Search

The essence of megacity ecosystem problems is the unbalanced relationship between humans and their living environment. The most notable features of this imbalance are the environmental quality decline and resource shortages, which cause human survival crises. This paper combines the drivers, pressures, state, impact, and response (DPSIR) framework to explore a new system dynamics (SD) model to achieve megacity ecosystems’ sustainability. First, indicator selection is conducted using the DPSIR framework model. Second, causal loop diagrams and stock-flow charts of systems are generated with the SD model to simulate the change tendency inside the megacity ecosystem. Finally, to validate the applicability of the proposed method, we select the urban ecosystem of Beijing as the case study. This study utilizes the proposed research framework to analyze the effect of the main driving factors among five development strategies and current trends. The results show that the combination of population, environmental protection policies and technical means had the greatest sustainability potential. This study reveals a dynamic relationship between the main influencing factors within megacity ecosystems and offers suggestions to the sustainability of the environment, resources and social economy of megacities.

Excessive phosphogypsum waste has caused significant environmental contamination and has consequently become a serious threat to sustainable socio-economic development. This paper proposes a recycling-equilibrium strategy from a regional policy perspective that integrates circular economic theory and modeling techniques to resolve phosphogypsum-related pollution problems. Specifically, three typical conflicts are analyzed to describe the problem complexity, and a multi-objective bi-level programming model is formulated under uncertainty for the assignment of practical disposal limits to achieve a compromise agreement between the multiple decision makers. A solution approach that employs fuzzy theory, an acceptable reduction target, and Karush-Kuhn-Tucker conditions is developed to identify the optimum phosphogypsum stack allowance allocation mechanism for regional authorities and an optimal purchase-transportation plan for the phosphate fertilizer plants. The results from the practical case validated the feasibility and efficiency of the formulated method and proved that a recycling-equilibrium strategy based stack allowance allocation mechanism could successfully achieve phosphogypsum pollution mitigation. The practical application findings were: (1) different phosphate fertilizer plants have different sensitivities towards changing stack reduction targets; (2) local authority revenue and phosphogypsum stack quantities are mainly impacted by environmental protection targets; (3) allocating larger stack allowances to phosphate fertilizer plants with smaller emissions coefficients can realize better phosphogypsum reduction.

Background When COVID-19 emerged in China in late 2019, most citizens were home-quarantined to prevent the spread of the SARS-CoV-2 virus. Extended periods of isolation have detrimental effects on an individual's mental health. Therefore, the impact of the COVID-19 pandemic should include assessment of psychological distress and its known risk factors, including coping style and emotional regulation. Methods This cross-sectional study surveyed 6,027 Chinese university students recruited from May 25, 2020 to June 10, 2020. In addition to sociodemographic information, participant data were collected using online versions of the 10-item Kessler Psychological Distress Scale (K10), Simplified Coping Style Questionnaire (SCSQ), and Emotion Regulation Questionnaire (ERQ). Results The incidence of psychological distress was found to be 35.34%. Negative coping style and expressing panic about COVID-19 on social media were the most important predictors of psychological distress. In addition, being male, being a “left-behind child” or having a monthly household income lower than 5000 CNY or higher than 20,000 CNY were associated with higher psychological distress. Conclusion The psychological consequences of the COVID-19 pandemic could be serious. Psychological interventions that reduce nervousness and negative coping style need to be made available to home-quarantined university students, especially those who are male, are “left-behind”, have a monthly household income lower than 5000 CNY or higher than 20,000 CNY, or express panic on social media.

With the widespread impacts of global warming in the world, the control of greenhouse gas emissions especially carbon dioxide has become a global focus. Since 2014, China has surpassed the United States and become the largest carbon emission country in the world; the greenhouse gas generated by the construction industry accounts for nearly 30% of the total domestic energy, so the carbon emission management and control of the construction industry have attracted the attention of experts and scholars. As a kind of tax system, carbon tax policy has been implemented in many countries and achieved significant carbon emission mitigation effects. Aiming at the problem of construction material supply, this paper optimizes and explores the problems of material supply and procurement in construction projects considering the characteristics of decision-making factors and multi-objective planning methods. Through the optimization of the mathematical model with carbon tax parameters, the proposed method can effectively reduce the total carbon emissions of the construction industry in the process of material production and supply, and achieve the objective of energy conservation and emission reduction.

