Search Results (67)

To achieve optimal performance of renewable hydrogen production systems (RHPS), this study proposes a novel optimization framework for synergistically integrating wind–solar resources with diversified electrolyzers. A comprehensive techno-economic model is developed, incorporating both alkaline electrolyzers (AEL) and proton exchange membrane electrolyzers (PEMEL), and enabling the determination of the optimal wind–solar configuration ratio, electrolyzer types and capacities, and system-level economic performance. The results reveal that the nature of the renewable energy source predominantly influences the selection of electrolyzers. Specifically, pure photovoltaic (PV) systems tend to favor PEMEL, with an optimal PEMEL:AEL capacity ratio of 2:1, whereas pure wind turbine (WT) systems and PV–WT hybrid systems are more suited to AEL, with corresponding AEL:PEMEL ratios of 8:3 and 7:3, respectively. The combined operation of wind–solar complementarity and diversified electrolyzers reduces the levelized cost of hydrogen (LCOH) to USD 4.52/kg, representing a 41.1% reduction compared to standalone PV systems, with a renewable energy utilization rate of 92.26%. Case studies confirm that collaborative AEL–PEMEL operation enhances system stability and efficiency, with PEMEL mitigating power fluctuations and AEL supplying baseload hydrogen production. This synergy improves hydrogen production efficiency, extends equipment lifespan, and provides a viable and theoretically sound solution for RHPS optimization. Full article

Decarbonising the construction industry’s substantial ecological footprint demands credible substitutes that preserve structural performance while valorising waste. Although construction and demolition waste (CD&W) has been widely studied, the vast potential of agricultural residues (e.g., corncob, rice husk) and, crucially, their synergy remains underexplored. This study couples a systematic literature review with mathematical modelling to evaluate binary CD&W–agro-waste binders. A modified Andreasen–Andersen packing framework and pozzolanic activity indices inform multi-objective optimisation and Pareto analysis. The optimum identified is a 70:30 CD&W-to-agricultural ratio at 20% total cement replacement, predicted to retain 86.0% of OPC compressive strength versus a 79.4% average for single-waste systems (8.3% non-additive uplift). Life-cycle assessment (cradle-to-gate) shows a 20.3% carbon reduction for the synergistic blend (vs. 19.6% CD&W-only; 19.3% agro-only); when normalised by strength (kg CO₂-eq/MPa·m³), the blend delivers 6.3% better carbon efficiency than OPC (5.63 vs. 6.01), outperforming agro-only (5.79) and CD&W-only (6.61). Global diversion arithmetic indicates feasible redirection of 0.246 Gt y⁻¹ of wastes (5.7% of CD&W and 1.8% of agricultural residues) at 30% market penetration. Mechanistically, synergy arises from particle size complementarity, complementary Ca–Si reactivity generating additional C–S–H, and improved rheology at equivalent flow. Monte Carlo analysis yields a 91.2% probability of ≥40 MPa and 78.3% probability of ≥80% strength retention for the optimum; the 95% interval is 39.5–55.3 MPa. Variance-based sensitivity attributes 38.9% of output variance to the Bolomey constant and 44% to pozzolanic indices; interactions contribute 19.5%, justifying global (not local) uncertainty propagation. While promising, claims are bounded by cradle-to-gate scope and the absence of empirical durability and end-of-life evidence. The results nevertheless outline a tractable pathway to circular, lower-carbon concretes using co-processed waste. The approach directly supports circular economy goals and scalable regional deployment. Full article

The global water crisis, intensified by climate change and population growth, underscores the critical need for sustainable water production. Desalination is a pivotal solution, but its energy-intensive nature demands a transition from fossil fuels to renewable sources. However, the inherent intermittency of solar and wind power poses a fundamental challenge to the stable operation of desalination plants. This review provides a comprehensive analysis of a specifically tailored solution: hybrid energy storage systems (HESS) that synergistically combine batteries and hydrogen fuel cells (FC). Moving beyond a general description of hybridization, this study delves into the strategic complementarity of this pairing, where the high-power density and rapid response of lithium-ion batteries manage short-term fluctuations, while the high-energy density and steady output of fuel cells ensure long-duration, stable baseload power. This operational synergy is crucial for maintaining consistent pressure in processes like reverse osmosis (RO), thereby reducing membrane stress and improving system uptime. A central focus of this review is the critical role of advanced energy management systems (EMS). We synthesize findings on how intelligent control strategies, from fuzzy logic to metaheuristic optimization algorithms, are essential for managing the power split between components. These sophisticated EMS strategies do not merely ensure reliability, they actively optimize the system to minimize hydrogen consumption, reduce operational costs, and extend the lifespan of the hybrid energy storage components. The analysis confirms that a lithium-ion battery-fuel cell HESS, governed by an advanced EMS, effectively mitigates renewable intermittency to significantly enhance freshwater yield and overall system reliability. By integrating component-specific hybridization with smart control, this review establishes a framework for researchers and engineers to achieve significant levels of energy efficiency, economic viability, and sustainability in renewable-powered desalination. Full article

