Search Results (2,617)

The rapid integration of renewable energy sources and increasing complexity of modern power grids demand advanced forecasting tools capable of simultaneously predicting multiple interconnected variables. While time series foundation models (TSFMs) have demonstrated remarkable zero-shot forecasting capabilities across diverse domains, their application in power grid operations remains limited due to complex coupling relationships between load, price, emissions, and renewable generation. This paper proposes GridFM, a novel physics-informed foundation model specifically designed for multi-task energy forecasting in power systems. GridFM introduces four key innovations: (1) a FreqMixer adaptation layer that transforms pre-trained foundation model representations to power-grid-specific patterns through frequency domain mixing without modifying base weights; (2) a physics-informed constraint module embedding power balance equations and zonal grid topology using graph neural networks; (3) a multi-task learning framework enabling joint forecasting of load demand, locational-based marginal prices (LBMP), carbon emissions, and renewable generation with uncertainty-weighted loss functions; and (4) an explainability module utilizing SHAP values and attention visualization for interpretable predictions. We validate GridFM using over 10 years of real-time data from the New York Independent System Operator (NYISO) at 5 min resolution, comprising more than 10 million data points across 11 load zones. Comprehensive experiments demonstrate that GridFM achieves state-of-the-art performance with an 18.5% improvement in load forecasting MAPE (achieving 2.14%), a 23.2% improvement in price forecasting (achieving 7.8% MAPE), and a 21.7% improvement in emission prediction compared to existing TSFMs including Chronos, TimesFM, and Moirai-MoE. Ablation studies confirm the contribution of each proposed component. The physics-informed constraints reduce physically inconsistent predictions by 67%, while the multi-task framework improves individual task performance by exploiting inter-variable correlations. The proposed model provides interpretable predictions supporting the Climate Leadership and Community Protection Act (CLCPA) 2030/2040 compliance objectives, enabling grid operators to make informed decisions for sustainable energy transition and carbon reduction strategies. Full article

Study region: This study focused on the Iznik Lake Watershed in northwestern Türkiye. Study focus: Climate change is increasingly affecting water resources worldwide, raising concerns about future hydrological sustainability. This study investigates the impacts of climate change on river streamflow in the Iznik Lake Watershed, a critical freshwater resource in northwestern Türkiye. To capture possible future conditions, downscaled climate projections were integrated with the SWAT+ hydrological model. Recognizing the inherent uncertainties in climate models and model parameterization, the analysis examined the relative influence of climate realizations, emission scenarios, and hydrological parameters on streamflow outputs. By quantifying both the magnitude of climate-induced changes and the contribution of different sources of uncertainty, the study provides insights that can guide decision-makers in future management planning and be useful for forthcoming modeling efforts. New hydrological insights for the region: Projections indicate wetter winters and springs but drier summers, with an overall warming trend in the study area. Based on simulations driven by four representative grid points, the results at the Karadere station, which represents the main inflow of the watershed, indicate modest changes in mean annual streamflow, ranging from −7% to +56% in the near future and from +19% to +54% in the far future. Maximum flows (Q_max) exhibit notable increases, ranging from +0.9% to +47% in the near future and from +21% to +63% in the far future, indicating a tendency toward higher peak discharges under future climate conditions. Low-flow conditions, especially in summer, exhibit the greatest relative variability due to near-zero baseline discharges. Relative change analysis revealed considerable differences in Karadere and Findicak sub-catchments, reflecting heterogeneous hydrological responses even within the same basin. Uncertainty analysis, conducted using both an ANOVA-based approach and Bayesian Model Averaging (BMA), highlighted the dominant influence of climate projections and potential evapotranspiration calculation methods, while land use change contributed negligibly to overall uncertainty. Full article

