• Introducing a novel feature value substitution methodology to simulate potential energy consumption savings for specific retrofit options. • Quantifying energy-savings on large-scale real-world data and solving data scarcity issues by introducing a feature value substitution methodology. • Providing a retrofit index to the research community that combines energy savings, carbon emission reduction, retrofit costs, and local subsidies into a comprehensible measurand. • Mitigating the uncertainty of homeowners and energy auditors in the decision-making process to identify the most suitable retrofit option for individual residential buildings. • Scenario analysis for different retrofit budgets and energy prices to identify the retrofit measure with the highest energy saving potential. The global building sector is one of the main contributors to annual global greenhouse gas emissions, yet homeowners remain hesitant regarding specific retrofit measures to reduce carbon emissions. This is unsurprising as the link between retrofits that reduce energy consumption and corresponding economic and ecological benefits remains elusive. Therefore, this study addresses the intersection of building energy performance, carbon emission reduction, and financial subsidies by quantifying expected energy savings based on specific energy-related retrofits with a real-world dataset containing 25,000 German residential buildings. The simulated energy savings for specific retrofit measures are based on a novel feature value substitution methodology and three sophisticated machine learning models, namely XGBoost, CatBoost, and LightGBM. This study then combines potential ecological gains, household investment budgets, and expected local governmental subsidies into a single informative yet comprehensible retrofit index to overcome the uncertainty regarding retrofits. The results show that glazing is the most impactful feature for potential energy savings of residential buildings, followed by heating system changes from oil to electric heating pumps. In contrast to the neglectable impact of better facade conditions on building energy performance, roof and wall insulation improvements lead to significantly lower energy consumption. This study underscores potential ecological savings of targeted retrofit measures and enables practitioners to cut expenses and reduce the associated financial risks.

Performance and feasibility of integrated microgrid and microalgae hybrid systems for net-zero energy solutions

Intelligent Arctic shipping route planning with dual objectives of economy and carbon emission reduction using deep reinforcement learning

Two-stage optimization for collaborative operations of an integrated energy system maximizing recovery efficiency of waste heat

• A combined premixing-direct injection strategy enhances methanol-hydrogen combustion. • Direct hydrogen injection reduces backfiring and forms controllable stratified mixtures. • Hydrogen blending (12%) increases peak cylinder pressure by 22.1%. The overuse of fossil fuels has intensified environmental challenges, highlighting the need for low-carbon alternatives in transportation. Methanol, a promising low-carbon fuel, is limited by its high latent heat of vaporization and low calorific value, while hydrogen offers high energy density and wide flammability limits, making it an effective combustion enhancer. This study adopts a methanol-air intake premixing combined with in-cylinder hydrogen direct injection strategy to mitigate backfire and enable stratified mixture formation. CFD simulations were conducted to investigate the effects of hydrogen energy ratios (3%–12%) and injection timings (140°CA, 180°CA, and 240°CA BTDC) on engine performance and emissions. Results show that optimizing injection timing reduces pressure loss by approximately 13% at 12% hydrogen ratio, and co-optimizing injection and ignition timing boosts combustion efficiency to over 90%. In terms of emissions, increasing hydrogen from 3% to 12% reduces CO by 23.08% and CO 2 by 8.43%, although NO X emissions rise from 0.7 × 10 − ⁶ kg to 1.1 × 10 − ⁶ kg under 12% hydrogen with 140°CA BTDC injection. Hydrogen supplementation effectively improves combustion efficiency and reduces carbon emissions, offering a viable pathway toward cleaner and more efficient low-carbon engines.

Synergizing renewable energy, women empowerment, and policy for emissions reduction

