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Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements. A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.

Civil construction and buildings account for a significant 36% of worldwide energy consumption, contributing to 37% of global CO2 emissions. In Brazil, buildings consume a substantial 51.2% of the nation’s electricity production. Remarkably, approximately one-third of this energy is allocated specifically for maintaining thermal comfort within these structures. The thermal performance of a building has a significant impact on its energy efficiency; in this way, technologies developed to contribute to the energy efficiency of envelopes can directly contribute to the reduction in the building’s overall energy consumption. PCMs are technologies capable of absorbing heat without increasing temperature and can contribute to the better energy performance of envelopes. PCMs are used as a thermal performance solution in cold climate regions, and studies show that they are likely to work in buildings in tropical climates. The objective of this work is to analyze the performance of PCMs in tropical regions of the southern hemisphere, specifically in Brazil, and their behavior according to the constructive system used. Computer simulation contributes to an analysis closer to the reality of the implementation of this technology in these regions. This work is carried out with simulations in the software EnergyPlusTM version 24.1. The results demonstrate that PCMs can effectively contribute to a reduction in energy consumption for the thermal comfort of buildings in tropical climates, demonstrating the possible feasibility of the development of this technology for tropical climates.

The availability of low-cost smart plugs that measure and control loads has encouraged their use as a research tool to disaggregate end-user loads. While there has been extensive research on the cybersecurity implications, and demand response capabilities, of smart plugs, there has been little investigation of their primary function: Measuring loads. In this study, we analyze the accuracy of power and energy measurements reported by 5 smart plugs from different manufacturers, with a specific focus on the accuracy of the meters when load levels change rapidly, as is often the case with power electronic loads. The study included Belkin, TP-Link, Etekcity, Emporia, and Sonoff smart plugs, with loads switching at frequencies of 0.01Hz to 2Hz, in addition to the steady-state loads often used for testing these devices. Data indicate significant errors in both energy and power measurement when used to monitor highly variable loads. While maximum energy measurement error for the Belkin product never exceeded 1.7%, maximum energy measurement errors were 54–100% for the other 4 brands. Power measurement accuracy was highly dependent on load variability, with all units exhibiting substantial errors when loads varied, even at rates as low as 0.01-0.05 Hz. All units also exhibited reporting delays of 3–6 seconds, with some delays as high as 20 seconds. The large, load-dependent, errors, call into question the use of these devices for research data acquisition, particularly for monitoring highly variable power electronic loads.

Methane is a greenhouse gas and identified as a key driver of near-term climate change. Bottom-up approaches estimate annual methane loss from US natural gas production and transport at 6 Tg, but recent studies suggest this may be an underestimate. To investigate this possibility, an equipment-based emissions inventory, using EPA emission factors, was developed to calculate methane emissions from oil and gas operations in the Delaware basin, USA. Emission factors and activity data were then updated using contemporary and region-specific measurement data. The original inventory estimated emissions at 315 Gg CH4 y−1 (gas production-normalized rate of 0.6% loss), while the updated inventory estimated emissions of 1500 Gg CH4 y−1 (2.8% loss). The largest changes resulted from large fugitive emissions from oil production (+430 Gg CH4 y−1), updating maintenance activity emissions (+214 Gg CH4 y−1), considering flaring inefficiency (+174 Gg CH4 y−1), and the inclusion of associated gas venting (+136 Gg CH4 y−1). This study suggests that a systematic underestimate probably exists in current bottom-up inventories and identifies sources currently missing or may be incorrect. We also strongly recommend that emission factors should be validated through direct comparison against measurement campaigns that include long-tail distributions typical of oil and gas activities.

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.

Rivers in tropical climates are characterized by highly variable flows which are becoming more variable due to climate change. In tropical conditions, most hydropower plants are designed as run-of-river plants with limited water storage. The aim of this study is the selection and sizing of a hydropower plant for highly variable flows, using the Sebeya River as a case study. As is often the case, flow data was incomplete, and the study also demonstrated the use of machine learning to predict the Sebeya flow rate for 2019. Stochastic modeling was used to estimate the energy generation for multiple turbine types and the levelized cost of energy for all configurations, capturing the uncertainty in many of the input parameters. River flow varies between 1.3 m3/s and 5.5 m3/s in a year; the minimum LCOE occurs at the knee in the flow exceedance curve of river flow rate, near 1.8 m3/s. The optimal LCOE for the Sebeya river is around 0.08 $/kwh with an uncertainty of −0.011/+0.009 $/kWh. Additionally, certain turbine types—notably propeller turbines—perform poorly in this type of highly variable flow. The method and findings can be used to guide future investments in small- to mid-sized hydropower plants in similar climatic conditions.

