic and environmental analysis of the process was performed considering Colombian economic conditions. As a result, it was found that different process scales showed great potential for biogas production. Thus, plants with greater capacity have a greater economic benefit than those with lower capacity. However, this benefit leads to high-energy consumption and greater environmental impact.

Energy savings, emission reductions, and health co-benefits of the green building movement.

Buildings consume nearly 40% of primary energy production globally. Certified green buildings substantially reduce energy consumption on a per square foot basis and they also focus on indoor environmental quality. However, the co-benefits to health through reductions in energy and concomitant reductions in air pollution have not been examined.We calculated year by year LEED (Leadership in Energy and Environmental Design) certification rates in six countries (the United States, China, India, Brazil, Germany, and Turkey) and then used data from the Green Building Information Gateway (GBIG) to estimate energy savings in each country each year. Of the green building rating schemes, LEED accounts for 32% of green-certified floor space and publically reports energy efficiency data. We employed Harvard's Co-BE Calculator to determine pollutant emissions reductions by country accounting for transient energy mixes and baseline energy use intensities. Co-BE applies the social cost of carbon and the social cost of atmospheric release to translate these reductions into health benefits. Based on modeled energy use, LEED-certified buildings saved $7.5B in energy costs and averted 33MT of CO2, 51 kt of SO2, 38 kt of NOx, and 10 kt of PM2.5 from entering the atmosphere, which amounts to $5.8B (lower limit = $2.3B, upper limit = $9.1B) in climate and health co-benefits from 2000 to 2016 in the six countries investigated. The U.S. health benefits derive from avoiding an estimated 172-405 premature deaths, 171 hospital admissions, 11,000 asthma exacerbations, 54,000 respiratory symptoms, 21,000 lost days of work, and 16,000 lost days of school. Because the climate and health benefits are nearly equivalent to the energy savings for green buildings in the United States, and up to 10 times higher in developing countries, they provide an important and previously unquantified societal value. Future analyses should consider these co-benefits when weighing policy decisions around energy-efficient buildings.

Wave energy resource of Brazil: An analysis from 35 years of ERA-Interim reanalysis data.

This paper presents a characterization of the wave power resource and an analysis of the wave power output for three (AquaBuoy, Pelamis and Wave Dragon) different wave energy converters (WEC) over the Brazilian offshore. To do so it used a 35 years reanalysis database from the ERA-Interim project. Annual and seasonal statistical analyzes of significant height and energy period were performed, and the directional variability of the incident waves were evaluated. The wave power resource was characterized in terms of the statistical parameters of mean, maximum, 95th percentile and standard deviation, and in terms of the temporal variability coefficients COV, SV e MV. From these analyses, the total annual wave power resource available over the Brazilian offshore was estimated in 89.97 GW, with largest mean wave power of 20.63 kW/m in the southernmost part of the study area. The analysis of the three WEC was based in the annual wave energy output and in the capacity factor. The higher capacity factor was 21.85% for Pelamis device at the southern region of the study area.

Life cycle water demand coefficients for crude oil production from five North American locations.

The production of liquid fuels from crude oil requires water. There has been limited focus on the assessment of life cycle water demand footprints for crude oil production and refining. The overall aim of this paper is address this gap. The objective of this research is to develop water demand coefficients over the life cycle of fuels produced from crude oil pathways. Five crude oil fields were selected in the three North American countries to reflect the impact of different spatial locations and technologies on water demand. These include the Alaska North Slope, California's Kern County heavy oil, and Mars in the U.S.; Maya in Mexico; and Bow River heavy oil in Alberta, Canada. A boundary for an assessment of the life cycle water footprint was set to cover the unit operations related to exploration, drilling, extraction, and refining. The recovery technology used to extract crude oil is one of the key determining factors for water demand. The amount of produced water that is re-injected to recover the oil is essential in determining the amount of fresh water that will be required. During the complete life cycle of one barrel of conventional crude oil, 1.71-8.25 barrels of fresh water are consumed and 2.4-9.51 barrels of fresh water are withdrawn. The lowest coefficients are for Bow River heavy oil and the highest coefficients are for Maya crude oil. Of all the unit operations, exploration and drilling require the least fresh water (less than 0.015 barrel of water per barrel of oil produced). A sensitivity analysis was conducted and uncertainty in the estimates was determined.

The Influence of Solar Power Plants on Microclimatic Conditions and the Biotic Community in Chilean Desert Environments.

