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The urban microclimate is essential for accurate simulation-based urban building energy modelling (UBEM). However, a high spatial-resolution microclimate can increase the computational resources demands of UBEM. Surrogate modelling is one of the promising approaches for fast UBEM. This study proposes a bidirectional Long Short-Term Memory (LSTM)-based approach for simulation-based UBEM surrogate modelling. The estimations are aggregated into census tracts using total building floor area. A case study using UBEM to estimate annual hourly building energy use and anthropogenic heat from all existing buildings in Los Angeles County found that most of the surrogate models can complete the annual hourly simulation within 90 minutes with a normalized mean absolute error lower than 10%, and that the bidirectional LSTM outperforms the standard LSTM in accuracy. This study demonstrates the advantages of bidirectional RNN architecture in building energy surrogate modelling and is expected to promote long-term and high-resolution UBEM with detailed microclimates.

Digestate is a product with valuable fertilizing properties, remaining after the anaerobic fermentation process. An essential feature of the substance in question is its high water content of up to 97%. To improve the fertilizer value of the digestate, it is necessary to dehydrate it to produce a concentrated product. This paper determined the possibility of dewatering the digestate using an innovative reactor design. The study, conducted on a laboratory scale, used digestate from a Polish biogas plant. The dewatering technique described in the paper is based on the evaporation and condensation of water vapor on the inner surface of the reactor dome. The condensate accumulated on the leach trough and was directed to a storage tank. During the weeks of testing, 11.5 kg of condensate was separated from the initial weight of the digestate (32 kg), with a dry weight of 6.11%. The resulting condensate from dehydration had an average pH value of 9.0 and an average ammonium nitrogen content of 2.07 g∙kg−1. The economic calculations made in the paper allowed for estimating the expected savings associated with the management of digestate in Poland. The research showed the proposed technology's high potential for dewatering digestate under laboratory conditions. [ABSTRACT FROM AUTHOR]

Seed crop production systems of velvet bean (Mucuna pruriens L.) were assessed in two field studies for ecosystem services. At flowering stage, long duration genotype Arka Shubra was significantly superior in biomass accumulation (14.61 t ha−1), while 100% recommended NPK + 15 t FYM ha−1 registered significantly higher biomass production (11.74 t ha−1). Biomass availability at harvest was higher in long duration genotypes (7.48–7.75 t ha−1) and the average biomass availability of 6.45 t ha−1 at harvest gives scope for including velvet bean as component crop in cropping systems/fallows. The average soil carbon stocks were estimated at 22.8 t ha−1 at the end of 2 yrs and 12.4 t ha−1 at the end of one crop season. Soil nutrient availability was optimum except for soil test P in pre-, standing and post crop growth periods. Highly significant relations (R2 = 0.949) were observed between nodule number and available N at harvest. The N availability was more in long duration genotypes (209–215 kg N ha−1) over pre-experimental status. Nutrient addition improved the available N status by 40–185 kg ha−1 over pre-experimental status and control. The nutrient uptake was 4–10% higher in Arka Shubra over other long duration genotypes and 100–200% higher over medium/short duration genotypes at flowering. The recyclable biomass and uptake of NPK are more in long duration genotypes implying huge nutrient recycling potential of the system. Overall, seed crop systems of velvet bean are efficient in resource use and energy use (>2.5 EUE) and ideal components for sustainable land management. [ABSTRACT FROM AUTHOR]

Carbon footprint measures evidence the impact of organizations and individuals' contribution to climate change. They can facilitate critical reflection. A community carbon footprint questionnaire is developed in cooperation with local people to enable them to reflect on how to reduce their personal carbon footprint in relation to their social and economic context. The instrument is operationalised in an Anglican church community who have stated an aim to reduce their footprint. It is designed to help participants make a self-assessment of where their behaviour change will make the most social impact. There are three components to the total score: (A) transportation, (B) accommodation energy use, and (C) consumer behaviour. Forty two participants respond. The average carbon footprint score is 5.8 tonnes per annum. Older and middle-aged people are more likely to have a higher footprint than younger adults. This is associated with them having a larger accommodation and being more dependent on private cars. Accommodation energy use contributes the most to the participants' total scores. Living in smaller accommodation and sharing an accommodation reduces an individual's carbon footprint. The second largest component is transportation, with the use of diesel- and petrol-fuelled cars contributing the biggest impact, especially where mileage is high. A minority are moving towards electric and hybrid cars. Finally, the smallest contributing component is consumer behaviour, where participants' scores are the least dispersed in the sample compared to the other components and closer to the mean average. Participants are more likely to make commitments to changing consumer behaviour than changing transportation and domestic energy use and often focus on recycling, reducing the consumption of meat and new goods, and repairing older items. In contrast, when the results are located in the context of changes in policy, the simplest gains to reducing carbon footprints are related to changing behaviour in the purchase of household electricity to ensure the purchase of renewable power. Other important considerations are reducing the size and heated area of an individual's accommodation space, or sharing an accommodation with more people, and moving away from the use of diesel- and petrol-fuelled private transportation, instead using public transport, cycling, and walking. More complex and expensive strategies for individuals are installing solar panels and heat pumps for accommodation energy generation, and switching personal transportation to electric cars. Policy analysis suggests that participants were largely unaware of new opportunities to change their consumption of electricity towards renewable generation by purchasing greener electricity options. [ABSTRACT FROM AUTHOR]

Resource management involves a temporal concern over long- and short-term consequences. It is underexplored how resource conservation behaviors can be influenced by individual differences in consideration of future consequences (CFC), which reflects how people perceive the immediate versus distant outcomes of their actions. By integrating individuals’ time orientations (i.e. CFC) into the value-belief-norm framework, the study investigated the norm activation process in utility-saving behavior. Survey data from 996 residents in Guangzhou, China, were analyzed using partial least squares structural equation modeling (PLSSEM). The results indicated that, compared to the low-CFC group, high-CFC individuals showed greater awareness of consequences, which in turn activated personal norms for utility saving through the ascription of responsibilities. The findings underscore how time orientations shape utility-saving behavior through environmental beliefs, offering insights for designing tailored interventions to induce behaviors that generate immediate personal outcomes and long-term environmental consequences. [ABSTRACT FROM AUTHOR]

