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Carbon emissions elimination in the rapid urbanization areas contributes to regional sustainable development and global climate change mitigation. With the target of carbon neutrality, the global top-class Beijing-Tianjin-Hebei Urban Agglomeration which confronts with the dual pressure of excess carbon emissions and shrink ecological space has increased its carbon reduction coordination cooperation, among which energy consumption carbon emission control and natural resource sink maintenance have been recognized as the key strategy. However, the study on carbon balance prediction is lack and the amount of energy consumption carbon emissions in the future can be offset by the ecological carbon sink is still unknown. To estimate the gap to carbon neutrality, this study proposes a framework for carbon offset analysis and prediction which takes various carbon emission scenarios and the potential of natural resource on carbon reduction into consideration. After the framework conduction in the agglomeration, it is revealed that the regional least carbon emissions of 29.51 Mt mainly derive from the population and economic growth brought by urbanization process, while the carbon sink predicted to be 2552.31 Kt is still far to cover the emissions. With the regional carbon offset rate decline from 0.68% to 0.63%, the ecological carbon sink in Beijing will offset 1.21% of its carbon emission, while the least ecological space keep city Tianjin is predicted to suffer the lowest offset rate of 0.09%. The research results contribute to recognize the key factors on carbon emission control and key areas for carbon maintenance in following years, as well as narrowing the gap to neutrality with both consideration of carbon emission reduction and sink maintenance. [Display omitted] • Framework on energy consumption carbon offset analysis was established. • Regional carbon emissions, sinks and offset rate were predicted. • Drop from 0.68% in 2020 to 0.63% in 2030, the declining offset rate indicates the gap to neutrality is still large. • Implications for each area's carbon emission offset rate improvement were discussed. [ABSTRACT FROM AUTHOR]

• Climate policy should be diversified to meet the needs of all countries. • The ability of renewable energy to solve the emissions problem is questioned. • The energy efficiency has no statistically significant changes in 2010–2020. • There is a contradiction between Sustainable Development Goals 7 and 13. Improving energy efficiency is considered to be important and cost-effective strategies to reduce greenhouse gas emissions, which is crucial in the face of global climate change. This study hypothesizes that there are significant differences in the impact of energy efficiency on economic and energy systems. Using quantile regression method, the impact of economic and energy characteristics on energy-related greenhouse gas emissions in 120 countries over the period 2010–2020 is investigated. Detailed analyses are conducted by dividing the countries into 12 groups based on gross national income per capita (Atlas method) and the share of resource rents in gross domestic product. A macro-level system of indicators for assessing energy efficiency is proposed, which can be linked to the economic and energy characteristics of the systems: National Energy Efficiency, Energy Intensity Ratio, Primary Energy Production Efficiency, Industrial Sector Energy Efficiency, Share of Low Carbon Energy, Population Energy Efficiency. The findings show that (1) global energy efficiency has remained largely unchanged over the decade; (2) there are differences in energy efficiency between fossil fuel producing and non-fossil fuel producing countries; (3) the factors that have an inverse effect on emissions in fossil fuels dependent countries include industrial energy efficiency and population energy efficiency, which are far from exhausting their potential; (4) despite the recognized importance of energy efficiency, its impact on reducing greenhouse gas emissions globally has been unnoticeable. The study highlights that Sustainable Development Goals 7 and 13 on energy affordability and emission reductions are conflicting and require harmonization of mechanisms to achieve them, such as balancing climate change mitigation investments, identifying the potential for energy efficiency improvements across economy or improving energy saving practices. The overall conclusion suggests that there is an urgent need to review current decarbonization and energy efficiency initiatives, given the lack of significant global progress in reducing greenhouse gas emissions or improving energy efficiency between 2010 and 2020. [ABSTRACT FROM AUTHOR]

