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The major crises that hit the world economy in the last 15 years caused a growing presence of the state in the economy. Deep crises almost inevitably give rise to growing public interventions to avoid the collapse of the economic and social system. However, the demand for more state interventions does not make it less important to be concerned about the extension and quality of these interventions in order to contain their possible negative effects on the economy as a whole. The paper is an attempt at dealing with these issues by using a simple growth model inspired by Domar's contributions. The main result is that state interventions can produce positive effects on the economy by not simply increasing aggregate demand but, most of all, by contributing to raise the productivity and the rate of growth of the economy. An objective that can be realized by mainly devoting public outlays to investment in physical and human capital (defined as productive public expenditures). • The crises that recently hit the world economy caused a growing presence of the state in the economy. • The issue is dealt with by focusing on the effects of public spending on the economy's growth rate. • Public spending can positively affect the growth rate by raising the economy's productivity. • Productivity is raised by concentrating outlays on investment in physical and human capital. • At higher growth rates the ratio Public Debt/GDP can be stabilized in spite of primary deficits. [ABSTRACT FROM AUTHOR]

In this paper, we review the theories of business cycles in the 20th century after the work of John Maynard Keynes. Fluctuations in economic activity have been observed with considerable regularity since the beginning of the last century, motivating empirical efforts to, identify, measure, and understand business cycles, contributing to the identification of stylized facts on business cycles, facts the business cycle theories should try to explain. Theories however have been very distinct through the years. Despite the different explanations for the sources of cycles, in mainstream economics, there was the underlying hypothesis of stability and equilibrium as a main characteristic of the economic system. The heterodox view on business cycles, in contrast, starts with Keynes pre-dynamic theory, considering the intrinsic instability of the system and extends through several other authors and theories. In this paper, we use the concepts of equilibrium and instability as a demarcating guide to separate theories in two groups: the mainstream view and the heterodox view. We notice however that, even though different authors and theories might share similar views on the self-equilibrating property of the economic system, there is no coherent integration between similar theories. We conclude the paper with some methodological insights that might lead to a coherent and integrated approach to explain business cycles in the heterodox view, requiring new and complex methods and tools. • Equilibrium and instability as demarcating guide to Business Cycles theories. • Empirical stylized facts on Cycles are to be explained by theories. • In mainstream, cycles are external shocks damped by internal response mechanisms. • The heterodox view instead assumes endogenous instability. • Despite common assumptions, cycle theories have been very distinct. • We propose an integrated heterodox approach under some guiding principles. [ABSTRACT FROM AUTHOR]

• A grid-connected solar PV-based multigeneration energy system is presented. • Economic, energy, environmental assessment for the proposed system is carried out. • Single objective/multi-objective optimization scenarios are analyzed and compared. • Sensitivity analysis is conducted to point out the effect on system performances. Solar photovoltaic-based multigeneration energy systems (SPVMES) which can use the excess energy of photovoltaic (PV) systems for heating and hydrogen production to improve the self-consumption of solar PV, have gained wide attention as a promising solution for clean and efficient production. To reliably meet diverse energy demands, gird system is integrated into a SPVMES as a backup energy source. In this paper, a grid-connected SPVMES is established to meet the electricity, heating and hydrogen loads, including PV, electrolysis, solid oxide fuel cell, electric heater for small-scale centralized heating and energy storage devices for electricity, heating and hydrogen storage, respectively. The emphasis to focus on when designing and dispatching the SPVMES lies in system performance evaluation. The innovation of this paper is to design and dispatch such a grid-connected SPVMES in a preliminary design stage through economic, energy and environmental assessment by considering cost of energy (COE), energy rate (ER) and renewable fraction (RF). Simultaneously, to explore which single objective/multi-objective optimization has better performance in comprehensive system evaluation, four different scenarios named COE optimization, RF optimization, ER optimization and multi-objective optimization are analyzed and compared. The specific application processes of component sizing and system dispatching with different optimization objectives are presented in detail. The results show that the proposed system has the COE of 0.0343$ in COE optimization scenario, the ER of 0.9128 in ER optimization scenario and the RF of 0.8811 in RF optimization scenario, which shows its significant potential in economic, energy efficiency and environmental performance. By comprehensively scoring the four optimization scenarios, it can be found that the multi-objective optimization scenario has better performance in system performance evaluation compared to the other three single objective optimization scenarios. Additionally, the multi-objective optimization could balance the tradeoff of COE, RF and ER and compromise the results of the single objective optimization scenarios. Potentially, sensitivity analysis is conducted to point out the effect of discharging depth of battery, PV subsidy, linear increasement of loads and seasonality effect on system performances. [ABSTRACT FROM AUTHOR]

• The paper elaborates on the complexity of Pasinetti's structural dynamics. • The movement of an economic system towards the natural growth path may require institutional changes. • The movement towards a natural growth path involves historical considerations and attention to the medium term. The paper elaborates on the complexity of Pasinetti's structural dynamics with particular reference to natural full employment growth. The movement of an actual economic system towards the path of natural growth may require institutional changes. A few examples are provided for the changes required to revive an economic system fallen in deep depression. It is argued that those changes may concern not only economic institutions but also political, sociological, and bureaucratic organisations. The analysis, which also involves historical considerations, gains in realism, and directs attention to the possible paths in the medium run. [ABSTRACT FROM AUTHOR]

• This paper explores the Newtonian roots of Adam Smith's thinking as a contribution to explaining the structural dynamics of the economic system. • Smith proposes an explanation of "social physics", where the intentionality of actors is the main distinction from Newton's natural dynamics. • In Smith's account, the sources of structural economic dynamics lie in the actors' capacity to organise production within the market. • This conceptual framework highlights a possible avenue along which to investigate Pasinetti's separation theorem. • The literature on industrial policy has moved in the last twenty years towards Pasinetti's insights, to which explicitly reference should be made. This paper explores the Newtonian roots of Adam Smith's thinking in the structural dynamics of the production system and of social organization at large. Newton's Principia Mathematica inspired a philosophical movement in Scotland that looked for principles that could explain the dynamics of social and economic bodies with the same scientific rigour. In Smith's account, the sources of structural economic dynamics lie in the actors' capacity to organise production within that domain of interaction of competing forces that he defines as the market. Against this background, Smith analyses the role of the institutional setup. This conceptual framework is central to the theory of structural dynamics in classical political economy. It highlights a possible avenue along which to investigate Pasinetti's distinction between the 'natural' (production-based) and the 'institutional' levels of analysis (Pasinetti's separation theorem) by exploring the dynamic interdependence of technological and institutional drives in the emerging new industrial revolution. [ABSTRACT FROM AUTHOR]

[Display omitted] • 2010-2018: Ecological-economic coordination was highest in Hebei and lowest in Tianjin. • The ecological-economic coordination degree of various regions has obvious spatial spillover effects. • Improved functional and development tactics and policy reforms can strengthen ecological-economic development relations. The Beijing-Tianjin-Hebei region is an integral part of the ecology and economy of northern China. Unique geographical factors closely interlink the regions; however, limited attention has been paid to urban clusters' ecological and economic spatial linkages. Therefore, this paper introduces Ecosystem service value and Ecological-economic coordination degree, considering extensive spatial spillover effects within the region under study. This paper adopts spatial autocorrelation and the spatial Durbin model to detect the coordination relationship. Moreover, examine the influence of population growth, sales of consumer goods, health facilities, green areas, and Tertiary Industry on Ecological-economic coordination. The relationship is tested economic growth, using the internal and external Thus, it determines that the change of coordination degree shows a "V"-shaped development in time and space and gradually realizes the overall coordinated development. It affirmed the judgment that the Ecological-economic coordination degree of each region has an obvious spatial spillover effect. Policy reforms, improved functions, and development mechanisms can enable the balanced and healthy development of the region's ecological and economic systems. [ABSTRACT FROM AUTHOR]

