Transport-related Greenhouse Gas Emissions Research Articles

Austria’s KlimaTicket: Assessing the short-term impact of a cheap nationwide travel pass on demand

Measures to reduce transport-related greenhouse gas emissions are of great importance to policy-makers. A recent example is the nationwide KlimaTicket in Austria, a country with a relatively high share of transport-related emissions. The cheap yearly season ticket introduced in October 2021 allows unlimited access to Austria’s public transport network. Using the synthetic control and synthetic difference-in-differences methods, we assess the causal effect of this policy on rail travel demand by constructing a data-driven counterfactual out of European railway companies to mimic the number of passengers of the Austrian Federal Railways (ÖBB) without the KlimaTicket. Overall, the results indicate that the KlimaTicket has no short-run passenger growth effects. While passenger numbers recovered faster after the COVID-19 pandemic, in 2023, the passenger growth rate of the ÖBB is even lower than it would be under no treatment.

Human-powered vehicles as a way to abate transport-related greenhouse gas emissions: Part 2 - A virtual prototype for emissions and performance analyses

Velomobiles, despite their potential for efficient transportation, remain relatively unknown compared to electric cars, receiving limited attention in academic research and public awareness. This paper highlights their untapped potential and underlines public interest in their adoption, provided a velomobile meeting customer requirements is available. Leveraging the Model Based System Engineering (MBSE) methodology, this work presents a structured approach to design, focusing on customer needs translation and digital prototype validation. This iterative process ensures velomobiles meet performance criteria while minimizing environmental impact. The lack of standardized testing for the energy consumption of Human-Powered Vehicles (HPVs) is addressed by proposing an analysis of consumption under diverse operating conditions, giving information on the environmental assessments. This study underscores velomobiles’ potential as a sustainable transportation solution and provides a framework for their design, validation, and optimization.

Food is Medicine Interventions and Climate Change

Food is Medicine (FiM), also known as Food as Medicine, integrates food and nutrition interventions into health care delivery with the primary goal to improve population health and address diet-related health conditions. To date, there has been little focus on the relation between FiM and climate change despite FiM’s involvement with 2 key drivers of climate change: health care delivery and food systems. FiM may be able to advance lifestyle medicine and population health objectives, as well as mitigate some of the health care and food-related drivers of climate change, by focusing on 4 key areas: (1) Increasing the absolute number and proportion of patients who follow plant-based diets; (2) reducing food waste; (3) reducing unnecessary health care utilization; and (4) lowering transportation-related greenhouse gas emissions related to food procurement. Measuring the ecological impact of FiM alongside clinical, utilization, and financial measures will require a different analytical approach than that used traditionally in health care. Ultimately, thoughtful, data-driven, and urgent interventions that span the food and health care sectors are needed to sustainably support not only FiM, but human, environmental, and planetary health as well.

Technology Oriented Struggle Against Climate Change in Transportation Sector: An Empirical Investigation

The transportation sector is one of the most important sectors in which greenhouse gas emissions (GHG) are the highest, thus causing the global warming problem to rise. One of the most effective and international solutions to this problem is considered to be a technology-oriented struggle, and the development of green technologies is encouraged by global authorities. The study aims to investigate the success of the technology-oriented struggle against global warming in the transport sector. In analyses, data on transportation-related greenhouse gas emissions, the number of patents (transport-related climate change mitigation technologies), trade openness, and GDP per capita of 12 OECD countries years between 1999-2017 were used. To identify the long-run and short-run relationship among variables, the Cross-Sectional Autoregressive Distributed Lags Estimator (CSARDL) and also the Mean Group (MG), Augmented Mean Group (AMG), and Common Correlated Effects Mean Group Estimators (CCE) were applied. According to the estimators' findings, no evidence was found that the number of patents and trade openness affected greenhouse gas emissions, but it was determined that GDP positively affected greenhouse gas emissions. As a result, it can be said that the technology-oriented struggle against climate change in the transportation sector alone isn't sufficient to reduce transportation-related GHG emissions.