As one of the major sources of global carbon emissions, the manufacturing industry urgently requires green transformation. The utilization of renewable energy in production workshop offers a promising route toward zero-carbon manufacturing. However, renewable energy fluctuations and dynamic workshop events make efficient scheduling increasingly challenging. This paper introduces a low-carbon and energy-efficient dynamic flexible job shop scheduling problem oriented towards renewable energy integration, and develops a multi-agent deep reinforcement learning framework for dynamic and intelligent production scheduling. Inspired by the Proximal Policy Optimization (PPO) algorithm, a routing agent and a sequencing agent are designed for machine assignment and job sequencing, respectively. Customized state representations and reward functions are also designed to enhance learning performance and scheduling efficiency. Simulation results demonstrate that the proposed method achieves superior performance in multi-objective optimization, effectively balancing production efficiency, energy consumption, and carbon emission reduction across various job shop scheduling scenarios. Full article

Electric vehicles (EVs) are widely promoted as a key strategy for reducing carbon dioxide (CO₂) emissions and advancing sustainable development. However, the real-world benefits of EV adoption may vary across countries with different income levels and energy systems. This study investigates the relationship between EV adoption and CO₂ emissions per capita, as well as overall sustainable development performance (SDG Index), across 50 countries from 2010 to 2023. Using panel quantile regression, we find that EV adoption is significantly associated with reduced CO₂ emissions particularly in the high-emitting countries in high-income countries (interaction coefficient at the 90th quantile = −0.24, p < 0.05) but positively associated with emissions in lower- and middle-income countries at lower quantiles of the emissions distribution. Similarly, while EV adoption correlates positively with the SDG Index in high-income countries, it shows negative effects at the median and several quantiles. These findings challenge the “zero-emission” assumption and demonstrate that the climate and development benefits of EV diffusion are context-dependent and unevenly distributed, highlighting the need for policies that link electrification to renewable energy deployment, infrastructure development, and equitable access. Full article

The building sector is significantly responsible for the world’s energy consumption and carbon emissions. Net-zero energy buildings (NZEBs) have become an effective solution to move towards sustainability, maximizing energy efficiency, and minimizing carbon footprint. However, achieving net-zero energy targets requires a comprehensive understanding of building performance from the perspectives of technologies, materials, and strategies, for which existing studies have a knowledge gap. This study aims to bridge the knowledge gap within existing studies through an empirical investigation. Based on a review of the literature, this study employs semi-structured interviews in the United Kingdom (UK) with industrial professionals experienced in NZEBs. The qualitative data collected from interview participants are analyzed minutely using NVivo to identify key themes and patterns, including 14 technologies, 12 materials, and seven strategies for NZEBs. Based on the literature review and, more importantly, the interview analysis, a conceptual framework is well established to describe an NZEB as a complex system that must incorporate appropriate technology adoption, careful material selection, and successful strategy implementation into consideration. This study provides a comprehensive understanding of NZEBs from a systematic point of view. It also contributes to the full fulfillment of Sustainable Development Goals (SDGs) established by the United Nations (UN). Full article

Individual actions play a pivotal role in climate change, one of the most urgent global challenges, as daily behaviors generate substantial greenhouse gas emissions. Saudi Arabia, in particular, demonstrates its strong commitment to environmental sustainability through the Saudi Green Initiative and Middle East Green Initiative, aiming for net-zero emissions by 2060 and advancing reforestation, land conservation, and renewable energy under Vision 2030. However, many Saudi individuals remain unaware of the environmental consequences of their choices, including transportation, energy consumption, and lifestyle habits. To address this gap, this study developed GreenKSA, the first Arabic-supported gamified mobile application designed to promote pro-environmental behavior within the Saudi culture. The app integrates gamification elements grounded in Self-Determination Theory (SDT) and Trans-Theoretical Model (TTM) in an attempt to bridge the gap between theory and practice. GreenKSA delivers multimedia content—short videos and infographics—demonstrating sustainable routines in households, workplaces, and mobility. The design and user experience of GreenKSA were evaluated in a pilot study of 10 participants. The results indicated high usability (SUS = 91.25) and a positive overall user experience. By combining theory-driven design with culturally relevant gamification elements, this study contributes to digital sustainability interventions and aligns with the global Sustainable Development Goals SDG 12: Responsible Consumption and Production, and SDG 13: Climate Action. Full article

