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The purpose of this paper is focused on introducing a new layout of an electricity and liquid hydrogen cogeneration power plant and evaluating its performance from the exergo-economic and environmental stand points. The system is based on the combination of a biomass gasification gas turbine cycle, a Rankine cycle, an electrolyzer unit, and a hydrogen liquefaction cycle. A parametric model is firstly developed to study the sensitivity of the system performance on the main design parameters (including biomass flow rate ṁ biomass , gas turbine inlet temperature T GT , compressor pressure ratio PR, and steam turbine inlet pressure P SRCT). Afterward, the optimal operation of system is selected using by a multi-objective optimization approach. The observations revealed that m ˙ biomass is the most effective design parameter. The optimal design parameters are obtained as ṁ biomass = 1.94 kg/s, T GT = 1421 K, PR = 5.52, and P SRCT = 3886 kPa, which results in the maximum electricity and hydrogen production of 3377 kW and 14.8 kg/h together with minimum total cost rate of 86.61 $/h. At this condition, the optimal environmental index is 1.09 kg CO₂ /kWh. • Optimizing proposed system is determined. • The subsystems are biomass unit, SRC, and PEM electrolyzer. • Tri-objective optimization and economic analyses are applied. [ABSTRACT FROM AUTHOR]

Multimodal transport is an effective method to reduce the energy consumption and carbon dioxide (CO 2) emissions in transportation sector. Evaluating the low-carbon performance is a prerequisite for developing multimodal transport. This paper establishes the new cross-efficiency (CE) network data envelopment analysis (DEA) approach, and applies it to evaluate low-carbon efficiency of railway-waterway intermodal transportation (RIT) in China from 2017 to 2022. The proposed approach takes advantage of network DEA and considers the internal structure in the RIT system as well as the interconnections between various transportation modes. This article comprehensively analyzes the evaluation results in terms of the overall situation, geographic distribution characteristics, internal stages and links, external influencing factors, and efficiency prediction, and the results find that: (1) the low-carbon efficiency of China's overall RIT needs further improvement. (2) The geographical distribution shows a trend that the efficiency in the Northern Region is higher than that in the Southern Region. (3) The level of urban industry, external transportation conditions, and foreign trade development will all affect the performance of RIT. Finally, according to the empirical results, management strategies are proposed. The main contributions include: proposing a network-structured CE-DEA method focusing on internal states; The advantages of CE network DEA are utilized to study CO 2 emissions of multimodal transport; The low-carbon efficiency of RIT in China is comprehensively analyzed. This study enriches the research on DEA methods, and the results can provide a basis for decision-making by the government and transport enterprises, help promote the development of low-carbon transport in China, and provide a reference for the optimization of multimodal transport in other countries. • Constructed a cross-efficiency DEA approach. • Analyzed the low-carbon efficiency of multimodal transport. • Discussed the distribution and influencing factors of efficiency. [ABSTRACT FROM AUTHOR]

• Identifying a common best practice frontier most similar to management goals. • The possible additional benefits generated from the global reallocation. • The stepwise reallocation paths for DMUs with limited reallocation potentials. • The case study based on 18 ports in Korea. Common benchmarking can identify a common best practice frontier as the benchmark to assess and improve the performance of Decision-Making Units (DMUs) experiencing similar circumstances. At present, further exploration in common benchmarking is still needed. For instance, the similarity between management goals and targets belonging to a common best practice frontier. To fill this gap, we propose the following innovative work: (1) A novel Data Envelopment Analysis (DEA) model is proposed to identify a common best practice frontier on which targets closest to management goals can be found for all DMUs experiencing similar circumstances. These targets need to be achieved through a global reallocation of inputs/outputs among DMUs; (2) Considering the targets closest to management goals are too ambitious for some DMUs, an iterative algorithm is given based on another new DEA model for providing the stepwise reallocation paths. The stepwise reallocation paths can distribute the total reallocation efforts into several intermediate steps; (3) The effectiveness of the proposed model and algorithm is illustrated by applying them to a case of 18 ports in Korea. For this purpose, we use the input–output data set of these ports in 2010 and assume actual management goals for every port. The results of the case show some conclusions. First, the target of each port located on the common best practice facet is closest to its management goal. Second, global redistribution can make all ports obtain the best input–output levels. Third, ports with limited reallocation potential can monotonically and gradually achieve their distant targets through our stepwise schemes. [ABSTRACT FROM AUTHOR]

