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Even though renewable energy development has gained momentum in China, thermal power generation still accounts for approximately 70% of the county's total power generation serving as the major source of carbon dioxide (CO 2) emissions in China. Facing the challenges of meeting 2030 peak target of CO 2 emission and realizing the coordinated development of thermal power generation in Beijing-Tianjin-Hebei region, this paper applies generalized Divisia Index Method (GDIM) to decompose the dynamics in the relevant CO 2 emission. The effects of five factors including electricity demand, energy consumption, technology, energy efficiency and energy-mix are considered. The decomposition suggests that electricity demand is the primary factor driving the CO 2 emission up, whereas technology effect decreases CO 2 emission the most. Given the significant roles of technology, energy-mix and energy efficiency in CO 2 emissions reduction, seven scenarios are designed to identify the optimal coordinated development pathway for thermal power generation in Beijing-Tianjin-Hebei region. Through upgrading energy structure and/or enhancing energy efficiency, the thermal power generation in Beijing-Tianjin-Hebei region can achieve coordinated development and realize the 2030 peak target under four scenarios. The detailed development pathways for CO 2 emissions and specific policy implications for Beijing, Tianjin and Hebei are provided to further govern CO 2 emissions and maintain sustainable development. • Proposed a five-factor Generalized Divisia Index Model (GDIM) for CO 2 emission analysis. • Analyzed the CO 2 from thermal power generation in China's Beijing-Tianjin-Hebei region. • Electricity demand and technology contributed the most to the positive and negative changes of CO 2 , respectively. • Designed seven thermal generation development scenarios to study the CO 2 change until 2030. • The 2030 CO 2 peak target can be achieved under four scenarios. [ABSTRACT FROM AUTHOR]

• Water use efficiency evaluation based on 3D water footprint using SBM model. • Two scenarios for water use efficiency evaluation. • Analyzing the driving forces affecting water footprint change using the LMDI model. Water shortage and the conflict between water supply and demand have become the main constraints to the sustainable development of sustainable societies in Beijing-Tianjin-Hebei (BTH) region. Scientific evaluation of water usage efficiency and clarification of the three-dimensional water ecological footprint (EF 3D) drivers are of great significance for the collaborative environmental management of BTH region. This paper firstly explores the evolution of water footprint breadth (EF size), depth (EF depth) and EF 3D in BTH region from 2004 to 2020. Using the super-efficient SBM (Slacks-Based Measure) model with EF 3D to evaluate the water use efficiency of BTH region in two scenarios. 22 impact factors were selected to analyze the dynamics affecting the change of EF 3D in BTH region by using the LMDI (Logistic Mean Divided Index) model. The results show that: (1) The water resources pressure of the three provinces are in the overload state from 2004 to 2020, and the EF 3D is at its maximum in 2011–2015. The EF depth of BTH region is fluctuating up and then fluctuating down around 2012, and the most serious capital consumption of water resources stock is in Tianjin. (2) The water resources in Hebei are all in inefficient use. The water resources in Tianjin are in a state of inefficient use in some study years, and since 2014, the water resources are in a state of fluctuating increase and high efficiency. As for Beijing, the water resources are in a state of efficient use in the study years. On the whole, scenario 2 better reflects the water resources utilization efficiency situation and is more in line with the real situation. (3) The water structure and endowment of water resources are pivotal factors positively influencing the EF 3D. To mitigate EF 3D and achieve sustainable utilization of water resources, both Hebei and Tianjin have ample room for progress in elevating agricultural water-saving technologies, optimizing industrial structure, and enhancing water usage patterns. Agricultural water consumption is no longer the primary driver of water resource depletion in Beijing, necessitating focused attention on the impact of external water diversions in terms of local water displacement, optimization of water usage structures, and their role in supporting socio-economic development. Additionally, excessive reliance on external water diversions may entail associated risks that warrant consideration. [ABSTRACT FROM AUTHOR]