Despite the tight articulation between Pasinetti's natural economic system and measurable inter-industry magnitudes, contributions inspired by his framework of structural economic dynamics have either focused on analytical developments or empirically implemented some of its features in isolation. To bridge the gap between theory and empirics, this paper introduces a computable formulation of Pasinetti's dual system of prices and quantities, including its natural configuration, starting from a set of inter-industry accounting identities. The analytical properties of the computable framework are discussed, using the logical structure of a closed Input–Output model. By articulating a dataset collating different OECD databases, the scheme is empirically implemented to explore the structural dynamics of six advanced industrial economies between 1995 and 2015. In particular, we quantify the required injection to close a country's unemployment gap via a public intervention, use the natural configuration of the economy to relate the evolution of demand, productivity, wages and the general price level, and compare the emerging trends of job creation and displacement across countries and hyper-integrated sectors. • Computable formulation of Pasinetti's dual system of prices and quantities. • Empirical application to six advanced industrial economies between 1995 and 2015. • Quantify required injection to close unemployment gap via a public intervention. • Relate demand, productivity, wages and price dynamics via natural configuration. • Manufacturing hyper-integrated sectors expel jobs and service subsystems absorb them. [ABSTRACT FROM AUTHOR]

Shifting from a traditional linear to an alternative circular paradigm can foster economic growth and support sustainable capital renewal in the European Union. This topic has attracted growing academic interest in recent years. However, the evaluation of case studies regarding Circular Economy implementation, strategies, and practices (at all levels) is still in its infancy. With the aim of bridging this gap, this paper analyses, through a systematic review of case studies, the implementation of circular practices in all economic sectors and industries of the European Union (from 2015 until April 2023). To this end, this research uses a framework of circular strategies built considering the European Union political framework. Based on this analysis, it can be deduced that recycling was the most used circular strategy (24.2%) to reintegrate materials into the economic system and reduce the use of raw materials (18.9%), demonstrating the existence of virtuous circles in the European Union's economic sectors. The results show that the best performing industry, in terms of circular strategies, is Food and Beverage (17.92%), within the Agri-food economic sector. While the economic sector with the least number of circular strategies (7.86%) is Capital Equipment. This paper proposes several tools for Circular Economy implementation that could lead to future research and support business, policymakers, and the scientific community. [Display omitted] • Circularity implementation in the European Union's economic sectors is evaluated. • The most important barriers and challenges are outlined and discussed. • Circular strategies are obtained from the European Union political framework. • The main performing economic sectors and industries are listed. • Food and Beverage was found to be the most circular industry in the European Union. [ABSTRACT FROM AUTHOR]

The uncertainty of renewable energy necessitates reliable demand response (DR) resources for power system auxiliary regulation. Meanwhile, the widespread deployment of energy-consuming 5G base stations (gNBs) drives internet service providers (ISPs) to seek energy expenses reduction. This paper intelligently addresses these two complementary needs by integrating gNBs into the power system dynamic economic dispatch (DED). To achieve this, a combined DED model that incorporates both the power system and 5G communication network is developed, where numerous distributed gNBs and their backup energy storage systems (BESSs) are integrated as a virtual power plant (VPP) to offer power support and obtain economic incentives. Instead of traditional optimization methods, the combined DED model is solved by a cooperative game-based solution method in a benefit-balanced manner, facilitating the power system and 5G network to achieve a win-win DED solution. This method comprises a two-stage game model and a solution algorithm based on improved random drift particle swarm optimization (RDPSO). The improved RDPSO constructs an uncertainty set in each iteration, facilitating its solution of stochastic optimization involving power system uncertainties. Lastly, a VPP management function is developed within the 5G core network (5GC) to efficiently evaluate the VPP's dispatchable capacity and formulate optimal control policies that can minimize control costs. Simulations based on the IEEE 118-bus system and real device data demonstrate that the proposed method can simultaneously reduce the power system's operating costs and increase the ISP's economic revenue. • Addressing complementary needs by integrating gNBs into power system DED. • Game-based solution for DED balancing supply and demand sides benefits. • Improved RDPSO algorithm for power system DED considering uncertainties. • VPP function efficiently evaluating dispatchable capacity and formulating optimal control policy. • Economic and technical win-win results in simulation based on real data. [ABSTRACT FROM AUTHOR]

This paper proposes a joint optimization framework for the demand response-capacity configuration design of the integrated energy system (IES), in which both the economic cost and closed-loop dynamic regulation performance under source-load fluctuations are considered. The joint optimization consists of two layers. The upper layer optimizes the time of use electricity price to adjust the demand response of electric load; while the lower layer optimizes the capacity configuration, scheduling instructions and incentive-based thermal load demand response under typical scenarios. To fairly evaluate the impact of equipment capacity and demand response on the dynamic control performance of the IES, multi-parameter programming-based predictive control approach is applied to develop an offline design and scheduling-perceptive control system. A closed-loop dynamic scheduler is then developed based on the control system, which can optimize the operating instruction of each equipment considering their dynamic operating practice. Simulation studies on a typical off-grid combined heat and power IES show that the proposed approach can effectively match the demand response to the capacity configuration of the IES, helping the system achieve a dynamically flexible and economic energy supply. • Joint capacity configuration and demand response optimization is proposed for IES. • Dynamic control performance is considered in the optimization. • Design and scheduling-perceptive controller is developed to bridge gap between design and operation. • Dynamic scheduling is proposed to consider IES operating practice in the optimization. • Both economic and dynamic control performance of IES is improved by the proposed method. [ABSTRACT FROM AUTHOR]

The exploration and promotion of new energy constitute a significant initiative for numerous countries in their pursuit of sustainable development and efforts to alleviate climate change. However, the influence of a multitude of uncertain factors on the evolutionary path of new energy is currently poorly studied. By establishing a dynamic evolution model for new energy under polymorphic uncertainty, this paper analyses the complex interaction between new energy, economic growth, and carbon trading over the period 2020–2060, using China as a case study. We employ numerical simulation and sensitivity analysis to investigate the evolutionary trajectories of the new energy system under various parameter value scenarios. We show that the evolutionary trajectories will undergo substantial fluctuations before 2030, subsequently stabilizing from 2030 onwards. The study highlights that an excessively rapid pace of new energy development is detrimental to new energy systems, whereas energy storage system deployment has the opposite effect. There exists a significant risk of the system collapsing as a result of slow new energy development, over-building energy storage facilities, or over-intervening in carbon trading. We also find that overdevelopment of energy storage system may have greater negative impacts on the economic system than underdevelopment. [Display omitted] • Dynamic evolution model of new energy under polymorphic uncertainty is constructed. • New energy production elasticity and energy ratio are innovatively constructed. • Excessive intervention in carbon market can lead to the collapse of new energy system. • Overdeveloped energy storage hinder the synergy of new energy and economic growth. [ABSTRACT FROM AUTHOR]

Renewable Energy Communities (RECs) are being deployed all around the World as a technically feasible solution to decreasing users' dependence on fossil fuels. Several demonstration facilities have shown their potential to provide final consumers with clean energy and all associated environmental benefits. However, the economic evaluation of these systems as a whole set is more complex than evaluating generation technologies individually, which can be considered a barrier, and it may be more complicated to calculate its uncertainty with precision. This paper deals with this challenge and adapts a model for the evaluation of the global Levelized Cost of Electricity (LCOE) of a polygeneration microgrid to the characteristics of a typical REC, allowing the assessment of the distribution of the LCOE depending on the uncertainty of the input parameters. Thanks to its simple analytical formulation, the proposed model, that can be used for any combination of technologies (both renewable and conventional), provides relevant information on uncertainty propagation in a symbolic way that avoids the need to run numerical simulations or make assumptions on the distribution of the random input parameters. A case study has been presented, considering a typical small electrical REC with photovoltaic plants and micro wind turbines. Although the model can be defined to any market, as a representative example, it has been evaluated according to the current Spanish and Italian regulations, which are analyzed in depth with reference to the scientific literature. Results show that uncertainties in parameter estimates give rise to a very large scatter in the LCOE, pointing out a set of quantities whose role is crucial for a reliable estimate, among which electricity purchase and selling prices, yearly power load, and self-consumption / virtually-shared energy rates stand out. [Display omitted] • The global LCOE for a typical REC has been defined. • The uncertainty propagation in the LCOE formulation has been studied. • The proposed model has been applied to an electrical polygeneration REC. • As an example, the Spanish and Italian regulatory frameworks have been considered. • The LCOE of RECs is mainly sensitive to the electricity price and the power load. [ABSTRACT FROM AUTHOR]