Core Indicators for Monitoring the Sustainable Urban Mobility Plan: A Case Study

The primary objective of this paper is to validate core indicators for monitoring Sustainable Urban Mobility Plans (SUMPs), focusing on the Functional Urban Area in Southern Poland. Given the high concentration of the population in urban areas within the European Union (EU)—currently at 70.9% and expected to rise to 83.7% by 2050—there is an urgent need to address associated challenges such as congestion and the significant contribution of cities to transport-related greenhouse gas emissions. Effective urban mobility planning is, therefore, more critical than ever. This study aims to provide a methodological framework for determining baseline values for four essential monitoring indicators: road safety, accessibility to public mass transit, greenhouse gas emissions, and air quality. These indicators are crucial for the European Commission’s evaluation of SUMPs. By focusing on these aspects, the research aims to enhance the effectiveness of urban mobility plans, ensuring they contribute meaningfully to the EU’s transport, climate, health, and social goals as outlined in the European Green Deal and the Sustainable and Smart Mobility Strategy.

Rapid Estimation of Static Capacity Based on Machine Learning: A Time-Efficient Approach

With the global surge in electric vehicle (EV) deployment, driven by enhanced environmental regulations and efforts to reduce transportation-related greenhouse gas emissions, managing the life cycle of Li-ion batteries becomes more critical than ever. A crucial step for battery reuse or recycling is the precise estimation of static capacity at retirement. Traditional methods are time-consuming, often taking several hours. To address this issue, a machine learning-based approach is introduced to estimate the static capacity of retired batteries rapidly and accurately. Partial discharge data at a 1 C rate over durations of 6, 3, and 1 min were analyzed using a machine learning algorithm that effectively handles temporally evolving data. The estimation performance of the methodology was evaluated using the mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE). The results showed reliable and fairly accurate estimation performance, even with data from shorter partial discharge durations. For the one-minute discharge data, the maximum RMSE was 2.525%, the minimum was 1.239%, and the average error was 1.661%. These findings indicate the successful implementation of rapidly assessing the static capacity of EV batteries with minimal error, potentially revitalizing the retired battery recycling industry.

Socioeconomic inequalities in greenhouse gas emissions from household travel in Aotearoa/New Zealand

BackgroundA just transition to a decarbonised transport system requires understanding current inequity in transport-related greenhouse gas emissions (GHGe). MethodsWe used the population-based nationally representative New Zealand Household Travel Survey (2015–2018 data) to examine inequalities in GHGe from household travel by NZDep (an area measure of socioeconomic position [SEP]). ResultsThere was a broadly linear association between SEP and GHGe from household travel. People resident in the least deprived areas emitted around 79 % more GHGe per week from household travel than those in the most [mean 63.6 CO2eq (95 %CI 58.5–68.6) compared to 35.6 kg CO2eq (95 %CI (32.6–38.6)]. Most of the difference was due to the additional 97 km per week travelled by car by people resident in the least deprived areas. Residents in the least deprived areas travelled further and more frequently for paid and unpaid work and leisure purposes than those in the most. Air travel also showed significant inequities with 2.4 % of residents in the least deprived areas reporting air travel in the last week compared to 0.1 % in the most deprived. Air travel was the second largest source of mean weekly transport emissions in residents living in the least deprived areas. ConclusionThere are large inequities by area deprivation in GHGe from household travel in Aotearoa/New Zealand. Transport policy needs to focus on measures to reduce emissions that are effective and reduce inequities. Significant work on policy processes, design and evaluation need to occur to facilitate this dual transformation.