Abstract The Pedra Branca suite (2.75 Ga) is located in the Canãa dos Carajás domain in the southeastern Amazonia Craton. It diverges from typical TTG in mineralogical and geochemical terms, by the presence of hornblende and clinopyroxene and because it has a high content of HFSE (Zr, Y, Ti, and Nb). It belongs to the low-K subalkaline series, which varies from metaluminous to peraluminous, and are mostly calc and ferroan granitoids. Amphibole is calcic and classified as ferroan-edenite, and hastingsite. Plagioclase is mainly oligoclase. The Fe/(Fe + Mg) ratios found in the amphiboles indicate that these granitoids were formed under high to moderate fO2 conditions. Geobarometric calculations suggest pressures between 9.3 and 71 Kbar for the origin and 4.8-53.4 Kbar for the emplacement. Geothermometric calculations suggest initial crystallization temperatures between 945 and 862°C, and the water content in the magma is estimated to be higher than 4 wt%. The magma source was defined as tholeiitic continental gabbro melted in an extensional setting (Carajás Rift) with geochemical features similar to diabase from Nova Canadá (PA). The Pedra Branca magma was originated by partial melting (~28%), leaving a residue with plagioclase (An40), hornblende, clinopyroxene, and may or may not have magnetite.

Advances in power electronics and their use in Miscellaneous Electric Loads (MELs) in buildings have resulted in increased interest in using low-voltage direct current (DC) power distribution as a replacement for the standard alternating current (AC) power distribution in buildings. Both systems require an endpoint converter to convert the distribution system voltage to the MELs voltage requirements. This study focused on the efficiency of these endpoint converters by testing pairs of AC/DC and DC/DC power converters powering the same load profile. In contrast to prior studies, which estimated losses based on data sheet efficiency and rated loads, in this study, we used part load data derived from real-world time-series load measurements of MELs and experimentally characterized efficiency curves for all converters. The measurements performed for this study showed no systematic efficiency advantage for commercially available DC/DC endpoint converters relative to comparable, commercially available AC/DC endpoint converters. For the eight appliances analyzed with the pair of converters tested, in 50%, the weighted energy efficiency of the DC/DC converter was higher, while, for the other 50%, the AC/DC converter was. Additionally, the measurements indicated that the common assumption of using either data sheet efficiency values or efficiency at full load may result in substantial mis-estimates of the system efficiency.

We present the first record for the genus Psalmopoeus Pocock, 1895, in Brazil. A female of Psalmopoeus irminia Saager, 1994, was collected in Pacaraíma, state of Roraima, Brazil. This country now has records of all New World tarantula genera of the subfamily Aviculariinae.

Knowing water consumption patterns in buildings is key information for water planning. This article aims to characterize the water consumption pattern and water end-uses in low-income houses in the region of Florianópolis, Southern Brazil. Data were collected by interviewing householders, as well as by measuring the flow rate of existing water fixtures and appliances. The results indicated that the shower was the fixture with the largest water consumption in households, i.e., about 30%–36% of total water consumption on average, followed by the toilet (18%–20%). The surveyed households consumed from 111 to 152 L/capita·day on average, based on different income ranges. No correlation was found between income and water consumption. The results of this study can be used to estimate the consumption of water for new buildings, as well as to develop integrated water management strategies in low-income developments, in Florianópolis, such as water-saving plumbing fixtures, rainwater harvesting, and greywater reuse. Likely, there would be a deferral of capital investments in new water assets for enhancing water and wastewater services by saving water in low-income houses.