Fact-based information campaigns aimed at encouraging more sustainable behaviour have typically resulted in minor effects that tend not to last. Scholars in the fields of entertainment education have proposed storytelling as an alternative strategy. Most existing studies have focused on health communication, but there is increasing interest in exploring storytelling to promote pro-environmental behaviours. Our focus in this study are behaviours which have both health and environmental implications: personal cleaning, household cleaning, and laundry. In a study using both quantitative and qualitative analyses (from a survey to which 77 individuals responded), we find that messages embedded into a short story significantly changed behavioural intentions in readers across all three domains. Readers reported gaining knowledge from the stories, in terms of the specific products and practices that one could undertake and with respect to the commonly held misconception that aggressive cleaning practices in the home (e.g., high temperatures, strong chemicals) are beneficial to human health. Results have implications for interventions aimed at promoting behaviours that have joint benefits for human and environmental health. Article highlights: Our findings show that self-reported behaviour three weeks after reading the stories was more sustainable than behaviours reported before reading the stories. These results contribute positively to the literature on the use of fictional narrative, especially solution-focused stories, as a behaviour change intervention tool. These findings are useful to policymakers when designing behaviour-change interventions. [ABSTRACT FROM AUTHOR]

Understanding the risks posed to humankind, the environment, and overall growth requires a deep exploration of the profound impact of greenhouse gas (GHG) emissions, especially carbon dioxide (CO2), on global climate change. This study explores the complex relationships among economic extension, energy utilization, financial progress, natural resource rents, and CO2 emissions in Bangladesh. By analyzing annual data from 1974 to 2022, our analysis reveals a long-term connection between the variables, as evidenced by the autoregressive distributed lag (ARDL) bounds test. We found that for every 1% rise in economic growth, energy use, financial progress, and natural resource rents, CO2 emissions rise by 0.13%, 1.50%, 0.39%, and 0.04%, respectively. This is based on the dynamic ordinary least squares (DOLS) method. The outcomes are further supported by the canonical cointegrating regression (CCR), followed by fully modified ordinary least squares (FMOLS). By illuminating the causes of Bangladesh's environmental degradation, this study offers actionable policy suggestions aimed at fostering sustainable growth and enforcing strict regulations that effectively mitigate environmental harm. Highlights: • This study explored the environmental effects of the economy, energy, finance, and natural resources. • Bangladesh's annual time series data were utilized for econometric assessment. • The results show that rising carbon emissions are connected to economic evolution, energy usage, financial development, and natural resource rents. • The results suggest policies toward CO2 emission reduction and sustainable development in Bangladesh. [ABSTRACT FROM AUTHOR]

The significance of the transportation sector, notably in terms of the carbon emission factor, is an undeniable fact. Along with this fact, individuals' transportation preferences depend on their income levels. In this context, when the issue is considered, the income level in the USA pushes people toward cheap air travel. The main reason for this is that it is cheap, accessible, and transports one to their destinations quickly. Thus, from the perspective of road transportation, bus transportation is popular among the public. The reason why both air and road transportation modes are empirically evaluated together through income distribution is due to the preference of the US people. In this context, the effectiveness of active transportation on both air and highways in the USA from 1975 to 2023 is investigated by taking into consideration the income distribution. Empirical findings obtained through the FMOLS, DOLS, CCR, and NARDL models demonstrate that all independent variables, including GDP, energy use, air transportation, and the Gini coefficient, affect carbon dioxide emissions. In addition, wavelet analysis is performed to comprehend the form of and fluctuations in the series, which are vital to monitoring the periodical changes. [ABSTRACT FROM AUTHOR]

Developing a green economy is key to achieving the 2030 Sustainable Development Goals. This paper uses the SBM-GML index, which includes non-desired outputs, to measure the trend of regional green economic efficiency changes and analyze the impact mechanism and realization path of industrial transformation on green economic efficiency. The research results show that advanced industrial structure has a positive influence on green economic efficiency nationwide, while energy utilization structure and energy utilization efficiency have positive partial intermediary effects in the influence path; industrial structure rationalization is also significantly positively related to green economic efficiency nationwide, and the mediating effect of energy utilization is positive. The impact of industrial transformation on green economic efficiency has regional heterogeneity, and the mediating effect of energy use also differs. Among them, the impact effect in the eastern region is basically consistent with the national sample, but is negative in the central and western regions. This paper proposes countermeasures in terms of adjusting the industrial structure, improving energy efficiency, and perfecting industrial and energy policies, which can provide theoretical and practical references for promoting the transformation and upgrading of regional industrial structure, optimizing energy utilization, and advancing the efficiency of the national and regional green economy. [ABSTRACT FROM AUTHOR]

In emerging economies like Kuwait, tourism funds national development and sustains local livelihoods. The rapid rise of tourism in several nations may have serious environmental effects due to increased energy usage that increases carbon dioxide (CO2) emissions and worsening global warming. Due to climate change’s growing effects on the environment, several efforts have been made by numerous countries worldwide to achieve carbon neutrality and environmental sustainability. Moreover, effective energy production prediction is crucial to establish an equilibrium between traditional and clean energy sources. However, there is a research gap investigating the environmental impacts of tourism within the framework of energy-economy-environment nexus in Kuwait’s context that propelled the development of this pioneering investigation. The present study’s objective is to determine how economic growth, energy consumption, and tourism affect carbon emissions in Kuwait. This study analyzes Kuwait’s time series data from 1995 to 2019 by using the autoregressive distributed lag (ARDL) method that analyzed the components’ relationships, allowing for long-term and short-term dynamics. The results show that increasing economic growth, energy consumption, and tourist arrivals increase CO2 emissions in Kuwait. This article proposes policies to achieve carbon neutrality in Kuwait by expanding renewable energy use and promoting sustainable tourism to boost the economy. [ABSTRACT FROM AUTHOR]

