Based on the social network analysis (SNA) and the cascading failure model, this paper develops a model of elasticity analysis of the Industrial Symbiosis (IS) network and evaluates the Nanjing Chemical Industry Parks (NCIP) by the metrics of network efficiency and survival rate of the nodes. This paper finds that the NCIP is mainly composed of three major industrial chains, involving the circulation flow of the material, by-products, and energy, and show heterogeneous. Under an intentional attack on the consumer nodes, most of the node's failure cause a chain reaction and bring about changes in network efficiency, and the resilience is not identical accordingly. The network efficiency increases with the augment of the elasticity level, it will not change when reached a certain peak, and the survival rate of the node also increases with the increase of the elasticity level. Therefore, the choice of the optimal elasticity level is helpful to the construction and normal operation of the symbiosis network. At the same time, in order to improve the resilience of the symbiotic network, enterprises should communicate periodically. Because of the ability to find and eliminate the adverse factors, periodic checks are critical for symbiosis between nodes. In order to prevent a network collapse, the NCIP management committee should evaluate the resilience of the IS network regularly, and the government should support the construction of the IS network and give tax subsidies or deductions.

Urban transportation in China is undergoing a revolution due to ride-sourcing. The strong growth in ride-sourcing travel requires the government and the industry to adopt strategies for reducing environmental impact. Here, we address a key gap in knowledge on the emerging ride-sourcing travel model by designing a roadmap for realizing low-emission ride-sourcing drawing from an analysis of raw big trip data for Beijing. We found that adopting the most effective low-emission strategies requires joint efforts involving governance and management, enterprise operations, and consumer behavior change. With respect to issues of feasibility and effectiveness, the enterprise operation strategy, involving polices that shorten the pick-up time and increase the vehicle occupancy, is the best option, offering approximately 44% CO2 and NOx emission reductions compared with the current situation. Promoting ride-sourcing usage among car users or potential car users could help reduce emissions attributing to less cars being manufactured (26% CO2 and 24% NOx) but with uncertainty. To achieve low-emission ride-sourcing travel, governments, enterprises, and consumers must collaborate closely and define clear roles, responsibilities, and relationships.

Emerging ridesharing travel could be an effective way in China to reduce travel demand by cars, which can further seek to shift personal transportation choices from an owned asset to a service used on demand and lessen the traffic jam and emissions. Drawing on the raw observed ridesharing trip data provided by DiDi Chuxing company, this study evaluated the direct environmental benefits of ridesharing resulted from the travel mode shift and the indirect environmental benefits resulted from the attitude change towards car purchase behavior. The megacity Beijing is taken as the empirical context given its more serious situation of traffic congestion and difficulties for car purchase. Estimation results show that direct annual energy savings made by ridesharing are approximately 26.6 thousand tce, and annual emission reductions of CO2 and NOx are approximately 46.2 thousand tons and 253.7 tons, respectively. Besides, using ridesharing service will lead to substantial energy savings and emission reductions from the long-term perspective attributing to the weakening willingness on purchasing new cars. Promoting EVs among ridesharing vehicles and switching to clean electricity generation as well as improving vehicle efficiency can further enhance the environmental benefits of ridesharing, with maximum effects amounting to 67% of energy savings and 57% of CO2 emission reductions compared to 2016 level of the fuel related energy consumption and emissions made by ridesharing. (C) 2017 Elsevier Ltd. All rights reserved.

It is an important measure for China to implement the strategy of major functional area (MFA) to promote the optimization and upgrading of the industry and the development of regional integration. In order to study spatial correlation structure between optimization development zone and key development zone, the paper chooses Beijing-Tianjin-Hebei Metropolitan Region (BTHMR) and Ha-Chang City Group (HCCG) as examples. Based on cross regional input-output table and Social Network Analysis (SNA), regional industrial spatial correlation network model is established. By analyzing the characteristics of network structure and the function of block, industrial spatial correlation structure between optimization development zone and key development zone is studied. Furthermore, with the grey target contribution analysis, the major causes of the formation of the industrial spatial correlation structure are discussed from the characteristics of the industry in the spatial correlation network.

This study evaluates the efficiency advantage of a market-based emission permit trading policy instrument over a command and control policy instrument in the case of China's thermal power industry. We estimate the unrealized gains achievable through emission permit trading with an optimization frontier analysis. These unrealized gains include potential recoveries of electricity generation through eliminating spatial and temporal regulatory rigidity on emission permit trading. The results of an ex post estimation during 2006 and 2010 indicate a potential gain of 8.48% increase in electricity generation if both the intra- and inter-period regulatory rigidities on CO2 emission permits trading had been eliminated. In addition, if the permit trading systems for three air pollutions, CO2, SO2, and NOx, had been completely integrated, a positive net synergy effect of 1.43% increase in electricity generation could have been secured. The unrealized gains identified in this study provide supports for establishing a nationwide emission permit trading system in China.

This paper develops an energy consumption network model with Chinese-2007 input-output table and the data of industrial sector energy consumption. The network characteristics and influencing factors on industrial scale are analyzed with the social network analysis and stepwise regression method. The results show that the energy consumption network might be characterized by close linkages however it isn't scale-free. The sequencing result of in-strength and out-strength shows that the energy consumption of General equipment manufacturing and Electrical equipment manufacturing can't be ignored for they are key sectors of indirect energy consumption. The structure parameters of the energy consumption network between industrial sectors have promoting effect on industrial scale.

The exiting DEA methods generally consider energy consumption as input indicator. It is reasonable from the perspective of economy or energy conservation. But from the perspective of environment or clean energy utilization, a region using more energy to generate lower pollutants is considered to be more efficient. Thus, energy consumption should be regarded as output indicator. If we consider the two perspectives at the same time, it will be difficult to judge energy consumption as input indicator or output indicator. To solve this problem, we incorporate Nash bargaining game (NBG) into DEA model to estimate the economic efficiency, environmental efficiency and united efficiency for China's 30 provinces during 2000-2011. It is found that the economic efficiency, environmental efficiency and united efficiency during 2000-2011 in China present distinct stage characteristics. The results obtained by employing the Mann and Whitney rank sum test imply that three efficiency measures among east area, central area and west area of China have significant heterogeneity, and the differences of provinces on the three performance measures are significant. On the basis of clear understanding about performance difference among provinces of China, it will contribute to realizing the win-win strategy as regard to the economy and environment on the whole by carrying out targeted economic and environmental policies for different regions.