Green paradox: Factors affecting travel distances and fuel usages, evidence from Japanese survey

Yoo, Sunbin; Cho, Arum; Salman, Faris; Yoshida, Yoshikuni

doi:10.1016/j.jclepro.2020.122280

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…Two types of carbon emission measurements have been studied-one based on miles traveled via transportation [45,46] and the other based on energy consumption [47,48]. Considering the availability of the data, the second method was chosen in this paper to calculate the transportation carbon emissions of 30 provinces and cities.…”

Section: Calculation Of Transportation Carbon Emissionsmentioning

confidence: 99%

Study on the Carbon Emission Spillover Effects of Transportation under Technological Advancements

2022

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Regional transportation emissions reduction is the key to realizing deep emission reduction and the neutralization of transportation. Transportation development is accompanied by technological progress, and inter-regional transportation technological progress and carbon emission spillover effects are issues worthy of study. Based on the 2011–2020 provincial data of 30 provinces and cities in China, a spatial Durbin model was constructed to explore the impact of technological progress on regional spillovers of carbon emissions and the driving effect of emissions reduction. The conclusions show that the “community effect” causes direct interactions between transportation carbon emissions reduction practices in various provinces; the “acquired effect” and “leakage effect” drive technological progress between regions and cause indirect interactions between transportation carbon emissions reduction practices; transportation technology progress is more likely to occur between regions with similar transportation development. Finally, some suggestions are put forward in terms of establishing a mechanism for the coordinated reduction of regional carbon emissions, strengthening the interactions and economic connections between inter-regional transportation technologies, optimizing the spatial layout of transportation infrastructure, and building a low-carbon transportation system, so as to lay a solid foundation for the coordinated reduction of regional transportation carbon emissions.

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Section: Calculation Of Transportation Carbon Emissionsmentioning

confidence: 99%

Study on the Carbon Emission Spillover Effects of Transportation under Technological Advancements

2022

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“…This effect is apparent, for example, in the automotive sector, where the increase in car energy efficiency has not led to reduced fuel consumption, but to increased vehicle weight and engine power [27,28]. Research in Japan also shows that more fuel-efficient hybrid cars cover greater distances [29,30]. A similar phenomenon was observed by Wilson and Boehland in single-family house construction in the USA, where the space occupied by one person tripled from 1950 to 2004.…”

Section: The Paradox Of Energy Efficiency and The Increase In Demand For Energy-powered Servicesmentioning

confidence: 68%

Households’ Electrical Energy Conservation and Management: An Ecological Break-Through, or the Same Old Consumption-Growth Path?

et al. 2021

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We examine the motivations behind the electrical energy conservation and smart management at households to verify whether we are observing an ecological breakthrough, or a mere continuation of the well-trodden consumption-growth path. We conducted an online survey in France, Spain, Italy, and Denmark (n = 3200) on the subject of electricity use and generation. We utilized a generalized structural equation model to simultaneously test the direct reasons behind different energy-use behaviors and intentions, as well as their motivating factors. Measures to conserve electrical energy and install renewable energy equipment are not solely driven by ecological concerns; a crucial role is played by openness to new technologies, which correlates with high financial status. Saving electrical energy and new-tech eagerness go hand-in-hand with attachment to consumption and comfort. Social environment is relevant, as it allows users to converse about electricity saving with friends, and to observe their habits. Individuals may aim not to consume less energy, but to enhance their standards of living by economizing energy to fund other purchases, which limits the reduction in carbon footprint. Increasing the popularity of energy-saving solutions, therefore, might prove insufficient in the face of environmental threats and the challenges of transforming the energy market.

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“…Moreover, most of the current studies have utilized traditional small sample data to analyze bus travel time and its related factors [16,17]. However, small sample survey data cannot fully and accurately obtain the origin, destination, and departure time of bus passengers, thereby making it challenging to accurately reveal the joint infuence of the built environment at the origin and destination, weather, and temporal and spatial characteristics on travel time.…”

Section: Introductionmentioning

confidence: 99%

What Affects Bus Passengers’ Travel Time? A View from the Built Environment and Weather Condition

Li,

Shi,

et al. 2023

Journal of Advanced Transportation

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The study aims to examine the impact of the built environment and weather conditions on travel time for bus passengers in Weinan, China. Various sources of data, including smart card data, bus GPS data, bus station data, road information data, and smart card swiping time, were integrated and analyzed. The study employed the light gradient boosting machine (LightGBM) model and SHapley Additive exPlanations (SHAP) value to assess the feature importance and nonlinear effects of different types of POI density, weather conditions, and time series on bus passengers’ travel time. The study findings indicate that several factors are associated with bus passengers’ travel time, including destination residential density, destination diversity, destination life service density, origin science and education density, origin residential density, origin diversity, humidity, visibility, boarding time between 7 and 8 a.m., and precipitation. This study also reveals nonlinear threshold effects. The study findings provide valuable insights that can be utilized to optimize the bus network and develop low-carbon-oriented land-use planning.

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Green paradox: Factors affecting travel distances and fuel usages, evidence from Japanese survey

Cited by 7 publications

References 26 publications

Study on the Carbon Emission Spillover Effects of Transportation under Technological Advancements

Study on the Carbon Emission Spillover Effects of Transportation under Technological Advancements

Households’ Electrical Energy Conservation and Management: An Ecological Break-Through, or the Same Old Consumption-Growth Path?

What Affects Bus Passengers’ Travel Time? A View from the Built Environment and Weather Condition

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