Search Results (951)

This study is situated at the critical stage of comprehensive implementation of China’s territorial spatial planning system, addressing the strategic need for planning evaluation and optimization. We innovatively construct a Computable General Equilibrium Model for China’s Territorial Spatial Planning (CTSPM-CHN) that integrates dual factors of construction land costs and energy consumption costs. Through designing two policy scenarios of rigid constraints and structural optimization, we systematically simulate and evaluate the dynamic impacts of different territorial spatial governance strategies on macroeconomic indicators, residents’ welfare, and carbon emissions, revealing the multidimensional effects and operational mechanisms of territorial spatial planning policies. The findings demonstrate the following: First, strict implementation of land use scale control from the National Territorial Planning Outline (2016–2030) could reduce carbon emission growth rate by 12.3% but would decrease annual GDP growth rate by 0.8%, reflecting the trade-off between environmental benefits and economic growth. Second, industrial land structure optimization generates significant synergistic effects, with simulation results showing that by 2035, total GDP under this scenario would increase by 4.8% compared to the rigid constraint scenario, while carbon emission intensity per unit GDP would decrease by 18.6%, confirming the crucial role of structural optimization in promoting high-quality development. Third, manufacturing land adjustment exhibits policy thresholds: moderate reduction could lower carbon emission peak by 9.5% without affecting economic stability, but excessive cuts would lead to a 2.3 percentage point decline in industrial added value. Based on systematic multi-scenario analysis, this study proposes optimized pathways for territorial spatial governance: the planning system should transition from scale control to a structural optimization paradigm, establishing a flexible governance mechanism incorporating anticipatory constraint indicators; simultaneously advance efficiency improvement in key sector land allocation and energy structure decarbonization, constructing a coordinated “space–energy” governance framework. These findings provide quantitative decision-making support for improving territorial spatial governance systems and advancing ecological civilization construction. Full article

The waste heat generated by high-performance computing (HPC) represents an opportunity for advancing the decarbonization of energy systems. Seasonal storage is necessary to regulate the balance between waste heat production and demand. High-temperature aquifer thermal energy storage (HT-ATES) is a particularly well-suited technology for this purpose due to its large storage capacity. However, integrating HT-ATES into energy systems for district heating is complex, affecting existing components. Therefore, this study applies a bi-objective mixed-integer quadratically constrained programming (MIQCP) approach to optimize the energy system at Forschungszentrum Jülich (FZJ) regarding total annualized costs (TAC) and global warming impact (GWI). The exascale computer Jupiter, which is hosted at FZJ, generates a substantial amount of renewable waste heat that is suitable for integration into district heating networks and seasonal storage. Case studies show that HT-ATES integration into the investigated system can reduce GWI by 20% and increase TAC by 1% compared to the reference case. Despite increased TAC from investments and heat pump (HP) operation, summer charging of the HT-ATES remains flexible and cost-effective. An idealized future scenario indicates that HT-ATES with a storage capacity of 16,990 MWh and HPs could cover most of the heating demand, reducing GWI by up to 91% while TAC increases by 6% relative to the reference system. Full article

Climate change and increasing greenhouse gas emissions are driving the global transition to clean energy, with solar energy experiencing the fastest growth among renewable sources in 2024. Solar PV for energy generation in Kenya is gaining momentum as the country moves towards achieving 100% clean energy by 2030. As solar PV penetration in the grid grows, it is necessary to evaluate its impact on system costs to inform policy decisions on capacity expansion options in the Least-Cost Power Development Plan (LCPDP). This study investigates the effect of large-scale solar PV expansion on electricity costs using the Open-Source Energy Modelling System (OSeMOSYS), a modular, bottom-up capacity expansion model. Four scenarios were developed to assess different levels of solar PV penetration: business-as-usual (BAU), moderate-solar-PV expansion (MSPV), high-solar-PV expansion (HSPV), and very-high-solar-PV expansion (VHSPV). The results indicate that, while overall solar PV expansion significantly contributes to decarbonising Kenya’s electricity mix by displacing fossil-based generation, it also increases annual investment obligations and, consequently, total system costs. The system-levelised cost of electricity (LCOE) is shown to rise by 0.2%, 5.7%, and 14.0% under MSPV, HSPV, and VHSPV, respectively, compared to BAU. Analysing the various cost components against sustainability indicators reveals that the least-cost scenario is BAU while the most favourable scenario based on sustainability indicators is VHSPV, which performs best across technical, environmental, and institutional dimensions but less favourably on economic and social aspects, thereby highlighting a trade-off between sustainability and cost minimisation, at least in the short term. Full article