The Polish coal-based power system faces the necessity of a pressing transition. Partially, the challenge may be addressed by floating photovoltaics. Since there is no analysis covering the implementation of this technology in Polish conditions, in this paper the design process of a 1 MWp floating photovoltaic system and its technical and economic assessment were performed. To find the best solution different floating assemblies were considered. Floating systems were compared with the reference ground mounted system and, based on simulations conducted in PVsyst, economic study with sensitivity analysis was carried out. The results revealed that even in case of the best performing floating system the extra yield cannot compensate the higher CAPEX. Currently, in Polish market conditions, this technology is not as profitable as the ground-mounted systems and higher product maturity stage need to be achieved for it to be considered as competitive. [ABSTRACT FROM AUTHOR]

The global society faces an existential threat if it fails to meet current and future material needs of its populations, while staying within the carrying capacity of our planet. An approach that has been put forwards to address this complex challenge is to aim to close our society's material flows through introduction of a Circular Economy (CE). This paper provides an extensive literature review to understand the evolution of material circularity concepts and strategies, and their potential for increasing material efficiency and reduce environmental impacts towards meeting the material needs of our societies in an environmentally sustainable manner. Based on the review it can be concluded that CE may have a strong potential to help address the challenge. However, this requires broadening the focus of CE from technical and economical to political and socio-cultural dimensions, adopting a whole-systems approach, aiming to redesign economic and social relations to not just reduce the impact humanity has on the environment but actually achieve a balance in human-nature relations with a planetary boundary thinking. Pursuing purely technical and economic avenues to implement CE for increasing material circulation and sustainable growth on the foundation of our current linear economic system, will not achieve its full potential. It will not be sustainable but continue to produce the challenges that we currently have. [ABSTRACT FROM AUTHOR]

Climate change is a pressing issue that is disrupting the economic systems through financial and monetary impairment. The extent is more severe in the frontiers markets and compliance with the COP26 agenda is the only recourse for low-income economies. The banks play a critical role in such countries to finance business operations and incorporating sustainability practices in asset liability management can ensure financial resilience. In this paper, we assess if climate change has any impact on the mortgage portfolio and deposit mobilization of the banking sector. Using a comprehensive sample of 175 banks across twenty-three frontier markets and employing data between 2011 and 2021, we found that climate risk is negatively associated with mortgage exposure and deposit growth. We argue that the impact on mortgages is via physical risk while for deposit mobilization the pressure emanates from transitional factors. The results remained robust even after differentiating the banks into big and small categories suggesting that climate change is bringing in risks that will impact the financial sector without any discrimination. The paper has important implications for both transitional and physical risks related to climate change. • Climate risk is negatively associated with mortgage exposure and deposit growth. • The mortgage growth is constrained due to physical risks. • The transitional pressures impede deposit mobilization. • Compliance with COP26 declarations is the way forward for frontier economies. [ABSTRACT FROM AUTHOR]

Utilizing renewable reservoirs as a primary source of energy in power systems significantly mitigates environmental concerns. This approach, coupled with the integration of various subsystems, yields multiple products, thereby enhancing economic benefits. This paper introduces an innovative multi-generation system based on a gasifier-fed solid oxide fuel cell. In this system, waste heat recovery is achieved through a bespoke transcritical CO 2 cycle, combined with a Kalina cycle and an organic Rankine cycle subsystem. Additionally, a proton membrane electrolyzer is employed to supply a reactor for ammonia production. A comprehensive analysis of this configuration is performed, employing thermodynamic, economic, and environmental assessment methodologies. Moreover, two multi-objective optimization strategies are implemented to determine the system's optimal operating conditions. The results demonstrate that the proposed system generates a net power output of 293.1 kW, provides cooling of 40.8 kW, produces hydrogen at a rate of 2.689 kg/h, and ammonia at a rate of 15.14 kg/h. The environmental and economic impacts of these products are quantified as an exergoenvironmental impact rate of 111.89 Pt/h and a cost rate of 11.77 $/h, resulting in an exergy efficiency of 27.59%. Furthermore, the system's financial feasibility is evident from its payback period of approximately 3.42 years and a net present value of 1.64 M$. The study also identifies that variations in the fuel cell's current density significantly influence the system's exergy performance and environmental footprint. • Design of a novel multi-generation based on the gasifier-SOFC integration. • Application of exergoenvironmental approach. • Producing 2.689 kg/h of hydrogen and 15.14 kg/h ammonia. • Assessing 27.59% exergy efficiency and 111.89 Pt/h exergoenvironmental impact rate. • Achieving a payback period of 3.42 years and 1.64 M$ net profit. [ABSTRACT FROM AUTHOR]

This paper presents the energy management of smart distribution network including integrated system of hydrogen storage and renewable sources. Objective is to assess economic, operation, flexibility, and reliability goals of the distribution system operator. Objective function minimizes costs of operation, reliability, energy losses, and network flexibility. Scheme is constrained by AC optimal power flow equations, network reliability limitation, and integrated system model. Scheme utilizes scenario-based stochastic optimization to model of uncertainties, such as load, parameters of renewable resources, energy prices, and the availability of network equipment. Novelty is modeling and performance evaluation of the proposed integrated system as a type of flexibility resource in the operation of distribution systems proportional to the economic, operation, flexibility, and reliability objectives of the network operator. Numerical results demonstrate energy management capabilities of the discussed integrated energy system, which contribute to enhancing economic and technical conditions of distribution network. The inclusion of hydrogen storage in the renewable integrated energy system has been found to enhance the economic viability, operational efficiency, and reliability of the distribution network by around 46.8%, 41%–53%, and 95%, respectively, when compared to network power flow. Aforementioned integrated system demonstrates 100% flexibility through the utilization of hydrogen storage. • Developing a model for assessing the efficiency and effectiveness of hydrogen storage and bio-waste units farm. • Considering an integrated energy system to evaluate the economic and technical objectives of the DSO. • The utilization of an integrated hydrogen storage and RESs system as a means to enhance the network flexibility. • Simultaneous modeling of economic, operation, reliability, and flexibility objectives of the DSO. [ABSTRACT FROM AUTHOR]

Cross-regional energy sharing is a promising way to alleviate the imbalance in energy distribution. However, there is a risk that the uncertain fluctuations of intermittent renewable energy sources (RES) could be transmitted across regional transmissions, resulting in large-scale system economic inefficiency and security concerns. To this end, a unified spatial-temporal cooperative framework for the integrated energy system, which considers the coordination between intra-regional multi-energy coupling and cross-regional multi-agent-system energy sharing, is proposed in this paper. First, in the temporal dimension, a multi-time-scale stochastic decision-making model is established based on stochastic model predictive control (SMPC). Thus, slow-response units are arranged to gain economic goals in day-ahead stage and the closed-loop rolling adjustment is implemented on fast-response units to achieve accuracy supply-demand balance in real-time stage. Second, in the spatial dimension, a fully distributed dispatch approach is adopted to address the information sharing barriers, which only requires neighboring information and considers consistency of boundary control variables on border lines. Finally, to improve the computational efficiency, the established complex time sequential model is decomposed into a set of time-discrete parallel sub-problems, using the optimal condition decomposition (OCD) technique. Simulation results on a cross-regional test system demonstrate that proposed framework can increase the wind power consumption capacity and reduce operation cost through cross-regional cooperation, while the parallel decomposition can save 67.25 % of the computation time relative to the serial computation. • A novel unified spatial-temporal cooperative dispatching framework is proposed for the cross-regional IES. • A multi-time-scale rolling stochastic decision-making model is established to handle RES uncertainties. • The ADMM is implemented to achieve cross-regional rapid interactions iteration with only neighboring information. • The OCD is applied to decompose the complex spatial-temporal problem. [ABSTRACT FROM AUTHOR]

