Transport-related CO2 Emissions Research Articles

ASSESSING THE POTENTIAL OF RAILWAYS TO REDUCE CO2 EMISSIONS: A COINTEGRATION STUDY OF ESTONIA'S TRANSPORT SECTOR

This The transportation sector is a major contributor to CO2 emissions, playing a significant role in exacerbating climate change. Railways, known for their greater energy efficiency compared to other modes of transport, present a viable solution for mitigating emissions, particularly in countries like Estonia. In 2014, transport-related CO2 emissions in Estonia were recorded at 12.7%, marking an overall upward trend since 1995, despite experiencing some fluctuations over the years. This study aims to explore the long-term equilibrium relationship between CO2 emissions from transport and railway passenger kilometers in Estonia through the application of cointegration analysis. Utilizing Engle-Granger and Phillips-Ouliaris cointegration tests, the analysis reveals a stable, long-term equilibrium relationship between the two variables. The findings suggest that an increase in railway passenger kilometers could potentially lead to a reduction in CO2 emissions from transport. These results underscore the importance of enhancing railway infrastructure and usage as a strategic measure to curb transportation-related emissions and contribute to environmental sustainability.

Examining Determinants of Transport-Related Carbon Dioxide Emissions by Novel Super Learner Algorithm

Combating carbon dioxide (CO2) emissions across sectors becomes inevitable due to negative impacts. The transport sector takes place among the most important sectors. Accordingly, the study examines transport-related CO2 (TCO2) emissions in the top four emitting countries (namely, the United States, Canada, Saudi Arabia, & Australia) by considering six explanatory variables, using data from 1990/Q1 to 2020/Q4, and performing an artificial intelligence approach. The outcomes show fresh insights that (i) super learner (SL) algorithm overwhelms other machine-learning algorithms in terms of model performance; (ii) energy intensity has an increasing impact on TCO2 emissions, whereas others (e.g., financial development, income, globalization, oil use, & urbanization) have a mixed impact across countries; (iii) the influential variables have some critical thresholds, where the power of impacts differentiate across these limits. Hence, the SL algorithm presents robust outcomes for TCO2 emissions. Accordingly, a set of policy endeavors for the countries examined are also discussed.

Urban transport emission prediction analysis through machine learning and deep learning techniques

About 6.6 million people die every year from air pollution diseases globally. Transportation industry is considered one of the leading contributors in air pollution. This research utilizes deep learning and machine learning techniques to predict China’s transport-related CO2 emissions and energy needs by utilizing variables like population, car kilometers, year and GDP per capita. The outcomes have been analyzed using six analytical measures: determination coefficient, RMSE, relative RMSE, mean absolute percentage error, mean bias error and mean absolute bias error. Findings indicate that yearly increase in transport-related CO2 emissions in China will be 3.66%, and transport energy consumption will increase by 3.8%. Energy consumption and transport CO2 emissions are projected to rise by roughly 3.5 times by 2050 as compared to current levels. Therefore, government should re-evaluate its energy investment plans for the future and institute new rules, and standards regarding transport-related energy consumption and pollution reduction.

Tourism Transport-Related CO2 Emissions and Economic Growth: A Deeper Perspective from Decomposing Driving Effects

This study explores the intricate dynamics of CO2 emissions stemming from transport within the tourism sector. It aims to unravel the multidimensional aspects of how transport-related tourism contributes to CO2 emissions and to elucidate the complex relationship between regional economic growth and CO2 emissions from transport-related tourism. Our study employed Logarithmic Mean Divisia Index (LMDI) and Panel Vector Autoregression (PVAR) models to analyze data from 30 Chinese provincial regions between 2010 and 2018. The tourism transport-related CO2 emissions were decomposed into four separate driving effects using the LMDI approach. Then, PVAR models were constructed to reveal dynamic interactions between each driving effect and per capita gross regional product (GRP). Our results demonstrate a decrease in both energy structure effect (tourism transport-related CO2 emissions from energy structure) and energy intensity effect (tourism transport-related CO2 emissions from energy intensity) during the pre-COVID decade. Notably, the positive impulse response of energy structure effect to per capita GRP is observed. However, we found no evidence of a cointegrated relationship between energy intensity effect and regional economic growth, although other factors demonstrated connections. These findings echo the necessity to integrate sustainable practices into the tourism transportation business, especially in the area of energy structure, in order to mitigate adverse environmental effects from tourism. This paper disseminates the main drivers of CO2 emissions in the tourism transport sector and their interrelationship with regional economic growth. It not only guides tourism policymakers in targeting efforts to reduce carbon footprints, but also sets a new benchmark for future studies on CO2 emissions.