Establishing a mechanism for ecological product value realizing (EPVR) is a critical component of China’s ecological civilization strategy, aimed at translating the concept that “lucid waters and lush mountains are invaluable assets” into actionable economic policies. Although central government investments in the form of project for EPVR have increased significantly, surpassing CNY 700 billion by 2024, studies rarely focus on these projects and how to evaluate them. Evaluating the performance of EPVR projects is essential for optimizing resource allocation, enhancing project accountability, and ensuring the sustainable realization of ecological, economic, and social values. This study innovatively defines the conceptual connotation of EPVR projects and constructs a comprehensive performance evaluation system based on a “benefit-cost” analysis, comprising a multi-dimensional indicator system, quantifiable calculation methods, and explicit evaluation criteria. As water source protection projects are typical EPVR projects, the comprehensive water environment management project of Hongfeng Lake is selected for an in-depth empirical study. The results reveal that (1) the total annual benefits amount to CNY 923.66 million, dominated by ecological benefits (84.04%); (2) with an investment of CNY 1194.66 million, the project yields a net loss and a moderate performance index (PCPI = 0.77); (3) the project performance is primarily affected by weak economic value conversion stemming from restrictive zoning policies and underdeveloped market mechanisms for ecological services; and (4) integrated development pathways—such as ecotourism, eco-aquaculture, and ecological branding—are proposed to enhance the long-term sustainability of the project. The Hongfeng Lake case establishes a replicable framework for global assessment of analogous projects and delivers actionable insights for enhancing benefit–cost ratios in public ecological initiatives, with costs confined to data collection, modeling, and validation. Therefore, this study contributes a quantifiable and reproducible tool for the full lifecycle management of EPVR projects, thereby facilitating more informed government decision-making. Key findings reveal the following: (1) A comprehensive “Benefit-Cost” performance evaluation framework, pioneered in this study and tailored specifically for individual EPVR projects, surpasses regional-scale accounting methodologies like Gross Ecosystem Product (GEP). (2) A novel consolidated metric (PCPI) is introduced to integrate ecological, economic, and social dimensions with cost input, thus enabling direct cross-project comparison and classification. (3) The framework operationalizes evaluation by providing a detailed, adaptable indicator system with explicit monetization methods for 26 distinct benefits, thereby bridging the gap between theoretical value accounting and practical project assessment. (4) The empirical application to a drinking water source protection project addresses a critical yet understudied category of EPVR projects, offering insights into “protection-oriented” models. Full article

In order to study the impacts of the carbon-green certificate trading mechanism and the fluctuation of feed-in tariffs on the low-carbon and economic aspects of the investment and operation of the integrated energy system, and to transform the system carbon emission into a low-carbon economic indicator, a two-layer capacity optimization allocation model is established with the objectives of the investment, operation, and maintenance cost and the operation cost, respectively. For the source-load uncertainty, the scenario reduction theory based on Monte Carlo simulation and Wasserstein distance is used to obtain the per-unit value of wind and photovoltaic output, and the K-means clustering method is used to obtain the typical day of electric-heat-cold multi-energy load. Based on the geometric Brownian motion in finance to simulate the feed-in tariffs under different volatilities, the multidimensional analysis scenarios are constructed according to different combinations of carbon emission reduction policies and tariff volatilities. The model is solved using the non-dominated sorting genetic algorithm (NSGA-II) with mixed integer linear programming (MILP) method. Case study results show that under the optimal scenario considering policy interaction and price volatility (δ = 1.0), the total annual operating cost is reduced by approximately 17.9% (from 2.80 million CNY to 2.30 million CNY) compared to the baseline with no carbon policy. The levelized cost of the energy system reaches 0.2042 CNY/kWh, and carbon-green certificate trading synergies contribute about 70% of the operational cost reduction. The findings demonstrate that carbon reduction policies and electricity price volatility significantly affect system configuration and operational economy, providing a new perspective and decision-making basis for integrated energy system planning. Full article