The UK’s net-zero by 2050 commitment necessitates urgent housing sector decarbonisation, as residential buildings contribute approximately 17% of national emissions. Post-1950 construction prioritised speed over efficiency, creating energy-deficient housing stock that challenges climate objectives. Current retrofit policies focus primarily on technological solutions—insulation and heating upgrades—while neglecting broader sustainability considerations. This research advocates systematically integrating Circular Economy (CE) principles into residential retrofit practices. CE approaches emphasise material circularity, waste minimisation, adaptive design, and a lifecycle assessment, delivering superior environmental and economic outcomes compared to conventional methods. The investigation employs mixed-methods research combining a systematic literature analysis, policy review, stakeholder engagement, and a retrofit implementation evaluation across diverse UK contexts. Key barriers identified include regulatory constraints, workforce capability gaps, and supply chain fragmentation, alongside critical transition enablers. An evidence-based decision-making framework emerges from this analysis, aligning retrofit interventions with CE principles. This framework guides policymakers, industry professionals, and researchers in the development of strategies that simultaneously improve energy-efficiency, maximise material reuse, reduce embodied emissions, and enhance environmental and economic sustainability. The findings advance a holistic, systems-oriented approach, positioning housing as a pivotal catalyst in the UK’s transition toward a circular, low-carbon built environment, moving beyond isolated technological fixes toward a comprehensive sustainability transformation. Full article

Worldwide the adoption of electric vehicles (EVs) is recognized as a key strategy for reducing transport-related greenhouse gas (GHG) emissions, a major contributor to global warming and climate change. The objective of this pilot study is to examine the key variables that might have influenced electric vehicle (EV) purchase decisions among current EV owners and how they are aligned or different for the prospective EV owners in North Carolina (NC). By adopting a web-based survey for data collection, the study specifically aims to identify economic, demographic, environmental, and commuting behaviors, along with existing government policies and incentives that might motivate consumer choices regarding EV adoption. Most existing EV owners who participated in the survey identified themselves as college-educated White men with USD 100 K or higher income, have more than two cars, commute more than 30 min, and live in single-family homes with EV charging. In contrast, among non-EV owners who plan to adopt an EV within the next three years, a significant proportion are non-White, women, and earn USD 50,000 or less annually. While home charging is important to both current EV owners and non-EV owners, EV incentive policies and proximity to public changing stations are found to be more important to non-EV owners’ decision to adopt EVs. A reasonable conclusion from this research is that expanding EV-friendly policies, incentives, and infrastructure will encourage first-time EV ownership in NC while providing deeper insights into the dynamics of sociodemographic among both EV owners and non-EV owners. Full article

Hybrid trolleybuses (HTBs) with in-motion charging (IMC) can extend zero-emission service using existing catenary, but high on-wire charging powers may concentrate loads and accelerate battery aging. We present a data-driven simulation that replays recorded high-resolution Controller Area Network (CAN) logs through a per-vehicle electrical model with (Constant-Current/Constant-Voltage) (CC/CV) charging and a stress-map aging estimator, a configurable partial catenary overlay, and fleet aggregation by simple summation and an iterative node-voltage analysis of a resistor-network catenary model. A parameter sweep across battery sizes, upper state of charge (SoC) bounds, and charging power caps compares a minimal “charge-whenever-possible” policy with a per-vehicle lookahead (“oracle”) policy that spreads charging over available catenary time. Results show that lowering maximum charging power and/or the upper SoC bound reduces capacity fade, while energy-demand differences are small. Fleet load profiles are dominated by timetable-driven concurrency using 40 recorded days overlaid into one synthetic day: varying per-vehicle power or target SoC has little effect on peak demand; per-vehicle lookahead does not flatten the peak. The node-voltage analysis indicates catenary efficiency around 97% and fewer undervoltage events at lower charging powers. We conclude that per-vehicle policies can reduce battery stress, whereas peak shaving requires cooperative, fleet-level scheduling. Full article