Modeling the long-term relationship between transportation, economic growth, poverty and environmental degradation in Tunisia

The transportation sector plays a crucial role in driving economic development, reducing poverty, and contributing significantly to environmental impacts. While there have been numerous studies exploring the interconnections among transportation, economic development, and environmental degradation, there hasn’t been extensive research on how poverty affects transport-related CO2 emissions in the Tunisian context. This study aims to address this gap by analyzing the complex relationship between poverty, economic growth, energy consumption in road transport, urbanization, trade openness, road infrastructure, and environmental degradation in the Tunisia's transportation sector from 1980 to 2020. To estimate the long-term relationship between these variables, we use the ARDL bounds test approach. The result of VECM Granger causality test indicates a feedback between road infrastructure, road energy consumption, and transport emissions in both the short and long term. Moreover, our study identifies a bidirectional causality between poverty and transport emissions, emphasizing the importance of poverty alleviation strategies that consider environmental consequences. Our research also reveals a feedback between poverty and road transport infrastructure, as well as between transport emissions and economic growth. These results provide a comprehensive overview of the factors influencing CO2 emissions in the transport sector and their relationship with poverty. They offer a valuable insight to the field of energy and environmental studies, serving as guidance to policymakers, researchers, and practitioners engaged in promoting sustainable transportation practices in Tunisia.

Biodiesel and its potential to mitigate transport-related CO2 emissions

Many studies have concentrated on the energy capacity of biodiesel to reduce CO2 emissions at the aggregate level and not much at the sectoral level. This study addresses this gap and attempts to estimate the impact of the use of palm biodiesel on the transport CO2 emissions in Malaysia during 1990–2019. It also predicts the impact of implementing the B10 blending program (10% biodiesel in diesel fuel) on CO2 emissions from transport in this country. For this purpose, this study uses the dynamic autoregressive distributed lag (ARDL) and Kernel-based regularized least squares. This model can plot and estimate the possible actual changes in biodiesel consumption to predict its impacts on transport CO2 emissions. The results suggest that a one-way Granger causality exists from transport GDP, diesel consumption, and motor petrol consumption to palm biodiesel consumption. An increase of 1% in the use of biodiesel reduces carbon emissions from road transport by 0.004% in the long run, while, in the short run, it is associated with a 0.001% increase in transport CO2 emissions. The simulated results from the dynamic ARDL model suggest that a 10% increase in the share of biodiesel consumption in fuel transport by 2030 would reduce the rate of the increase in road transport carbon emissions. The improvement and management of new technologies in oil palm plantation and harvesting can help increase palm oil production for biofuels and edible oil and to reduce forest replacement and therefore biodiversity and food security.

Understanding the challenge of decoupling transport-related CO2 emissions from economic growth in developing countries

The transition to net zero requires full decarbonization of the transport sector, currently one of the leading sources of emissions globally. Transport-related carbon emissions are growing fastest in the developing world. This makes it particularly critical to understand whether low- and middle-income countries are making progress towards decoupling transport sector emissions from economic growth, as well as the extent to which their current emissions trajectory is being shaped by structural factors versus more amenable policy choices. This paper assembles and analyzes a comprehensive dataset on transport-related emissions with a uniquely broad coverage of developing countries. The paper employs the Tapio decoupling model over the period 1990–2018 to demonstrate that high-income countries are almost twice as likely to have reached relative decoupling as low and middle-income countries (70 vs 36 percent, while the latter are almost twice as likely to be in a state of negative decoupling as the former (17 versus 41 percent). This paper conducts index-decomposition and econometric analysis to shed light on the factors driving transport-related carbon emissions. Index decomposition reveals that there have been only relatively modest reductions in the transport emissions intensity of GDP since 1990 and that these have not been large enough to offset economic growth in middle-income countries and demographic growth in low-income countries. Regression analysis further shows that urbanization and industrialization are important correlates of transport-related emissions, while the correlation of policy choices with reduced emissions is rather weak.

