ABSTRACT
End-of-life vehicles (ELVs) present both opportunities and challenges for the environment and the economy, where effective recycling management plays a decisive role. Recently, the primary focus of recycling management has shifted from simply meeting demand to refining and optimizing processes at the city-scale. However, the mismatch in recycling capacity has become a significant obstacle to maximizing environmental and economic benefits. To reveal this issue and propose improvements in the context of China, this study simulates end-of-life internal combustion engine vehicles (ICEVs) and new energy vehicles (NEVs) at the city-scale from 2021 to 2050, and analyzes their spatio-temporal pattern and recycling capacity matching. The results indicate that the number of ELVs in China will continue to increase, peaking between 3.5 and 3.7 million. This growth will be mainly driven by third- to fifth-tier cities, as well as central and southwestern cities. Regarding recycling capacity matching, most cities possess excess dismantling capacity, while first-tier cities face coordination problems in battery collection. Spatial coordination across cities or provinces is a viable approach for dismantling enterprises and should be prioritized over indiscriminate deregistration or establishing new facilities. The absence of initiative within the recycling system results in uncoordinated battery collection. Implementing a recycling-sharing mechanism and establishing a reuse market can effectively tackle this problem by leveraging market incentives. These analyses provide practical suggestions to maximize the environmental and economic benefits of resource recycling, thereby contributing to the UN's 2030 Sustainable Development Goals (SDGs).
ABSTRACT
Public transport performance not only directly depicts the convenience of a city's public transport, but also indirectly reflects urban dwellers' life quality and urban attractiveness. Understanding why some regions are easier to get around by public transport helps to build a green transport friendly city. This paper initiates a new perspective and method to investigate how public transport network's morphology contributes significantly to its performance. We investigate the significance of morphology from the perspective of graph classification - by extracting the typical local structures, called "motifs", from the multi-modal public transport multigraph. A motif is seen as a certain connectivity pattern of different transport modes at a local scale. Combinations of various motifs decide the output of graph classification, particularly, public transport performance. We invent an innovative method to extract motifs on complex spatial multigraphs. The proposed method is adaptable to unify complex factors into one simple form for swift coding, and depends less on observational data to handle data unavailability. In the study area of Beijing, we validate that the measure can infer varied public transport efficiencies and access equalities of different regions. Some typical areas with undeveloped or unevenly distributed public transport are further discussed.