It is critical to the sustainable development of agricultural production that balances between increased grain yield with economic returns and carbon emissions in intensive oasis irrigation agroecosystems. Crop rotation and nitrogen management have been shown to have great potential in enhancing soil carbon sequestration and reducing carbon emissions. However, the comprehensive assessment of different planting systems in terms of crop productivity, economic benefits, soil carbon sequestration and greenhouse gas emissions remains unclear. A continuous field experiment was conducted since 2018 in the Hexi Oasis irrigation area, and data were collected from 2022 to 2025. Four planting patterns (W: spring wheat continuous cropping; WV: spring wheat-common vetch; WWV: spring wheat-winter wheat-common vetch; WRV: spring wheat-winter rapeseed-common vetch) and three nitrogen rates (N2: local conventional nitrogen amount, 360 kg ha −1 ; N1: 270 kg ha −1 , nitrogen amount reduced by 25%; N0: no nitrogen application, 0 kg ha −1 ) were set up as experiment treatments. The results showed that rotation significantly increased equivalent yield compared to continuous cropping. The cropping systems followed a decreasing yield order: WRV> WWV> WV. Compared to the spring wheat continuous cropping with local conventional nitrogen amount (WN2), the wheat-winter rapeseed-common vetch rotation combined with a 25% nitrogen reduction (WRVN1) significantly increased the equivalent yield by 10.7%. Furthermore, WRVN1 increased the soil organic carbon content by 3.9%, organic carbon stock, and carbon management index compared to WN2. In addition, crop rotation reduced carbon emissions (excluding WV), while the carbon emission efficiency of WV pattern was higher than W pattern. The carbon emission efficiency of WRVN1 was 24.2% higher than WN2 and had no significant difference with WRVN2. Furthermore, crop rotation increased net income (excluding WV). And net income of WRVN1 increased by 29.7% compared to WN2. Incorporating winter crops with leguminous green manure and moderate nitrogen reduction can achieve a trade-off between agronomic performance, economic benefits and ecological development in oasis irrigation districts. Our case provides pathways for N management and sustainable production practices in oasis irrigation agroecosystems. ● Diversifying continuous wheat with winter rapeseed and vetch increased system yield and farm net income in the Hexi Oasis. ● Winter crop–legume rotations with 25% less N maintained or increased wheat-equivalent yield while reducing soil CO₂ emissions. ● A spring wheat–winter rapeseed–vetch rotation with less N optimized trade-offs among yield, profit, and carbon sequestration.

Intelligent optimization of steam-curing for precast concrete tunnel lining: Insight from sample data parameters analysis and interpretable machine learning

Progress and performance in synergizing the reduction of pollution and carbon emissions in China from 2015 to 2022

Dynamics and environmental thresholds of ecosystem respiration across the conterminous United States: Insights from AmeriFlux and remote sensing data

Collaborative optimization of integrated energy systems in energy-intensive industrial clusters considering carbon-green-certificate trading

• High initial investment influences solar energy (SE) integration the most. • Cost of storage solution has the second most significant impacts on SE integration. • Incentives and subsidies have the third most significant impacts. • Uncertain return on investment has the fourth most significant impact. • Existing grid capacity has the lowest impact on SE integration. Renewable energy production is crucial for transitioning to a low-carbon economy, as there is a global push for sustainable energy sources. Integrating renewable energy, such as solar, presents economic challenges, including obtaining high efficiency and cost-effectiveness on a large scale. Solar energy (SE) is becoming a key component of national energy strategies to decrease CO 2 emissions and address rising energy demand and climate change. This article analyses the economic problems of integrating solar energy for sustainable development, including cost-effectiveness, efficiency, reliability, resilience and minimising transmission losses to reduce carbon emissions in the Global South. This research adopts an in-depth methodology, mostly literatures from 2018 to 2025, to analyse these economic challenges and their impacts on solar energy integration, plus a survey as a primary data source. 71 (67.6%) stakeholders agreed that high initial investment influence SE integration to a very large extent, 55 (52.4%) stakeholders agreed that cost of storage solutions affect SE integration to a very large extent, while 27 (25.7%) stakeholders believed that incentives and subsidies influence SE integration to a very large extent. The study shows that policies must prioritise constant investment in solar energy, giving incentives and subsidies and lowering the initial investment to encourage solar energy investments, integration, installations, reliability and sustainability. Recommendations are made to mitigate these challenges in SE integration in terms of initial investments, storage solutions costs, grid capacities, return on investment, transmission losses and incentives and subsidies to ensure solar energy reliability, affordability, efficiency, resilience and sustainability.

