Many cities in China have opened a subway, which has become an important part of urban public transport. How the metro line forms the metro network, and then changes the urban traffic pattern, is a problem worthy of attention. From 2005 to 2018, 10 metro lines were opened in Nanjing, which provides important reference data for the study of the spatial and temporal evolution of the Metro network. In this study, using the complex network method, according to the opening sequence of 10 metro lines in Nanjing, space L and space P models are established, respectively. In view of the evolution of metro network parameters, four parameters—network density, network centrality, network clustering coefficient, and network average distance—are proposed for evaluation. In view of the spatial structure change of the metro network, this study combines the concept of node degree in a complex network, analyzes the starting point, terminal point, and intersection point of metro line, and puts forward the concepts of star structure and ring structure. The analysis of the space‒time evolution of Nanjing metro network shows that with the gradual opening of metro lines, the metro network presents a more complex structure; the line connection tends to important nodes, and gradually outlines the city’s commercial space pattern.

The rapid development of cities has brought new challenges and opportunities to traditional traffic management. The usage of smart cards promotes the upgrading of intelligent transportation systems, and also produces considerable big data. As an important part of the urban comprehensive transportation system, Nanjing metro has more than 1 million inbound and outbound records of traffic smart cards used by residents every day. How to process these traffic data and present them visually is an urgent problem in modern traffic management. In this study, five working days with normal weather conditions in Nanjing were selected, and the swiping records of the smart cards were extracted, and the space–time characteristics were analyzed. In terms of time analysis, this research analyzed the 24-h fluctuation of daily average passenger flow, peak hour coefficient of passenger flow, 24-h fluctuation of passenger flow on different metro lines, passenger flow intensity on different metro lines and passenger flow comparison at different stations. In spatial analysis, this study uses thermodynamic charts to represent the inflow and outflow of passengers at different stations during early and evening peak periods. The analysis results and visualized images directly reflect the area where Nanjing metro congestion is located, and also shows the commuting characteristics of residents. It can solve the problem of urban congestion, carry out the rational layout of urban functional areas, and promote the sustainable development of people and cities.

With the strengthening of environmental awareness, the government pays much more attention to environmental protection and thus implements carbon trading schemes to promote the reduction of global carbon dioxide emissions. The carbon Generalized System of Preferences (GSP) is an incentive mechanism for citizens to value their energy conservation and carbon reduction. Individual travel needs to rely on various means of transportation, resulting in energy consumption. Carbon tax or subsidy can only be carried out after carbon GSP accurately measures individual carbon emissions. The big data acquired from the smart cards of passengers’ travels provide the possibility for carbon emission accounting of individual travel. This research proposes a carbon emission measurement of individual travel. Through establishing the network model of the Nanjing metro with a complex method, the shortest path of the passengers’ travels is obtained. Combined with the origination–destination (OD) records of the smart cards, the total distance of the passengers’ travels is obtained. By selecting the operation table to estimate the carbon emissions generated by the daily operation of the subway system, the carbon emissions per kilometer or per time of passenger travel are finally obtained. With the accurate tracking of carbon emissions for individual travel, the government may establish a comprehensive monitoring system so as to establish a carbon tax and carbon supplement mechanism for citizens.

With the enhancement of environmental awareness, China has put forward new carbon peak and carbon neutrality targets. Electric vehicles can effectively reduce carbon emissions in the use stage, and some retired power batteries can also be used in echelon, so as to replace the production and use of new batteries. How to calculate the reduction of carbon emission by the echelon utilization of retired power batteries in energy storage power stations is a problem worthy of attention. This research proposes a specific analysis process, to analyze how to select the appropriate battery type and capacity margin. Taking the BYD power battery as an example, in line with the different battery system structures of new batteries and retired batteries used in energy storage power stations, emissions at various stages in different life cycles were calculated; following this in carbon emission, reduction, by the echelon utilization of the retired power battery, was obtained. Finally, the overall carbon emissions that might be reduced by echelon utilization in the future were calculated according to the BYD’s battery loading volume and China’s total power battery loading volume in 2021. This research provides a quantitative analysis idea for the carbon emission reduction of power battery echelon utilization. Using this method could improve the process of echelon utilization, optimize the supply chain of power batteries, drive the development of the new-energy vehicle industry, and explore new business models, so as to achieve the environmental protection goal of carbon neutrality.

Metro plays an important role in an urban public transport system. With the use of metro lines, the increasing flow of people has brought tremendous pressure to the operation of metro lines, resulting in different faults, thus affecting the travel of residents. How to qualitatively evaluate the robustness of the metro network after encountering faults is a problem worthy of attention. By 2018, ten metro lines have been opened in Nanjing, forming a radiation structure from the urban center to the surrounding suburbs. In this study, the metro faults in Nanjing in the past three years are counted and classified. The space L and space P models for the metro network are constructed. The robustness of a Nanjing metro network is measured by the three indicators: network connectivity efficiency, largest connected subgraph size, and average subgraph size. The concept of supernetwork is proposed, and the metro line is considered as a whole. The robustness changes of the Nanjing metro network caused by the attacks on the nodes and hyperedges of the metro network are analyzed. The results show that deliberate attack causes more damage than a random attack. When traffic hub stations and trunk lines are attacked, the performance of the metro network will decline sharply. The research conclusion has certain practical value to enhance the anti-fault ability of the metro network.

In recent years, many researchers have applied complex network theory to urban public transport network to construct complex network and analyze its network performance. The original analysis method generally uses the Space L and Space R model to establish a simple link between public sites but ignores the organic link between the overall network system and the line subsystem. As an important part of urban public transport system, subway plays an important role in alleviating traffic pressure. In this paper, a supernetwork model of Nanjing metro network is established by using the supernetwork method. Three parameters, node‐hyperedge degree, hyperedge‐node degree, and hyperedge degree, are proposed to describe the model. The model is compared with the traditional Space L and Space P models. The study on the supernetwork model of Nanjing metro complex network shows that the network density, network centrality, and network clustering coefficient are large, and the average network distance is small, which meets the requirements of traffic planning and design. In this study, the subway line is considered as a subsystem and further simplified as a node, so that the complex network analysis method can be applied to the new supernetwork model, expanding the thinking of complex network research.