In the context of sub‐Saharan Africa (SSA), characterized by abundant natural resources and persistent challenges in economic growth, this paper explores the effect of economic complexity (EC) on natural resource depletion (NRD) from 1997 to 2017. To this end, the study employs data mainly from the World Development Indicators on 36 SSA countries. Using both the pooled ordinary least squares and the two‐step system generalized method of moments estimation techniques, the results indicate that EC significantly contributes to reducing the exhaustion of natural resources in SSA during the study period. The findings equally suggest that government expenditure on education, as well as gross domestic product per capita, exert a reducing effect on NRD, while energy use, foreign direct investment, and urbanization are vectors of resource exhaustion in the region. The results remain consistent when an alternative measure of EC is applied as well as when different estimation strategies are used. This offers scope for a reminder for proper management policies to be edited and applied regarding these mostly nonrenewable resources. [ABSTRACT FROM AUTHOR]

The escalating utilisation of second homes has led to an extension in heating periods and, to a certain degree, renovations to elevate the standard, resulting in augmented energy and resource consumption. A comprehensive survey was conducted in Sweden, examining user patterns across different seasons, heating systems, and implemented energy efficiency measures. The results indicate that second homes are occupied for extended periods during the summer season and intermittently throughout the year. Over half of the second homes are heated even when unoccupied, with 12% maintaining a temperature above 16 °C. The predominant heating method is direct electricity (32.2%), followed by heat pumps (29.5%) and stoves (17.5%). A variety of renovations are undertaken, primarily to enhance the standard and technical performance, but also to implement energy efficiency measures such as window replacement, additional insulation, or heat pump installation. Based on the reported user and heating patterns, and the energy renovations carried out, the potential energy savings with different energy renovation strategies were estimated for the Swedish second home stock. The results show that though lowering the temperature when a second home is unoccupied emerges as the most efficient measure, both in terms of cost-effectiveness and climate impact, it needs to be complemented with intermittent heating or dehumidification to ensure that the relative humidity is below critical levels, to avoid the risk of damages caused by, for example, mould growth. Installing a heat pump is the second most energy- and cost-effective measure and has the advantage that the indoor temperature can be maintained at rather high levels. [ABSTRACT FROM AUTHOR]

Water shortage and food security concerns are amplified by the spread of irrigated cultures within the context of climatic unpredictability. In the hot, arid MENA area, the frequent drought periods and the continuous deterioration of water resources limits the ecological system's functioning and the sustainable agricultural productivity. Thus, this study aims to evaluate the potential impacts of the evolution of water resources management on the environmental components, using Westerlund's (2007) panel cointegration and the Common Correlated Effects Mean Group (CCE-MG) estimator for a sample of six MENA economies over 35 years ((1990–2015). In the short run, there is unidirectional causality from agricultureadded value to CO 2 and from water productivity to CO 2 without any feedback. while, a bidirectional causality nexus was detected between energy consumption and CO 2 emission In the long run, however, a feedback causality has been obtained between CO 2 emissions, agriculture added value, water productivity, and energy consumption. Sustainable water management, smart water systems, and energy transition in the water related activities are highly recommended as priorities towards a NetZero carbon global economic trend. [ABSTRACT FROM AUTHOR]

Energy use analysis and greenhouse gas (GHG) emissions are among the most important aspects regarding the sustainability performance of a farming system. The aim of this study was to assess the environmental impact, in terms of energy consumption and GHG emissions in thirty vineyards located on Crete, Greece, and deliver a digital, decision support tool (DST). A simplified life cycle approach was used to collect data from the vineyards up to farm gate, located in the top wine-producing Cretan municipalities, regarding farming practices, inputs, and yield for a 2-year period. Sum energy and non-renewable energy intensity and efficiency were calculated. GHG emissions were estimated in terms of CO2 equivalents, following IPCC methodology, while the emissions intensity is also reported. Fossil fuels consumed by machinery for weed management, transportation, soil management, pest control, and synthetic fertilizers were the practices found to be accountable for the higher energy consumption. Synthetic fertilizers and fossil fuel consumption were the main sources of GHG emissions, followed by burning of the pruning residues. Omitting burning pruning residues, reducing tillage intensity, and replacing mechanical weed management are highlighted as the main practices that can improve the sustainability of viticulture on Crete. Making use of the collected data, a crop-specific DST, named "ECO2VINE", for calculating a vineyard's energy use and GHG emissions was developed, validated, and made publicly available. [ABSTRACT FROM AUTHOR]

The economic development of any nation depends on energy production and consumption, thereby, needing more exploration from researchers. The current article thus makes an attempt to examine the role of REW and non-REW energy on the economic development in China. The current article has used renewable energy production (REP), and renewable energy consumption (REC) to measure renewable energy. The current research has used fossil fuel energy consumption, energy use, energy import, and electric power consumption to measure non-renewable energy. The present study has taken secondary data from world development indicators from 1986 to 2020. The article has applied the nonlinear autoregressive distributed lagged model to evaluate the association among the understudy constructs. The findings indicated that REP and REC, fossil fuel energy consumption, energy use, energy import, and electric power consumption are linked with economic development in a positive manner in China context. The study guides the regulators in establishing the regulations related to economic development through both type of energy resources. [ABSTRACT FROM AUTHOR]

This paper delves into the critical determinants of renewable energy consumption, focusing on the contrasting roles of oil imports and exports. It aims to bridge the knowledge gap by comparing these determinants across both oil-importing and oil-exporting nations, offering a comprehensive and nuanced perspective to inform policy recommendations. Using annual data from 1990 to 2018 sourced from the World Bank database, the study employs panel multiple regression analysis and adopts a fixed effects model to explore two main questions: What drives the use of renewable energy sources? How does a country's oil importer or exporter status affect these factors? The findings reveal a significant but inverse relationship between oil rents and renewable energy consumption (REC) for both types of countries. Additionally, there is a notable negative correlation between GDP growth and REC for both oil-exporting and oil-importing countries. Interestingly, the crude oil average closing price and inflation show an insignificant impact on REC in both contexts. The study also highlights that net energy imports significantly affect REC, with a much stronger inverse relationship in oil-importing countries compared with oil-exporting ones. For oil-importing countries, diversifying energy sources is a crucial investment. Governments should prioritize research and development in renewable energy to spur technological advancements, enhancing efficiency and affordability. Economic growth-promoting policies, such as tax incentives and subsidies for renewable energy businesses, are vital for encouraging sustainable practices. Consistent, long-term policies are essential for providing investor confidence and supporting the transition to renewable energy. For oil-exporting countries, similar strategies are recommended. Additionally, allocating a portion of oil revenues to renewable energy infrastructure and funding research and development in renewable technologies through local universities and startups are crucial steps. This dual approach will not only enhance energy diversification but also foster innovation and sustainability in the energy sector. [ABSTRACT FROM AUTHOR]