Evaluating the effect of recycling Pesticide Packaging Waste (PPW) is essential for improving recycling rates, which plays a crucial role in controlling environmental pollution and optimizing the efficiency of agricultural resources worldwide. Based on the micro-survey data of 1223 farmers in Yunnan and Hainan provinces of China, this study measures the economic effect by the farmers’ annual total household income and the ecological effect by the ecological environment quality of villages. The propensity score matching method (PSM) is employed to empirically test the economic and ecological effects of farmers’ recycling behavior of PPW and their differences. The research findings are as follows: Farmers’ recycling of PPW can generate significant positive economic and ecological effects, which are 116.7% and 4%, respectively. The heterogeneity analysis shows that farmers with a low degree of land fragmentation have a more obvious economic effect from PPW recycling, while farmers with a higher degree of land fragmentation have a more significant ecological effect; farmers with high pesticide costs have more significant economic and ecological effects from PPW recycling. Based on these findings, it is suggested to increase the attention at the policy level, enhance farmers’ environmental awareness and capacity, and focus on the characteristics of different groups. Full article

Power generation and transmission systems face increasing challenges in coordinating maintenance planning under economic pressure and carbon emission constraints. This study proposes an optimization framework that integrates preventive maintenance scheduling with operational dispatch decisions, aiming to achieve both cost efficiency and emission reduction. A bi-layer scenario-based mixed-integer optimization model is formulated, where the upper layer determines annual preventive maintenance windows, and the lower layer performs hourly economic dispatch considering renewable generation and demand uncertainty. To manage the exposure to extreme carbon outcomes, a Conditional Value-at-Risk (CVaR) constraint is embedded, jointly controlling economic and environmental risks. A parallel cut-generation decomposition algorithm is developed to ensure computational scalability for large-scale systems. Numerical experiments on six-bus and IEEE 118-bus systems demonstrate that the proposed model reduces total carbon emissions by up to 32.1%, while maintaining cost efficiency and system reliability. The scenario analyses further show that adjusting maintenance schedules according to seasonal carbon intensity effectively balances operation and emission targets. The results confirm that the proposed optimization framework provides a practical and scalable approach for achieving low-carbon, reliable, and economically efficient power system maintenance planning. Full article

Frequent extreme-weather events pose severe challenges to the secure and economical operation of power systems with high renewable energy penetration. To strengthen grid resilience against such low-probability, high-impact events while maintaining good performance under normal conditions, this paper proposes an optimal energy storage allocation method for power systems with high-wind-power penetration. We first identify two representative extreme wind power events and develop a risk assessment model that jointly quantifies load-shedding volume and transmission-line security margins. On this basis, a multi-scenario joint siting-and-sizing optimization model is formulated over typical-day and extreme-day scenarios to minimize total system cost, including annualized investment cost, operating cost, and risk cost. To solve the model efficiently, a two-stage hierarchical solution strategy is designed: the first stage determines an investment upper bound from typical-day scenarios, and the second stage optimizes storage allocation under superimposed extreme-day scenarios within this bound, thereby balancing operating economy and extreme-weather resilience. Simulation results show that the proposed method reduces loss-of-load under extreme-weather scenarios by 32.46% while increasing storage investment cost by only 0.18%, significantly enhancing system resilience and transmission-line security margins at a moderate additional cost. Full article

To address the challenge of the synergistic optimization of carbon reduction and economic operation in the integrated energy systems (IES) of industrial parks, this paper proposes an optimization scheduling model that incorporates carbon trading and supply–demand response (SDR) coordination mechanisms. This model is based on an IES coupling power-to-gas (P2G) and carbon capture and storage (CCS) technologies. First, the K-means clustering algorithm identifies three typical daily scenarios—transitional season, summer, and winter—from annual operation data. Then, we construct a synergistic optimization model that integrates a carbon trading mechanism, tiered carbon quota allocation, and SDR coordination. The model is solved via mixed-integer linear programming (MILP) to minimize total system operating costs. Systematic comparative analysis across six scenarios quantifies the incremental benefits: P2G–CCS coupling achieves a 15.2% cost reduction and 49.3% emission reduction during transitional seasons; supply–demand response contributes 3.5% cost and 5.6% emission reductions; technology synergies yield an additional 21.6 percentage points of emission reduction beyond individual contributions. The integrated system achieves 100% renewable energy utilization and optimizes peak-to-valley differences across electricity, heating, and cooling loads. Carbon price sensitivity analysis reveals three response stages—low sensitivity, rapid reduction, and saturation—with the saturation point at 200 CNY/t (28.6 USD/t), providing quantitative guidance for tiered carbon pricing design. This research provides theoretical support and practical guidance for achieving low-carbon economic operations in industrial parks. Full article