O trabalho tem por objetivo apresentar os usos finais de eletricidade e rotinas de uso em habitações de interesse social. Os dados foram obtidos por meio de auditoria energética em uma amostra de 60 habitações de interesse social da região de Florianópolis-SC, por meio de aplicação de questionários aos moradores e medições do consumo de energia elétrica. Os dados obtidos com os questionários se referem à situação socioeconômica dos moradores e às rotinas de uso dos equipamentos eletroeletrônicos e iluminação, estimados para períodos de verão e inverno. As medições foram utilizadas para a caracterização dos equipamentos e lâmpadas, determinação do consumo de energia elétrica e o tempo de uso, por um período maior do que duas semanas em cada habitação. O tratamento de dados foi feito em forma de intervalos de confiança, por meio de métodos estatísticos paramétricos e não paramétricos. Os resultados mostraram que o chuveiro elétrico representa o maior uso final da amostra, com 36,8% de mediana, seguido dos refrigeradores, televisão e iluminação. Os dados não mostraram diferenças significativas entre os períodos de verão e inverno, devido ao tamanho reduzido da amostra e à variabilidade dos dados. As rotinas de uso encontradas, quando associadas à densidade potência média respectiva, são variáveis de entrada para estudos de simulação computacional do desempenho térmico dessas habitações, além de ajudarem na caracterização desse tipo de edificação. A correta quantificação dos usos finais de eletricidade de amostras pequenas leva à adoção de medidas corretas e específicas para a eficiência energética dessas habitações.

The objective of this paper is to show the importance of measuring electricity end-uses in order to promote energy efficiency in low-income houses in Southern Brazil. Sixty low-income houses were surveyed, and data of socioeconomic variables, electricity use, and usage pattern were measured and obtained. Confidence intervals were assigned to obtain representative electricity end-uses and usage patterns. The results showed that the electric shower has the greatest electricity end-use, i.e., 33.5 to 40.3%, followed by the refrigerators, with end-use of 27.4 to 33.1% with 90% non-parametric confidence interval. Usage patterns were obtained for appliances and lighting for each room and also for the electric shower. The results of this study will provide basis for determination of guidelines for low-income houses and government programmes for energy efficiency, rational use of energy and renewable energy.

Civil construction and buildings account for a significant 36% of worldwide energy consumption, contributing to 37% of global CO2 emissions. In Brazil, buildings consume a substantial 51.2% of the nation's electricity production. Remarkably, approximately one-third of this energy is allocated specifically for maintaining thermal comfort within these structures. The thermal performance of a building has a significant impact on its energy efficiency; in this way, technologies developed to contribute to the energy efficiency of envelopes can directly contribute to the reduction in the building's overall energy consumption. PCMs are technologies capable of absorbing heat without increasing temperature and can contribute to the better energy performance of envelopes. PCMs are used as a thermal performance solution in cold climate regions, and studies show that they are likely to work in buildings in tropical climates. The objective of this work is to analyze the performance of PCMs in tropical regions of the southern hemisphere, specifically in Brazil, and their behavior according to the constructive system used. Computer simulation contributes to an analysis closer to the reality of the implementation of this technology in these regions. This work is carried out with simulations in the software EnergyPlusTM version 24.1. The results demonstrate that PCMs can effectively contribute to a reduction in energy consumption for the thermal comfort of buildings in tropical climates, demonstrating the possible feasibility of the development of this technology for tropical climates. [ABSTRACT FROM AUTHOR]

Resumo O objetivo deste trabalho é analisar incertezas físicas em simulação computacional de uma edificação residencial e sua implicação no desempenho térmico. O experimento foi elaborado com o método de Monte Carlo, que envolve as propriedades térmicas e físicas dos materiais da edificação. Foi analisada a sensibilidade das variáveis com coeficientes de regressão e correlação. Considerou-se o critério de graus-hora de desconforto por calor e por frio para o clima de Florianópolis, SC, conforme limites de conforto térmico adaptativo. Os resultados mostraram que as incertezas obtidas nos graus-hora são relativamente grandes, sendo de 32% no desconforto por frio e de 53% no desconforto por calor. Grande parte da incerteza é decorrente da temperatura média mensal do solo. Outras variáveis, como a absortância solar da cobertura e o calor específico da argamassa das paredes, resultam em impacto relevante no desconforto por calor, bem como a massa específica da argamassa e o calor específico da cerâmica das paredes no desconforto por frio. Essas variáveis precisam de maior precisão, seja por meio de bases de dados mais confiáveis, ou mesmo por medições em campo e/ou em laboratório.