In the pursuit of sustainable development, accurate renewable energy demand forecasting holds great significance for climate change mitigation and promoting sustainability. However, renewable energy forecasting has been consistently challenged by seasonality and nonlinearity. Identifying the periodic and nonlinear characteristics concealed within renewable energy sources accurately is still an unexplored problem. Consequently, an innovative nonlinear discrete seasonal grey model is proposed for renewable energy forecasting, which incorporates seasonal dummy variables and a power exponent term for handling the seasonality and nonlinear patterns in time series. Furthermore, an intelligent algorithm matching framework is proposed to augment the flexibility of the newly developed model. For practical purposes, the new methodology is contrasted against a range of benchmarks encompassing statistical, machine-learning, and traditional grey models in forecasting the quarterly total renewable energy consumption in the United States. The proposed model exhibits over 27% improvement rates over its counterparts, achieving the most superior predictive accuracies of 1.45%, 39.27, and 0.79 in MAPEP , RMSEP , and MASEP metrics, respectively. Furthermore, the probability density and sample size analyses are conducted to validate the robustness of the new model, confirming its adaptability and stability towards algorithm randomness and historical information volume. Consequently, the novel model is employed to forecast the short-to-long-terms renewable energy consumption in the U.S., showcasing an upward trend and seasonal fluctuations of the consumption for the forthcoming 24 quarters from 2023Q4 to 2029Q3. These insights can offer valuable implications to the stakeholders such as energy suppliers, utility managers, and policy advocates, highlighting actionable strategies for optimizing renewable energy consumption forecasting and aiding sustainable development initiatives. • An innovative nonlinear discrete seasonal grey model is proposed for renewable energy forecasting. • The optimum algorithm matching the novel model is determined from five alternatives. • The Monte Carlo Simulation and parameter sensitivity analysis advance the robustness. • PSO with the optimal parameter group has been selected for searching coefficients. • The new model possesses higher accuracy and robustness than various competitors. [ABSTRACT FROM AUTHOR]

• Buildings potential for climate change mitigation is high. • Mitigation actions in the buildings sector can have significant social and economic values. • These enable the achievement of 4 SDGs, reinforce 7 other. • And are linked to the achievement of 5 SDGs (SDG3, SDG7, SDG8, SDG11, and SDG13). • Trade-offs were identified for 9 SDGs. Buildings are responsible for a big part of total GHG emissions; therefore, their climate change mitigation potential is high. But research shows that mitigation actions in the sector can have significant social and economic values beyond reduction of energy consumption and the associated GHG emissions. This paper summarizes these multiple impacts of mitigation actions in buildings, which are related to microeconomic and macroeconomic effects, health impacts, environmental benefits, better management of natural resources, impacts on social well-being, and energy security implications, and assesses their interactions (synergies and trade-offs) with the UN SDGs. The findings of our analysis show that climate change mitigation actions in buildings enable the achievement of 4 SDGs, reinforce 7 others, and are inextricably linked to the achievement of 5 SDGs, namely SDG3: good health and well-being, SDG7: affordable and clean energy, SDG8: decent work and economic growth, SDG11: sustainable cities and communities, and SDG13: climate action. On the other hand, trade-offs were identified for 9 SDGs, with rather minor implications, which can be further eliminated with the implementation of appropriate policies. [ABSTRACT FROM AUTHOR]

• Proposal of a method to construct typical generic block models using local datasets. • Urban form influences strategy of solar technology in low-carbon scenario. • Solar cooling contributes to carbon reduction in subtropical areas. • Technology and morphology design can overcome the high-density constraints. The use of solar energy in an urban context is essential for low-carbon urban development and global climate change mitigation. In this paper, the application of multiple solar energy techniques, namely, photovoltaic (PV), photothermal (PT), and photothermal-driven cooling (PC) techniques, in tropical Macau was investigated. Based on the typological method, sixty generic block typologies were formulated. A parametric workflow was constructed to facilitate block modelling and simulate energy consumption and solar radiation. The optimal technique strategy for each typology was identified under a low-carbon scenario. The energy and environmental performance levels of the blocks were evaluated by calculating and comparing the solar potentials, load matching conditions, primary energy consumption levels, and carbon dioxide emissions. The results indicated that the PT technique should be preferred for blocks with high floor area ratio (FAR) values, while the PV technique should be prioritized for blocks with low FAR values under the low-carbon scenario. Moreover, the PC technique is necessary in subtropical areas to reduce carbon emissions. In addition, it is suggested that solar energy should be adopted in blocks with high site coverage ratio (SC) and low surface area-to-volume ratio (SAV) values, as well as blocks with low FAR values. Regarding blocks constrained by high-density urban development, appropriate decisions on technology and morphological design could help to overcome constraints and realize low-carbon community targets. This study could provide suggestions for urban planners and building designers in the application of the urban solar potential at the early stages of urban design or urban regeneration. [ABSTRACT FROM AUTHOR]