Combining economics and psychology: Does CO[formula omitted] framing strengthen pro-environmental behaviors?

This paper considers valence-based framing, i.e. a description of equivalent outcomes in either a positive or negative light, in order to reduce transport-related CO2 emissions. This nudge is easier to implement than more traditional tools, such as taxation, and does not rely on the stringent assumption that individuals are fully rational. The findings from a discrete choice experiment focusing on long-distance travel choice are reported herein. Results indicate that a loss framing on CO2 emissions significantly increases the respondents’ pro-environmental behaviors. Moreover, it is shown that the magnitude of the framing effect depends on individuals’ motivational orientation, and that preferences are sensitive to individuals’ psychological factors (i.e. preference for the future and environmental self-identity).

How do pandemics affect intercity air travel? Implications for traffic and environment

This paper investigates how a pandemic affects the distribution of traffic between public and private transport and the emissions from the transport sector. By assuming that there exists higher health risk of traveling in public transport than in private transport and using air transport and private cars as examples, we find the following results. First, the effects of a pandemic on the traffic volumes of airline services and private cars depend crucially on, for instance, the willingness-to-pay of travelers, the degree of substitution between transport modes, the demand-side network effect (via schedule delays), and the supply-side network effect (via the economies of traffic density). In particular, heterogeneous effects of the pandemic on the traffic volumes and flight frequencies of different airline services are found. Second, the total transport-related CO2 emissions decrease after the pandemic if the CO2 emissions per air traveler (or per flight) are sufficiently high, or the degree of substitution between airline services and private cars is sufficiently low. Third, numerical examples on the change in price of car travel and the introduction of high-speed rail show consistent insights. Finally, several policy implications are discussed.

Advances in Delivery of Selective Internal Radiation Therapy (SIRT): Economic and Logistical Effects of Same-Stay Work-Up and Procedure in the Treatment of Unresectable Liver Tumors in England.

Selective internal radiation therapy (SIRT) is a targeted method of treatment for unresectable liver tumors in which radiation therapy is directly delivered to the tumor(s) via the hepatic vasculature. Successful outcomes with SIRT are dependent on the specific vasculature of the liver and tumor, and the patient therefore needs to attend a "work-up" to map the hepatic vasculature prior to the SIRT procedure. Recent advances in SIRT delivery have enabled same-day or same-stay work-up and procedure, requiring only one hospital visit rather than two. We aimed to evaluate the economic, travel time, and transport-related environmental impact of a new brachytherapy device delivery program, the order-map-treat (OMT) program, in patients with unresectable hepatocellular carcinoma (HCC) in England. A healthcare resource group (HRG)-based analysis of costs from a national payer (Department of Health and Social Care, DHSC) perspective was conducted assuming that, with OMT, patients would have to attend hospital only once for both the SIRT work-up and procedure versus twice without OMT. Patient travel time and CO2 emissions were then estimated by identifying the SIRT center closest to the centroid of each clinical commissioning group (CCG) and calculating straight-line distances with a "detour index" to capture the effect of indirect routes via road or rail. It was estimated that 856 patients per annum would be eligible for SIRT treatment for unresectable HCC in England. OMT would be anticipated to save GBP2842 per patient versus performing SIRT without OMT. Furthermore, across all patients with HCC eligible for SIRT in England, OMT would avoid 74,500km of travel, 2299h of travel time, and 13.9 metric tons of patient transport-related CO2 emissions annually. OMT reduces the number of hospital visits required for SIRT by 50%, resulting in financial savings from the DHSC perspective, time savings from the patient perspective, and reduced CO2 emissions arising from patient transport.