• A regional division method of municipal solid waste incinerators based on incineration characteristics is proposed. • The material balance equation of municipal solid waste incineration (MSWI) process is established. • The energy balance equation of MSWI process is established. • A multi-input and multi-output controlled object model is constructed, which lays the foundation for optimal control. Municipal solid waste incineration (MSWI) is an important part of energy recovery and sustainable development, constructing the model of controlled object is the basis of studying its optimal control. MSWI is a typical multi-input and multi-output industrial process, which has many uncertain characteristics such as strong nonlinearity and multivariable coupling. To solve this problem, a model of controlled object in MSWI process is proposed in this paper. Firstly, the MSWI process based on grate incinerator is analyzed to summarize its relevant variables and control requirements. Secondly, the solid phase and gas phase of MSWI process are divided to construct material balance equations of subsystems. Next, the energy transfer process in incinerator is deduced and calculated through thermodynamic laws. Finally, the validity of the model is verified by the process data of a MSWI plant in Beijing, China, which lays a model foundation for the study of the optimal control of MSWI process. [ABSTRACT FROM AUTHOR]

Freshwater ecosystem service is essential to human’s survival and development. Many studies have documented the spatial differences in the supply and demand of ecosystem services and proposed the concept of ecosystem services flows. However, few studies characterize freshwater ecosystem service flow quantitatively. Therefore, our paper aims to quantify the effects of freshwater ecosystem service flow on downstream areas. We developed a freshwater ecosystem service flow model and applied it in the Beijing–Tianjin–Hebei (BTH) region, China, for the year of 2000, 2005, and 2010. We assessed the regional water security with an improved freshwater security index by integrating freshwater service provision, consumption and flow; and found that most areas of the BTH region (69.2%) were affected by upstream freshwater flows. The areas achieving water security in the region also expanded to 66.9%, 66.1%, and 71.3%, which were 6.4%, 6.8% and 5.7% increments compared to no-flow situation, in 2000, 2005 and 2010, respectively. Setting quota for human water consumption is suggested to further improve water security. These results highlight the need to fully understand the connections between distant freshwater ecosystem service provision and local freshwater ecosystem service consumption. This approach may also help managers to choose more sustainable strategies for critical freshwater resource management across different regions. [ABSTRACT FROM AUTHOR]

Long-term observation of the urban ecological footprint will present useful knowledge of anthropogenic impact on and sustainable solutions for cities. This paper proposed a new framework to predict dynamic change and intrinsic structure of urban ecological footprint with the Markov chain. The system dynamic model based on Markov chain was then established for estimating Beijing's footprint during the period of 2001–2020. The results showed that Beijing's footprint kept stable in the long term due to steady consumption pattern and environmental mitigation policy. The footprint intensity has been decreasing constantly due to the expanding population against the stable total footprint. Energy consumption was found to be the major contributor to Beijing's footprint. Sensitivity analysis was also presented by testing the population and economic growth under five scenarios. This work may provide insights into the land metabolism mechanism and guidance for urban planning. [ABSTRACT FROM AUTHOR]

Energy consumption has always been a central issue for sustainable urban assessment and planning. Different forms of energy analysis can provide various insights for energy policy making. This paper brought together three approaches for energy consumption accounting, i.e., energy flow analysis (EFA), input–output analysis (IOA) and ecological network analysis (ENA), and compared their different perspectives and the policy implications for urban energy use. Beijing was used to exemplify the different energy analysis processes, and the 42 economic sectors of the city were aggregated into seven components. It was determined that EFA quantifies both the primary and final energy consumption of the urban components by tracking the different types of fuel used by the urban economy. IOA accounts for the embodied energy consumption (direct and indirect) used to produce goods and services in the city, whereas the control analysis of ENA quantifies the specific embodied energy that is regulated by the activities within the city’s boundary. The network control analysis can also be applied to determining which economic sectors drive the energy consumption and to what extent these sectors are dependent on each other for energy. So-called “controlled energy” is a new concept that adds to the analysis of urban energy consumption, indicating the adjustable energy consumed by sectors. The integration of insights from all three accounting perspectives further our understanding of sustainable energy use in cities. [ABSTRACT FROM AUTHOR]

The coordination development among various subsystems, especially among economic, social and environmental subsystems, is an important part of urban sustainability that directly affects the quality of urbanization. This paper evaluated the sustainability of the 9 China's national central cities using the coupling coordination model. In the evaluation process, an objective coupling weighting method was developed by the combination of the coupling analysis and the sequential relationship analysis method. The validity of this method was illustrated by comparing the coordination level of the cities with that obtained by the entropy method. Long-term use of this method can guide the coordination development among economy, society and environment of cities. The assessment results indicate that the coordination development among economy, society and environment of the cities was not ideal. Only one city, Beijing, located in the good coordination grade. The main reason is the lower development of economic sustainability. Policy recommendations were provided to address the problem. In addition, the paper concludes that there is a great room for improvement in the coordinated development of the cities, because they showed an increase trend in coordinated development and the economic growth rate was relatively high. [ABSTRACT FROM AUTHOR]