Abstract Fact-based information campaigns aimed at encouraging more sustainable behaviour have typically resulted in minor effects that tend not to last. Scholars in the fields of entertainment education have proposed storytelling as an alternative strategy. Most existing studies have focused on health communication, but there is increasing interest in exploring storytelling to promote pro-environmental behaviours. Our focus in this study are behaviours which have both health and environmental implications: personal cleaning, household cleaning, and laundry. In a study using both quantitative and qualitative analyses (from a survey to which 77 individuals responded), we find that messages embedded into a short story significantly changed behavioural intentions in readers across all three domains. Readers reported gaining knowledge from the stories, in terms of the specific products and practices that one could undertake and with respect to the commonly held misconception that aggressive cleaning practices in the home (e.g., high temperatures, strong chemicals) are beneficial to human health. Results have implications for interventions aimed at promoting behaviours that have joint benefits for human and environmental health.

Abstract Understanding the risks posed to humankind, the environment, and overall growth requires a deep exploration of the profound impact of greenhouse gas (GHG) emissions, especially carbon dioxide (CO2), on global climate change. This study explores the complex relationships among economic extension, energy utilization, financial progress, natural resource rents, and CO2 emissions in Bangladesh. By analyzing annual data from 1974 to 2022, our analysis reveals a long-term connection between the variables, as evidenced by the autoregressive distributed lag (ARDL) bounds test. We found that for every 1% rise in economic growth, energy use, financial progress, and natural resource rents, CO2 emissions rise by 0.13%, 1.50%, 0.39%, and 0.04%, respectively. This is based on the dynamic ordinary least squares (DOLS) method. The outcomes are further supported by the canonical cointegrating regression (CCR), followed by fully modified ordinary least squares (FMOLS). By illuminating the causes of Bangladesh's environmental degradation, this study offers actionable policy suggestions aimed at fostering sustainable growth and enforcing strict regulations that effectively mitigate environmental harm. Graphical Abstract

• Electrical heating reduced carbon emissions by 31 % compared to gas heating. • 36 % carbon emission savings were attained with the use of R-744 compared to R-448A. • Doors on chilled cabinets reduced energy consumption and carbon emissions by 26 %. • The combined application of technologies led to 68 % carbon emission savings in 2020. • Decarbonisation of the electrical grid in 2050 will reduce carbon emissions by 87 %. New refrigeration system configurations and other innovating technologies in retail supermarkets need to be considered to reduce energy use and greenhouse gas emissions. In supermarkets, there is a strong interaction between the refrigerated display cases, supermarket structure, internal machinery, customers, and the store's HVAC system. The impact of these interactions on the energy and carbon emissions of a medium sized supermarket in Paris was modelled using EnergyPlus™. The results were calibrated against a typical UK store and validated against the Paris store. The effects of applying the technologies identified to have the greatest potential to reduce carbon emissions (changing the refrigerant to R-744, switching from gas to electrical heating and adding doors to chilled cabinets) were modelled. The impact of climate change on ambient temperature and the impact of changes to the grid conversion factor were predicted for the store in Paris from 2020 to 2050. [ABSTRACT FROM AUTHOR]

Irrigation is important for the growth of world agriculture, as it enables greater security in agricultural production. The use of center-pivot for irrigation is very common in Brazil. However, there are some information gaps, mainly related to spatial variability in the water application in variable topography. Thus, the present study aimed to apply the geostatistical approach to characterize and evaluate the magnitude of the pressure head (PH) spatial variability in center-pivot lateral lines operating in plots with variable topography. For this analysis, six different points were installed along the lateral line and measured with PH transducers in 18 lateral line angular positions in the study area. Universal kriging (UK) was used to estimate PH across the whole field. The semivariogram was adjusted by the hole effect theoretical model, indicating a strong spatial dependence on PH. A decision support system tool was developed to assist in the analysis of the PH spatial distribution along the center-pivot lateral line using a geostatistical approach (kriging). The proposed tool can be useful for managers of irrigable areas and to identify zones with high energy use (wasted PH) along lateral lines of center-pivot systems. The estimation of PH distribution using geostatistical and UK techniques was satisfactory, allowing the creation of a thematic map. Precision irrigation and monitoring using a thematic map of PH distribution from kriging can help monitor the operating conditions of a center-pivot, as well as improve the decision-making regarding proper management of the whole irrigation system. Practical Applications: Center-pivot irrigation systems are very common in agricultural production areas around the world. Due to the large area irrigated by center-pivots, it is very important to study the reduction in water and energy use in these equipment. Thus, an important point to be studied is the PH distribution along the center-pivot lateral line in areas with undulating topography, where there is a significant PH variation. In this study, we present an analysis of the PH distribution along the lateral line using a geostatistical approach (kriging) to obtain PH values in the entire irrigated area. For this, PH data collected at six different points along the lateral line were used in a decision support system tool, developed to estimate PH in the entire irrigated area using the geostatistical approach. This estimate was satisfactory, allowing the creation of a thematic map. The proposed tool proved to be useful for easily identifying zones with high energy use (wasted PH). In this way, the use of precision irrigation and the analysis of the equipment through thematic mapping can help irrigators in monitoring the operating conditions of a center-pivot. [ABSTRACT FROM AUTHOR]