Sustainability and Industry 4.0 have been emerging topics in recent years, in theory as well as in practice. Related technological topics like 5G technology, blockchain, artificial intelligence and digital twins among others, are gaining importance. In addition, these themes are becoming increasingly merged with a discussion on I4.0 from societal and organizational perspectives. As a background to this paper, we discuss recent research in this area as covered in this Special Issue. We identify accepted submissions covering four conceptual themes and three methodological themes in the SI. Finally, we outline opportunities for future research: these include human interaction with I4.0 technology-enabled workspaces as well as societal aspects of I4.0 in relation to sustainability efforts. Last, but not least, interaction of I4.0 with other disciplines, such as sustainable manufacturing, reliability, maintenance and disaster management are proposed. • Sustainability and Industry 4.0 (I4.0) are emerging topics from societal and organizational perspectives. • Related technological topics like blockchain, artificial intelligence, digital twins among others, are gaining importance. • This SI outlines opportunities for: human interaction with technology-enabled workspaces and societal aspects of I4.0. • Interaction of I4.0 with other disciplines, such as sustainable manufacturing, disaster management, are proposed. [ABSTRACT FROM AUTHOR]

• We reconstructed a complex wetland with nature-based solutions. • This eco-economic system was driven by renewable emergy flows and high exergy. • The mulberry-related industry provided good economic benefits. • The stable equilibria of the eco-economic coupling mode represented a state of synergistic symbiosis. Nature-based solutions (NBS) are effective approaches for solving ecological and economic problems related to wetland reconstruction, while emergy and exergy are well suited for evaluating reconstructed eco-economic systems. In this paper, we executed a wetland reconstruction project involving a mulberry-fir woodland and dike-pond complex (MFWDPC) with NBS in the water-level fluctuation zone of the Three Gorges Reservoir (TGR), China. We evaluated the coupling mode of this eco-economic system by using emergy and exergy theories. After wetland reconstruction, the emergy density that entered the MFWDPC was 1.48E + 18 sej yr−1 hm−2, in which the naturally renewable flow accounted for 96.31 % of the emergy inflows, and the emergy sustainability index (ESI) for the eco-economic system was 708.88. The exergy and specific exergy were 2.41E + 14 j yr−1 and 2.08E + 08 j yr−1 kg−1, respectively, and the emergy/exergy ratio was 1.55E + 03 for the MFWDPC. In addition, mulberry trees with strong flooding tolerance provided good economic benefits due to the use of these plants in reconstructed eco-economic systems. Our study of NBS for wetland reconstruction helps in understanding the synergistic symbiosis between ecosystems and economic systems, thereby promoting the reconstruction of degraded wetlands in China and other regions. [ABSTRACT FROM AUTHOR]

• A composite index named GLCDES is developed to dynamically assess the level of Green Low-carbon Circular Development. • The combined-assignment VIKOR model based on game theory is developed to thoroughly estimate the construction level of GLCDES. • Southwest China's Green Low-carbon Circular Development Economic System construction level is examined from 2012 to 2021, showing how the long-side principle governs each region's value. • Selecting and strengthening the long side in combination with its reality is an effective way to improve the construction level of GLCDES. Emission peak and carbon neutrality are critical components of China's overall ecological civilization, and the establishment of a sound Green Low-carbon Circular Development Economic System (GLCDES) is a fundamental countermeasure for solving China's resource, environmental, and ecological problems. This paper used the new development concept as entry points to establish a comprehensive evaluation index system encompassing six subsystems: development dynamics, production and living systems, green benefits, low-carbon benefits, circularity benefits and socio-economic benefits. The combined-assignment VIKOR model, based on game theory, was used to thoroughly estimate the construction level of GLCDES by combining panel data from four southwestern provinces, including Chongqing, Sichuan, Guizhou and Yunnan, from 2012 to 2021. The study discovered that: the construction level of GLCDES in all four southwestern provinces increased over the past ten years, but the increase was not significant, the four development effectiveness indices, including green, low-carbon, circularity and socio-economic, were significantly improved, the development dynamics index was not significantly enhanced, and the index of production and living systems declined in fluctuation from year to year. The construction level of GLCDES between regions was very uneven and can be divided into two echelons, with the gap between Chongqing and Guizhou being particularly obvious. Regions can be categorized into three major categories based on the number of dominant subsystems. According to the above results, the total value of the dynamic comprehensive evaluation of each region is governed by the principle of the long side, which is an effective way to improve the construction level of GLCDES by selecting and strengthening the long side in combination with its reality. [ABSTRACT FROM AUTHOR]

• The Monte Carlo method is used to construct the charging load of EV in the planning area divided into four different vehicles type. • The Prim algorithm is adopted to search for the optimal network layout of energy transmission pipelines. • Proposed collaborative planning modeling promotes the time-of-use electricity price scheme to change the temporal and spatial characteristics of EV charging load. • The growth of EV charging load in the planning area has not increased the investment and operation-maintenance costs of DES equipment, and reduced carbon transaction costs as well as improved economic of system operation. • Simulations are conducted to verify the effeteness of proposed method. Under the dual-carbon goal, the number of electric vehicle (EV) has surged, and the uncertainty of the temporal and spatial characteristics of the load has become prominent, which brings the challenge for higher requirements to the equipment composition of distributed energy station (DES) and performance of station-network. This paper proposes a collaborative planning method for low-carbon DES with networks, which is focusing on the characteristics of EV charging behavior. First of all, based on the quantitative analysis of the temporal and spatial distribution of charging load of four typical types of EV, including private vehicle, public vehicle, taxi and bus, the Monte Carlo method is used to construct the charging load modeling of EV in the region area. In addition, the low-carbon DES is modeled equipped with photovoltaic (PV) and power to gas (P2G) devices, and the Prim algorithm is adopted to search for the optimal network layout of energy transmission pipelines in the region area. Under carbon trading mechanism, aiming at the lowest annualized total cost of the regional station-network, a station-network collaborative planning modeling strategy for the capacity allocation of low-carbon DES with networks is established. Finally, the case study for a project in Beijing China is implemented on MATLAB, to prove the effectiveness of the method proposed in the paper. The time-of-use electricity price scheme changes the temporal and spatial characteristics of EV load. For example, more than 2 MW the EV load can be brought into the valley price range, which reduces the carbon transaction cost and energy purchase cost of DES by 50 thousand yuan almost when peak-valley electricity price difference is close to 1.2 yuan. At the same time, the growth of EV charging load(the penetration rate of EV can reach up to 20%) in the planning area has not increased the investment and operation-maintenance costs of DES equipment. [ABSTRACT FROM AUTHOR]

Compartmental models are widely used in epidemiology, engineering, and physics to describe the temporal behavior of complex systems. This paper presents how compartmental models may be applied to the digital economy—more specifically, how the Bass model can be extended to more complex economics systems such as markets with customer churning, competition, multisided platforms, and online games. It is demonstrated that it is straightforward to establish the equations describing the various economic systems under study, however, the equations are often too complex to be solved analytically in the general case. Though the paper presents simple and idealized cases, the solutions may, nevertheless, uncover important strategic aspects that otherwise may be hidden by complexity in the general case, for example, the reasons for slow initial market growth. The paper also discusses how the developed models may be used to evaluate digital economic market evolution and business policy. • Analytical models that capture competition and churning in digital markets. • How complex digital economic system may be modelled using compartmental models. • How the strength of the network effects impacts market evolution. [ABSTRACT FROM AUTHOR]

In this paper, the development of the blue economy is considered from the perspectives of integrity, relevance, and operability. First, to further expand blue living space and achieve blue growth, development thinking must shift from supporting the development of a single agent to supporting the coordinated development of multiple agents. Thus, we set a list of 116 blue products. Second, we construct a conceptual model of the national blue economic system space. Taking China as an example, the product data, firm data and province data in China's blue economic system are collected and processed based on the needs of the study, and the basic dataset for constructing China's blue economic system space is obtained. Third, based on the blue product space, the blue firm network and the blue province network of China, as well as the mapping relationship that existed among them in 2010, China's blue economic system space in 2010 is constructed. Finally, evolutionary maps of China's blue economic system space from 1985 to 2018 are drawn to identify the spatial structure and characteristics of China's blue economic development. We use application examples to verify that the national blue economic system space can play an important role in assisting countries in conducting systematic multicriteria assessments of blue growth strategies, and the use of such a complex network makes countries more likely to formulate evidence-based policies without being influenced by vested sectoral interests. [ABSTRACT FROM AUTHOR]