Abstract: Since the open door policy in 1978 China has undergone enormous economic and social changes making China to be one of the largest economies and consumers of resources in the world. The pronounced differences in income and lifestyles especially between urban and rural China were also part of China''s economic rebirth. This paper explores current trajectories and scenarios for urbanization and lifestyle changes and other important socio-economic trends in China. The implications of these changes are analysed for Beijing in particular and then compared to China for the year 2020. These changes by 2020 are modelled using input–output analysis in combination with the Ecological Footprint and Water Footprint. [Copyright &y& Elsevier]

Agricultural sector is the basic industry supporting the construction and development of national economy. With the continuous deterioration of agricultural pollution, measuring and understanding agricultural total factor productivity (AGTFP) is the important premise to achieve agricultural green development and clean production. Regarding carbon emissions and agricultural non-point source pollution (ANSP) as undesired outputs, this paper applies a three-stage Data Envelopment Analysis (DEA) method combined with the Slack-Based Measure (SBM) model to eliminate the influences of environmental factors and random errors and explore the real AGTFP of 30 provinces in China from 2000 to 2017.On this basis, the spatial distribution and dynamic changes of AGTFP before and after adjustment are further discussed to seek the underlying reasons. The empirical results demonstrate that AGTFP is lower when carbon emissions and ANSP are both considered, and it decreases from east to west in StageⅠbut the Northeast region surpasses the East to achieve the highest productivity after removing the interferences. Moreover, China's AGTFP has been restricted by the external environment, and superior external environment disguises the poor management efficiency of Beijing and Shanghai. Therefore, some policy implications to balance agricultural environment and economic development are proposed. [Display omitted] • Non-point source pollution and CO 2 are integrated to measure agricultural green efficiency. • A three-stage SBM-DEA approach is employed to calculate the real agricultural green total factor productivity. • Different environmental factors have different effects on the slack of agricultural inputs. • China's agricultural green total factor productivity is restricted by the external environment. [ABSTRACT FROM AUTHOR]

• We assess the regional water resources carrying capacity (WRCC) scientifically. • Level of regional WRCC is assessed from three subsystems. • Change of WRCC can assess benefits of South-to-North Water Diversion Project (SWDP). • A new variable precondition S-type cloud algorithm is proposed to assess WRCC. • SWDP can increase carrying capacity of local water resources by 3.80% in Beijing. The purpose of water resources carrying capacity (WRCC) research is to meet the sustainable utilization of water resources and realize its sustainable development strategy. Scientifically evaluating the carrying capacity of regional water resources is extremely important. In this study, a variable precondition S-type cloud algorithm (VPSCA) is developed for assessment of regional WRCC based on social economic subsystem, water resources subsystem, ecological and environmental subsystem including thirteen indicators, which can overcome the shortcoming that the existing evaluation methods rarely consider fuzziness, randomness, and dynamic variability of parameters at the same time. First, forward S-type cloud generator algorithm (FSCGA) is developed based on segmented S-type membership function. On this basis, precondition S-type cloud generator algorithm (PSCGA) is proposed. Moreover, the VPSCA is developed by embedding PSCGA into variable fuzzy evaluation (VFE) method. Taking Beijing as a typical research area, this paper analyzes and forecasts the comprehensive benefits of water supply of the Middle Route of South-to-North Water Diversion Project (SWDP) in 2030 using VPSCA. The results show that SWDP can increase the carrying capacity of local water resources by 3.80%. In addition, feasibility and validity of VPSCA are further verified by comparison with other existing methods. This study aims to provide some suitable theoretical and practical implications of the evaluation of WRCC. [ABSTRACT FROM AUTHOR]