How to reasonably evaluate the performance of scientific research activities in universities has attracted people's extensive attention. This study identifies the scientific research activity of Chinese universities as a two-process system with three sub-stages, including technical accumulation and research commercialization processes. Where, the process of technical accumulation includes the production of scientific research and patenting stage, while the process of research commercialization is a separate stage. First, this study proposes a network DEA model with two processes and three sub-stages to evaluate and decompose the performance of scientific research activities in universities. Secondly, taking 61 Chinese universities in the "Double First-Class" initiative (DFIU) as examples, this study evaluates the overall efficiency, stage efficiency and coordination efficiency of scientific research activities in Chinese universities. The final main conclusions are as follows: (1) The average score associated with the transformation efficiency of scientific research achievements based on the internal structures is only 0.2406, lower than the CCR efficiency and merger efficiency, indicating that most universities are still facing problems such as low resource utilization efficiency or unsatisfactory results. (2) The universities in the "First-class Discipline" construction plan (UFDCP) have outstanding performance in the technical accumulation process and the production of scientific research stage. Professional characteristics universities are generally much less efficient than polytechnic universities and comprehensive universities. (3) The universities in the "First-class Discipline" construction plan (UFDCP) are better than the universities in the "First-class Universities" construction plan (UFUCP) in terms of average efficiency values and polytechnic universities are better than other types of universities in terms of average efficiency values. We can find part of the reason for this difference in average efficiency from the evaluation of coordination efficiency. • This paper analyses the internal structure and internal operating mechanisms of research activities in universities. • Constructed a two-process network model with three sub-stages as a method to deal with unique efficiency decompositions. • The coordination efficiency of university scientific research system is calculated. [ABSTRACT FROM AUTHOR]

Most literature focusing on the issue of ship pollutant emission and diffusion is based on static meteorological conditions. The relevant literature seldom analyzes the emission and diffusion of ship pollutant gas according to real-time meteorological data when wind direction, wind speed and other meteorological conditions have changed. This paper presents a fast translational diffusion algorithm, and empirically demonstrates it through ship and meteorological data from the Huangpu River field in Shanghai. First, CO 2 emissions were estimated using the actual speed of the ship engine changed under the influence of variable wind, and simulation analysis was performed to the scenario of hourly diffusions. The research findings are as follows: In comparison with the traditional algorithms, the fast algorithm can significantly improve calculation efficiency, save calculation time and achieve the long-distance and long-time parallel calculation of multiple ships. As proven by the empirical research using the ships on Huangpu River in Shanghai, the maximum difference of CO 2 emissions is 34.5%, 36.85% and 19.97% respectively after upwind, downwind and real-time meteorological conditions are taken into account. The research finding indicates that wind direction changes have a greater impact on the carbon emission of ships. • Air pollutant emissions and dispersion from ships under variable wind conditions were calculated. • A fast translational diffusion algorithm was used to efficiently simulate multi-vessel, long-distance diffusion in real time. • Ship and meteorological data from the Huangpu River field in Shanghai were validated. • Empirical analysis in variable wind direction scenario shows that the difference in CO2 emissions can be up to 36.85%. [ABSTRACT FROM AUTHOR]

The cruise industry, which serves as a prominent exemplar of globalized business, is characterized by unique features that render its supply chain operations highly susceptible to various risk factors, thereby giving rise to significant consequences. Evaluating the risks associated with major disruptive events and enhancing the robustness of the cruise supply chain have become crucial issues of concern for various stakeholders. This study first develops an indicator evaluation system for assessing the risks of China's cruise supply chain, drawing upon relevant literature and expert interview opinions. Secondly, set pair analysis is utilized to identify the scores and trends of risk indicators in China's cruise supply chain. Thirdly, the Set pair analysis-Markov chain model is employed to forecast the future risk status of China's cruise supply chain system, and the influence of different weights on the prediction results is discussed. Finally, the risk evolution network of China's cruise supply chain is constructed to identify common risk consequences and visualize the evolution path of risk events, with the aim of providing reference for the formulation of prevention and control measures. The findings of this article have important consequences for improving risk mitigation strategies and enhancing the resilience of the cruise supply chain. [ABSTRACT FROM AUTHOR]

The transportation industry is the main source of carbon dioxide (CO 2) emissions, and the development of multimodal transport is conducive to reducing transportation carbon emissions. In order to evaluate the low carbon efficiency of multimodal transport, this article proposes a cross efficiency data envelopment analysis (DEA) method for complex network structures from the perspective of fairness, and takes China's rail-water intermodal transport as an example for research. The proposed method includes two secondary goal models that reduce the unreasonable differences between self-evaluation and peer-evaluation and treat all stages within the network system equally. Then, the improved entropy weight method is used to aggregate the cross efficiency. In addition, a numerical example is given to verify the effectiveness of the proposed method. The results of the case study show that the efficiency of Tangshan Port and Rizhao Port is relatively high, and others should learn from the successful experiences and develop improvement strategies based on their own characteristics. The conclusions can provide reference for transportation enterprise management and policy formulation, and the proposed method can be widely applied to the performance analysis of enterprise network, industrial chain, and supply chain. [Display omitted] • A novel cross efficiency DEA model is proposed. • The proposed approach includes two secondary goal models. • The low carbon efficiency of multimodal transport is evaluated. [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]