Are there synergies in the decarbonization of aviation and shipping? An integrated perspective for the case of Brazil

SummaryAviation and shipping account for 22% of total transport-related CO2 emissions. Low-carbon fuels (such as biofuels and e-fuels) are the most promising alternatives to deeply decarbonize air and maritime transport. A number of technological routes focused on the production of renewable jet fuel can coproduce marine fuels, emulating the economies of scope of crude oil refineries. This work aims to investigate possible synergies in the decarbonization of aviation and shipping in Brazil, selected as an interesting case study. An Integrated Assessment Model (IAM) of national scope is used to explore different combinations of sectoral and national climate targets. This IAM represents not only the energy supply and transport systems but also the agricultural and land-use systems. In the absence of a deep mitigation policy for Brazil, results indicate synergies related to oilseed- and lignocellulosic-based biofuels production routes. Imposing a strict carbon budget to the Brazilian economy compatible with a world well below 2°C, the portfolio of aviation and shipping fuels changes significantly with the need for carbon dioxide removal strategies based on bioenergy. In such a scenario, synergies between the two sectors still exist, but most renewable marine energy supply is a by-product of synthetic diesel produced for road transport, revealing a synergy different from the one originally investigated by this work.

Modeling municipal solid waste disposal consortia on a regional scale for present and future scenarios

Efficient Waste Management Systems (WMS) management is a global challenge since the waste volume has grown continuously. In WMS Life Cycle Assessment (LCA), collection and transport are the primary environmental and economic impact sources. This study aims to analyze the best inter-municipal consortia configuration for adequate Municipal Solid Waste (MSW) disposal in landfills using Linear Programming (LP) and Mixed Integer Linear Programming (MILP) for the current and future scenarios for the years 2021 and 2033, respectively. It was considered factors such as MSW volume generated by each municipality, transportation distance, and landfill construction cost applied on a regional scale to the Rio Grande do Sul State in Brazil. Our findings appointed a 56% reduction in fuel consumption and carbon dioxide (CO2) emissions for the current scenario of 2021, with annual savings exceeding US$10 million. In addition, the best consortia configuration and the optimal number of landfills were determined for the future scenario, and a 60% reduction in fuel consumption and CO2 emissions was achieved, reaching an annual saving of over US$13 million per year exceeding US$250 million until 2033. In addition to economic savings for municipalities and taxpayers, the optimized WMS would result in environmental and health gains, reducing transport-related CO2 emissions by around 411 thousand tons.

Investigating the impacts of transit-oriented development on transport-related CO2 emissions

Transit-oriented development (TOD) is considered as one of the most sustainable neighborhood planning practices, yet relatively little evidence exists on the environmental sustainability of TODs. This study examines transport-related CO 2 emissions of TODs in Dhaka, Bangladesh. Individual-level CO 2 emissions were calculated for three types of trips (home-based work, home-based school, and home-based other non-work) of 31,101 residents living in TOD and non-TOD neighborhoods. Three multi-level models were estimated, one for each trip type, to identify the effects of TODs on CO 2 emissions, controlling for spatial heterogeneity and spatial dependency of the neighborhoods and other confounding effects. Findings show that TODs have the potential to reduce CO 2 emissions for work and school trips, but not for other non-work trips in Dhaka. While the results partially verify the environmental sustainability outcome of TODs, how to design TODs to capitalize full environmental benefits remains a challenge for planners in developing countries.