This study presents an analysis of the temporal complementarity between photovoltaic and wind power generation based on real measurement data obtained in the Lublin Voivodeship (Poland) in 2024. The main objective of the research was to evaluate the degree of time-dependent interaction between two renewable energy sources and to determine the potential for hybrid operation in a regional renewable energy mix. The measurements were conducted under real operating conditions, with a sampling frequency of 15 min for photovoltaic data and 10 min for wind data. After synchronization and resampling to a common 30 min interval, both datasets were compared using the Dynamic Time Warping (DTW) algorithm, which allows for the nonlinear alignment of time series with phase shifts. The results confirmed significant variability in the relationship between the two sources depending on the month. In April, a higher DTW distance (174.281) indicated the predominance of source substitutability, where one source compensated for the low generation of the other. In May, the DTW distance decreased to 138.978, revealing stronger source complementarity, where both PV and wind contributed simultaneously to the total output. The study demonstrates that DTW is a useful analytical tool for identifying temporal complementarity patterns and for quantifying the synergy between renewable sources. The proposed methodology can be applied to optimize hybrid system design and to improve grid balancing in energy systems with a high share of renewables. Full article

Australia’s renewable energy transition will be dominated by solar and wind power, yet their contrasting variability necessitates hybrid integration with storage to ensure reliability. This study uses Australian reanalysis data, BARRA (Bureau of Meteorology Atmospheric High-Resolution Regional Reanalysis for Australia), to quantify solar (global horizontal irradiance, GHI) and wind (wind power density, WPD) resources by examining their availability, variability, synergy, episode length, and lulls. The novelty of this work is the use of rarely examined metrics such as variability, availability, episode length, and extended lull events (Dunkelflaute) with a high-resolution and 29-year duration reanalysis dataset. The results show that solar is the more reliable resource, with high daytime availability and relatively short lulls. Wind, despite being abundant in coastal regions, is highly intermittent, characterized by a skewed distribution, low availability, and extended periods of lulls. Synergy metrics demonstrate significant complementarity, with combined solar–wind synergy reducing deficits in single resources, while joint non-synergy events define critical system vulnerabilities. Importantly, hybrid systems limit maximum joint lulls, which are far shorter than wind-only extremes, thereby reducing the scale of long-duration storage required. These findings underscore that, while solar provides a stable baseline supply and wind contributes spatial diversity, hybrid systems supported by batteries offer a resilient pathway. Synergy and non-synergy statistics provide essential parameters for optimally sizing storage to withstand rare but severe shortfalls, ensuring a reliable, utility-scale renewable future for Australia. Full article

Based on Agenda-Setting Theory, Media Agenda Synergy (MAS) can enhance the communication effectiveness of public issues (e.g., climate change, social justice, and public health) through the information resonance and agenda complementarity among cross-media platforms, thus reconstructing the public perception. In this paper, we focus on the dynamic impact of cross-media agenda synergy on public agenda intensity and innovatively propose a “HMM-Granger” hybrid modeling framework for Media Agenda Synergy: Firstly, we quantify the causal weights of agenda shifting based on the deconstruction of the nonlinear time-series dependence of multisource media data by using LSTM neural networks. Secondly, the state transfer probability matrix of the Hidden Markov Model reveals the dual paths of “explicit collaboration” (e.g., issue resonance) and “implicit competition” (e.g., agenda masking) in media agenda coordination. The results of this study show that the Agenda Synergy between mainstream media and social media during major events can generate an Agenda Multiplier Effect, resulting in a significant increase in the intensity of the public agenda. This study provides a computable theoretical paradigm for Inter-Media Agenda Network modeling and data-driven decision support for optimizing opinion guidance strategies. Full article