From coal to code: The transformative role of fintech and renewable energy in China's low-carbon transition

The global construction sector seeks to use sustainable materials to reduce its environmental footprint. In this direction, steel manufacturing by-products like electric arc furnace slag (EAFS), basic oxygen furnace slag (BOFS), and induction furnace slag (IFS) present a viable alternative to natural aggregates, offering environmental and cost benefits. These slags are underutilized resources with transformative potential for concrete and other applications, potentially reducing carbon emissions by up to 60 kg CO2 per metric ton of concrete. This review article critically examines the properties, applications, and challenges associated with steel slag coarse aggregates (SSCA) in concrete, highlighting key characteristics through ternary plots and whisker diagrams, which depict each slag’s variability, median values, and outlier ranges, making it an invaluable repository for researchers. The compositional analysis through these visualization tools demonstrates that BOFS is CaO-rich, EAFS has a balanced CaO-SiO2-FeO composition, whereas IFS is FeO-dominant. This study also clearly depicts different slag replacement ratios with optimal dosage varying from 50% to 75%, enhancing compressive strength by 10–20%, chloride and sulphate resistance by 30%, and fire resistance up to 1,200°C. The performance of steel slag-based concrete with more than 75% replacement level showed higher porosity and poor interlocking. Challenges like volumetric instability due to free CaO/MgO and workability loss can be mitigated through pretreatment and adding supplementary cementitious materials (SCMs), making a viable alternative to conventional concrete. The environmental benefits are substantial, as life cycle assessment (LCA) studies reveal that steel slag concrete has a 30%–40% lower environmental impact than conventional concrete, demonstrating its potential for reducing the construction industry’s carbon footprint. Looking toward future developments, nanoengineered SSCA composites present even better prospects for enhanced performance and sustainability. Combined with the proven environmental advantages, these advanced applications position steel slag utilization as a key strategy for achieving sustainable development goals (SDGs) 9, 11, and 12, driving toward circularity and sustainable concrete innovation.

In the original publication [...]

Air-to-air heat pumps are a key technology for improving energy efficiency and reducing carbon emissions in residential buildings, yet their optimal control remains challenging under real-world conditions. This study evaluates the performance of a hybrid physical–LSTM model for controlling an air-to-air heat pump in a residential building in Zadar, Croatia. The hybrid framework integrates a first-order energy balance model of the building envelope with LSTM-based temperature correction using adaptive weighting. The physical model was calibrated and validated against 52,128 real IoT measurements collected during the 2024/2025 heating season, achieving high accuracy (RMSE ≈ 0.076 °C). Rolling one-day and continuous multi-day closed-loop simulations (up to 15 days) show that the hybrid model yields slightly lower RMSE in long-term runs compared to the pure physical model. However, this apparent statistical improvement is accompanied by systematic underestimation of indoor temperature and significantly higher simulated energy consumption. The results indicate that the observed effect originates from an implicit virtual heat flux introduced by the LSTM correction, which affects thermodynamic consistency in closed-loop operation. The findings highlight that short-term error metrics such as RMSE alone are insufficient for evaluating hybrid models intended for model predictive control (MPC). The main contribution of this study is the explicit demonstration and quantification of an implicit virtual heat flux generated by the LSTM correction in closed-loop multi-day operation, which leads to misleading statistical improvements while causing significant thermodynamic inconsistency and energy overconsumption. In 15-day continuous simulations the hybrid model (ω = 0.05–0.10) caused an indoor temperature underestimation of 1.25–1.31 °C and increased simulated electricity consumption by more than 300% (316 kWh vs. 72 kWh) compared to the physical model. These results have direct implications for the development of reliable digital twins and model predictive control strategies in residential HVAC systems.