There is a lack of empirical analysis of macro-level energy policy through a gender lens, and there exists a research gap in tools for such analysis. This paper proposes a novel empirical approach to explore the gender dimension of the language used in energy policy documents such as the National Energy and Climate Action Plans (NECPs) of European Union (EU) member states. We first review the literature to identify existing approaches that analyse the energy/gender nexus. We then describe how we adapt Natural Language Processing (NLP) techniques to quantify the degree to which the language used in the NECPs is male or female associated. Our work shows the gap in suitable tools. We demonstrate using NLP that all EU NECPs tend to use more male associated language than female. In a ranking of EU member states, the Portuguese NECP demonstrated the most bias, while the Slovenian demonstrated the least. Our work provides novel insights using NLP to understand the genderised use of language, and contributes a methodology to conduct empirical analysis of energy policy documents. [Display omitted] • Review of methods used in energy/gender nexus analysis. • Empirical approach to analyse energy/gender concepts in the Global North. • Measurement of a gender dimension (bias) of the language used in European Union National Energy and Climate Plans. • Identification of Energy Domain NLP training corpora and vocabulary. [ABSTRACT FROM AUTHOR]

Energy efficiency measures are a key element in the fight against climate change. However, their effectiveness is threatened by so-called rebound effects—behavioral changes that lead to increased use and thus to lower-than-expected absolute savings. The moral licensing bias might cause rebound effects on the individual level: When people implement energy efficiency measures, they may feel that they have done something good for the climate and thus license themselves to less climate-friendly behavior later on. We test this prediction with three pre-registered experiments (total n = 2315). While our manipulated efficiency does increase the feeling of having done something good for the climate, no negative effects emerge on subsequent climate-friendly behavior—contrary to the predictions derived from the moral licensing literature. Climate-friendly behavior is thus not hampered by prior energy efficiency behavior; rather, demographics (women and older people act in a more climate-friendly manner) and environmental attitude determine it. Our results imply that the literature suggesting moral licensing is probably not transferable to the field of energy efficiency, and thus moral licensing may not lead to rebound effects in this context. We discuss possible explanations, implications for climate policy making, and needs for future research. [ABSTRACT FROM AUTHOR]

Renewable energy consumption is a crucial aspect of global sustainability efforts, particularly in light of climate change mitigation and the pursuit of energy security. Technological innovation can play a pivotal role in driving the advancement and adoption of renewable energy. However, geopolitical risks can exert profound influences on the landscape of renewable energy deployment, posing challenges to energy security and the transition to a sustainable energy future. This study contributes to the existing literature by providing new empirical evidence on how geopolitical risk, along with technological innovation, environmental taxes, and environmental degradation affect renewable energy consumption in G7 countries. The findings indicate that geopolitical risks exert a negative influence on renewable energy consumption in G7 countries, whereas environmental degradation, technological advancements, and environmental taxes have positive effects. The results further indicate that at different quantile levels, the impact of each variable on renewable energy consumption has heterogeneous characteristics. Panel Grager causality results revealed a one-way causal relationship between environmental taxes and renewable energy consumption, while other variables have a two-way causal relationship with renewable energy consumption. Based on the results, the study suggests design policies to address geopolitical tension, increased funding for research and development to drive technological innovation, and supportive regulatory frameworks that incentivize renewable energy investment and innovation to achieve Sustainable Development Goal 7 (SDG7). • Explored the determinants of renewable energy consumption in G7 countries. • Advanced panel data estimation methods are employed. • Geopolitical risk negatively affects renewable energy consumption. • Technological innovation and taxes promote renewable energy consumption. • Designed a policy framework to achieve Sustainable Development Goal 7. [ABSTRACT FROM AUTHOR]