A decoupling analysis of transport CO2 emissions from economic growth: Evidence from Vietnam

Since economic reforms in the late 1980s, Vietnam’s economy has grown rapidly, but transport activity has grown faster presenting a significant challenge for reducing transport related CO2 emissions. This paper explores this challenge by comprehensively evaluating decoupling in Vietnam’s transport sector over the period 1995 to 2017. Decoupling elasticities reveal that there is no decoupling of transport volumes from GDP, but between 2011 and 2017, CO2 emissions from transport were decoupling from GDP. Digging deeper reveals that the income driver is in an expansive coupling state, and this is mostly due to the structure of the economy. Different drivers of carbon intensity were important at different times. The importance of the drivers fit a hypothesis of economic restructuring and household income growth. Energy intensity constrained emissions growth, especially from 2011, and was the key driver aiding the decoupling process. The analysis suggests that reducing transport intensity together with modal switching offers the most scope for future decoupling. Barriers that limit the decoupling process include cheap fuel prices and a lack of modal alternatives to private road transport as such appropriate policy responses should target these areas. Highlights Comprehensive analysis of decoupling in the transport sector of Vietnam. Vietnamese transport volumes are not decoupling from GDP, but transport CO2 emissions are. Transport intensity, incomes and economic structure hampered decoupling while energy intensity aided decoupling. The decoupling effort model suggests emissions are reducible. Policy responses include removing market inefficiencies and increasing modal choices.

Lifespans of passenger cars in Europe: empirical modelling of fleet turnover dynamics

Cars have a high share of global transport-related CO2 emissions. To model the market diffusion of new energy carriers and powertrains like electric vehicles, fleet turnover models are commonly used. A decisive influence factor for the substitution dynamics of such transformations is the survival rate of the national car fleet of a country. It represents the likelihood of a car reaching a certain lifespan. Due to a lack of data, current methods to estimate such survival probabilities neglect the imports and exports of used cars. Existing studies are limited to countries with a predominant market of new cars, compared to low numbers of imported and exported used cars. In this study, we resolve this marked simplification and propose a new method to estimate survival probabilities for countries with a high number of imported and exported used cars. Empirical data on the car stock, on inflows of new and used cars, and on outflows of exported and scrapped cars are gathered from 71 national statistics offices. Survival rates of the car fleets of 31 European countries are derived, for which we find a pronounced regional variability. Average lifespans of cars vary from 8.0 to 35.1 years, with a mean of 18.1 years in Western and 28.4 years in Eastern European countries, revealing the high impact of cross-border flows of cars. The study also shows that survival rate estimates can be improved significantly even in the absence of reliable data if a combination of a Weibull and a Gaussian distribution is used. It is likely that the predictive power of existing models (regarding the future environmental impact of car fleets) could be improved significantly if these findings were considered accordingly. The findings of this study can directly be included in fleet turnover and policy assessment models. They also enable the analysis of economic and environmental spillover effects from the imports and exports of used cars between countries.

Land transport development in three integrated scenarios for Germany – Technology options, energy demand and emissions

Today, transportation contributes significantly to greenhouse gas emissions and air pollution. However, new technologies are emerging and existing technologies are being further improved. This article presents the results of a comprehensive study on the development of drive-trains, resulting electricity and fuel consumption as well as emissions of CO2 and selected air pollutants in land transport in Germany. This includes a quantitative assessment of technological potentials and of resulting energy consumption and emissions. The scenario building followed an explorative approach. Only the scenario depicting a consistent transition towards electrified mobility and regulated emissions from the energy system leads to a significant reduction in transport related CO2 emissions. Yet, the analysis shows that it is unlikely that the German emission reduction target in 2030 for the transport sector will be met. Nevertheless, the integrated scenario analysis demonstrates that only a joint de-carbonization of both transport and electricity systems lead to a significant reduction of emissions.

