Search

The current analysis method for temporal-spatial characteristics of carbon emissions from port vessels overlooks the multidimensionality of the carbon emission process. To address this issue, this paper proposes a multidimensional approach for extracting characteristics of carbon emissions from vessels, aiming to enable multidimensional analysis of carbon emission information. Firstly, an inventory for calculating carbon emissions from port vessels was established using AIS data. Secondly, a method for constructing a three-dimensional tensor of carbon emissions from port vessels was proposed. This approach entails discretizing and encoding time, space, vessel type, and operating mode to generate a dataset with carbon emission labels. Following this, a three-dimensional tensor of carbon emissions was created using mapping rules. Thirdly, non-negative tensor factorization (NTF) was employed to decompose the tensor into multiple sub-vectors. The impact of tensor rank on the decomposition results was discussed, and an appropriate tensor rank value was determined, achieving multidimensional feature extraction of vessel carbon emissions. To validate the feasibility of this method, Tianjin Port was taken as the study area, and six major characteristics of vessel carbon emissions are obtained. This study reveals the temporal and spatial distribution of carbon emissions from different vessels under various operating modes. Compared to unidimensional analysis, this method provides more detailed multidimensional information on vessel carbon emissions, thus offering data support and decision-making basis for formulating energy-saving and emission reduction measures for ships and promoting green and sustainable development in the shipping industry. • A spatial-temporal analysis method of carbon emissions from ships in ports is proposed. • A three-dimensional ship carbon emission tensor construction method is developed. • The proposed model is verified through real case analysis and model comparison. [ABSTRACT FROM AUTHOR]

In this paper we argue that to analyse the eco-development process we need to explore it as a whole, from design, through delivery and then to how these developments influence the behaviour of the people who live and work in eco-developments. At each stage of the development process it is important to analyse and understand what key actors understand by the term ‘eco’ (resource efficiency of land and materials), how they understand the institutional, economic, social and communicative mechanisms to effectively produce ‘eco’ developments and ‘green economy’, and what learning opportunities exist to promote positive ecological and competitiveness ideas. Perhaps, because so little is known, the greatest need of all is to analyse how the new residents of eco-cities are living their lives and whether or not they are more environmentally friendly than before. In this paper we provide empirical data on those who have moved to the most profile eco-development in China, the Sino-Singapore Tianjin Eco-City. The data reveals that whilst the habits of some residents are sympathetic to the environment, other parts of their lifestyle – linked to comfort and convenience – are not. Moreover, the aspirations of the residents for an increasingly middle class lifestyle mean that resource use could be even higher in the future. This is a highly significant finding both for those engaged in academic debates on eco-development and for policy makers and practitioners involved in the development of eco-cities. [ABSTRACT FROM AUTHOR]

Under the restriction of carbon neutral and carbon peak, the development of green building has become the strategic demand of most countries in the world. Despite the rapid development of green building in China, there are still some problems, such as insufficient market development force under the government's leadership, emphasizing design and neglecting operation. In order to realize high-quality synergistic development of green building market, this paper constructs a new synergistic development framework of green building market, establishes a tripartite evolutionary game model including local governments, developers and consumers, uses the analysis tool of evolutionary game theory and synergistic theory to explore the unilateral ESS and the system ESS of green building market. In order to verify the model, this paper adopts a case study method, takes a residential building project in Tianjin, China which has awarded a three-star mark in green building design evaluation as an example for numerical simulation, discusses the influence of government guidance on the system evolution trajectory, demonstrates the interactive process of stakeholders' behavior, and finds out the key factors affecting the system equilibrium strategy. The result shows that (1) the means of government guidance will affect the speed and result of system evolution; (2) the strategy of stakeholders depends on the comparison of costs and benefits; (3) the probability of ideal events is positively correlated with the economic benefits and negatively correlated with incremental cost of green building. This study can provide theoretical guidance for local governments, developers and consumers to make scientific decisions, and provide practical enlightenment for government to play a more active role in green building market. [ABSTRACT FROM AUTHOR]