Energy performance and heat release from buildings can differ with variations in envelope and operational parameters. This study presents an evidence-based assessment for different study locations in Japan including Sapporo, Tokyo, and Osaka. The analysis used a comparative approach using a reference energy performance simulation model for large office buildings using EnergyPlus to assess the impact of design variations on building performance. The analysis included 66 simulations with 10 design parameters and 2 construction types. The study coupled energy performance with heat release from the building towards outdoor environments since heat release can influence the local thermal environments. Desirable tradeoffs were observed for timber constructions by increasing the cooling setpoint by 1°C reduced cooling and heating energy use by 10.7% and 11.9% in Sapporo, 8.5% and 22.7% in Tokyo, and 6.8% and 24.4% in Osaka. Similarly, cooling and heating peak loads were reduced by 5.9% and 2.4% in Sapporo, 5.4% and 2.0% in Tokyo, and 6.5% and 5.2% in Osaka. Additionally, nighttime heat release also decreased by 12.4% and 13.6% in Sapporo and Tokyo, and 6.2% and 5.7% in Osaka for concrete and timber constructions. The study provides early-stage design support for energy-efficient buildings and improved local thermal environments. [ABSTRACT FROM AUTHOR]

China's economic development has achieved great success in recent years, but the problems of energy scarcity and environmental pollution have become increasingly serious. To enhance the reliability and efficiency between energy, the environment and the economy, sustainable development is an inevitable choice. In the context of measuring sustainability efficiency, a network data envelopment analysis model is proposed to formulate the two-stage process of energy use and operations management. A double frontier is derived to optimize the available energy for sustainable development. Due to nonlinearity, previous linear methods are not directly applicable to identify the double frontier and calculate stage efficiencies for inefficient decision-making units. To address this problem, this study develops the primal-dual relationship between multiplicative and envelopment network models based on the Lagrange duality principle of parametric linear programming. The newly developed approach is used to evaluate the sustainability efficiency of 30 administrative regions in China. The results show that insufficient sustainability efficiency is a systemic problem. Different regions should take different measures to conserve energy and reduce pollutant emissions for sustainable development. To increase sustainability efficiency, regions should support energy-saving and emission-reducing technologies in production processes and strengthen their capacity for technological innovation. Compared with energy use efficiency, operations management efficiency in China has a wider range of changes. During the operations management stage, there is not much difference between the capacity and quantity of each region. Based on benchmark regions at the efficiency frontier, there is an opportunity to improve operations management in the near future. Blockchain technology can effectively improve energy allocation efficiency. [ABSTRACT FROM AUTHOR]

This study investigates how carbon dioxide emissions, natural gas, energy consumption, energy investment, coal and crude oil, and per capita exports affected the economic growth of the United States from 1993 to 2023 using the Vector Error Correction (VEC) model. The findings highlight the importance of exports and energy investment in driving both short- and long-term economic growth, while also highlighting interactions between carbon emissions, coal use and crude oil. It was determined that changes in natural gas and exports affected energy investment in the short term, while coal and exports affected natural gas. These results provide valuable information about the dynamics of the American economy and contribute to our understanding of the complex interactions between various factors and their effects on economic growth, offering implications for further research and policy development to promote sustainable economic development. [ABSTRACT FROM AUTHOR]

Climatic change and environmental degradation have become a worldwide discourse. Green innovation is commonly viewed as a means of lowering environmental pollution in the era of climate change. Considering this, the primary purpose of this study is to investigate the effects of environmental technology (ET) on CO2 emissions by controlling Saudi Arabia's ICT use, energy use, energy intensity, and financial development. It uses a quantile-based multiple-threshold "nonlinear autoregressive distributed lag (NARDL)" estimation utilizing data from 1990 to 2020. It also conducts the ARDL and NARDL estimation techniques simultaneously for comparative outcomes. The Toda–Yamamoto (T-Y) causality assessment also crosschecks the primary multiple-threshold NARDL estimates. The outcomes reveal that ET promotes environmental pollution due to its low scale compared to the Kingdom's technological base. ICT improves environmental quality, and energy consumption deteriorates it. All three estimation techniques confirm these findings. The multiple-threshold NARDL estimation appears robust and reveals damaging impacts of energy intensity and financial development on emissions. The T-Y causality assessment also authenticates the primary estimation outcomes. The outcomes have important implications for policymakers to focus on enhancing patents for ET, raising ICT diffusion, reducing energy intensity through generating more renewable energies, expanding financial support for ICT and green investments, and ensuring a sustainable environment. [ABSTRACT FROM AUTHOR]

Background: Controlled environment agriculture, particularly vertical farms (VF), also called plant factories, is often claimed as a solution for global food security due to its ability to produce crops unaffected by weather or pests. In principle, essential macronutrients of the human diet, like protein, could technically be produced in VF. This aspect becomes relevant in the era of protein transition, marked by an increasing consumer interest in plant‐based protein and environmental challenges faced by conventional farming. However, the real question is: what does the cultivation of protein crops in VF imply in terms of resource use? To address this, a study was conducted using a VF experiment focusing on two soybean cultivars. Results: With a variable plant density to optimize area use, and because of the ability to have more crop cycles per year, protein yield per square metre of crop was about eight times higher than in the open field. Assuming soy as the only protein source in the diet, the resources needed to get total yearly protein requirement of a reference adult would be 20 m2 of crop area, 2.4 m3 of water and 16 MWh of electricity, versus 164 m2, 111 m3 and 0.009 MWh in the field. Conclusions: The study's results inform the debate on protein production and the efficiency of VF compared to conventional methods. With current electricity prices, it is unlikely to justify production of simple protein crops in VF or promote it as a solution to meet global protein needs. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