With the increasing trend of global warming, the frequent occurrences of natural disasters have brought serious challenges to the sustainable development of the society. Therefore, emergency decision making (EDM) for natural disasters plays an increasingly significant role in improving the capability to respond disasters. In this paper, we first elaborate the concept and characteristics of EDM for natural disasters and briefly expound emergency decision contents in different stages of natural disasters. Then, an overview is provided for the EDM theory and methods of natural disasters from the methodological perspective. After that, we give a detailed illustration of the construction of emergency decision support system. Finally, we summarize the main conclusions of the paper and point out the prospect of future researches. [ABSTRACT FROM AUTHOR]

Under the background of climate change, the haze days in China have increased significantly, which seriously hinders the sustainable development of society and arouses wide attention from the public. However, the researches on the effect of air pollution on the stock yield of heavy pollution enterprise in key control cities are quite limited, This paper collects the Air Quality Index (AQI) from key control cities above prefecture level in China as well as the stock yield data of these cities’ heavy pollution enterprises in December from 2014 to 2016 and through multi-discontinuities regression model, testes the effect of air pollution on the stock yield of heavy pollution enterprise. The results show that: (1) Heavy air pollution (AQI = 300) has negative influence on the stock yield. (2) There exists time effect of air pollution on stock yield. Since the year 2014, heavy air pollution has exerted significantly negative influence on the stock yield in that 2013 may be the “first year” when the Chinese society began to take air pollution seriously. This paper gives a brief discussion on the cause of it and suggests that severe air pollution should be strictly controlled. Only by facing air pollution seriously, can we eliminate air pollution with collective wisdom and concerted efforts and achieve the sustainable development of city. Being the first study to look into the effect of air pollution on stock yield in key control cities in China, this paper provides empirical reference for government supervision departments, stock investors as well as enterprises. [ABSTRACT FROM AUTHOR]

Competition and cooperation in the environmental governance of cities are popular around the world. However, empirical research based on the prefecture-level city level in China is rare. Since the central government of China proposed to strengthen the construction of ecological civilization, whether there are strategic interactions of "race to the bottom" or "race to the top" among local governments is an important issue of academic and public interest. This paper constructs a game-theoretic model to reveal the strategic interactions of environmental governance among local governments. And then, based on the data of 221 prefecture-level cities collected from 2007 to 2018, the spatial econometric model is used to conduct multi-dimensional testing "race to the bottom" behavior of environmental protection expenditure among local governments. Moreover, this paper further analyses the impact of performance assessment indicators on the strategic interactions of local governments, so as to provide policy reference for improving environmental public welfare. Empirical results suggest that local governments in China show strategic imitation in environmental protection spending decisions, which is manifested as "race to the bottom", and this behavior is gradually weakening with the strengthening of environmental protection assessment. Furthermore, environmental performance indicators relieve the government's strategic imitation, while economic performance indicators intensify the government's strategy imitation. Thus, reasonable performance evaluation indicators are conducive to benign strategic interaction among governments. Finally, the current environmental protection expenditure has not yet significantly affected pollution reduction, providing new evidence for the "race to the bottom" behavior of local governments. Based on the findings of our study, the central government should optimize the performance evaluation system of local officials and strengthen the implementation of the environmental supervision system and accountability mechanism. Meanwhile, the local governments should further increase environmental protection expenditure, and enhance the supervision and utilization efficiency of environmental protection funds. • Strategic interaction among 221 prefecture-level cities in China was multi-dimensionally studied. • It has been found that China's local governments have strategic imitation as "race to the bottom". [ABSTRACT FROM AUTHOR]

• A novel method that achieves optimal allocation efficiency is proposed. • Our novel method can lead to less economic losses of cities in China. • The deprivation coefficient per capita was used for the fairness of the method. • A case study on 27 polluted cities with high homogeneity in China is conducted. Rational allocation of pollutant emission rights is one of the ways to promote the sustainable economy and environment of cities. Based on the overall goal of emission reduction in the 13th Five-Year Plan proposed by China, the Yangtze River Delta city agglomeration with high homogeneity is selected as the research object, and three allocation models of SO 2 emission rights are established using data envelopment analysis (DEA), shadow price and information entropy. The fairness of the three allocation schemes is evaluated by the per capita relative deprivation coefficient (RDC). The study shows that: (1) the three-objective information entropy allocation model takes into account the principles of maximum output-input efficiency, protection of regional GDP and scheme fairness, and the relative deprivation coefficients (RDCs) are all less than 0.5, which can be used as the best scheme for SO 2 emission rights allocation in the Yangtze River Delta city agglomeration. (2) Cities in Jiangsu province need to reduce SO 2 emissions. (3) Taking city agglomerations with high homogeneity as the research object has more practical significance, which can provide policy advice for sustainable development of similar city agglomerations. [ABSTRACT FROM AUTHOR]