The current coronavirus pandemic has produced severe consequences on economic and health systems all over the world, with the governments being challenged in searching for containment solutions balancing virus diffusion and limitations to social and work activities. In this paper, we propose a framework for the real-time optimization of restrictions in epidemics, based on the use of a time-varying SIRD model. Despite their simplicity, this class of models is able to capture the essential features of the epidemic spread, with the inherent parameter variation allowing accurate adaptation to real data. An optimization problem is formulated, properly balancing health and economic costs, and is solved parametrically by following a receding-horizon approach, resulting in an optimal sequence of social contact restrictions, which are assumed to be actuated via governmental containment measures. Numerical simulations based on the real data of the Italian COVID-19 emergency highlight the potential of the proposed approach and can be possibly helpful for the decision makers in present and future pandemics. [ABSTRACT FROM AUTHOR]

The optimal scheduling of power systems with a high penetration of wind power integration has always been a hot research topic due to their dramatic uncertainty. Furthermore, it is increasingly aware that the economic benefits should not be the sole optimal benchmark. A more dynamic low-carbon operation mechanism is needed to build an environment-friendly power system. In this paper, a Two-stage Stochastic Energy and Reserve Scheduling (TSERS) model with low-carbon operation constraints is proposed, which can effectively hedge against the worst-case distribution of wind power. First, a copula-based Worst-case Conditional Value-at-Risk (WCVaR) model is developed to quantify the operational risk of economic dispatch under uncertain wind power. Then, a carbon quota optimization (CQO) model is presented, taking into account both generation and carbon costs. Numerical experiments are conducted on the modified IEEE systems. Simulation results exhibit the ability of the WCVaR method, as is evident from a 44.8% reduction in the extreme loss with respect to Distributionally Robust Optimization (DRO). the proposed CQO model achieves 37.27% more profit compared to the conventional model at an average carbon price growth rate of 36.1%. This demonstrates the model's ability to adjust to carbon cost fluctuations and provide a sensible optimization proposal. • A copula-based WCVaR method is provided under wind uncertainty. • A carbon quota optimization model is established for economic benefits. • Carbon emission and system economic cost are considered comprehensively. • A multivariate copulas set is constructed for characterizing uncertainty [ABSTRACT FROM AUTHOR]

In line with national targets, sub-national governments – including cities – are introducing targets to reduce the emissions associated with economic activity within or associated with a particular geography. Cities are important drivers of not only emissions but also economic activity and are embedded into complex economic systems which reach beyond their boundaries, which can raise major issues in identifying whether a city is assisting in promoting sustainability across a wider spatial level. This paper sets out a methodology to downscale global Input Output tables to city-level and use these to calculate production- (territorial) and consumption-based carbon accounts at the city level simultaneously. Illustrating this for the case of Glasgow, Scotland, we show that the city's territorial emissions are significantly lower than its consumption-based carbon footprint (considering both the Areal and Personal Carbon Footprint), but that both metrics are sensitive to assumptions about the emissions intensity of individual sectors. Our results highlight the importance of data quality and accuracy, and the benefits of local knowledge, rather than the unquestioned use of national metrics. [Display omitted] • Extending Multi Regional Input Output accounts can produce cities emissions metrics. • Framework derives Production- and Consumption-based metrics from global accounts. • Application to Glasgow reveals city as net importer of carbon emissions. • Sensitivity of results to key assumptions shows value of local knowledge. [ABSTRACT FROM AUTHOR]

In this paper we propose a condition-based maintenance policy for continuously monitored multi-component systems subject to stochastic dependence through load sharing and economic dependence through maintenance set-up costs. Stochastic dependence provides an incentive to replace failed components as soon as possible, since component failures increase the load, and hence the deterioration rates, of the remaining components. In contrast, economic dependence encourages the clustering of component replacements to reduce maintenance frequency, resulting in less downtime and fewer maintenance set-up costs. In this paper, we propose a novel, condition-based maintenance policy to obtain the optimal replacement decisions at maintenance opportunities. Through numerical studies we see the importance of a policy that incorporates both types of system dependence. The policy incorporates a utility/reward function that is a combination of interpretable penalties that encapsulate the costs of stochastic and economic dependence. The utility function trades off the rewards of clustering components with the loss due to load sharing. The policy minimizes the overall cost of the system by choosing actions that minimize the total long-term penalty. We show that the proposed policy outperforms various alternative policies by reducing system life-cycle costs. • A CBM policy for systems subject to economic and stochastic dependence is proposed. • We define penalties that encapsulate the costs of stochastic and economic dependence. • A Bayesian sequential decision framework incorporates the proposed penalties. • The proposed policy suggests a way to coherently incorporate uncertainty. • We model component failure times using a random degradation threshold. [ABSTRACT FROM AUTHOR]

• Introduce the state-of-art temporal fusion transformers (TFT) into economic system forecasting based on the high compatibility between deep learning and the nonlinear characteristics of socio-economic systems. • Propose a scientific economic system forecasting framework on the foundation of the extended gross final product (GFP). • Build a four-dimensional evaluation system including numerical error, direction accuracy, timing error and turning point accuracy. • Empirically forecast the monthly output indicators of the Chinese macroeconomic system. • TFT results have obvious advantages over benchmark models including ARIMA, BP, LSTM, TCN and N-BEATS through comparison analysis. Although helpful in reducing the uncertainty associated with economic activities, economic forecasting often suffers from low accuracy. Recognizing the high compatibility between deep learning and the nonlinear characteristics of socioeconomic systems, in this paper, we introduce state-of-the-art temporal fusion transformers (TFTs) into the field of economic system forecasting and predict the performance of the Chinese macroeconomic system. Based on an extended analysis of gross final product (GFP) and the intertemporal dynamic relationship between demand-side indicators and output indicators, we establish a scientific economic forecasting framework. To summarize the forecasting characteristics of the TFT algorithm, we compare its one-step and three-step modeling effects in forecasting output indicators with a series of representative benchmark models. According to our proposed four-dimensional evaluation system, the forecasts for China's macroeconomic system provided by the TFT model have obvious advantages in terms of overall stability, forecasting efficiency, reduction of numerical and timing errors, direction accuracy, and turning point accuracy. The forecast results show that China's economy faces a risk of slowing growth in the post-pandemic period. [ABSTRACT FROM AUTHOR]

The transition to a circular economy relies on systems that facilitate waste recovery and recirculation of resources. These systems are based on certain enabling technologies. The aim of this paper is to explain how socio-economic structures influence the diffusion of such technologies. It applies a framework built on societal embedding and varieties of capitalism to compare the diffusion of anaerobic digestion (AD) in Sweden in northern Europe and Paraná in southern Brazil. Both Sweden and Paraná have experienced accelerated diffusion of AD, but there are significant differences in the respective diffusion patterns. The comparative analysis points to a tradeoff between system complexity and speed of diffusion. It illustrates how AD can be presented as a solution to various problems, and it further shows how the specific problems that gain attention shape diffusion patterns. By showing how socio-economic structures influence the appointment of problem owners, their agency, and legitimate forms of institutional support, the analysis demonstrates how economic systems condition technology diffusion. • The paper compares the diffusion of anaerobic digestion in Sweden and Paraná. • It shows how socio-economic structures have shaped diffusion patterns. • There is to a trade-off between sociotechnical system complexity and speed of diffusion. • Economic systems condition the diffusion of key technologies for a circular economy. • Analyses of recirculation potential must consider socio-economic structures. [ABSTRACT FROM AUTHOR]