Industrial effluents often contain azeotropic mixtures that are difficult to separate by conventional distillation. An illustrative case is the methanol/methyl acetate/ethyl acetate (MA/ME/EA) mixture. To address these challenges, this work studies the conceptual design and optimization of the reactive distillation-based hybrid processes for separating the MA/ME/EA mixture with an EA-rich feed composition (0.25/0.20/0.55 mol fraction). An improved triple-column extractive–reactive distillation with a side-draw product (TCERD-SP) and its heat-integrated variant (TCERD-SP-HI) have been developed. In the TCERD-SP process, EA is strategically withdrawn as a side product, reconfiguring the extractive column into integrated pre-separation and entrainer-recovery sections, thereby reducing entrainer and energy demands. A four-step process design methodology is applied, including thermodynamics analysis, conceptual design, rigorous optimization via Aspen Plus integrated with the genetic algorithm to minimize total annual cost (TAC), and comparative evaluation of economic and environmental performance. The results show that the basic double-column pre-separation-reactive distillation (DCPSRD) process, optimal for a previous feed composition, exhibits unsatisfactory TAC performance for this EA-rich feed composition. Among the configurations studied, the TCERD-SP process exhibits superior performance, saving TAC by 8.4% and 14.4% compared to the TCERD and DCPSRD processes, respectively. In addition, based on the advantage of convenient heat integration between the side reboiler and the reactive distillation column condenser, the heat-integrated TCERD-SP-HI process achieves a further 10.7% TAC reduction. Thus, for this EA-rich feed examined in this work, the TCERD-SP and TCERD-SP-HI processes are demonstrated as effective solutions for recovering these valuable chemicals. Full article

This study presents an integrated ex-post evaluation of a municipal window-retrofit program in Goyang, Republic of Korea (heating-dominated, Dwa). Using field surveys and pre- and post-utility bills for 36 dwellings, mainly pre-2000 low-rise reinforced-concrete buildings, we normalize climate with HDD and CDD and prices with CPI-deflated tariffs to isolate the intrinsic effect of window replacement. Area-normalized indicators ($∆e$, $\eta$, DPB, NPV, AC) were computed. Average annual savings were 30.2 kWh per m² per year ($\eta$ ≈ 16 percent), consisting of 10.6 kWh per m² per year of gas and 19.6 kWh per m² per year of electricity (n = 36). The median discounted payback was 7.0 years. Under a 50 percent subsidy, about 80 percent of projects recovered private investment within 15 years and showed positive NPV with a median of about USD 4944. The electricity-tariff multiplier had the largest influence on cash flows and payback. The median abatement cost was about USD 352 per tCO₂-eq. A portfolio view indicates that prioritizing low-cost cases maximizes total abatement, and that higher-cost cases merit design or cost review. Using the first post-retrofit year 2023, portfolio abatement is about 623 tCO₂-eq per year. The framework jointly normalizes climate and price effects and yields policy-relevant estimates for heating-dominated contexts. Full article

In arid regions, rainfall is scarce, summer-concentrated, and prone to extreme events, while evaporation exceeds precipitation, creating fragile ecosystems that need scientific stormwater management for flood resilience. Sponge cities, through the implementation of green infrastructure, can alleviate urban flooding, improve rainwater utilization, and enhance the urban ecological environment. Under the “dual carbon” target, sponge city construction has gained new developmental significance. It must not only ensure core functions and minimize construction costs but also fully leverage its carbon reduction potential, thereby serving as a crucial pathway for promoting urban green and low-carbon development. Therefore, this study focused on Xining, a typical arid city in Northwest China, and couples the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) with the Storm Water Management Model (SWMM) to construct a multi-objective optimization model for Low Impact Development (LID) facilities. The layout optimization design of LID facilities is conducted from three dimensions: life cycle cost (LCC), rainwater utilization rate (K), and carbon emission intensity (CI). Hydrological simulations and scheme optimizations were performed under different design rainfall events. Subsequently, the entropy-weighted TOPSIS method was utilized to evaluate and compare these optimized schemes. It is shown by the results that: (1) The optimized LID schemes achieved a K of 76.2–80.43%, an LCC of 2.413–3.019 billion yuan, and a CI of −2.8 to 0.19 kg/m²; (2) Compared with the no-LID scenario, the optimized scheme significantly enhanced hydrological regulation, flood mitigation, and pollutant removal. Under different rainfall return periods, the annual runoff control rate increased from 64.97% to 80.66–82.23%, with total runoff reduction rates reaching 46.41–49.26% and peak flow reductions of 45–47.62%. Under the rainfall event with a 10-year return period, the total number of waterlogging nodes decreased from 108 to 82, and the number of nodes with a ponding duration exceeding 1 h was reduced by 62.5%. The removal efficiency of total suspended solids (TSS) under the optimized scheme remained stable above 60%. The optimized scheme is highly adaptable to the rainwater management needs of arid areas by prioritizing “infiltration and retention”. Vegetative swales emerge as the primary facility due to their low cost and high carbon sink capacity. This study provides a feasible pathway and decision-making support for the low-carbon layout of LID facilities in arid regions. Full article