Wind power is getting more attention globally as a renewable and cost-efficient power generation resource. However, its characteristics of intermittency and weather-dependent make the accurate prediction a real challenge. This paper tries to achieve an accurate wind power prediction based on analyzing significant meteorological factors included in the predictor. Three advanced algorithms of decision tree, K-nearest neighbors, and random forest are used to construct predictors based on the processed dataset. The models are tuned with hyperparameters varying in a certain range to find the optimal value, and the evaluation indexes indicate that how well the models fit the data. The results show that the average wind speed and wind direction have main effects on wind power output, and the K-nearest neighbors algorithm performs better in the simulation than the other two methods.

As the environmental problems increasing seriously, governments have to take environmental protection as one of the most important development directions in the future. Large emissions of greenhouse gases (GHGs) will accelerate the greenhouse effect. Comparing with the traditional fuel vehicles, electric vehicle (EV) is a cleaner technology with lower emissions, which can slow the pace of global warming effectively and it has been promoted by governments around the world vigorously. However, there are still some challenges in the development of EV, such as range anxiety, battery safety and so on which will influence consumers’ choices. In order to promote the promotion of new energy vehicles, the government has promulgated a series of incentive policies on EV area. Scholars from all over the world have also studied the policy impact in the field of new energy vehicles. By using CiteSpace literature visualization tool, this paper analyzes relevant literature on the web of science (WOS) to determine the policy influence in EV area. The results indicate the research background of this field. In another hand, costumer and energy supply are the two important impact factors in this area.

In order to enhance operational efficiency and break up the monopoly, Chinese electricity market has undergone reforms since 2002. This paper considers a spot electricity market in a discrete-time setting that includes two types of power generation firms, renewable firms (wind generators) and conventional firms (thermal power plants). A stochastic bi-level model for an upper-level wind power producer aiming profit maximization and lower-level maximizing the social welfare has been proposed in this work. This strategic wind producer participates as a price-maker in the day-ahead market, and a deviator in the balancing market to compensate for production deviations due to wind power uncertainty. Accordingly, the potential analysis considering wind power output scenarios, price mechanisms, coordinated bidding strategy, and policy implications are investigated. This paper could guide a better integration of renewable energy into the electricity market.

Considering serious environmental pollution caused by phosphogypsum and the scarce of phosphate rock resource, the recycling utilisation of phosphogypsum has significant influence on the sustainable development. To promote the recycling utilisation of phosphogypsum, this paper studies the phosphogypsum reduction in phosphate fertilizer plants based on the stack allowance trading mechanism. According to the detail analysis, an optimization model has been established to describe and resolve the complexity of the phosphogypsum reduction problem. In the optimization process, the uncertain environment and stack allowance trading mechanism have been fully considered. A practical case is given to demonstrates the efficiency of the formulated method. The results indicates that the stack allowances trading mechanism all the phosphate fertilizer plants to make more flexible operation decision, which not only realize the environmental pollution mitigation and PG recycling, but also promote each phosphate fertilizer plant sustainable development.

As coalbed methane, the natural gas adsorbed in coal seams, is a greenhouse gas that is 21 times stronger than CO2, coalbed methane extraction significantly influences carbon reduction and energy conservation efforts. While the injection of CO2 into coal seams is known to effectively enhance coalbed methane recovery, this process has been limited because of high investment and production costs. Therefore, to promote the application of CO2 injection techniques in coalbed methane industry, this paper proposes an authority–enterprise equilibrium based mixed subsidy mechanism which combines direct subsidies with indirect tax-incentives. Specifically, a multi-objective bi-level programming model is established under uncertainty to assign a practical constraint and achieve a trade-off between the local authority and the coalbed methane plants. A practical case validates the feasibility and efficiency of the proposed method, proving that an authority–enterprise equilibrium based mixed subsidy mechanism is able to achieve carbon emissions reductions and conserve energy. Further analysis indicated that the marginal energy efficiency gains were greater than the authority costs under a strict energy utilization policy and that the environmental protection target had larger impacts on the coalbed methane plant performances.