Excessive carbon emissions pose a significant threat to the sustainable development of society and have an irreversible impact on climate change. Local energy trading in low-carbon communities and the implementation of carbon tax policy are considered effective means to improve energy efficiency and reduce carbon emissions. In this regard, this paper proposes a multi-energy sharing mechanism based on Nash bargaining theory among communities with distributed energy systems. The impact of heterogeneous carbon emission responsibilities, including production responsibility, consumption responsibility, and shared responsibility, on the economic and environmental benefits of shared communities is explored under a carbon tax policy. The distributed solution of the multi-energy sharing problem is carried out through the alternating direction method of multipliers algorithm, which protects the privacy of stakeholders and maximizes social welfare and the fair allocation of shared benefits. Additionally, sensitivity analyses of electric and thermal coupling loads, carbon emission accounting coefficients, and carbon taxes, are conducted to provide further insights into the optimal schedule of distributed energy systems and the economic and environmental performance of community clusters. The method proposed in this paper can effectively address the problem of multi-energy sharing in the interconnected communities and reasonably determine the carbon emission responsibility of each trading entity under the carbon tax policy. Numerical results show that, compared with the traditional no energy sharing scenario, the proposed sharing mechanism can achieve a maximum of 5.91% cost savings and 9.25% carbon emission reduction. In addition, under the production responsibility scheme, the communities show the best economic performance, while under the consumption responsibility scheme, the communities achieve excellent environmental benefit. [Display omitted] • A Nash bargaining based community P2P multi-energy sharing mechanism is proposed. • Different carbon emission responsibilities are considered in the P2P sharing problem. • Distributed solving ensures the autonomy and privacy of participants. • The economic and environmental performance under different scenarios are compared. [ABSTRACT FROM AUTHOR]

• The composition structure of the disaster economic resilience theory has been further developed and quantitatively verified. • The correction effect of the resilience on the economic fluctuations (secondary shock) that occurred during the recovery process has been quantitatively evaluated. • The sustainable improvement of the economic system's performance by the resilience at the end of the post-disaster recovery process has been quantitatively evaluated. • Results can provide a multi-dimensional optimization plan for improving the efficiency of post-disaster recovery and reconstruction management. Quantitative measuring disaster resilience especially dynamic economic resilience (DER) belongs to a frontier research in the past decades, which can effectively improve post-disaster economic recovery effects, reducing post-disaster loss. However, DER focuses more on the overall shape changes of recovery path, two features that commonly appear in the dynamic change process of recovery curve are also worth evaluating separately: the "secondary shock" caused by adverse factors during the recovery process and sustainable improvement of economic output at the end of recovery. Therefore, we adopt a dynamic input–output model that integrates capital damage and affected people and apply it to an extreme flood in 2016, Wuhan City, China, building the relationship between 7 recovery actions (rescue funds) and changes of two features, analyzing the impact of resilience on the dynamic recovery path features through 6 characteristic variables constructed in this paper. Results show that (1) economic resilience increases from no to actual action, the dropping rate caused by "secondary shock" decreases 30.4%, and Wuhan's economic output has achieved an improvement in sustainability of 0.088% compared to the pre-disaster level, which contributes permanently to reducing vulnerability to future disasters. (2) only 21.81% (compared to the actual scenario) of the rescue funds is needed to support 30% reduction action plus 0.02% sustainable improvement. But to support the 50% recovery action, 78.92% of the rescue funds is needed. This paper aims to provide a new perspective for the refined dynamic assessment of resilience and to prove the role of resilience in promoting short-term post-disaster recovery and long-term sustainable development. [ABSTRACT FROM AUTHOR]

Collaborative consumption in the fashion industry has been put forward as a way to overcome current challenges of the 'take-make-use-dispose' economic system that is currently dominating the market, and has gained interest from practitioners, academics, and policy-makers. The purpose of this paper is to explore the state of collaborative fashion consumption research across various disciplines by critically reviewing and synthesizing this fragmented body of work. To do so, this systematic literature review critically evaluates where, how, and what research has been conducted on collaborative consumption in the fashion context, by further outlining gaps and a future research agenda. The paper reviews publications between 2004 and 2020 within peer-reviewed journals written in English, focusing on product service systems, access-based consumption, and collaborative consumption as key words. The analysis demonstrates that scholarly work addresses issues of terminology, attitudes, and motivations, specific modalities of engagement and practices of use and disposal, as well as business models that can help facilitate collaborative fashion consumption. The review also highlights that various gaps remain that require further enquiries, arguing that a deeper and more critical research agenda is required in order to provide a coherent terminology, better understand motivations to uptake collaborative consumption practices, as well as more cross-country analysis. [ABSTRACT FROM AUTHOR]

• A global optimal flow pattern for unbalanced distribution systems is proposed in this paper. • The proposed global optimal flow pattern is the lower bound of the feeder reconfiguration for loss minimization problem. • A first order estimation search strategy is developed to find a near optimal solution in a very short time. • A modified branch and bound search strategy is proposed to locate the global optimal solution. The loss minimization has been an important optimization problem in distribution systems because of the economic incentives. The state-of-the-art feeder reconfiguration for minimizing unbalanced distribution systems' losses cannot prove the optimality of solutions mathematically due to the non-convexity of the problem. This paper proposes a global optimal flow pattern of feeder reconfiguration to provide a best start point and convergence direction for search strategies. The global optimality and the uniqueness of the global optimal flow pattern are proved. Therefore, the loss of the global optimal flow pattern is the lower bound of the feeder reconfiguration for loss minimization. Two global optimal flow pattern-based search strategies are developed to find the global or near optimal solutions. The performance of the proposed algorithms is validated with three test systems for different application scenarios. Test results demonstrate that the efficiency of the search strategies is greatly improved by the global optimal flow pattern and the optimality of solutions can be verified. [ABSTRACT FROM AUTHOR]

With the general recognition of the awareness of carbon neutrality, economic development growth momentum for carbon neutrality scenario has become research focus. This paper introduces the carbon neutrality double input level based on the perspective of the initiative, consciousness, and self-discipline of firms and residents to practice green low-carbon behavior. By constructing a balanced economic system of green low-carbon behavior, this paper explores the new endogenous growth power in production and consumption, and finds that there exists a carbon neutrality realization regulation of green low-carbon behavior in the new system. Based on the penetration capacity of green low-carbon behavior, this paper studies the endogenous growth law of economic system driven by the evolution of carbon neutrality double input level. The production and consumption processes are considered in the new economic system in this paper, the production of green low-carbon goods is considered in the production sector and the technical equation under carbon neutrality double input level is studied, the consumption process of green goods affected by environment and carbon emissions is considered in the household, then the household utility function is constructed, and the new growth rate is obtained. Using carbon emissions growth rate of green low-carbon goods and its relationship with absorption rate derive the carbon neutrality realization regulation. Then the general equilibrium solution and growth rate under endogenous growth driven by carbon neutrality double input level are also obtained. Furthermore, the carbon neutrality effects which are the endogenous effect of carbon neutrality double input level and the effect of carbon neutrality realization regulation are obtained by numerical simulation and empirical analysis. [ABSTRACT FROM AUTHOR]

As the division of work within the world economic system becomes increasingly complex, the impact of disturbing events on the economic system is expanding. Recently, Japan proposed to discharge nuclear wastewater into the Pacific Ocean, which will cause damage to marine fisheries, thereby seriously affecting fisheries and other industries in Japan and other countries and regions around the world. Considering different scenarios of final and intermediate demand shifting, this paper uses the Inoperability Input-Output Model (IIM) and Multi-Region Input-Output Model (MRIO) to simulate the economic consequences of nuclear wastewater discharge in Japan and calculate the economic changes of each industry and country (region). The results show that: In the short term, when only the final demand for Japanese fishery products decreases. (1) The ten countries (regions) with significant economic losses are Japan, the United States, Chinese Taipei, Canada, Chile, South Africa, Mexico, Peru, the United Kingdom, and Ireland. (2) The ten countries (regions) with a significant increase in total output due to demand shift are China (People's Republic of), the Rest of the World, India, Indonesia, Viet Nam, the Philippines, Brazil, Myanmar, the Russian Federation, and Malaysia. (3) A ranking of changes in the total output of different industries. In the long term, when both intermediate and final demand for Japanese fishery products decrease. (4) The change in value added in Japan. (5) The change in value added of 67 countries (regions) worldwide. The ten countries (regions) with the most significant increase in value-added are the Russian Federation, China (People's Republic of), the Rest of the World, the United States, Indonesia, Australia, Norway, Korea, Viet Nam, and Myanmar. The ten countries (regions) with the most significant decrease in value-added are Japan, Chinese Taipei, Chile, South Africa, Peru, Thailand, Mexico, Cambodia, Costa Rica, and Morocco. Changes in value added of 45 industrial sectors worldwide. • The impact of Japan's nuclear wastewater discharge on the global industrial economy was estimated. • Negative impacts of the shift of intermediate goods on the Japanese economy are more significant than that of final goods. • Economic losses of countries (regions) and industries caused by reduced demand for fishing products were ranked. • Economic growth of countries (regions) and industries driven by substitution of demand for fishing products were ranked. [ABSTRACT FROM AUTHOR]