Este estudo tem por objetivo investigar a incerteza do método de simulação da NBR 15575-1 (ABNT, 2013) nos resultados dos níveis de classificação de desempenho térmico de habitações. A investigação compreendeu análise do desempenho térmico de uma habitação por simulação computacional no programa EnergyPlus, para o clima de Florianópolis - SC. Foram analisadas variáveis imprescindíveis para a definição de um dia típico, as quais são desconsideradas pelo método de simulação da norma, como data do dia típico de verão e inverno, velocidade e direção do vento, algoritmo de cálculo da irradiação solar e tipo de céu. Tais variáveis foram utilizadas em projeto de experimento estatístico com combinação fatorial para determinar a incerteza nos resultados e a sensibilidade das variáveis no nível de classificação de desempenho. As simulações foram realizadas com nove modelos diferentes de envelope da habitação. Os resultados mostraram que os piores níveis de classificação de desempenho, tanto no verão quanto no inverno, foram os modelos sem contato com o solo. A variável de maior influência para a análise no verão e inverno, para todos os modelos de envelope analisados, foi o tipo de céu. Pode-se concluir que as variáveis desconsideradas pela NBR 15575-1 (ABNT, 2013) na criação de um dia típico para simulação exercem considerável influência nos resultados dos níveis de classificação do desempenho térmico, gerando imprecisão nos resultados.

ste trabalho tem por objetivo analisar comparativamente os resultados do desempenho térmico da envoltória de uma edificação residencial por meio dos métodos de simulação do RTQ-R e da NBR 15575-1. Para obter níveis de desempenho variados, foi realizado um experimento aleatório com amostragem pelo hipercubo latino. Selecionaram-se os parâmetros variáveis e geraram-se 500 combinações aleatórias. Foi considerado o clima de Florianópolis, SC, e utilizado o programa EnergyPlus para as simulações. Observou-se que, dependendo do cenário de análise, os métodos podem produzir resultados equivalentes ou não. A maior parte dos casos diferiu na análise do inverno, ou seja, 134 casos apresentaram nível A ou B no RTQ-R, e Mínimo ou Não atende pela NBR 15575-1. Para as análises de verão, há 66 casos em que o RTQ-R resulta em nível E, enquanto a NBR 15575-1 resulta em nível Intermediário. Apesar de a análise de sensibilidade indicar semelhança entre os métodos de simulação, o RTQ-R contempla um método de avaliação mais completo e abrangente. No entanto, mais atenção deve ser dada às próprias tabelas de classificação dos métodos, que podem ser as causas de algumas das discordâncias.

Este trabalho tem por objetivo analisar a sensibilidade global de parâmetros termofísicos considerados no Regulamento Técnico da Qualidade para o Nível de Eficiência Energética de Edificações Residenciais (RTQ-R). Um estudo de caso de uma habitação em Florianópolis, SC, foi realizado por meio de simulação computacional no EnergyPlus com o arquivo climático TRY. Foram definidos 15 parâmetros utilizados no RTQ-R, variados por meio de amostragem com o Hipercubo Latino e geraram-se 500 simulações aleatórias. As variáveis dependentes são os graus-hora de resfriamento, consumo relativo com aquecimento e com refrigeração. Para a análise de sensibilidade foram utilizados os métodos dos Coeficientes de Regressão Padronizados e Coeficientes de Correlação Parcial. Foram feitas análises de variabilidade e comparação de simulações individuais. Os resultados mostraram que os parâmetros mais influentes diferem para cada variável dependente, o que dificulta a proposta de soluções de desempenho que atendam às condições de verão e inverno simultaneamente. A absortância solar e a emissividade da cobertura foram os parâmetros mais influentes em geral. O trabalho contribuiu para a identificação quantitativa dos parâmetros mais influentes no desempenho da edificação, o que pode auxiliar nos processos de otimização e na proposta de níveis de classificação de desempenho em certificações.