In recent years, long-term vehicle rental has gained importance as a flexible and cost-effective mobility solution. This model reduces the high initial costs associated with vehicle purchases, ensures predictable expenses through fixed monthly payments, reduces the risk of depreciation, and enables systematic fleet renewal, supporting its adaptation to changing environmental regulations and technological advancements. This paper proposes a tool to support the process of selecting propulsion technologies in long-term rental fleets, taking into account their economic, technical, environmental, and social implications for sustainable fleet management. The developed procedure combines secondary fleet data analysis, expert research conducted among service providers, and multi-criteria analysis conducted using the Analytic Hierarchy Process method. The results indicate that under current conditions in Poland, combustion vehicles remain the optimal solution for fleet operators, while electric vehicles—despite their environmental benefits and additional benefits—remain the least competitive. The proposed approach is comprehensive, adaptable, and easy to implement, providing a practical tool for fleet operators and end users. The results also provide guidance for public decision-makers on strengthening the market position of low- and zero-emission vehicles. Full article

The cement industry is at the core of global economic and infrastructure development accounts, but it also accounts for 7% to 9% of total emitting CO₂ For Pakistan, it is a major consumer of coal, emitting 8.9 Mt of CO₂ annually, resulting in nearly 49% of the country’s coal While several strategic initiatives are being adopted to lower conventional fuel consumption in the cement sector such as an increased shift towards solar energy deployment, initiating the shift from coal to alternate materials, but a well-regulated alternative fuel policy framework across cement production processes remains a clear gap in the industry’s decarbonization efforts. Given this challenge, this study conducts a scenario-informed quantitative evaluation using the Low-Emission Analysis Platform (LEAP) to explore the decarbonization potential of fuel switching in Pakistan’s cement industry, aligning it with NDC, Net-zero, and energy transition targets. The results reveal that swapping out coal and petroleum coke for cleaner alternatives would be necessary for reducing emissions by 13.5 Mt under the NDC scenario and 17.1 Mt for net-zero by 2050. However, achieving these targets requires a well-defined policy framework, regulatory support for Refuse-Derived Fuel (RDF) and Tire-Derived Fuel (TFD), building a sustainable biomass chain and quality control units, and capital investment in cleaner fuels. Full article

The Turkish steel industry aims to reduce its sectoral carbon dioxide (CO₂) emissions by 55% by 2030, in line with Türkiye’s Paris Agreement commitments and the European Green Deal (EGD), and consistent with the ambition of the European Union’s economy-wide ‘Fit for 55’ emissions-reduction target. Türkiye faces significant challenges in achieving net-zero greenhouse gas (GHG) emissions, particularly as a developing country confronting the impacts of climate change and in the market situation, such as the effects of the ongoing Russia-Ukraine conflict, limited access to affordable raw materials, and rising operational costs. This study serves as a guideline for the Turkish steel sector’s roadmap towards modernization and eventual compliance with net-zero targets. The consideration and integration of new technologies planned for the Turkish steel industry, in both electric arc furnace (EAF) and blast furnace-basic oxygen furnace (BF-BOF) facilities, have been outlined in conjunction with green hydrogen and with Carbon Capture and Storage (CCS) technologies. Four different scenarios were analysed to understand the reduction in CO₂ emissions: (1) In a Business-As-Usual (BAU) scenario without any reduction, (2) 39.9% CO₂ emission reduction with the Moderate scenario, (3) 59.6% reduction with the Advanced scenario, and (4) 82.9% reduction in CO₂ emissions from the Turkish steel sector with the Net-Zero scenario. To quantify the uncertainty in these long-term projections, a Monte Carlo simulation was conducted, generating probabilistic confidence intervals that reinforce the robustness and credibility of the net-zero pathway. The official roadmap for the sector is not available as of today; however, an in-depth discussion with a policy innovation leading to it is the objective of this study. Full article