• The study presents a comprehensive review on optimal economic dispatch in single and multi-area power system. • The review covers the formulation of the MAELD; cost functions and constraints and techniques applied in its solution. • The relationship between the MAELD and other ancillary services such as unit commitment, electrical vehicle, smart grid and demand side management is concisely reviewed. • Optimal economic dispatch carried out in centralized and non-centralized (decentralized and distributed approaches established devoid of central operator) is comprehensively surveyed. • The central aim of the review is to establish state-of-the-art in the multi-area economic dispatch and identify future research avenues for improving the existing techniques and developing novel ones. Efficient and cost-effective coordination of online generation facilities is essential to the reliable operation multi-area power system (PS) especially in a deregulated environment. This made multi-area system economic load dispatch (MAELD) one of the most crucial services in modern PS due to economic and environmental considerations. The aim of MAELD is to optimally compute the generation levels and cross-border energy trading between adjacent areas at a minimum cost of generation and transmission while fulfilling physical and operational constraints. MAELD problem can be solved using either centralized or decentralized approaches. Centralized approach requires a central coordinator that determines optimal conditions of the network. While the decentralized approaches decouple the network into several independent sub-units. The decoupling approach devoid of central operator improves data fidelity, information privacy, and decision independence among the adjacent areas. This paper comprehensively reviews the recent advances in MAELD, which covers the problem formulation and techniques applied for the solution. The relationship between the MAELD and other ancillary services such as unit commitment, electrical vehicle and demand side management is concisely reviewed. The cornerstone of the survey is to establish state-of-the-art in the MAELD and identify future research avenues for improving the existing techniques and developing novel ones. [ABSTRACT FROM AUTHOR]

• A distributed solar hybrid CCHP system is constructed by using PV/T panels. • A bi-level sizing optimization model of the PV/T-CCHP system is established. • The economic, energy, and environmental objectives are considered. • The impacts of solar energy and energy storage equipment are quantitatively evaluated. In this paper, a distributed solar hybrid combined cooling, heating, and power (CCHP) system is constructed by installing photovoltaic/thermal (PV/T) panels in the CCHP (PV/T-CCHP) system. A bi-level optimization model is established to obtain the optimal sizing of the equipment in the PV/T-CCHP. The upper-level optimization model is formulated as a multi-objective optimization problem, which considers the economic, energy, and environmental performance of the PV/T-CCHP system compared with the conventional separated production system. The equipment sizing results obtained by the upper-level optimization model can achieve the trading off in terms of cost, primary energy consumption, and carbon emission reduction. The lower-level optimization model, which is formulated as a mixed-integer linear programming, determines the operating strategy of the PV/T-CCHP system. Non-dominated sorting genetic algorithm-II is employed to solve the upper-level optimization model. The final optimal sizing results are obtained from the Pareto solution set leveraging fuzzy decision theory. The optimal sizing results demonstrate that PV/T-CCHP saves 5.82% in annual total cost, 22.63% in annual primary energy, and 37.51% in annual carbon emissions reduction, which verifies the effectiveness of the proposed optimization model. In addition, the impacts of solar energy and energy storage equipment on the system performance are quantitatively evaluated. [ABSTRACT FROM AUTHOR]

Basin water ecological compensation is an effective means of coordinating environmental protection and economic development and promoting sustainable development. A reasonable compensation interval (the value range of the compensation standard) is the basis for final pricing. At present, the calculation method of the compensation interval has not been unified in the current research, and it is rarely considered comprehensively from the perspective of both parties of compensation. Based on the perspectives of upstream water resources suppliers and downstream water resources consumers, this paper proposes a water ecological compensation interval accounting method based on emergy analysis theory and water ecological footprint method. From the perspective of the supply side, the remaining ecological economic system services value supplied by the upstream area is taken as the lower limit; from the perspective of the consumer side, the value of ecological economic system services actually occupied by downstream areas is taken as the upper limit. Taking the Qingyi River Basin as an example, the results show that there is a serious ecological deficit in the lower reaches of the Qingyi River Basin, and reasonable compensation needs to be given to the supplier Xinzheng City; the accounting method based on dual perspectives is better than traditional. The method is more precise and greatly shortens the value range of the compensation standard. This study provides a novel and complete ecological compensation interval accounting method, which provides a more accurate and reasonable reference for the determination of ecological compensation standards in the basin, and helps the government to improve and implement the ecological compensation mechanism. • The study proposes a new quantification method of watershed compensation interval. • Different amounts of spillover value from different perspectives. • Lower Qingyi River has a high ecological deficit. • Compensation interval based on dual perspective is more accurate. • Compensation interval difference is mainly affected by downstream. [ABSTRACT FROM AUTHOR]

Moving towards a circular economy (CE) has become one of the main strategic initiatives on a global scale in the search for sustainable economic systems. However, the conceptual relationship between sustainable development and the circular economy is a matter of ongoing debate. In particular, the extent to which CE initiatives are contributing to the mitigation of resource extraction seems to be a still unclear topic. This paper investigates the relationship between the extraction of natural resources and the CE, and also analyses the effects of critical socioeconomic drivers such as economic and population growth and economic structures. The analysis is based on a panel data covering 28 European countries during the period 2010–2019. Results confirm that promoting a shift towards more circular economic systems can reduce the extraction of primary resources. However, the mitigating effect of CE initiatives remains rather marginal when compared to the impact of economic growth. Namely, estimates show that the primary resources extracted annually linked to economic growth are roughly four times the resources saved by CE initiatives. The findings provide evidence that the circularity of economic systems should be approached from a systemic perspective that includes both production and consumption as well as waste management. In particular, complementary measures addressing behavioural consumption are needed if we want to achieve a sustainable development. • GDP growth increases resource extraction 4 times more than the savings achieved by CE initiatives. • A 1% increase in GDP can increase resource extraction between 0,3 and 0,6%. • Promoting circular material use and circular economy activities contribute to reduce raw material extraction. • More effective policy interventions should be sought targeting behavioural consumption [ABSTRACT FROM AUTHOR]

• An optimization of eco-industrial structure considering economy-society-ecology. • A multi-objective optimization model meeting three dimensional objectives is built. • The hybrid ACO-PSO algorithm is applied to solve the model. • Optimized scenarios realize overall development of economic-social-ecological benefits. • The optimized scenarios with different tendencies promote different benefits. The establishment of ecological economic system has become the key to realize the transformation of China's economy from high-speed development to high-quality development. This paper considers the multiple goals of economic, social, and ecological benefits to achieve sustainable development. Firstly, it establishes an indicator system affecting economic, social, and ecological benefits to guide the construction of the subsequent model. Secondly, this study constructs a multi-objective optimization model for ecological industrial structure. According to the different emphasis of objectives, a hybrid approach based on ant colony optimization and particle swarm optimization (ACO-PSO) is implemented to solve the optimal solution set of feasible schemes. Finally, Sichuan Province is selected as the case study area, and three scenarios including economic oriented scenario, employment protection scenario and environment-friendly scenario are screened and analyzed. The results show that: (1) After reasonable optimization and adjustment of the industrial structure, it realizes the overall development of economic benefits, social benefits, and ecological benefits. The comprehensive benefits of sustainable development have been significantly improved. (2) The optimized scenarios with different tendencies promote different benefits. Decision makers can make better choices based on the diverse needs of the different development stage. [ABSTRACT FROM AUTHOR]