Systematic literature review of urban charging infrastructure planning over time

The transition from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs) is imperative to achieve the goal of reducing transport-related greenhouse gas emissions by 90 % in 2050. As urbanization intensifies, vehicle miles in urban environments increase and cities already consume 75 % of global energy, there is a pressing need for efficient charging infrastructure (CI) placement tailored to urban environments. Accordingly, this paper conducts a systematic literature review to outline prevailing research and derive requirements for a future CI model adaptable to urban environments. Analysis of N = 57 studies underscores the necessity for agent-based demand models to capture the intricate behaviors of EV drivers, which are currently underrepresented due to their data-heavy nature (n = 28 flow-based; n = 18 node-based). Furthermore, with a projected surge of 800 % in CI installations in Europe by 2030, strategic placement according to demand and urban-specific requirements is paramount. Still, multi-periodicity considerations are largely absent in current literature (n = 50). Geometric segmentation is presented as a solution to mitigate partial coverage issues. Ultimately, agent-based models, coupled with geometric segmentation, emerge as pivotal requirements for future CI models in urban environments, facilitating the transition to EVs, aligning with emission reduction targets, ensuring resource efficiency, and fostering urban sustainability.

Carbon footprint of hospital laundry: a life-cycle assessment

ObjectivesTo assess greenhouse gas (GHG) emissions from a regional hospital laundry unit, and model ways in which these can be reduced.DesignA cradle to grave process-based attributional life-cycle assessment.SettingA large hospital...

Urban street network design and transport-related greenhouse gas emissions around the world

This study estimates the relationships between street network characteristics and transport-sector CO2 emissions across every urban area in the world and investigates whether they are the same across development levels and urban design paradigms. The prior literature has estimated relationships between street network design and transport emissions – including greenhouse gases implicated in climate change – primarily through case studies focusing on certain world regions or relatively small samples of cities, complicating generalizability and applicability for evidence-informed practice. Our worldwide study finds that straighter, more-connected, and less-overbuilt street networks are associated with lower transport emissions, all else equal. Importantly, these relationships vary across development levels and design paradigms – yet most prior literature reports findings from urban areas that are outliers by global standards. Planners need a better empirical base for evidence-informed practice in under-studied regions, particularly the rapidly urbanizing Global South.

Urban Street Network Design and Transport-Related Greenhouse Gas Emissions around the World

Urban Street Network Design and Transport-Related Greenhouse Gas Emissions around the World

Interval-valued Fermatean fuzzy heronian mean operator-based decision-making method for urban climate change policy for transportation activities

Climate change affects the world. Due to excessive GHG emissions, urban transportation contributes to this threat. Policymakers and authorities want to reduce transportation-related GHG emissions. An imaginary urban area with high transportation-related greenhouse gas emissions, dense, interconnected transportation modes, and a high population density is considered. Istanbul, Turkey meets the criteria of this imaginary place, so the case analysis considers this city. Istanbul’s decision-makers are looking for effective strategies to prioritize urban climate change policy alternatives for transportation activities. Four alternative strategies and 13 criteria are presented in this context. Innovative multi-criteria decision-making (MCDM) method with the interval-valued Fermatean fuzzy sets (IVFFSs) strategies is proposed for advantage-prioritization so decision-makers can select the most effective strategies for policies. Utilizing the IVFFSs, the proposed method effectively tackles the qualitative/quantitative data and uncertain information that occurs in realistic applications. In this study, firstly IVFF-heronian mean operators with their desirable characteristics are presented to aggregate the IVFF information. The proposed operators can overcome the drawbacks of existing IVFF information-based operators by considering the relationships between IVFF numbers. Based on IVFF heronian mean operators, a hybrid decision-making framework is proposed by integrating criteria importance through inter-criteria correlation (CRITIC), rank sum (RS), and the double normalization-based multi-aggregation (DNMA) methods with IVFF information. In this method, the CRITIC and RS methods are implemented to derive the objective and subjective weights of the considered evaluation criteria and DNMA is applied to prioritize urban climate change policy alternatives for transportation activities. Sensitivity and comparative analyses with existing studies confirm the proposed framework. The evaluation results show that the integration of transportation sectors, strategies, and innovations across different urban areas in all regions option has the highest overall utility degree (0.731) among a set of four urban climate change policy alternatives for transportation activities.

Sustainable Transportation for the Climate: How Do Transportation Firms Engage in Cooperative Public-Private Partnerships?