Contrary to the conventional approach that utilizes the planar electrode model to achieve the electrochemical parameters of the electrode in flow batteries, this work proposes an intelligent cyclic voltammetry (CV) analysis method to accurately capture the electrochemical parameters of the carbon-based porous electrode: (i) the transient diffusion process is elaborated by the Fick's second law; (ii) the thin-layer diffusion boundary condition is determined based on the structural characteristics of porous electrodes; (iii) CV response on the porous electrode is obtained by the Bulter-Volmer equation in assocition with the Fick's first law; and (iv) the electrochemical parameters of the porous electrode are automatically extracted from the experimental data via the genetic algorithm. The feasibility of the intelligent CV analysis method is proven by studying the electrochemical parameters including the diffusion coefficient D and the standard rate constant k 0 of [ Fe (CN) 6 ] 4 − / [ Fe (CN) 6 ] 3 − . Additionally, this analysis method is applied to investigate the vanadium redox flow battery by providing accurate electrochemical parameters for the 3D multi-physics model to predict the charge/discharge performance at different current densities. The simulation results demonstrate a maximum relative error of 2% in comparison to the experimental data, suggesting the good reliability in developing the advanced model. The proposed intelligent CV analysis method provides a potential application in accurately capturing the electrochemical parameters in other electrochemical energy conversion and storage devices. [Display omitted] [ABSTRACT FROM AUTHOR]

Schematic diagram of the research framework: A new network DEA method. [Display omitted] • A new network DEA allocation model considering cross-border transmission of SO 2. • The WRF-CMAQ is combined with the DEA allocation model for the first time. • The principles of optimal efficiency, GDP protection and fairness is considered. • The per capita relative deprivation coefficient was used to evaluate the fairness. • The new network DEA model is a powerful tool for SO 2 emission rights allocation. Currently SO 2 emission rights are allocated without considering the cross-border transmission characteristics of pollutants, and the allocation scheme cannot reflect the fact that air pollutant overflows in space. In this paper, the WRF (Weather Research and Forecasting Model)-CMAQ (Community Multiscale Air Quality) is combined with the data envelopment analysis (DEA) allocation model for the first time, and a two-stage (Stage-1: SO 2 formation, Stage-2: SO 2 treatment) network DEA allocation model is proposed with the SO 2 spatial transmission taken as the intermediate output or input index between decision-making units. Based on the principles of efficiency, economic protection and fairness, the model is applied to the study of SO 2 emission rights allocation in the Yangtze River Delta city agglomeration with high homogeneity in China. The results show that: (1) When the weight coefficient (α 1) in stage-1 is 0.7, 0.8 or 0.9, the per capita relative deprivation coefficient (PRDC) of each decision-making unit (DMU) is less than 0.5 in the allocation scheme, indicating that our scheme can be used as a reference to allocate emission rights in the Yangtze River Delta city agglomeration. (2) With great robustness and universality, our allocation model allows decision-makers to adjust the GDP constraint coefficient and the weight coefficients in the two stages according to their preferences, so as to obtain the optimal allocation results. The model proposed in this paper can help decision-makers to formulate effective policies to reduce pollutant emission, and promote energy conservation & emission reduction and coordinate environmental governance in regions of city agglomerations. [ABSTRACT FROM AUTHOR]

Regional planning plays an important role in controlling air pollution in urban agglomerations with spatial spillover characteristics. This paper empirically examines the control effect of the Development Plan for the City Cluster in the Yangtze River Delta (Plan). We first use a spatial autoregression (SAR) model to analyze the spatial and temporal effects of air pollution in 41 cities in the Yangtze River Delta (YRD) from 2011 to 2018. We then use a difference-in-difference (DID) model to investigate the implementation effect of the Plan. Finally, we combine the SAR and DID models and study the Plan 's spatial effect of pollution between cities. Our empirical findings reveal the spatial correlation of air pollution between cities in the YRD and show that the Plan has significantly reduced the annual average fine particulate matter (PM 2.5) concentration. This paper enriches the literature about effects of socio-economic plans and provides an empirical reference for collaborative management of air pollution in city clusters. • A spatial autoregression (SAR) model was used to analyze the spatial and temporal effects of air pollution. • The control effect of the Development Plan for the City Cluster in the Yangtze River Delta (Plan) was empirically examined. • Empirical findings reveal the Plan has significantly reduced the annual average fine particulate matter (PM 2.5) concentration. [ABSTRACT FROM AUTHOR]