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]

• Redesigns dimensions and key indicators for circular transformation in industrial parks. • The newly-designed DEARA model has advantages over the traditional DEA model for data with large distributions. • There is a strong, positive correlation between resources and environmental performance in industrial parks. • The driving factors of circular transformation are mainly GDP and types of leading industries. • Circular transformation of industrial parks is more effective in improving resource efficiency than the national average. Checking the circular economy (CE) efficiency of industrial parks and exploring the potential reasons involved have not been systematically investigated. Recent researches lacked a unified and up-to-date framework toward CE in industrial parks emerging in high-quality development stage. It is therefore critical to build a new dimension and quantify the CE efficiency of industrial parks under the new historical period, so that appropriate policies can be formulated. This paper measures the CE efficiency of circular transformation by developing an original DEARA (Data Envelopment-Regression Analysis) model, and highlighting its advantages over the traditional DEA (Data Envelopment Analysis) model. To do this, an evaluation model is constructed that combines eight key indicators for environment, resources, economics and driving factors. The first batch of circular transformation pilot parks in China were selected for empirical analysis. The results show that the CE efficiency of sample parks has high variability from 0.112 to 1.030 in 2011. The efficiency matrix reveals a positive correlation between resources and environmental performance, with the driving factors for circular transformation being mainly GDP and leading industries. Compared with national indicators, the circular transformation of park levels is more effective in improving CE efficiency than the national average level of circular development, among which the experiences of the Beijing and Tianjin development zones are worthy of being exported to other industrial parks. Ultimately, this paper intends to contribute to policy instruments for developing viable and efficient industrial parks. [ABSTRACT FROM AUTHOR]

This paper is an analysis of the spatiotemporal evolution characteristics of arable land in the Beijing-Tianjin-Hebei region from 1990 to 2015 and detects the driving factors of arable land change. On the basis of the study, the existing problems of arable land are discussed and some suggestions to promote regional rural development are proposed. The conclusions are as follows: (1) The proportion of arable land gradually decreased from 1990 to 2015 and the proportion of arable land in the south of the Beijing-Tianjin-Hebei region was larger than that in the north of the Beijing-Tianjin-Hebei region: arable land with a proportion of more than 75% lies in the low elevation and slope. The proportion of arable land in Beijing has also decreased faster than in other regions because most arable land was converted primarily into construction land due to urban expansion. (2) The mechanism showed that county economies and populations influenced the change in the quantity of arable land, and the position and natural conditions influenced the pattern changes in arable land. (3) Finally, this paper details some suggestions on the terms of legal institutions, the land consolidation project, and developing modern agriculture and industrial upgrading, which could provide scientific support for rural sustainable development and arable land protection in the Beijing-Tianjin-Hebei region. • This paper analyzed the spatiotemporal differences of arable land in Beijing-Tianjin-Hebei region from 1990 to 2015. • The study detected the driving factors and mechanism using multiply regression models and geographical detector. • This paper proposes to develop land consolidation project and modern agriculture to realize arable land sustainable use. [ABSTRACT FROM AUTHOR]

Rapid urbanization and industrialization in China have seriously threatened the ecosystem and urban sustainability. This paper estimated the dynamic variations of ecosystem service value (ESV) in response to changes of land use/land cover (LULC) under rapid urbanization, and it analyzed their impacts on sustainability of urban system. Tianjin, the largest coastal city in China, was selected as the study area. The total ESV of Tianjin was approximately 8791.86 million Yuan in 2003, 7948.04 million Yuan in 2007, and 8378.53 million Yuan in 2011. By taking the total dynamic ESV as one of the key factors, we calculated the indexes of urban sustainability from 2003 to 2011. It was found that the dynamic variations of ESV in response to LULC changes had significant impacts on the sustainability of urban system. Therefore, in order to increase the capacity for urban sustainable development, there is an urgent need to lighten the heavy burden on the ecosystem through rational land use management during rapid urbanization. [ABSTRACT FROM AUTHOR]