The EPBD 2024 recast sets the deadline for new Zero-Emission Building standards for all new publicly owned buildings to 2028 and to 2030 for all new buildings. In the scope of Life Cycle Assessment stages, all steps resulting in major emissions from buildings must be considered and presented. The research evaluates the life cycle greenhouse gas emissions of a single-family house, focusing on diverse construction types and the hourly method of the annual energy calculations for continental and coastal climate areas in Croatia under the upcoming standards. Embodied carbon of diverse construction types was compared mutually, and required steps to meet the operational zero-emission standards were analyzed. Embodied energy of a 137.0 m² family house built out of reinforced concrete results in up to 67 tons of CO₂eq emissions, while wood in cross-laminated timber structures absorbs more carbon than emitted for all other materials and construction processes—23 tons of CO₂eq. Regarding operational energy and accompanying emissions, in order to cost-effectively meet future ZEB standards in Croatia and offset the remaining operational emissions, photovoltaic systems of up to 2.5 kWp are required in continental areas and 1.6 kWp in coastal regions. Full article

This study investigates the environmental and economic dynamics of sustainable aviation through the perspectives of senior executives in Türkiye’s civil aviation sector. As global aviation continues to face increasing pressure to decarbonize, understanding how industry leaders perceive and respond to carbon emission challenges is critical. The research employs a qualitative methodology based on semi-structured interviews with ten executives across airlines, airports, and aviation authorities. Using Python-based data mining techniques and thematic analysis, three core themes emerged: (1) sustainable aviation experience and economic dimensions; (2) carbon emissions reduction and efficient aviation systems; (3) sustainable energy and alternative fuel technologies. Findings reveal that while environmental sustainability is a growing concern, operational costs, technological constraints, and regulatory uncertainties significantly influence implementation. Stakeholders emphasized the importance of coordinated action among governments, industry, and international organizations, especially in scaling Sustainable Aviation Fuels (SAFs) and enhancing infrastructure for electric and hydrogen-powered aircraft. The study concludes that achieving net-zero aviation by 2050 requires an integrated approach that balances technological innovation, policy incentives, and stakeholder engagement. This multidimensional insight contributes to the ongoing discourse on low-carbon transition strategies in aviation, offering policy-relevant implications for developing countries. Full article

Biomass gasification, as a thermochemical process, has attracted growing interest due to the increasing popularity of biofuel production based on syngas or pure hydrogen. Moreover, when integrated with CO₂ capture, this method of producing gaseous fuels can achieve negative CO₂ emissions, making it competitive with other production systems based on either fossil or renewable sources. This paper presents the results of a process and economic analysis of synthetic natural gas (SNG) production systems integrated with a commercial fluidized-bed gasification reactor based on Synthesis Energy Systems (SES) technology. The study examines the potential integration of the system with a water electrolyzer at two levels of coupling: one providing oxygen for the gasification process, and the other eliminating the need for CO₂ separation before the SNG synthesis stage. Using a single gasification unit with a raw biomass feed rate of 60 t/h, the system produces 188 t/d of SNG. Integration with a water electrolyzer increases SNG production to 259 and 621 t/d. For cases without electrolyzer integration and under the assumption of zero emissions from biomass processing, the application of CO₂ separation enables the achievement of negative CO₂ emissions. This creates an opportunity for additional revenue from the sale of CO₂ emission allowances, which can significantly reduce SNG production costs. In this analysis, the break-even CO₂ price, above which the SNG production cost becomes negative, is USD 251/t CO₂. In systems integrated with water electrolysis, the cost and carbon footprint of the electricity consumed in the electrochemical water-splitting process have a decisive impact on both the overall SNG production cost and its carbon intensity. Full article