Under the combined influence of global climate change and intensified human activities, ecosystem services (ESs) are undergoing substantial transformations. Identifying their nonlinear driving mechanisms is crucial for promoting regional sustainable development. Taking Anhui Province as a case study, this research evaluates the spatial patterns and temporal dynamics of six key ecosystem services from 2000 to 2020—namely, biodiversity maintenance (BM), carbon fixation (CF), crop production (CP), net primary productivity (NPP), soil retention (SR), and water yield (WY). The InVEST and CASA models were employed to quantify service values, and the XGBoost–SHAP framework was used to reveal the nonlinear response paths and threshold effects of dominant drivers. Results show a distinct “high in the south, low in the north” spatial gradient of ES across Anhui. Regulatory services such as BM, NPP, and WY are concentrated in the southern mountainous areas (high-value zones > 0.7), while CP is prominent in the northern and central agricultural zones (>0.8), indicating a clear spatial complementarity of service types. Over the two-decade period, areas with significant increases in NPP and CP accounted for 50% and 64%, respectively, suggesting notable achievements in ecological restoration and agricultural modernization. CF remained stable across 98.3% of the region, while SR and WY exhibited strong sensitivity to topography and precipitation. Temporal trend analysis indicated that NPP rose from 395.83 in 2000 to 537.59 in 2020; SR increased from 150.02 to 243.28; and CP rose from 203.18 to 283.78, reflecting an overall enhancement in ecosystem productivity and regulatory functions. Driver analysis identified precipitation (PRE) as the most influential factor for most services, while elevation (DEM) was particularly important for CF and NPP. Temperature (TEM) and potential evapotranspiration (PET) affected biomass formation and hydrothermal balance. SHAP analysis revealed key threshold effects, such as the peak positive contribution of PRE to NPP occurring near 1247 mm, and the optimal temperature for BM at approximately 15.5 °C. The human footprint index (HFI) exerted negative impacts on both BM and NPP, highlighting the suppressive effect of intensive anthropogenic disturbances on ecosystem functioning. Anhui’s ES exhibit a trend of multifunctional synergy, governed by the nonlinear coupling of climatic, hydrological, topographic, and anthropogenic drivers. This study provides both a modeling toolkit and quantitative evidence to support ecosystem restoration and service optimization in similar transitional regions. Full article

Since 2008, the Chinese government has been intensively implementing policies to control plastic pollution. This study employs text mining and scientific statistical methods to quantitatively analyze 223 policy documents spanning the period from 2008 to 2025. The novelty of this study is associated with the analysis of temporal coherence, content complementarity and subject collaboration in the field of policy aimed at limiting the use of plastic and the development of a universal methodology for the design of complex environmental policies. The results show that policy releases peaked in 2008 and 2020. The average number of policies issued by each province in the eastern region is the highest, with 6.8 items. In terms of policy content, A3, B3, and C3 are the most prominent policy objectives, means and safeguard measures, respectively. The synergy of policy content indicates that market-oriented policies have stronger implementation, for example, the synergy strength between A2 and B2 is 0.7467. The synergy between legislative and enforcement policies is insufficient. For example, the synergy strength between A1 and B1 is only 0.2903. The regional synergy decreases from southwest to northeast. The northeast region lags comprehensively. In terms of time, the similarity of policy texts between 2021 and 2023 remained stable (0.3256–0.3666). The three-dimensional framework offers an approach to policy synergy evaluation. It indicates that the core governance framework of the Chinese Government has strong continuity. This study also has positive value for global environmental protection, such as reducing plastic pollution. Full article

Τhe Greek Seas are one of the most favorable locations for offshore wind energy development in the Mediterranean basin. In 2023, the Hellenic Hydrocarbons & Energy Resources Management Company SA published the draft National Offshore Wind Farm Development Programme (NDP-OWF), including the main pillars for the design, development, siting, installation, and exploitation of offshore wind farms, along with the Strategic Environmental Impact Assessment. The NDP-OWF is under assessment by the relevant authorities and is expected to be finally approved through a Joint Ministerial Decision. In this work, the preliminary offshore wind energy assessment of the Greek Seas is performed using the CERRA wind reanalysis data and in situ measurements from six offshore locations of the Greek Seas. The in situ measurements are used in order to assess the performance of the reanalysis datasets. The results reveal that CERRA is a reliable source for preliminary offshore wind energy assessment studies. Taking into consideration the potential offshore wind farm organized development areas (OWFODA) according to the NDP-OWF, the study of the local wind characteristics is performed. The local wind speed and wind power density are assessed, and the wind energy produced from each OWFODA is estimated based on three different capacity density settings. According to the balanced setting (capacity density of 5.0 MW/km²), the annual energy production will be 17.5 TWh, which is equivalent to 1509.1 ktoe. An analysis of the wind energy correlation, synergy, and complementarity between the OWFODA is also performed, and a high degree of wind energy synergy is identified, with a very low degree of complementarity. Full article