• Studying on dynamic ecological footprint (EF) in Jing-Jin-Ji from 1996 to 2020. • Six impact factors for driving EF is decomposed. • The EF in Jing-Jin-Ji will increase of 10% from 2015 to 2020. The ecological footprint (EF) describes the complex relationship between the eco-environment and economic development. EF dynamics can better reflect the appropriation of natural resources in various countries or regions compared with previous studies. This paper identified six dominant factors including population, per capita GDP, three major industrial added values, and energy consumption using grey correlation model for the EF changes of the Beijing-Tianjin-Hebei (Jing-Jin-Ji) region from 1996 to 2015. Then, we predicted the EF of the Jing-Jin-Ji region from 2016 to 2020 based on support vector machine model. (1) Since 1996, the EF and per capita EF of the overall Jing-Jin-Ji region have increased, of which those of Hebei Province and Tianjin increased while Beijing decreased. (2) Energy consumption dominated the EF of Jing-Jin-Ji region. The population of Beijing had a high correlation coefficient of 0.735 with the local EF, and the degree of correlation between the EF and per capita GDP was 0.812 in Hebei Province. In Tianjin, the added value of the tertiary industry was closely correlated with its EF, with a correlation coefficient of 0.741. (3) The EF of the Jing-Jin-Ji region will reach 778.30 million hectares by 2020, an increase of 10% compared with the value in 2015. Finally, suggestions for the development of industrial structure and energy consumption are listed for the sustainable development of Jing-Jin-Ji region. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to build an objective and effective environmental performance evaluation model of air pollution control. Based on the severe air polluted region in China, that is Beijing-Tianjin-Hebei region, this evaluation model consists of four parts, including economic benefits, public service, government management and development potential, and uses the balanced scorecard theory. The weights of the indexes are measured by comprehensive evaluation method, which combined entropy weight method and analytic hierarchy process (AHP). To test the applicability of the evaluation method to different stages, back propagation (BP) neural network is introduced to simulate air pollution control in the future. The results reveal that the environmental performance of air pollution control in Beijing had an upward trend during 2010–2016, and the trend would continue in the next five years. The environmental performance of Tianjin continuously increased, especially from 2014 to 2016. Tianjin has great potential of air pollution control in the future. The environmental performance of air pollution control in Hebei fluctuated from 2010 to 2016 and it dropped to the lowest level in 2015, which mainly due to the large increase in number of days with air quality levelⅡor above compared with 2014 and the nonsignificant growth in the amount of expenditure on atmospheric prevention and control, the amount of investment in the control of industrial pollution sources and the number of law enforcement personnel. Moreover, the environmental performance of air pollution control closely related with industrial structure, especially with the proportion of the tertiary industry. The upgrading of urban industrial structure and the coordinated development of green industry should be implemented to restructure the environmental transformation in air-polluted region. Image 1000 • The traditional Balanced Scorecard is revised and applied into the environmental performance evaluation. • The effective control of vehicle emission directly determines the air quality of Beijing. • A fundamental improvement in air quality in Hebei requires a large amount of environmental investment. • The environmental law enforcement is an important guarantee for air quality improvement of Tianjin. [ABSTRACT FROM AUTHOR]

Carbon emissions and energy consumption have serious impacts on humans and ecosystems. This paper investigates the effects of industrial reconstructuring on energy conservation and emission reduction. A multi-objective optimization model was established. The model classifies industrial sectors into four groups according to their carbon emission levels and contributions to economic growth, then non dominated sorting genetic algorithm is applied to solve the model and the Pareto frontier is obtained. The best solution is selected from the Pareto frontier by using a super data envelopment analysis model which measures the degree of coordination between economy and environment. The model is used to analyze the effects of industrial reconstructuring in Beijing during 2018–2020. The results show that industrial reconstructuring enabled economic growth to reach the government's planned rate while the carbon intensity and energy intensity surpassed the goal of the 13th Five-Year Plan. This case can provide decision-making basis for the sustainable development of ecology and economy in other regions. Fig. 6. Pareto front in Beijing region in 2020 The optimal Pareto solution for carbon emissions, energy consumptions and GDP targets after industrial structure reconstructuring. Image 1 • Classifying industrial sectors into four groups according to carbon emission levels and economic growth contributions. • A multi-objective optimization model was established and solved by the genetic algorithm. • A super DEA model evaluates the final plan which reflects the coordination of the economy and environment. • The analysis of each group can help achieving maximum benefits of economic and environment. [ABSTRACT FROM AUTHOR]