[Display omitted] • Energy access, oil price fluctuations, and energy use as new environmental factors. • Energy use contributes to climate change, land degradation, and air pollution. • An increase in energy use is associated with an increase in CO 2 emissions. • Sustainable societies rely on energy access and the quality of the environment. • Environmental quality in APEC countries is affected by oil price fluctuations. Energy security has moved to the forefront of international policy agendas and boosted efforts to deploy clean energy technologies. In the past few years, clean energy investment has accelerated at a faster rate than investment in fossil fuels, contributing to the emergence of peak oil demand. This study examines the impact of energy use, energy access, and oil price fluctuations on environmental quality in APEC countries between 1991 and 2020 using shadow economies and agricultural lands as moderating variables. The results of the Arellano-bond dynamic panel data estimation show that energy use, energy access, agricultural land, and a shady economy are positively related to CO 2 emissions, while oil price fluctuations are negatively associated with CO 2 emissions in APEC nations. There is a positive correlation between energy use and carbon dioxide emissions among APEC nations. As energy use increases, CO 2 emissions increase as well. APEC nations have a positive relationship between energy access and carbon dioxide emissions. Policymakers in APEC countries must understand the implications of rising energy consumption and CO 2 emissions. To mitigate negative environmental consequences, develop sustainable energy sources, and promote economic growth, energy efficiency measures can help to minimize energy consumption and reduce CO 2 emissions. APEC countries are encouraged to develop carbon pricing mechanisms to encourage companies to reduce greenhouse gas emissions through cap and trade systems or carbon taxes. The implementation of carbon pricing mechanisms encourages businesses to switch to cleaner, renewable energy sources as a result of putting a price on carbon emissions. [ABSTRACT FROM AUTHOR]

The present study aims to ascertain the causes of environmental vulnerabilities in Pakistan, Bangladesh, and India. The countries are ranked top ten in the Global Climate Risk Index list in 1998–2017, 1999–2018, 2000–2019, 2018, and 2019. Hence, we determine whether the observing nations’ increasing GDP per capita, energy use, and population density intensify greenhouse gas emissions. This study also considers structural breaks in the time-series data from 1990 to 2019. Using the bounds-testing approach, we discover evidence of long-run cointegration among the variables. Furthermore, the long-run autoregressive distributed lag (ARDL) estimations disclose that GDP per capita positively correlates with greenhouse gas emissions, with this effect observed across all sample countries except India in the short run. Additionally, in the long and short run, energy use intensifies greenhouse gas emissions in all sample countries except Bangladesh. Population density also harms the environment in both time horizons in all the observed countries. The study also incorporates fully modified OLS (FMOLS) and dynamic OLS (DOLS) regressions for robust interpretations. Findings of FMOLS and DOLS also support the ARDL model’s outcomes. Moreover, diagnostic tests confirm the stability and reliability of ARDL models. Based on the varying findings on the impacts of energy use on greenhouse gas emissions across countries in the short and long run and the influence of GDP per capita in the short run, policymakers should tailor environmental policies according to nations’ energy and income structures.Highlights: This study sought to ascertain the causes of environmental vulnerabilities in Pakistan, Bangladesh, and India. The countries are ranked in the top ten list of environmentally vulnerable nations in the Global Climate Risk Index. The study examined the impact of increasing GDP per capita, energy use, and population density on greenhouse gas emissions. The authors utilized the bounds-testing approach to reveal long-run cointegration among variables in the study. In further assessment, the study discovered a positive correlation between GDP per capita and greenhouse gas emissions in all countries except for short-term results for India. The study also identified energy use as a contributor to greenhouse gas emissions in all countries except Bangladesh, both in the short and long run. Population density was also found to exacerbate environmental degradation in all observed countries, with a more significant impact in Pakistan compared to Bangladesh and India. Results suggested that GDP per capita, energy use, and population density contribute to environmental degradation in Pakistan in the long run. In Bangladesh, population density and GDP per capita were identified as dynamic factors contributing to environmental degradation in the long run. In India, GDP per capita, energy use, and population density positively affected greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

In recent years, urban areas like Lucknow have faced increasing challenges related to energy consumption and sustainability. As cities grow, the demand for energy rises, necessitating efficient use of resources to mitigate environmental impact and ensure long-term urban livability. Energy efficiency in urban neighborhoods plays a pivotal role in achieving these goals by reducing energy consumption, promoting sustainable practices, and enhancing the quality of life for residents. Despite the importance of energy efficiency, many urban neighborhoods in Lucknow face significant challenges in implementing effective strategies. Variations in infrastructure, socioeconomic factors, and policy frameworks influence the adoption and success of energy-efficient practices across different neighborhoods. Understanding these variations and identifying successful approaches are crucial steps towards fostering sustainable urban development. Urban areas worldwide face growing challenges related to energy consumption and sustainability, prompting cities like Lucknow to explore strategies for enhancing energy efficiency within their urban fabric. This research conducts a comparative analysis of energy efficiency practices across diverse neighborhoods in Lucknow, aiming to identify effective strategies and contextual factors influencing their implementation. Utilizing a mixed-methods approach, qualitative data from interviews and site observations complement quantitative data on energy usage patterns and infrastructure development. Findings reveal significant variations in energy efficiency initiatives, impacted by local governance, community engagement, and technological adoption. Successful practices emphasize multi-stakeholder collaborations, policy coherence, and tailored interventions that address neighborhood-specific needs. The study contributes empirical insights into urban sustainability by informing policy-makers and urban planners on effective pathways for promoting energy efficiency in Lucknow's neighborhoods, thereby advancing broader goals of environmental sustainability and livability in urban environments. [ABSTRACT FROM AUTHOR]

In parallel with the growing interest in cryptocurrencies, the relationship between crypto trading and CO2 is critical to drive financial markets and environmental sustainability efforts. The aim of this study is to analyse the impact of crypto trading on carbon emissions (CO2) through the mediating roles of international trade and energy use. Within the scope of the study, path analysis was carried out using the 2007-2021 period data of the top 20 countries with high crypto trade volume. A model proposal was presented to examine the relationships between the variables used in the study and the necessary analyses were carried out. The results of the analysis show that crypto trade volume has a positive and significant effect on carbon emissions. It is also concluded that international trade and energy use mediate the relationship between crypto trade and carbon emissions. It is seen that crypto mining activities and cryptocurrencies lead to an increase in energy use and environmental impacts. At this point, it is important for countries to switch to renewable energy sources and to regularly report and monitor the impact of cryptocurrency mining activities on carbon emissions. [ABSTRACT FROM AUTHOR]