To reveal the regional differentiation characteristics of carbon emissions during the construction phase of expressways and to improve prediction accuracy, six typical expressway projects located in the plain, hilly, and mountainous regions of Anhui Province were selected as case studies. A carbon emission accounting model for the construction phase was established based on the life cycle assessment method, and the effects of the bridge-tunnel ratio, subproject structure, and material and energy consumption on carbon emission intensity were systematically analyzed. On this basis, a regional carbon emission prediction model was developed and optimized using data from 21 completed expressways across the province. The results indicate that carbon emission intensity exhibits a significant topographic gradient, with mountainous regions showing higher values than hilly regions, and hilly regions higher than plain regions. The maximum carbon emission intensity in mountainous projects reaches 5.27 × 10⁷ kg CO₂/km, which is 2.86 times that of plain regions. As terrain complexity increases, the carbon emission structure shifts from being dominated by subgrade engineering and interchange engineering to being dominated by structural engineering, such as bridges and tunnels. In mountainous regions, emissions from structural engineering account for more than 50% of the total emissions. At the material level, cement and steel are identified as the primary emission sources, jointly accounting for 78% of total emissions in mountainous projects, and demonstrating the highest sensitivity to variations in total emissions. The prediction results show that the baseline model using the bridge-tunnel ratio as a single variable achieves a coefficient of determination (R²) of 0.69. After incorporating material and energy consumption variables, the optimized XGBoost model improves the coefficient of determination to 0.9517, achieving high-accuracy prediction using only eight categories of material and energy consumption indicators. Based on the analytical results, differentiated emission reduction pathways are proposed. In mountainous regions, priority should be given to optimizing the design of tunnels and interchange engineering and controlling the intensity of high-carbon structural materials. In plain and hilly regions, emphasis should be placed on low-carbon design and construction optimization of bridge and culvert engineering and subgrade engineering. This study provides a data-driven basis for regional carbon emission prediction and emission reduction decision-making during the construction phase of expressways.

Financial subsidies provided by the government have been validated as an effective means to stimulate carbon emission reductions among manufacturers. This paper examines the impact of two types of financial subsidies-namely, one-off subsidies and quantity-based price subsidies-on the bank’s optimal interest rate, the manufacturer’s optimal emission reduction level and wholesale price, and the retailer’s optimal retail price. The benefits of these two subsidy policies are compared from both economic and environmental perspectives. Our findings reveal the following insights: Both subsidy policies effectively enhance market demand and improve the economic performance of the green supply chain. However, when subsidies are below certain thresholds, total carbon emissions increase, leading to reduced environmental benefits. Under a fixed subsidy amount, one-off subsidies result in less environmental harm compared to quantity-based price subsidies. Conversely, at a given level of carbon reduction, quantity-based price subsidies yield higher economic benefits due to greater government expenditure, albeit with lower environmental benefits. These results provide valuable guidance for policymakers: quantity-based price subsidies are preferable when prioritizing economic benefits, whereas one-off subsidies are more suitable for enhancing environmental outcomes.

Purpose In e-commerce, eco-conscious consumers' focus on fresh produce has shifted from singular quality/safety to a composite dimension of quality, low-carbon and environmental attributes. This elevates information screening difficulty and disclosure management complexity, with blockchain technology (BT) offering a breakthrough for such issues. Design/methodology/approach We model a two-echelon supply chain (supplier-platform) under decentralized/integrated decision frameworks, constructing profit models with/without BT-based disclosure to derive optimal pricing, commission, carbon reduction and BT investment strategies. Findings Under any power structure, information disclosure motivation is jointly determined by information credibility and disclosure level: Full disclosure enhances the profit advantage of integrated decision-making while driving up prices; partial disclosure weakens this advantage and reduces carbon emission reduction sensitivity; BT's unit data maintenance cost solely influences the disclosure motivation's direction in integrated decision-making; platforms exhibit stronger disclosure willingness than suppliers when the pre- and post-disclosure trust gap is significant; and under specific conditions, BT-based integration outperforms decentralized decision-making in economic and environmental performance. Originality/value This study explores how BT-enabled multi-information disclosure affects fresh e-commerce optimization and management, advances BT's expanded application in e-commerce supply chains and provides theoretical guidance for balancing economic and environmental performance in sustainable fresh e-commerce by adjusting strategic information disclosure in complex scenarios.

Purpose This paper aims to investigate the impact of several governance mechanisms, including board meetings, board independence, board gender diversity, chief executive officer (CEO) duality, sustainability committees and environmental, social and governance (ESG)-based compensation, on corporate carbon emission performance. Design/methodology/approach This study draws a sample of 414 companies listed in the STOXX Europe 600 index, spanning the period from 2017 to 2023. The main findings were derived using the feasible generalized least squares method. Additionally, a generalized method of moments analysis was conducted to assess the robustness of these results. Findings The results show that board meetings, board gender diversity and CEO duality are associated with better carbon performance (i.e. reducing carbon emissions). However, board independence, sustainability committee and ESG-linked compensation were found to increase carbon emissions levels, contrary to expectations. Originality/value Thus, this study first provides new empirical evidence on the relationship between corporate governance mechanisms and carbon performance in the European Union market. Second, it provides useful insights for regulators, investors and corporate executives.