Background: Burns result in approximately 180,000 deaths annually, with the majority occurring in rural regions of Africa and Southeast Asia. This study aimed to assess the available resources, key challenges, and potential solutions in burn care from the perspective of healthcare providers in India. Methods: An online survey was conducted among burn care professionals across India. The survey was disseminated via social media platforms, burn care networks, and hospital representatives. Results: A total of 105 respondents, primarily from tertiary care centers, participated in the survey. Of these, 64.2% were affiliated with government hospitals, and 40.1% served catchment areas extending beyond 300 km. Dedicated burn units were present in 88.0% of government hospitals, compared to 66.9% in non-government facilities. Treatment costs were significantly lower in government hospitals, with 88.8% offering care either free of charge or at minimal cost (p ≤ 0.00001). Conclusions: The findings reveal significant gaps in staff training, intensive care monitoring, and infection prevention. Many patients initially seek help from traditional healers, often delaying appropriate treatment and worsening outcomes. Enhancing education, implementing standard monitoring practices, and ensuring adherence to clinical protocols are critical steps toward improving burn care outcomes in India. Full article

Thermal insulation is essential in lowering the energy consumption of buildings. However, many fossil-based insulation and exterior cladding materials are derived from petrochemical components, which often have adverse ecological impacts. This study explores the effectiveness of integrating sustainable thermal insulation solutions into building design to reduce energy consumption and minimize ecological impact. Focusing on an energy-efficient breakfast house located in Van, Turkey, the project was modeled using Autodesk-Revit software (2023). A comprehensive analysis was conducted by generating eighty alternative scenarios, combining two distinct wall structures, eight fiber-based natural insulation materials, and five wood-based exterior cladding materials. The energy performance of each scenario was evaluated using IES-VE software (2024.1), focusing on annual total energy consumption and CO₂ emissions, while accounting for regional climatic conditions and targeted indoor comfort levels. To further refine the selection of optimal materials, a hybrid evaluation was performed using multi-attribute decision approaches, including LODECI, MAXC, and DEPART. These methods provided a systematic framework for comparing the performance of wood-based insulation materials across multiple criteria. In order to verify the accuracy of the proposed multi-attribute decision models, a comparative analysis has been undertaken with other multi-attribute decision methods (COPRAS, ARAS and WASPAS). The study highlights the technical feasibility of incorporating cost-effective, eco-friendly fiber-based and wood-based materials into building envelopes, demonstrating their potential to significantly enhance energy efficiency and reduce environmental impact. By combining advanced simulation tools with robust decision-making methodologies, this research offers a scientifically grounded approach to sustainable architectural design, providing important outputs for future applications in energy-efficient construction. Full article

This study presents an integrated framework for lifecycle assessment (LCA) and lifecycle costing (LCC) of buildings and districts that combines machine learning-based temporal disaggregation, physics-based simulation, and holistic environmental evaluation. The methodology addresses a key limitation of conventional LCA practice: the reliance on temporally aggregated energy data, which obscures daily and seasonal variability affecting environmental and economic indicators. A hierarchical disaggregation algorithm was used to reconstruct hourly electricity profiles from monthly totals and was coupled with the INTEMA building energy performance simulator and the VERIFY LCA/LCC platform. The disaggregation algorithm was validated on an office building in Cardiff, UK, supported by cross-validation across multiple UK office buildings, and achieved strong agreement with measured hourly consumption (R² = 0.81, RMSE = 3.71 kWh). In the Cardiff case, the reconstructed hourly profiles reproduced lifecycle greenhouse gas emissions and costs within 0.5% of the reference hourly measurement approach, compared with deviations of 44.1% and 2.9% under conventional monthly aggregation. The complete hybrid framework was then applied to a district in Massagno, Switzerland, encompassing eight buildings with heterogeneous typologies, for which only aggregated energy data were available (monthly for the office building and annual for the others). Over a 20-year horizon, total emissions reached 9429 tCO₂-eq and primary energy demand approached 226 GWh, equivalent to 41 kgCO₂-eq·m⁻²·yr⁻¹. The results illustrate the framework’s applicability to multi-building systems and its ability to support LCA and LCC in contexts with limited temporal data availability. Full article