GEP (Generation Expansion Planning) is one of the most complex tasks in which planning is done to find the best possible distinct solutions to install new generating units to meet future load demands. This paper uses the Low Emission Analysis Platform (LEAP) software environment to analyse the GEP for the AP Power sector from 2021 to 2050. In recent years, the AP power sector has faced several issues, such as frequent service cuts due to power shortages. In this paper, five scenarios such as Business As Usual (BAU), Low Demand Growth (LDG), High Demand Growth (HDG), Least Cost Optimization (LCO) and Climate Mitigation Scenarios, have been analysed with environmental, technical, and economic parameters. This study has estimated the total environmental emissions and total cost of all scenarios. At present, Andhra Pradesh has a total installed capacity of 25.4 GW. The best scenarios can be selected based on environmental impact, cost-effectiveness, efficiency, and reliability. The results show that the LDG scenario will be an optimal choice for AP due to the state's economic crisis, and the government should also focus on energy conservation and limit demand growth to 4.5%. While presenting a general GEP, the study presents comprehensive system performance scenarios from which planners can choose. • Making a generation expansion planning • Making a sustainable environment • Presented a good solution for power generation • Analysed the total environmental emissions • Analysed the energy demands. [ABSTRACT FROM AUTHOR]

In the quest for carbon neutrality, the cement industry employs various CO 2 mitigation strategies, including material efficiency, cement plant technologies, and clinker-to-cement ratio reductions. This study reviews the past decade's Life Cycle Assessment (LCA) literature on cement production to assess the feasibility of modeling these strategies. Heating energy is the predominant factor in energy consumption, benefiting from energy efficiency measures. Allocation consistently favors cement in evaluations of secondary fuel-related impacts, leading to significant reductions in energy consumption and Greenhouse Gas (GHG) emissions. However, transparency improvements are necessary to clarify the origin and calculation of combustion-related emissions. Challenges arise from limited data availability when assessing grinding energy, especially for high-quality cement aligned with a material efficiency strategy. In our examination of Ground Granulated Blast Furnace Slag (GGBS) as Supplementary Cementitious Materials (SCMs), we have observed that production process variations and allocation assumptions significantly influence LCA models, while highlighting the absence of waste availability consideration in current substitution-focused LCA methods for both secondary fuels and SCMs. • Cement functionalities are generally not described and should be based on strength. • Existing models overlook impacts of increased cement quality due to grinding energy. • Allocation method choice affects climate change impacts of slag-blended cement. • Excluding allocation methods, slag recovery shows climate change impacts variability. • Substantial variability is also found for heating energy for clinkerization. [ABSTRACT FROM AUTHOR]

Animal production faces challenges related to thermal comfort, air quality, and carbon dioxide (CO 2) emissions, thereby the need for more efficient and sustainable systems due to climate change. This study examines green roofs and their potential to absorb atmospheric CO 2 and reduce heat load through photosynthesis and evapotranspiration, resulting in decreased energy consumption and increased CO 2 emissions. The maximum CO 2 concentration limit in animal production facilities is 3000 ppm. Depending on the ventilation system used in broiler production facilities, the CO 2 concentration can exceed 2000 ppm. Dark House poultry facilities tend to have higher concentrations reaching up to 777 ppm. In pig farming, the nursery sector has higher concentrations of CO 2 , exceeding 1200 ppm. In dairy farming, the number of milkings, the type of ventilation system and local climatic conditions can affect the CO 2 concentration, reaching values of up to 1401 ppm. C3 plants have a CO 2 saturation point at 800 ppm and C4 plants at 200 ppm. The CO 2 balance in animal production facilities that use a green roof can be done considering the CO 2 produced and the CO 2 absorbed. Green roofs are therefore considered a sustainable solution for animal production. Its implementation enhances air quality in the facilities, supporting the reduction of environmental impacts and mitigation of climate change effects caused by the agroindustry. This investigation underscores the significance of green roofs, emphasizing their environmental, social, and economic benefits, as well as their applicability in animal production. • It is possible to estimate the CO 2 balance in animal production facilities with a green roof. • Green roof can improve air quality in animal production. • Green roof can reduce the thermal stress of the animals in the premises. • Green roof can contribute to the sustainability of animal production. [ABSTRACT FROM AUTHOR]