How can we more fully analyze potential progress toward the 17 Sustainable Development Goals, globally and by country? Methodological challenges include (1) the comprehensiveness of issue coverage, integration of causal elaboration, and geographic detail in available models; (2) clear quantification of goal targets; and (3) specification of scenario interventions that connect meaningfully to the potential leverage of agents. This study uses a large-scale, global but country-based analytical system that tightly integrates multiple issue-area models to push against methodological challenges. It explores the prospects for progress toward selected quantified targets across all goals, using scenarios that consider potential agency-linked interventions relative to the Current Path (CP). The scenarios distinguish interventions focused on Human Development (HD) and natural system sustainability (NSS) plus a Combined SDG scenario (CSDG). Even with a large, integrated push through 2030 and 2050, the world in aggregate will fail to reach many targets, and a great many of the 188 countries represented will fall short. Also of interest is possible tension between the underlying thrusts of HD- and NSS-oriented interventions. Both the Current Path of key variables and intervention leverage constraints make NSS goals harder to reach than HD goals. Because synergies of action considerably outweigh trade-offs, however, complementarity better characterizes the two intervention sets. Full article

Agriculture faces a dual challenge in the context of climate change, serving as both a significant contributor to greenhouse gas (GHG) emissions and a sector highly vulnerable to its impacts. Addressing this requires a transition toward climate-resilient agriculture (CRA). Emerging technologies, including geospatial tools (e.g., Geographic Information Systems (GISs) and remote sensing (RS)), as well as artificial intelligence (AI), offer promising methods to support this transition. However, their individual capabilities, limitations, and appropriate applications are not always well understood or clearly delineated in the literature. A common issue is the frequent overlap between GISs and RS, with many studies assessing GIS contributions while concurrently employing RS techniques, without explicitly distinguishing between the two (or vice versa). In this sense, the objective of this review is to conduct a critical analysis of the existing state of the art in terms of the distinct roles, limitations, and complementarities of GISs, RS, and AI in advancing CRA, guided by an original definition we propose for CRA (structured around three key dimensions and their corresponding targets). Furthermore, this review introduces a synthesis matrix that integrates both the individual contributions and the synergistic potential of these technologies. This synergy-focused matrix offers not just a summary, but a practical decision support matrix that could be used by researchers, practitioners, and policymakers in selecting the most appropriate technological configuration for their objectives in CRA-related work. Such support is increasingly needed, especially considering that RS and AI have experienced exponential growth in the past five years, while GISs, despite being the more established “big brother” among these technologies, remain underutilized and is often insufficiently understood in agricultural applications. Full article

With the shift of the global innovation model from traditional closed-loop to open ecosystems, knowledge sharing and collaborative cooperation among firms have become key to obtaining sustainable competitive advantages. However, existing studies mostly focus on the static structure, and there is an insufficient exploration of the dynamic evolutionary mechanism and multi-party game strategies. In this paper, a two-dimensional analysis framework integrating the evolutionary game and the Lotka–Volterra model is constructed to explore the behavioral and strategic evolution of core enterprises, SMEs and the government in the innovation ecosystem. Through theoretical modeling and numerical simulation, the effects of different variables on system stability are revealed. It is found that a moderately balanced benefit allocation can stimulate two-way knowledge sharing, while an over- or under-allocation ratio will inhibit the synergy efficiency of the system; a moderate difference in the knowledge stock can promote knowledge complementarity, but an over-concentration will lead to the monopoly and closure of the system; and the government subsidy needs to accurately match the cost of the openness of the enterprises with the potential benefits to the society, so as to avoid the incentive from being unused. Accordingly, it is suggested to optimize the competition structure among enterprises through the dynamic benefit distribution mechanism, knowledge sharing platform construction and classification subsidy policy, promote the evolution of the innovation ecosystem to a balanced state of mutual benefit and symbiosis, and provide theoretical basis and practical inspiration for the governance of the open innovation ecosystem. Full article

Based on digital patent data from 359 Chinese cities between 2006 and 2022, this paper calculates the gravitational value of the digital economy using a modified gravity model and employs social network analysis and QAP analysis to investigate the correlation network of cities’ digital economy and the influencing factors. The study found the following: (1) Chinese cities have a high level of digital economy, showing a consistent increase in growth rate, and density and relevance are rising without revealing a distinct hierarchical network structure. (2) The inner economic network demonstrates a significant imbalance, as illustrated by the “Matthew effect”. Core cities like Shenzhen and Beijing show greater net spillover, indicating their role as network hubs, while less developed cities have lower net spillover, necessitating improvements in interconnection capacity. (3) Differences in economic scale, population quality, scientific and technological innovation, and infrastructure construction, which have a positive effect, are the main sources of linkage network formation. At the same time, the difference in urbanization rates is stage-specific, reflecting the dual logic of factor complementarity and policy synergy. Overall, this study reveals the dynamic evolution of the digital economic spatial network through city-scale innovation and provides theoretical support for promoting the region’s sustainable and coordinated development. Full article