It is an urgent task for China to control haze emission in environmental treatment. Emission right trading is a feasible way to achieve the reduction of pollutant emission on the premise that the total pollutant emission amount is under control, and the allocation of initial emission rights based on the target total amount is the key to emission right trading. In this paper, via the input-oriented ZSG-DEA model, the inter provincial allocative efficiency of PM 2.5 emission rights is investigated under the condition that the target total amount is fixed. The results showed that (1) after initial emission rights were allocated in accordance with the ZSG-DEA model, PM 2.5 emission amounts of all provinces would be in a new common DEA frontier so as to realize the overall Pareto optimality with a set total amount; (2) two factors, namely land areas and atmospheric environmental capacities of all provinces, were considered in the actual allocation to avoid the homogenization of all evaluated units found in the previous evaluation literature on allocative efficiency, thereby making the evaluation results more in line with the actual situations in all provinces. Such an investigation approach can provide guidance on the allocation of initial emission rights in emission right trading; and the research results can offer empirical support for haze-reducing work load conducted by central and local governments of China. [ABSTRACT FROM AUTHOR]

The systematic development of the hydrogen energy industry is inseparable from government subsidies and co llaboration among enterprises in the industrial chain. Unlike existing studies on the overall impact of government subsidies on enterprise economic profits, this study discusses the impact of research and development (R&D) and production subsidies on the economic profits of upstream and midstream enterprises in the hydrogen energy industry chain. The empirical results based on hydrogen-related A-share listed enterprises from 2011 to 2019 in China show that the government's R&D and production subsidies have effectively improved the economic benefits of hydrogen energy enterprises. In particular, government R&D subsidies significantly improve the economic profits of upstream enterprises, whereas production subsidies have insignificant effects. For midstream enterprises that produce hydrogen fuel cells, the economic effect of government production subsidies is more significant than that of R&D subsidies. The results of this study may provide references for optimizing the distribution of subsidies in the hydrogen energy industry chain and promoting the sound development of the hydrogen energy industry worldwide. • Government subsidies promote the profit of hydrogen energy enterprises. • R&D subsidies promote the profit of upstream hydrogen energy enterprises. • Production subsidies are more effective for midstream hydrogen energy enterprises. [ABSTRACT FROM AUTHOR]

The Japanese government intended to discharge more than 1.2 million tons of nuclear wastewater from the Fukushima Daiichi Nuclear Power Plant into the Pacific Ocean, arousing great attention from governments and people around the world. Using the Global Trade Analysis Project (GTAP) model, this article describes the impact of this event on the economic output of global countries and regions under different scenarios. The empirical results showed that: (1) The negative effects caused by nuclear wastewater discharge would reduce the GDP of affected areas, while other unaffected areas will increase. The total global social welfare loss could reach up to 219.8 billion U.S. dollars, accounting for 0.26% of global GDP in 2020. In addition, this negative impact would increase with the expansion of nuclear wastewater. (2) The discharge of nuclear wastewater would increase the trade imbalance between several regions and reduce the total production value of most countries or regions. This paper evaluated the economic losses caused by the discharge of nuclear wastewater on global countries or regions, and further revealed the negative consequences of the discharge of nuclear wastewater into the ocean. [Display omitted] • The GTAP model assessed the impact of Fukushima nuclear wastewater discharge on the global economy. • The total global social welfare loss will reach up to 219.8 billion U.S. dollars. • The nuclear wastewater discharge would reduce the GDP of affected areas, while other unaffected areas will increase. [ABSTRACT FROM AUTHOR]

• A dynamic general equilibrium model about air pollution in china was established. • Empirical impacts of environmental regulation on air pollution in china were analysed. • Reasons about recent decline in china's air pollution were provided. In recent years, the average concentration of PM 2.5 in China's air pollution has generally declined, but literature discussing reasons for the decline are scarce. This study provides an explanation of the reasons for the decline in China's air pollution through theoretical model construction and simulation. Firstly, a DGE (Dynamic General Equilibrium) model, including time and space dimensions, is used to describe the mechanism for energy structure adjustment and environmental regulation affecting air pollution in China. Secondly, the parameters of the theoretical model are adjusted for simulation. The simulation results show that the government environmental control has positive policy effect, both in reducing air pollution and in promoting economic growth, while energy structure adjustment only works in curbing air pollution. Further simulations found that the effectiveness of government environmental control depends on whether there are regional differences in policy implementation and the choice of policy paths. Thirdly, panel data from 286 cities at prefecture level and above in China from 2010 to 2018 verified the simulation. The empirical results verified the availability of government environmental control and energy structural adjustment in improving air quality. From the analysis of heterogeneity, the government environmental control showed better air pollution control effect in big cities, and the policy effect of government environmental control was gradually improving over time. The following policy implications are proposed: research on alternative energy sources, adjustment of energy structure, and the coordinated development of government environmental control in various regions are the main strategies for improving air quality. Adopting the "fast first and then slow" governance policy, designing the "north first and then south," and "heavy first and lighter" air pollution control measures can achieve better control effects. Figure 1 Research framework [Display omitted] [ABSTRACT FROM AUTHOR]

