“…The device, fuel, and time costs were used to determine the transport costs and were calculated using historical fuel prices, energy intensity, and door-to-door travel speeds collected from existing studies 29 – 31 . For the bottom-up technology detailed recursive dynamic optimization model, we established a detailed technology database, including the initial cost, lifetime, energy efficiency, and emission factors, based on the AIM/Enduse datasets and related studies 32 , 33 .…”
The transport sector will play a pivotal role in achieving China’s carbon neutrality goal by 2060. This study develops a regional transport-energy integrated model to analyze the long-term pathways and strategies toward the carbon-neutral ground transport sector in China. A set of scenarios are created to identify the effectiveness and feasibility of low-carbon policy measures based on the well-known transport strategies within the Avoid–Shift–Improve framework. Our simulations shed light on synergistic coupling and trade-offs among different strategies and instruments for prescribing a desirable mix of policy measures that maximize the synergies and minimize the trade-offs. Here, we show that a region-specific policy package designed from a balanced perspective under the Avoid–Shift–Improve framework has the potential to realize a deep decarbonization in the transport sector and will greatly assist in achieving China’s carbon neutrality by 2060.
“…The device, fuel, and time costs were used to determine the transport costs and were calculated using historical fuel prices, energy intensity, and door-to-door travel speeds collected from existing studies 29 – 31 . For the bottom-up technology detailed recursive dynamic optimization model, we established a detailed technology database, including the initial cost, lifetime, energy efficiency, and emission factors, based on the AIM/Enduse datasets and related studies 32 , 33 .…”
The transport sector will play a pivotal role in achieving China’s carbon neutrality goal by 2060. This study develops a regional transport-energy integrated model to analyze the long-term pathways and strategies toward the carbon-neutral ground transport sector in China. A set of scenarios are created to identify the effectiveness and feasibility of low-carbon policy measures based on the well-known transport strategies within the Avoid–Shift–Improve framework. Our simulations shed light on synergistic coupling and trade-offs among different strategies and instruments for prescribing a desirable mix of policy measures that maximize the synergies and minimize the trade-offs. Here, we show that a region-specific policy package designed from a balanced perspective under the Avoid–Shift–Improve framework has the potential to realize a deep decarbonization in the transport sector and will greatly assist in achieving China’s carbon neutrality by 2060.
“…Here, we incorporate further more elaborate energy technology descriptions. The technology shares, energy intensities, and fuel-specific emission factors were obtained from the outputs of a technology bottom-up energy system model ( Akashi and Hanaoka, 2012 ; Akashi et al, 2012 ; Hanaoka et al, 2015 ; Mittal et al, 2015 ; Xing et al, 2018 ). Figure 1 Study area.…”
The novel coronavirus disease 2019 (COVID-19) crisis has influenced economies and societies across the globe and will thoroughly reshape our world as it continues to unfold. The pandemic is likely to trigger permanent long-term impacts on the transport sector in the post-COVID world. While a post-COVID “new normal” will be likely to incur negative consequences, it may provide an opportunity to move toward a more sustainable transport sector. This paper is aimed at developing an urban economic model with an energy focus to depict the dynamics of travel demand, energy consumption, and emissions in the post-COVID world. A set of scenarios was created according to model assumptions regarding lifestyle changes and policy interventions accompanied by the expected post-COVID new normal, to explore long-term pathways toward a deep decarbonization of the transport sector. Scenario simulations demonstrated that working from home, online shopping, and a bike-friendly infrastructure will contribute to a reduction in energy consumption and CO
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emissions, whereas a significant shift from bus to car transport and the decreasing use of car-sharing services will adversely affect CO
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emission reductions. The arrival of the post-COVID world may contribute to an 11% reduction in CO
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emissions by 2060, while the maximum reduction potential could be as high as 44%. Supporting policies and strategies for encouraging remote work and online shopping as well as for promoting safe public transport, active transport, and carpooling services are needed to strongly decarbonize the transport sector in the post-COVID world. Moreover, population distribution and urban structure may also be influenced by the arrival of the post-COVID new normal, which warrant further attention for urban planning.
“…GDP is the direct indicator to measure the economic development of a city. The proportion of the tertiary industry is often used as an important indicator for judging high-quality economic development (Xing et al , 2018). Therefore, GDP and the proportion of the tertiary industry are integrated to measure the economic development.…”
Purpose
A lot of people share their living or travelling experiences about cities by writing posts on social media. Such posts carry multi-dimensional information about the characteristics of cities from the public’s perspective. This paper aims at applying text mining technology to automatically extract city images, which are known as how observers perceive the status of the city, from these social media texts.
Design/methodology/approach
This paper proposes a data processing pipeline for automatic city image extraction and applies sentiment analysis, timing analysis and contrastive analysis in a case study on Wuhan, a central China megacity. Specifically, the city image constructed with social media text and the expected policy outcomes by the government are compared.
Findings
Results reveal gaps between the public’s impression and the strategic goals of the government in traffic and environment.
Originality/value
This study contributes a novel approach to assess government performance by complementary data from social media. This case study implies the value of social media-based city image in the identification of gaps for the optimization of government performance.
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