The rapid emergence of the platform economy has accelerated the practice of embedded innovation, with ecosystem partner selection serving as a critical first step in platform enterprises’ innovation collaborations and playing a key role in enhancing innovation efficiency and outcomes. Based on the theory of embedded innovation, this study identifies the core innovation demands of platform enterprises at distinct stages. It then employs QFD to quantify decision indicator weights for ecosystem partner selection. By integrating Prospect Theory with Field Theory, this study develops both a decision evaluation model and an optimization model to achieve the optimal screening of ecosystem partners. Specifically, this study contributes in the following ways: (1) It constructs an embedded innovation direction selection model to uncover the evolving innovation demands at each stage. Within the QFD framework, we map these demands onto selection evaluation indicators, assess their importance via the maximum entropy principle, and determine indicator weights through a correlation matrix. (2) It proposes a Prospect Theory-based TOPSIS evaluation model, incorporating decision-makers’ psychological preferences to mitigate bias arising from singular or excessive risk attitudes. This model ranks potential partners according to their closeness to an ideal solution. Finally, (3) it designs a Field Theory-based optimization model that accounts for the platform enterprise’s perspective, partner-matching rationality, and continuity of interaction. This model emphasizes the complementarity and synergy of innovation resources to enhance cooperation fit and strategic alignment between the platform and its partners. Finally, this study conducts an empirical analysis on platform enterprise XM and validates the model’s feasibility and stability through sensitivity testing and comparative analyses. This study enriches the understanding of ecosystem partner selection within platform ecosystems by advancing methods for quantifying partner demands and refining the selection of evaluation indicators. It also deepens the depiction of non-rational characteristics in behavioral decision-making and elucidates the mechanisms underlying the ongoing interactions between platform enterprises and their ecosystem partners. These theoretical contributions not only extend the scope of research on platform ecosystems and embedded innovation but also provide feasible approaches for platform enterprises to improve partner governance and foster collaborative innovation in dynamic and complex environments. Ultimately, the findings offer strong support for enhancing innovation performance and building sustainable competitive advantages. Full article

Considerable losses are inflicted by plant-parasitic nematodes (PPNs) due to their obligate parasitism; serious damage occurs in many susceptible crops, and the parasites have a broad distribution worldwide. As most PPNs have a subterranean nature, the complexity of soils in the plant rhizosphere and the structures and functions of the soil food webs necessitate a grasp of the relevant biotic/abiotic factors in order to ensure their effective control. Such factors frequently lead to the inconsistent performance and untapped activity of applied bionematicides, hindering efforts to develop reliable ones. Research efforts that take these factors into account to back the usage of these bionematicides by combining the disease-suppressive activities of two or more agricultural inputs are highlighted herein. These combinations should be designed to boost useful colonization in the rhizosphere, persistent expression of desirable traits under a wide range of soil settings, and/or antagonism to a larger number of plant pests/pathogens relative to individual applications. Relevant ecological/biological bases with specific settings for effective PPN management are exemplified. Determining the relative sensitivity or incompatibility of some biologicals entails studying their combinations and reactions. Such studies, as suggested herein, should be conducted on a case-by-case basis to avoid unsatisfactory outputs. These studies will enable us to accurately define certain outputs, namely, the synergistic, additive, neutral, and antagonistic interactions among the inputs. In optimizing the efficiencies of these inputs, researchers should consider their multi-functionality and metabolic complementarity. Despite previous research, the market currently lacks these types of safe and effective products. Hence, further explorations of novel integrated pest management plans that boost synergy and coverage to control multiple pathogens/pests on a single crop are required. Also, setting economic incentives and utilizing a standardized regulation that examines the authentic risks of biopesticides are still called for in order to ease cost-effective formulation, registration, farmer awareness, and usage worldwide. On the other hand, tank mixing that ensures legality and avoids physical and chemical agro-input-based incompatibilities can also provide superior merits. The end in view is the unraveling of the complexities of interactions engaged with in applying multiple inputs to develop soundly formulated, safe, and effective pesticides. Sophisticated techniques should be incorporated to overcome such complexities/limitations. These techniques would engage microencapsulation, nanopesticides, volatile organic compounds as signals for soil inhabitants, bioinformatics, and RNA-Seq in pesticide development. Full article