The renewable energy sector is growing at a rapid pace in northern Chile and the solar energy potential is one of the best worldwide. Therefore, many types of solar power plant facilities are being built to take advantage of this renewable energy resource. Solar energy is considered a clean source of energy, but there are potential environmental effects of solar technology, such as landscape fragmentation, extinction of local biota, microclimate changes, among others. To be able to minimize environmental impacts of solar power plants, it is important to know what kind of environmental conditions solar power plants create. This study provides information about abiotic and biotic conditions in the vicinity of photovoltaic solar power plants. Herein, the influence of these power plants as drivers of new microclimate conditions and arthropods diversity composition in the Atacama Desert was evaluated. Microclimatic conditions between panel mounts was found to be more extreme than in the surrounding desert yet beneath the panels temperature is lower and relative humidity higher than outside the panel area. Arthropod species composition was altered in fixed-mount panel installations. In contrast, solar tracking technology showed less influence on microclimate and species composition between Sun and Shade in the power plant. Shady conditions provided a refuge for arthropod species in both installation types. For example, Dipterans were more abundant in the shade whereas Solifugaes were seldom present in the shade. The presented findings have relevance for the sustainable planning and construction of solar power plants.

Efecto del manejo sobre la diversidad de árboles en vegetación secundaria en la Reserva de la Biosfera de Calakmul, Campeche, México / Effect of management on tree diversity in secondary vegetation in the Biosphere Reserve of Calakmul, Campeche, Mexico

ResumenEl bosque tropical seco (BTS) de la Península de Yucatán ha sido manejado por siglos, pero la relación del efecto del manejo sobre la diversidad de árboles no ha sido completamente entendida. El objetivo de este estudio fue evaluar el efecto del manejo forestal (aclareos, aprovechamiento y enriquecimiento de especies) en la estructura de la vegetación secundaria derivada de bosques tropicales secos, en dos comunidades en Calakmul, Campeche, Sureste de México. Se analizaron cambios en la composición, riqueza de especies, diversidad de especies y estructura en vegetación secundaria sujetas a los siguientes tipos de manejo: 1) vegetación secundaria con manejo apícola (MA), 2) vegetación secundaria con manejo forestal (MF), 3) vegetación secundaria sin manejo (SM) y bosque tropical seco (BTS). La composición de especies fue similar entre vegetación secundaria manejada y no manejada. Por otro lado, entre vegetación secundaria manejada y el BTS hubo diferencias en la composición de especies. La riqueza de especies no fue diferente entre todas las condiciones. La MA mostró la más baja diversidad de especies y presentó la mayor densidad promedio (5 413 ± 770.26 ind./ha). La MF tuvo la menor densidad promedio (3 289 ± 1 183.60 ind./ ha). El BTS mostró la mayor área basal promedio (24.89 ± 1.56 m2/ha) respecto a las demás condiciones. Se concluye que es necesario mantener el monitoreo de las áreas manejadas, para detectar efectos del manejo que pueden ser adversos o favorables para la conservación de la diversidad florística de los BTS.

Abstract:The tropical dry forest (BTS) of Yucatan Peninsula has been managed for centuries, but the relationship between these management efforts and their effects on trees diversity has not been fully understood. The aim of this study was to evaluate the effect of forest management (thinning, harvesting and enrichment of species), in the structure of secondary vegetation derived from dry tropical forests, in two communities in Calakmul, Campeche, Southeast Mexico. We analyzed changes in the composition, species richness, species diversity, and structure in secondary vegetation subject to following types of management: (1) secondary vegetation with beekeeping management (MA), secondary vegetation with forest management (MF), natural secondary vegetation (SM) and tropical dry forest (BTS). The species composition was similar between secondary vegetation managed and unmanaged. On the other hand, between managed secondary vegetation and BTS there were differences in species composition. Species richness was not different between all conditions. MA showed the lowest species diversity and presented higher average density (5 413±770.26 ind.ha-1).MF had lowest average density (3 289 ± 1 183.60 ind.ha-1). BTS showed the highest average basal area (24.89 ± 1.56 m2.ha-1) regarding the other conditions. We concluded that is necessary to keep monitoring the managed areas to detect effects of management that may be adverse or favorable to conservation of floristic diversity of BTS. Rev. Biol. Trop. 65 (1): 41-53. Epub 2017 March 01.