Does metropolitan form affect transportation sustainability? Evidence from US metropolitan areas

In this paper, we examine transportation sustainability in American metropolitan areas using transportation-related CO2 emissions, public transit accessibility, and commuting times as indicators. Though variations in these indicators may stem from historic contexts, policies, institutional arrangements, social and cultural origins, the spatial structure of metropolitan areas—in particular their formal characteristics—may also be a contributing factor. To test this relationship, we identify metropolitan form metrics from prior literature that are expected to impact transportation outcomes, and choose five metrics to which we introduce significant improvements. We apply the metrics to all 166 Combined Statistical Areas in the US, using an open-source GIS toolbox released along with the paper. Our findings demonstrate that form-based metrics provide a better explanation to CO2 emissions, public transit accessibility, and commuting times in US metro areas than the simpler population size or density metrics typically used in practice. We also show that counter to prior literature on urban scaling laws and economies of scale, which have argued that larger cities and metro areas are more sustainable per capita, transport-related CO2 emissions and transit accessibility are actually less favorable in larger CSAs when controlling for formal characteristics of metropolitan areas. Instead of scale, compactness has the highest elasticity with respect to transportation sustainability of metro areas.

Identification of Key Factors to Reduce Transport-Related Air Pollutants and CO2 Emissions in Asia

Asian countries are major contributors to global air pollution and greenhouse gas emissions, with transportation demand and emissions expected to increase. However, few studies have been performed to evaluate policies that could reduce transport-related emissions in the region. This study explores transport-related CO2 and air pollutant emissions in major Asian nations along with the impacts of transport, climate, and emission control policies using the Asia-Pacific Integrated Model (AIM)/Transport model. Our results show that by 2050, CO2 emissions in developing countries will be 1.4–4.7-fold greater than the levels in 2005, while most air pollutant emissions will show large reductions (mean annual reduction rates of 0.2% to 6.1%). Notably, implementation of transport, emission control, and carbon pricing policies would reduce CO2 emissions by up to 33% and other air pollutants by 43% to 72%, depending on the emission species. An emission control policy represents the strongest approach for short-term and mid-term reduction of air pollutants. A carbon pricing policy would lead to a direct reduction in CO2 emissions; more importantly, air pollutant emissions would also be effectively reduced. Shifting to public transportation in developing countries can also greatly influence emissions reductions. An increase in traffic speed shows relatively small effects, but can be meaningful in Japan.

Low-carbon travel mode choices: The role of time perceptions and familiarity

Academic studies and recent social movements alike highlight the importance of changing flying behavior for reaching global climate goals. A particularly effective strategy for minimizing transport-related CO2 emissions is to substitute flights with train travel. The same trip causes around 80–90% less CO2 emissions by train than by plane. The results of this paper are based on two independent samples, the first representing the Swiss population, the second one including international business students. Both empirical studies consistently show that respondents who are familiar with train travel are also more prone to consider the train as an alternative for international, long-distance trips. Furthermore, both studies find systematic differences when it comes to travel time perceptions of likely air and train travelers: While people who are inclined to travel by plane see a high value in minimizing the total travel time of their journey, likely train travelers put less emphasis on minimizing total travel time. At the same time, prospective train travelers find it highly important to be able to use their travel time productively, which does not seem to be the case for potential air travelers. As consumer insights about the willingness to substitute flying with train travel are rare, the results of this paper build a basis for developing communication strategies and policies aiming at increasing low-carbon travel mode choices.

Net CO2-emission effects of relocating freight facilities to free up land for urban development in central and semi-central urban areas

This article investigates net CO2 emissions effects of relocating freight facilities (wholesale warehouses) away from central areas and replacing them with more area-effective activities (mix of dwellings and workplaces) that would otherwise have been located more peripherally. This development is ongoing in many urban regions, and it is often part of land use strategies aimed at reducing CO2 emissions from transport. However, whether this strategy is efficient has not been investigated much. The study contributes empirical research on two Norwegian regions, where net differences in total CO2 emissions between two scenarios were analysed. In Scenario 1, wholesale warehouses have remained in their central location, and new dwellings and workplaces have been developed in relevant peripheral areas. In Scenario 2, centrally located warehouses have relocated to peripheral areas, and they have been replaced by dwellings and workplaces. The main finding is that relocating warehouses away from central and semi-central urban areas, to make land available for dwellings and workplaces, results in reduced net transport-related CO2 emissions. The effects are stronger when the warehouses were originally more centrally located and the alternative locations of dwellings and workplaces are more peripheral. If warehouse relocations cause detours, the effects are somewhat reduced.