This paper describes an empirical experiment of Internet of Things (IoT)'s integration in the Post-Occupancy Evaluation (POE) process. The experiment aimed to trial a novel IoT approach to enabling building user responsiveness to prevalent IEQ for individualised comfort. The purpose is to provide a system that mitigates a common issue of centralised air conditioning that limits occupants' control over their immediate environment. To achieve this, an IoT platform was developed with smart IEQ monitoring sensors and wearable devices and trialled with PhD researchers in a shared university workspace. The findings provided empirical evidence of IoT's enhanced benefits to improving user control over their individual comfort and enabling positive energy behaviour in buildings. Specifically, the IoT system provided real-time insight into CO2 concentration data while enabling responsive occupant interaction with their immediate environment and at-the-moment mitigation actions. Outputs of the experiment showed that the perceptions of participants about the stuffiness of the air, productivity, and healthy environment were significantly better after taking the mitigation action compared to before. Also, we found a significant relationship between measured CO2 concentration readings and perceived air stuffiness (p = 0.004) and productivity (p = 0.006) and a non-significant relationship between CO2 concentration readings and perceived healthy environment (p = 0.058). Interestingly, we observed that irrespective of the similarities in recorded CO2 concentration readings being within acceptable ranges (632–712 ppm), the perception of air stuffiness significantly differed (p = 0.018) before and after the mitigation actions. The effectiveness of the developed IoT platform was evidenced as most of the participants found the process very easy to participate in with little interruptions to their work as little time was consumed. The results are useful in modifying approaches to building occupant comfort and energy behaviour in commercial and residential settings. [ABSTRACT FROM AUTHOR]

Establishing connections between ecosystems and agricultural mechanization can help address the challenges of poor decisionmaking in agriculture and prevent further damage to ecosystems. It is essential for agricultural authorities and decision-makers to thoroughly understand ecosystem dynamics and the factors that influence them to develop effective policies for sustainable development. This study focuses on determining optimal conditions for crop patterns and input allocation across fields, specifically in the agricultural landscape of Ilam Province, with an emphasis on technical and energy aspects. The research targets farmers cultivating wheat, barley, fodder maize, and canola in the southern region of Ilam Province, covering Abdanan, Dareshahr, and Dehloran cities. Findings from a survey of 240 farmers reveal significant disparities in machinery, labor, and diesel fuel inputs across the different field levels. Recommendations include adjusting crop patterns by reducing wheat cultivation by 140 hectares and increasing irrigated fodder maize cultivation. Moreover, exploring rainfed cultivation or enhancing rainfed wheat yields is suggested to compensate for the decreased wheat cultivation. Utilizing an objective planning model, the study advocates for a more sustainable cropping model, highlighting wheat, barley, fodder maize, and canola crops. The proposed model introduces 210 additional hectares of irrigated wheat cultivation, along with expansions in irrigated barley and fodder maize cultivation areas. Although rainfed cultivation is uncommon in the area, efforts are directed towards improving the productivity of irrigated crops to support sustainability and enhance agricultural practices in the province. [ABSTRACT FROM AUTHOR]

Anthropogenic stressors can have an impact in a broad range of physiological processes and can be a major selective force leading to rapid evolution and local population adaptation. In this study, three populations of the invasive crayfish Procambarus clarkii were investigated. They are geographically separated for at least 20 years, and live in different abiotic environments: a freshwater inland lake (Salagou lake) with no major anthropogenic influence and two other coastal wetlands regularly polluted by pesticides along the Mediterranean coast (Camargue region and Bages-Sigean lagoon). Collected adults were genetically characterized using the mitochondrial COI gene and haplotype frequencies were analyzed for genetic variability within and between populations. Results revealed a higher genetic diversity for these invasive populations than any previous report in France, with more than seven different haplotypes in a single population. The contrasting genetic diversity between the Camargue and the other two populations suggest different times and sources of introduction. To identify differences in key physiological responses between these populations, individuals from each population were maintained in controlled conditions. Data on oxygen consumption rates indicate that the Salagou and Bages-Sigean populations possess a high inter-individual variability compared to the Camargue population. The low individual variability of oxygen consumption and low genetic diversity suggest a specific local adaptation for the Camargue population. Population-specific responses were identified when individuals were exposed to a pesticide cocktail containing azoxystrobin and oxadiazon at sublethal concentrations. The Salagou population was the only one with altered hydro-osmotic balance due to pollutant exposure and a change in protease activity in the hepatopancreas. These results revealed different phenotypic responses suggesting local adaptations at the population level. [ABSTRACT FROM AUTHOR]

Due to increasing energy consumption, there has been a significant expansion in worldwide trade, leading to the emergence of severe environmental issues. This situation is further compounded by the non-negotiable requirement to simultaneously mitigate environmental degradation and achieve economic progress. To ensure a healthier future, it is imperative to identify and address the factors that contribute to environmental contamination. The purpose of this study is to examine how Malaysia's carbon dioxide (CO2) emissions are affected by energy consumption, economic growth, and the economic complexity index (ECI). Time series data from 1997 to 2020 are used in this study, along with the autoregressive distributed lag model. The environmental Kuznets curve theory holds true in Malaysia, according to the study's findings, and energy use has a negative impact on CO2 emissions. There is also evidence suggesting that a higher ECI is linked with increased levels of CO2 emissions over a prolonged period. Malaysia's main export, electrical and electronic goods, generates substantial CO2 emissions during the manufacturing process. The outcomes of this research have important ramifications for environmental strategies concerning the mitigation of CO2 emissions. The electrical and electronics industries can implement energy-efficient technologies and practices in manufacturing processes. This would include upgrading to more efficient machinery, optimizing production schedules, and reducing idle times. It is also crucial to work with governments and industry bodies to advocate for policies that support sustainable manufacturing practices. [ABSTRACT FROM AUTHOR]

Recent working time reduction policies aim at achieving a triple dividend, yet their impact is uncertain due to potential rebound effects. Saved work time may be spent on energy-intensive leisure activities, complicating the overall outcomes. In our study, we conduct a time use analysis to investigate how different work schedules affect leisure time and its associated energy consumption, using the Italian Time Use Survey from Istat. Our analysis examines how predictive factors such as employment status, gender, and variables related to the household environment affect preferences for leisure activities, employing various econometric models, including Dirichlet regression which best suits compositional data. Results suggest that working time predominantly affects leisure time allocation; employment status, gender, and the presence of a teenager in the household also play a role. From an energy usage standpoint, a time rebound effect is present, although it is not mediated by the aforementioned factors. [ABSTRACT FROM AUTHOR]