This research examines the effectiveness of transportation-sector public-private partnerships (PPPs). Coordination across sectors is needed to reduce transportation-related greenhouse gas emissions. PPPs are of interest to transportation firms, but they may prefer private-sector opportunities given that working with the public sector can present challenges. However, the challenges are not clear and, therefore, this needs research investigation to develop understandings for policy to make PPPs work better for firms. Moreover, this research informs firms so that they may better comprehend and manage the risks of PPPs or choose other opportunities. This empirical research uses a sample of 300 transportation firms across 28 countries. The findings suggest that, although government contracts may be lucrative, the institutional environment of the PPP context is not preferable to other business-oriented private-sector opportunities. If more sustainable transportation is to be constructed to address climate change and other public interests, policymakers may need to rethink PPPs to adapt to the needs of transportation firms.

Vehicle-cycle and life-cycle analysis of medium-duty and heavy-duty trucks in the United States

Medium- and heavy-duty vehicles account for a substantial portion (25 %) of transport-related greenhouse gas (GHG) emissions in the United States. Efforts to reduce these emissions focus primarily on diesel hybrids, hydrogen fuel cells, and battery electric vehicles. However, these efforts ignore the high energy intensity of producing lithium (Li)-ion batteries and the carbon fiber used in fuel-cell vehicles. Here, we conduct a life-cycle analysis to compare the impacts of the vehicle manufacturing cycle for Class 6 (pickup-and-delivery, PnD) and Class 8 (day- and sleeper-cab) trucks with diesel, electric, fuel-cell, and hybrid powertrains. We assume that all trucks were manufactured in the US in 2020 and operated over 2021–2035, and we developed a comprehensive materials inventory for all trucks. Our analysis reveals that common systems (trailer/van/box, truck body, chassis, and lift-gates) dominate the vehicle-cycle GHG emissions (64–83 % share) of diesel, hybrid, and fuel-cell powertrains. Conversely, propulsion systems (lithium-ion batteries and fuel-cell systems) contribute substantially to these emissions for electric (43–77 %) and fuel-cell powertrains (16–27 %). These vehicle-cycle contributions arise from the extensive use of steel and aluminum, the high energy/GHG intensity of producing lithium-ion batteries and carbon fiber, and the assumed battery replacement schedule for Class 8 electric trucks. A switch from the conventional diesel powertrain to alternative electric and fuel-cell powertrains causes an increase in vehicle-cycle GHG emissions (by 60–287 % and 13–29 %, respectively) but leads to substantial GHG reductions when considering the combined vehicle- and fuel-cycles (Class 6: 33–61 %, Class 8: 2–32 %), highlighting the benefits of this shift in powertrains and energy supply chain. Finally, payload variation significantly influences the relative life-cycle performance of different powertrains, while LIB cathode chemistry has a negligible effect on BET life-cycle GHGs.

Life cycle assessment of biodiesel production from selected second-generation feedstocks

Biodiesel has the potential to substitute conventional diesel and reduce global transport-related greenhouse gas emissions. In this study, the environmental impacts of biodiesel production from three East African second-generation feedstocks: Castor (Ricinus Communis), Croton Megalocarpus, and Jatropha, were assessed in comparison with petroleum-diesel. Inventory data analyzed was obtained from primary and secondary sources in Uganda and existing literature. Life Cycle Assessment methodology was applied in accordance with ISO 14040. Reductions in global warming and human toxicity potentials of up to 7% for B10 biodiesel blends relative to imported petroleum diesel were obtained. Similar reductions were obtained for the other assessed mid-point impact categories. Though relatively very low in absolute terms, this reduction rate is in sync with the target annual reductions of 7.6% and 2.7% required to meet the Paris Agreement temperature targets of 1.5 °C and 2 °C respectively. Transesterification accounted for about 70% of the biodiesel production carbon footprints. Sensitivity analysis revealed that feedstock seed yield per ha is a key determinant of biodiesel's life cycle environmental performance. This study established that B10 from second-generation feedstocks is environmentally more competitive than petroleum-diesel from a life cycle perspective.