Accurate evaluation of emission governance efficiency can build fundament to develop haze control strategy towards sustainable development. By features of the haze, we view the haze formation stage as the first sub-process and the haze control stage as the second sub-process. This paper proposes an additive aggregation network data envelopment analysis (DEA) model with undesirable intermediate measures and undesirable outputs, which have not been thoroughly studied in previous literature. We found the newly developed network DEA model was nonlinear and cannot be converted into a linear program, and then developed an improved second-order cone programming approach to solve this problem. After analyzing the data of haze control in China, we drew the following conclusions: Firstly, different weights of preference for two sub-process can lead to the variation in the overall efficiency. Under different weights of preference, although the efficiency of the haze formation has a very small change in some provinces, the efficiency of the haze control has a large change. Secondly, decision makers can achieve the adjust goal of reducing haze by adjusting their preferences on the information of the haze formation and haze control stages, which are helpful for policy making in haze control strategy and sustainable development. [ABSTRACT FROM AUTHOR]

Shipping management has an essential influence on the development of shipping industry. Management efficiency is one of the important indexes to measure the quality of shipping management. This paper aims to assess the management efficiency from a new perspective of congestion index to point out the causes affecting efficiency and provide suggestions to the shipping company. Based on a two-stage data envelopment analysis, we establish a novel congestion management system to comprehensively examine the organization's congestion from three aspects, including the macro-level, the micro-level, and resource allocation. Accordingly, we apply three congestion models, namely stage congestion, slack-based congestion, and resource reallocation congestion, respectively, to measure Hapag-Lloyd's congestion index from 2017 to 2020. We find that: 1) Hapag-Lloyd's capacity is higher than its market share; 2) major events (e.g., merger and acquisition, COVID-19) have significant impacts on the congestion index of the company; 3) excessive redistributable resource input invalidate the congestion index. [Display omitted] • The management efficiency of shipping company was assessed by a two-stage data envelopment analysis. • A novel congestion management system was established to comprehensively examine the organization's congestion. • It is found that COVID-19 have significant impacts on the congestion index of the company. [ABSTRACT FROM AUTHOR]

With the acceleration of industrialization and urbanization, the problem of air pollution in China has become increasingly serious. Particulate matter (PM) is a representative indicator of pollutants, and it is of great significance to carry out targeted treatment by studying its periodicity of concentration. In this paper, as a data mining information technology, the Empirical Mode Decomposition-Wavelet Analysis (EMD-WA) model is used to conduct a multi-scale periodic study of the PM 2.5 concentration time sequence in the Yangtze River Delta region in China and it is found that: (1) through the decomposition and reconstruction of the EMD-WA model, the period characteristics of four scales from short to long can be obtained, which are seasonal, short, medium and long period terms respectively; (2) the PM 2.5 concentration in the Yangtze River Delta region shows obvious multi-scale periodicity for the four scales, which includes a seasonal cycle of 46 days (about 1.5 months), a short cycle of 101 days (about 3.5 months), a medium cycle of 294 days (about 10 months), and a long cycle of 671 days (about 22.5 months), respectively. (3) The results are consistent in terms of season, short and middle cycle scales, in north (Jiangsu), east (Shanghai), south (Zhejiang) and west (Anhui) of the Yangtze River Delta region, but there are significant differences in the terms of long cycle scales. (4) The PM 2.5 concentration still shows obvious periodicity within 240 h during severe haze in the Yangtze River Delta region. This paper provides a framework for the government to make policies on energy conservation, emission reduction and air pollution control, and also provides a strong basis for haze prediction. [ABSTRACT FROM AUTHOR]