• A proposed design of a hierarchical multi-agent control system for a hybrid-energy isolated microgrid is presented. • The control system efficiently manages the energy resources to achieve optimal cost. • The designed system is decentralized and adaptive. • The control scheme ensures security and resiliency of the microgrid. Multi-agent control is widely recognized as an effective management system for modern microgrids. This paper proposes a hierarchical distributed multi-agent control system for an islanded microgrid with hybrid-energy resources and a battery-storage bank. The dispatchable dispersed generators are to be online-controlled to stabilize the islanded microgrid and minimize operation cost. A non-dispatchable agent is assigned to each bus with a non-dispatchable generator or a load. A dispatchable agent is assigned to each bus with a dispatchable generator. The control scheme is organized into three layers. The primary control layer comprises only the agent which runs the very fast local voltage/frequency droop-control of the battery-storage bank. It achieves a quasi-instantaneous power balance under any disturbance to maintain the frequency and voltage stability of the microgrid. The secondary control layer is formed by fast control algorithms on the dispatchable agents working at 2 ms time step. It is responsible for regulating the islanded microgrid frequency and voltage at minimum participation time of the battery-storage bank. The tertiary control layer is made by relatively slow control algorithms on the dispatchable agents working at a time step of 200 ms. It copes with the economic operation of the microgrid. Each agent behaves autonomously and shares data with others via communication links. The architecture and control algorithms of each layer are presented. Besides, the coordination protocol between different layers is described. The scheme is implemented by a parallel Matlab-Jade computing setup. Results of a case study islanded microgrid are analysed and compared to literature. [ABSTRACT FROM AUTHOR]

In the era of network economic development, the Internet of Things has become a key factor in economic growth and urban competitiveness. Inter-regional interconnection promotes economic growth, and urban economic growth provides innovative elements for regional innovation such as technology, capital, talent, and information. These elements are indispensable for the development and optimization of the innovation environment. On this basis, establish an urban economic network structure system based on the Internet of things, analyze the three relationships between the city's industrial structure and urban economy, urban economy and urban spatial characteristics, and the Internet of Things and urban network structure systems. The system framework, the construction process and the specific content of the framework are checked. The description method is suitable for the similarity analysis of complex network topologies and the evaluation of the effect of complex network scanning algorithms. The samples generated by the evolutionary network model are used to analyze the similarity of network topologies. Several different sampling algorithms are used to compare the evolution model samples and the empirical network samples to evaluate the sample results. The experimental results confirm the practicability and effectiveness of the description method. The data of the article is downloaded in the city's commercial network module through the Internet of Things. According to the relevant information of the city's commercial logistics, calculate the ratio of each interval to the overall to measure the economic development status. According to different development situations, set up indicators to measure traffic conditions, determine the causal relationship between quantities, and observe the relationship between data and urban economic management. The urban business network system based on the Internet of Things constructed in this paper provides reports on the transformation and upgrading of urban industries, enriches the urban distribution theory and the application of the Internet of Things, and provides Internet of Things reports and foundations for organization and management, surpassing the national bourgeoisie In the economic system, the efficiency of urban economic management has increased by more than 30%. • The samples generated by the evolutionary network model are used to analyze the similarity of network topologies. • Several different sampling algorithms are used to compare the evolution model samples and the empirical network samples. • The efficiency of urban economic management has increased by more than 30%. [ABSTRACT FROM AUTHOR]

This study deals with the analysis of regional economic development in Europe. Specifically, it examines the extent to which the performance and characteristics of higher education systems (HESs) influence regional economic development. The analysis employs data at the regional level, examining 649 NUTS-3 in 29 European countries, from 2014 to 2016. The empirical analysis, based on an original dataset that we developed, employs a novel methodological strategy that combines a traditional econometric approach with random forest. The findings detect the existence of nonlinear relationships between regional GDP per capita and HES indicators, which could have been overlooked by previous studies in the literature. Furthermore, the empirical results demonstrate the importance of comprehensively modelling the diversity of HESs, since distinct characteristics and performance can contribute differently to the economy of the regions. In particular, the most important factors for regional economic development are the size of HESs, the internationalisation of the students and research productivity. Finally, this paper provides useful insights for policymakers by suggesting new instruments for driving and fostering the economic development of their regions. [ABSTRACT FROM AUTHOR]

• Thermoeconomic performance of various HDH configurations is compared. • Single, double, and triple humidifiers are examined and contrasted. • The effectiveness of humidifiers and dehumidifiers influences freshwater production. • The water-heated multi-humidifier HDH cycle generates more freshwater. • A double humidifier air-heated HDH cycle generates fresh water at 2.06 $/m3. Drought has hit several water-stressed regions, with serious consequences for water and food security. In this regard, the low-cost and low-grade thermally driven humidification-dehumidification desalination cycle has good potential to provide freshwater in arid regions. From energy and economic point of view, different configurations of the humidification-dehumidification cycle have been proposed in the literature without a comprehensive comparison to identify the most suitable one. Thus, this paper investigates the thermal and economic performance of several multi-humidifier water- and air-heated humidification-dehumidification cycles. Thermodynamic models are structured to study the behavior of each cycle. The models rely on heat and mass transfer balances for each component. The effectiveness method is implemented for humidifiers and dehumidifiers to evaluate heat and mass exchangers. The models are validated using previously published data. The series seawater flow, triple humidifier, water-heated humidification-dehumidification cycle could deliver 151.2 kg/h of fresh water at a maximum temperature of 70 °C, with a gain output ratio of 1.995 and a specific cost of 2.73 $/m3. This cost rises by around 16% when a maximum temperature of 60 °C is employed. Results reveal that using a double-humidifier in an air-heated humidification-dehumidification cycle produces freshwater of 102.2 kg/h at the lowest price of $2.06/m3. It is concluded that the multi-humidifier water-heated humidification-dehumidification cycle produces more freshwater and less gain output ratio than the multi-humidifier air-heated humidification-dehumidification cycle. [ABSTRACT FROM AUTHOR]

Critical infrastructures (CIs) include the vital resources for the country's economic and health systems and should be kept secure. We face improvements in the Internet of Things which brings benefits and, at the same time, dependency for CIs. Internet of Medical Things (IoMT) is among the CI sectors that gather health-related information from patients via sensors and provide healthcare services accordingly. However, research has highlighted that this large-scale system opens the door to the patients' private data disclosure. Recent work has concentrated on proposing authentication schemes to address this challenge. Motivated by this, in this paper, we introduce a secure and lightweight authentication and key agreement model named Slight. We informally prove Slight's security and robustness against attacks and formally by using the Scyther tool. We analyze Slight's performance to show it causes minimal computational overhead (0.0076 ms) and comparable communication overhead (1632 bits), making it suitable for IoMT. [Display omitted] • We propose secure and lightweight authentication and key agreement model named Slight for IoMT environments to provide privacy and security of patients' health-related data. • The security of the proposed protocol is validated formally through the Scyther tool. • The proposed protocol provides resistance against well-known potential security attacks. • The performance analysis showed that proposed protocol is more efficient than other competing protocols in terms of computational and communication overhead. [ABSTRACT FROM AUTHOR]

Sustainable development goals (SDG) represent one of the pillars of the UN's 2030 agenda aiming to secure a more sustainable future for all nations. The 17 goals comprising the SDG framework form a transformative action plan that is designed to help nations achieve a more sustainable future focusing on their environmental, social, and economic systems. Achieving the goals within the designated timeframe, however, entails overcoming multiple challenges related to policy design, resources management, and harnessing the synergies and trade-offs among the goals themselves. Recognizing the vital role modeling and simulation can play in facilitating the achievement of the SDG, this paper provides a review of the academic literature published between 2015 and 2021 relating to the models developed to tackle SDG related issues. The main purpose of this review is to explore the modeling practices related to SDG and to determine how aligned those modeling practices are with the priorities of sustainability science. We developed a multi-dimension classification scheme to categorize the models retrieved from the literature based on their main characteristics focusing on characteristics such as the modeling approach used, model uncertainty treatment, model temporal and spatial scales, and which science priority the model focuses on. The results of this research show that most of the models focused on studying policy changes needed to achieve the SDG and monitoring the progress of the SDG. The results also highlight missing important characteristics in SDG models such as cross-scale treatment and advanced uncertainty treatment. While this research can be valuable in informing modelers about the gaps need to be filled in SDG modeling and facilitates the communication between modelers and policy makers, it can be further extended by including an evaluation for the modeling approaches used in SDG contexts as well as adding more characteristics to the model categorization scheme. [ABSTRACT FROM AUTHOR]