Decoupling transport-related greenhouse gas emissions and economic growth in the European Union countries

Decoupling transport-related greenhouse gas emissions and economic growth in the European Union countries

Sustainable air transportation through the operational use of a social cost index

Air transportation is responsible for more than 10% of transportation related greenhouse gas emissions in the U.S. As policymakers and engineers search for methods to reduce aviation fuel consumption and the associated negative externalities, a metric used by aircrew on the flight deck may hold the key. The cost index metric and associated ECON speeds inputted into the flight management system control the aircraft's flying speed and ultimately the fuel consumed, and emissions produced. This study assesses the use of this operational tool to further green air transport production in U.S. domestic operations. Data from four major airline Boeing 737 NG routes are analyzed to estimate the effect of each carrier's cost index and ECON speeds on fuel consumption and emissions. Then a social cost index, which incorporates environmental costs, is estimated and tested using a Boeing 737 NG simulator across identical routes to determine the changes in fuel consumption and emissions. On average, we find that for every one unit decrease in an airline's cost index they reduce their fuel consumption by 5.37 lbs. per hour. Further, the average impact of implementing a social cost index is estimated to save nearly 22 gallons of jet fuel and reduce CO2 emissions by 453 lbs. per flight hour. These fuel and emissions reductions are estimated to generate a penalty of 1 min and 43 s on average per flight hour. Overall, we find that airlines can substantially reduce fuel consumption and emissions with minimal impact to operations via implementation of a social cost index.

LNG Bunkering Dynamics: An Exploratory Study for Türkiye

United Nations’ decarbonization and greenhouse gas reduction targets are to be achieved through the utilization of alternative fuels globally. LNG is a viable alternative for mitigating maritime transport-related greenhouse gas emissions. This study investigates LNG bunkering supply chain development in Türkiye. Semi-structured interviews with bunkering supply chain representatives were conducted to explore phenomena. The results of the research provided a pathway to establish a new supply chain for alternative marine fuels. The research findings indicate that collaboration and setting a regulatory framework are vital for supply chain development.

The Role of Land Use Planning in Urban Transport to Mitigate Climate Change: A Literature Review

With the growing urbanisation phenomenon, ambitious policy interventions are needed to limit transport-related greenhouse gas emissions in urban areas. Cities are a predominant source of pollution, with urban transport contributing significantly to emissions. To address climate change, decision-makers must implement appropriate and effective mitigation instruments. This literature review focuses on the different approaches and supporting measures of urban transport land-use planning, such as mixed-used zoning plans and the compact city approach. These solutions can increase the modal shift towards zero emissions transport options. They can also reduce reliance on private vehicles and bring co-benefits and positive externalities to urban residents. Many barriers exist for policymakers, such as financial limitations or institutional immobility. Nevertheless, innovative approaches such as Artificial Intelligence and Mobility-as-a-service provide new perspectives for policymakers and can be helpful in the fight against climate change.

Energy and greenhouse gas implications of shared automated electric vehicles

Automated vehicles can facilitate vehicle sharing within and between households, thus decreasing ownership rates, albeit increasing miles travelled. While electrification can achieve deep reductions in transportation-related greenhouse gas emissions, shared automated electric vehicles will have different charging needs considering their higher mileage. In this study, travel survey data collected in Toronto is used to optimize the charging needs of shared automated electric vehicles, with the objective of reducing greenhouse gas emissions from electricity generation by choosing charging times that are associated with lower marginal emission factors. Optimized charging schedules reduce greenhouse gas emissions by at least 50% relative to vehicles charging once they return home. Life cycle assessment of multiple sharing scenarios indicates that higher levels of sharing increase emissions. Indeed, empty mileage associated with vehicle relocation and higher deterioration lead to a higher fleet turnover. With vehicle sharing, there is a risk of increasing mileage and vehicle production emissions.