The output loss between cooperation and non-cooperation strategies for areas 1–4 (2012–2016). • Environmental control parameters are set to manipulate multiple situations. • Non-equal proportional change of indices and preference coefficient for ports are proposed. • A distance formula of expected output for PM emission reallocation is provided. • New DEA models are applied to 11 Chinese main ports. The emission of particulate matter (PM) and other atmospheric pollutants in port operations and shipping have caused a huge negative impact on the environment. Consequently, how to evaluate the environmental efficiency of ports and put forward corresponding countermeasures on this basis is becoming a more important issue than ever before from the perspectives of the government, academia, and society. We construct three data envelopment analysis (DEA) models to evaluate the environmental efficiency of ports under the circumstances of environmental control, non-environmental control and PM emission through inter-ports cooperation. The innovation of the DEA models constructed in this paper lies in: (1) Setting environmental control parameters to uniformly manipulate the situations of environmental control and non-environmental control, etc.; (2) Allowing non-equal proportional change of input index, expected output and non-expected output index; (3) Setting preference coefficients for ports to admit favorable decisions; (4) Providing a distance formula of expected output for PM emission reallocation. Further, data from 11 major ports in China are collected to compare the expected output under different PM emission standards assuming the situation of environmental control and non-environmental control, port cooperation, and non-cooperative sewage discharge. The empirical results show that: (1) Ports in the eastern China (Shanghai, Ningbo, and Nanjing) have higher port efficiency; (2) Port cooperation can improve the overall expected output but it will lose its edge with the improvement of PM emission standards. (3) Ports follow the same trend of output loss regardless of favorable decisions. In the end, the author makes a summary, puts forward relevant policy suggestions and makes the recommendation for future research. [ABSTRACT FROM AUTHOR]

Disasters are serious challenges to human development and the sustainability of the planet and, due climate change, natural disasters are becoming more frequent. International aid, which can effectively alleviate resultant losses and sustainable implications, has become an important way for humans to resist disasters cooperatively. Relevant research on how much each country should donate sustainably is barely seen. Against such a background, by taking into account indirect economic loss to and payment ability of donors, this paper proposes a novel framework and detailed input-output model for determining the amount of international aid that countries and multilateral organizations should allocate to disaster-stricken countries. To validate our method, the May 12th Wenchuan earthquake of 2008 is taken as example, and the indirect economic loss to each country is calculated based on the world input-output tables. Assuming that the total amount of aid is unchanged, the greater the indirect economic loss and payment ability are, the larger the amount of aid should be. Otherwise, the smaller the amount of aid should be. Based on the China's Ministry of Foreign Affairs statistics, the results show that among the 41 donors, 6 countries including Indonesia, Australia, South Korea, Spain, Turkey, and Japan donated too much while 23 countries such as India donated too little. Next, the recommended amount of aid is given by considering the indirect economic loss to and payment ability of each country. The advantage of this framework and method line in that the calculation results are objective and concise, while the disadvantage is that the indirect economic loss is relatively large and the recommend donate is uncertain. This paper demonstrates a new perspective for the study of standards for determining the amount of international aid that countries and multilateral organizations should provide to alleviate sustainable implications. [ABSTRACT FROM AUTHOR]

The economic loss evaluation of disaster is the basis for disaster prevention and disaster emergency management and thus needs to be solved urgently. Computable general equilibrium (CGE) model and input-output (IO) model are the major disaster assessment methods, each of which has its own strengths and weaknesses currently. However, few comparative researches have been conducted on the economic losses of one disaster evaluated by CGE Model and IO Model based on the same disaster impact. Therefore, this paper first constructs multi-sectoral CGE model and IO model, which are commonly used in disaster loss assessment. Then, taking the Beijing "7.21 Rainstorm" in 2012 as an example, the direct losses of agricultural and transportation sectors are introduced to the basic model. After that, the economic loss ratio and comprehensive losses based on the two models can be obtained. Finally, by comparing the assessment results, the main conclusions of the evaluation mechanism are summarized. The results showed that: (1) The CGE model has a greater spillover effect upon sectors and a wider distribution of disaster-affected sectors than the IO model; (2) the range of economic loss determined by the assessment results of the CGE model and the IO model is [67.9396, 74.2739] (100 million yuan); (3) agricultural, transportation, and mining sectors are high-sensitivity sectors to rainstorm disasters. Through the comparison of the two models, the accurate economic loss of disaster can be obtained, according to which governments can take targeted measures for the prevention and early warning of disasters. [ABSTRACT FROM AUTHOR]

This study applies the DEA-Malmquist productivity index methodology to estimate the total factor productivity of the three major cruise companies worldwide from 2003 to 2022. This is done in an effort to reveal the resilience characteristics under the impact of the epidemic shock and examine the features of the growth of operational efficiency in the cruise sector. The findings indicate that Tech is the primary factor causing an increase in the TFP of cruise firms, while scale efficiency change is the primary method of technical efficiency change improvement. This study analyzes the efficacy of the commercial methods employed by significant cruise lines in response to the outbreak,in order to understand the resilience of major cruise companies under the impact of the epidemic. The framework for reaction countermeasures and the essential components of technological efficiency enhancement for cruise operating enterprises are also presented. [ABSTRACT FROM AUTHOR]