Interregional trade not only contributes to economic growth but also causes a large amount of virtual water transfer. The virtual water transfer brings about two-way impact of environmental stress between regions. It is essential to examine the two-way impact mechanism to achieve water sustainability. Interregional virtual water transfer includes three aspects of effects: multiplier, spillover and feedback effects. Among them, multiplier effect is the interaction in a single region. Spillover effect generally refers to the one-way impact of former region's economic development on latter region, while the feedback effect refers to the economic change of latter region in turn has an impact on the former region on the basis of the spillover effect. However, most studies have been focusing only on the one-way impact of virtual water transfer, which are the multiplier and spillover effects. This paper introduces a new spillover-feedback effects model to measure the two-way impact of virtual water transfer in urban agglomerations, and takes the Beijing, Tianjin and Hebei capital agglomerations in China as a specific case. The results illustrate that the spillover-feedback effects had significant contributions to virtual water transfer. From the perspective of regional scale, Beijing was a net importer of virtual water, with a net import volume of 1.019 × 108 m3. Tianjin and Hebei were net exporters of virtual water, with net exports of 0.069 × 108 m3 and 0.950 × 108 m3 respectively. The values of the feedback effect were large and should not be ignored, which accounted for up to 40% of the spillover effect. Furthermore, at the sectoral scale, the sectors with large ratios of spillover-feedback effects to total effects in regions included mining, agriculture, manufacturing and transportation. In Beijing, this ratio of mining exceeded 50%. Additionally, the effect intensity patterns were different from the effect patterns, which prove that the regional ability to stimulate water consumption was not consistent with the actual impacts. Finally, regions should pay more attention to managing the industries and enterprises with high virtual water export, adjust the trade structure, strengthen inter-regional cooperation and clarify regional responsibilities for water-saving. In a word, understanding interregional two-way impact mechanism is essential for the sustainable and collaborative development of the economy and environment in urban agglomerations. • Application of spillover-feedback effects in environmental field was expanded. • Spillover-feedback effects of virtual water transfer were measured in urban agglomeration. • The feedback effects were significant and could not be ignored. • More attention should be paid on the two-way impacts of environmental stress. [ABSTRACT FROM AUTHOR]

This paper proposes a hierarchical Bayesian network model (BNM) to quantitatively evaluate the resilience of urban transportation systems. Based on systemic thinking and taking a sustainability perspective, we investigate the long-term resilience of the road transportation systems in four cities in China from 1998 to 2017, namely Beijing, Tianjin, Shanghai, and Chongqing, respectively. The model takes into account various factors collected from multi-source data platforms involved in stages of design, construction, operation, management, and innovation in road transportation systems. We test the model with the forward inference, sensitivity analysis, and backward inference. The result shows that the overall resilience scores of all four cities' transportation systems are within a moderate range with values between 49% to 59%. Although they all have an ever-increasing economic level, the levels of transportation resilience in Beijing and Tianjin decrease first and then gradually increase in a long run, which indicates a strong multi-dimensional, dynamic, and non-linear characteristic in resilience-economic coupling effect. Additionally, the results obtained from the sensitivity analysis and backward inference suggest that decision makers should pay more attention to the capabilities of quickly rebuilding and making changes to cope with future disturbances. As an exploratory study, this study clarifies the concepts of long-term multi-dimensional resilience and specific hazard-related resilience and provides an effective decision-support tool for stakeholders when building resilient infrastructure. • A novel BNM is proposed to evaluate multi-faceted transportation resilience. • Forward inference, sensitivity tests, and backward inference are conducted. • Long-term transportation resilience is highly dynamic in the tested cities. • The coupling effects of resilience with economic level is not always linear. • Abilities to rebuild and adapt through reconfiguration are of importance. [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]