Considering serious environmental pollution caused by chemical industry residual(CIR) and the scarce of chemical resource, the recycling utilisation of CIR has significant influence on the sustainable development. To promote the recycling utilisation of CIR, this paper develops an equilibrium strategy based bi-level programming model which fully reflects the conflicts between the government and the chemical industry. Combining CO\(_{2}\) mineralization technique, a bi-level programming model based on equilibrium strategy is established to develop a optimal allocation mechanism of phospho gypsum (PG) stack allowance under uncertain environment in the recycling utilisation of PG problem. A practical case is given to demonstrates the efficiency of the formulated method. The optimization method proposed in this paper is also appropriate for other chemical residuals recycling utilisation problem.

Location problem is a fundamental task for the cement plant enterprises. This paper mainly investigates this problem with carbon emission trading mechanism. In practice, most of cement plant location problems are multi-objective and uncertain in nature. To enhance the general practice of cement plant location problem, this paper proposes a fuzzy random bi-level multi-objective model with carbon emission trading mechanism. Genetic algorithm is used to seek the approximate best solution of the model. A numerical example is also given to show the effectiveness of the proposed model.

Environmental pollution caused by coal gangue has been a significant challenge for sustainable development; thus, many coal gangue reduction approaches have been proposed in recent years. In particular, coal gangue facility (CGF) construction has been considered as an efficient method for the control and recycling of coal gangue. Meanwhile, the identification and selection of suitable CGF sites is a fundamental task for the government. Therefore, based on the equilibrium strategy, a site selection approach under a fuzzy environment is developed to mitigate coal gangue contamination, which integrates a geographical information system (GIS) technique and a bi-level model to identify candidate CGF sites and to select the most suitable one. In this situation, the GIS technique used to identify potential feasible sites is able to integrate a great deal of geographical data tofitwithpracticalcircumstances;thebi-levelmodelusedtoscreentheappropriatesitecanreasonably dealwiththeconflictsbetweenthelocalauthorityandthecolliery. Moreover,aKarush–Kuhn–Tucker (KKT) condition-based approach is used to find an optimal solution, and a case study is given to demonstrate the effectiveness of the proposed method. The results across different scenarios show that appropriate site selection can achieve coal gangue reduction targets and that a suitable excess stack level can realize an environmental-economic equilibrium. Finally, some propositions and management recommendations are given.

The “cap-and-trade” mechanism, an effective way to control emissions, is a market-based approach focused on the efficient allocation of initial emissions allowances. The equality principle is established to make most allocating objects be satisfied with the allocation, which could promote emission reduction. This paper employs the Gini coefficient, a measurement of inequality in economics, to implement the equality principle, and build relative mathematical model for the allocation problem. Two indicators, output and investment, are chosen to calculate the Gini coefficient, because the output stated for its contribution to the society, while the investment implied its scale and attitude towards the environment. Finally, an example in Guangdong ETS was taken to demonstrate the efficiency of the method proposed in this paper.

Channel estimation error problem is among the main causes of performance degradation in wireless networks. In this paper, we investigate the impact of channel estimation error on cooperative communications. We analyze the symbol error rate (SER) performance of decode-and-forward (DF) cooperative communications with channel estimation error over nakagami-m channels. For the classical three-node cooperation model, the exact SER expressions for M-PSK are derived. We also provide upper bound expressions for the SER. Simulations are finally provided to verify the correctness of our analysis. Given to high SNR, it shows that performance does not improve along with increasing SNR and the SER performance depends more on the channel link between relay and destination than link between source and relay.