[Display omitted] • A framework of water quality factors analysis considering scale effect is developed. • The optimal scales of influencing factors on water quality in YJRB are given. • Optima-scale non-linear effects of influencing factors on water quality are found. • Thresholds for key factors that accelerate water quality degradation are clarified. Accurately identifying the optimal spatial scales of effect analysis of influencing factors on water quality is crucial for effective water environment management. To address this, we propose a framework that consists of mix scale division (watersheds, riparian buffers, and circular buffers), and conduct a case study in the Yuanjiang River Basin (YJRB). Scale effects and non-linear impacts of various influencing factors on water quality were identified. The case study results revealed the variations of these water quality indicators were predominated by different influencing factors at various sales, such as by slope (SL) at the scale of riparian buffer (w) = 500 m and circular buffer (r) = 15 km (with a contribution percentage of 16.6 %), mean annual temperature (TE) at the watershed scale (23.4 %), annual precipitation (PR) at the scale of w = watershed and r = 15 km etc. The percentage of cultivated land (CL) > 28 % at the scale (w = 500 m, r = 50 km) will lead to increase in total phosphorus (TP) and SL > 26° at the scale (w = 500 m, r = 15 km) will lead to increase in pondus hydrogenii (pH). While, POP > 30 person per unit area at the scale (w = 100 m, r = 1 km), SL > 24° at the scale (w = 500 m, r = 15 km), NDVI > 0.48 at the scale (w = 500 m, r = 5 km) and PR > 1300 mm at the scale (w = watershed, r = 15 km) will lead to decrease in ammonia nitrogen (NH 3 -N) , total nitrogen (TN), electrical conductivity (EC) and turbidity (NTU) respectively. Results indicated that the precision can be improved by regulating influencing factors within scale effects and considering the non-linear effects of factors on water quality. [ABSTRACT FROM AUTHOR]

Confronted with the constraints of carbon dioxide reduction, R&D improves the production efficiency of enterprises. However, China's diversified economic entity structure makes enterprises with different attributes exhibit different R&D behaviors under the constraints of external carbon dioxide reduction. This paper takes Ten Thousand Enterprises Plan as an example, which belongs to the front-end policy and restricts the enterprise's carbon emission rights, reveals the impact of carbon dioxide reduction constraint on enterprises' R&D investment and alleviates the endogenous bias of previous research. Moreover, this paper explores the moderating effect of ownership structure on the relationship between carbon dioxide reduction policy and enterprises' R&D investment. The results show that the relationship between carbon reduction policy and enterprises' R&D investment in China is manifested as a significant "cost effect", that is, mandatory carbon emission reduction policy limits the expansion of enterprises' R&D investment scale. Comparing state-owned enterprises with non-state-owned enterprises, carbon dioxide reduction policy can hardly stimulate the R&D investment in non-state-owned enterprises, while the state-owned enterprises can easily obtain factor resources, which decreases carbon emission reduction costs and improve R&D investment intention, resulting in stronger R&D behaviors. • Alleviates the endogenous bias of previous research focus on carbon dioxide reduction and R&D based on front-end policy. • Policy implementation limits enterprises' R&D investment through investment intention and carbon dioxide reduction cost. • Carbon dioxide reduction policy hardly stimulates the R&D investment in non-state-owned enterprises. • Incentivizing investment intention and reducing reduction costs are effective ways to enhance the policy effect. [ABSTRACT FROM AUTHOR]

Urbanization has been viewed as an important factor in rapidly increasing carbon emissions. While urbanization relates to various aspects across space and time, a comprehensive assessment of its influences on carbon emission remains scare. In order to explore the multiple effects of urbanization on carbon emissions, a spatial panel data model was applied in this study, by combing nighttime light remote sensing data form 1995 to 2015 in the case of Zhejiang, China. The results showed that on time series, carbon emissions showed an overall trend of growing rapidly first and slowing down then, and its growth rate was closely related to the socio-economic development. Spatially, high carbon emission areas were mainly concentrated in the northeast and eastern coastal areas, while the southwest regions were the main low-carbon emission areas. Furthermore, the investigation of impact factors revealed that the expansion and fragmentation of urban land, augment of the secondary industry, and consumption behavior would lead to growth in carbon emissions, while the connectivity between urban lands, rising of urban population, and residents' low-carbon awareness could promote carbon mitigation. To be noticed, the impact of economic growth on carbon emissions may gradually be weakening as the industry upgrades. Overall, this research has provided a useful insight into the relationship between urbanization and carbon emissions that can support policy makers and urban planners. [ABSTRACT FROM AUTHOR]