This study assessed the environmental impacts of beef cattle production and their effects on the overall sustainability of Canadian beef production. Cradle to farm gate, cradle to processor's gate, and cradle to consumer plate life cycle assessments were carried out to quantify greenhouse gases (GHG), resource use (i.e., water, land, and fuel), and potential water and air pollution (i.e., freshwater eutrophication, terrestrial acidification, and photochemical oxidants formation). Across the production chain, feed production had the greatest impact on most environmental indicators. The GHG intensity without dairy meat was estimated as 10.4 kg CO2-eq per kg of live weight (LW), corresponding to 32.8 kg CO2-eq per kg of consumed boneless beef. Including dairy meat reduced GHG intensity by 5.8% (0.6 kg CO2-eq kg LW–1) compared to when it was excluded. Other environmental metrics per kg of LW were 657 L, 38.7 m2 annual crop-eq, 0.4 kg oil-eq, 2.6 kg P-eq, 115.9 kg SO2-eq, and 8.7 kg NOx-eq for water use, land use, fossil fuel use, freshwater eutrophication, terrestrial acidification, and photochemical oxidants, respectively. Data provide benchmarks for use in future regional and national assessments that are designed to encourage the adoption of sustainable management practices that can lower the environmental footprint of Canadian beef production. [ABSTRACT FROM AUTHOR]

In areas with a deep floor plan, the distribution of natural light is not uniform. Consequently, relying solely on daylight may not suffice to meet the space's lighting requirements, necessitating the use of artificial lighting in darker areas. Therefore, a lighting system is needed that not only controls the glare near the windows but also increases the light at the end of the room and provides uniform daylight. One of the widely used systems is the "light shelf", which has three main functions: shading, increasing the depth of light penetration, and reducing glare. Review articles about light shelves were published in 2015 and 2017, while more than 80% of the studies have been carried out since 2016, and light shelves with more diverse forms and dynamic elements and many consolidations have been proposed. Therefore, there is a need for a more comprehensive review. The main question of this research is how different parameters (including climate, material, ceiling, and integrated systems) can help to increase the efficiency of light shelves. By using a systematic review, studies in the past three decades were classified in order to determine the effect of these parameters on improving lighting performance and controlling solar heat gain. [ABSTRACT FROM AUTHOR]

This article examined the nexus between energy consumption and economic growth in selected Southern African Development Community countries for the period 1980 to 2015. The study used both simple and multiple linear regression models to examine the relationship between the variables. The statistical results of the simple linear regression model between energy use and economic growth show a correlation coefficient of 0.060. This represents a weak positive correlation between the model variables. A coefficient of determination of 0.00476 depicts that energy use explains only 0.476% of the variability in the gross domestic product of countries investigated. The multiple linear regression model results show a multiple R of 0.3684, and an R2 of 0.1358. This also depicts a weak positive correlation between the model variables. A coefficient of determination of 0.1358 means that energy use and electric power consumption accounts for only 13.58% of the values of the gross domestic product of selected Southern African Development Community countries and the balance is explained by the terms that are not specified in the model. This article is of value to policy makers in the region as well as the academia as it strives to close the gap in knowledge.

We used crowdsourced data in Alaska and the literature to develop a light-duty electric vehicle model to help policymakers, researchers, and consumers understand the trade-offs between internal combustion and electric vehicles. This model forms the engine of a calculator, which was developed in partnership with residents from three partner Alaskan communities. This calculator uses a typical hourly temperature profile for any chosen community in Alaska along with a relationship of energy use vs. temperature while driving or while parked to determine the annual cost and emissions for an electric vehicle. Other user inputs include miles driven per day, electricity rate, and whether the vehicle is parked in a heated space. A database of community power plant emissions per unit of electricity is used to determine emissions based on electricity consumption. This tool was updated according to community input on ease of use, relevance, and usefulness. It could easily be adapted to other regions of the world. The incorporation of climate, social, and economic inputs allow us to holistically capture real world situations and adjust as the physical and social environment changes.

The use of energy-efficient technologies tends to reduce the overall energy use of a country and foster the energy transition pathways. However, a change in energy can occur either due to a change in activity effect, intensity effect, or structural effect. The objective of the study is firstly to examine and measure the magnitude of change in energy use and identify the factor responsible for the change in energy use in the selected sectors. Secondly, the paper aims to analyze the impact of the Norwegian economy on the three effects of energy use. The study contributes significantly to identifying the sector that experiences a reduction in energy use due to energy efficiency and examining the impact of the economy on energy use. The overall energy use between 1990 and 2017 is decomposed into three different effects for selected energy-intensive sectors by deploying the ‘Logarithmic Mean Divisia Index’ (LMDI) method. Further, the impact of the Norwegian economy is examined on the three effects of energy use. It is observed that in each Phase, the key driver for change in energy use in all three Phases is the transport sector. Post-recession, the energy use in the transport sector was due to structural effects. Consumer behavior and limitations of sources of finance are the challenges for the deployment of electric vehicles even after technological breakthroughs in energy efficiency. Finally, the policies to enhance energy efficiency in energy-intensive sectors, such as the transport, and services sector must be undertaken to efficiently visualize energy efficiency-driven energy transition.

This data article refers to the paper “A method for generating complete EV charging datasets and analysis of residential charging behaviour in a large Norwegian case study” [1]. The Electric Vehicle (EV) charging dataset includes detailed information on plug-in times, plug-out times, and energy charged for over 35,000 residential charging sessions, covering 267 user IDs across 12 locations within a mature EV market in Norway. Utilising methodologies outlined in [1], realistic predictions have been integrated into the datasets, encompassing EV battery capacities, charging power, and plug-in State-of-Charge (SoC) for each EV-user and charging session. In addition, hourly data is provided, such as energy charged and connected energy capacity for each charging session. The comprehensive dataset provides the basis for assessing current and future EV charging behaviour, analysing and modelling EV charging loads and energy flexibility, and studying the integration of EVs into power grids.