Road Transport Sector Research Articles

An innovative triple-screw pump for engine cooling in the road transportation sector

The efficiency improvement of Internal Combustion Engines (ICEs) is still necessary, providing them a valid contribution to the future of road propulsion, increasingly governed by regulations aimed at curbing CO2 emissions. In this context, technologies related to engine thermal management, and more specifically to the cooling pump, offer a good potential. Screw-type cooling pumps, notably triple-screw pumps (TSP), emerge as a solution, demonstrating superior efficiency compared to centrifugal pumps at design and off-design operating conditions.A TSP optimized in terms of efficiency for the cooling system of a turbocharged gasoline engine was investigated. The requested high speed of rotation suitable for engine cooling to reduce size and weight led to the introduction of a new screws' arrangement, which improved pump durability and mechanical efficiency, but enhanced the impact of clearances on the so-called blowhole backflow, usually negligible for bigger pump sizes. Hence, a refined mathematical model capable to predict the new screw pump's performances was developed and experimentally validated. A stable and high mechanical efficiency (>80 %), and a global efficiency greater than 50 % even very far from the design point, were reached. This feature applies in engine cooling, but can be useful also in industrial applications requiring high pump efficiency.

The long term price elastic demand of hydrogen – A multi-model analysis for Germany

Hydrogen and its derivatives are important components to achieve climate policy goals, especially in terms of greenhouse gas neutrality. There is an ongoing controversial debate about the applications in which hydrogen and its derivatives should be used and to what extent. Typically, the estimation of hydrogen demand relies on scenario-based analyses with varying underlying assumptions and targets. This study establishes a new framework consisting of existing energy system simulation and optimisation models in order to assess the long-term price-elastic demand of hydrogen. The aim of this work is to shift towards an analysis of the hydrogen demand that is primarily driven by its price. This is done for the case of Germany because of the expected high hydrogen demand for the years 2025–2045. 15 wholesale price pathways were established, with final prices in 2045 between 56 €/MWh and 182 €/MWh. The results suggest that – if climate targets are to be achieved - even with high hydrogen prices (252 €/MWh in 2030 and 182 €/MWh in 2045) a significant hydrogen demand in the industry sector and the energy conversion sector is expected to emerge (318 TWh). Furthermore, the energy conversion sector has a large share of price sensitive hydrogen demand and therefore its demand strongly increases with lower prices. The road transportation sector will only play a small role in terms of hydrogen demand, if prices are low. In the decentralised heating for buildings no relevant demand will be seen over the considered price ranges, whereas the centralised supply of heat via heat grids increases as prices fall.

Single mixed refrigerant biomethane liquefaction plant integrated with solar energy: Dynamic simulation for the decarbonization of the heavy road transport sector

This works proposes a dynamic thermoeconomic analysis of a liquefied biomethane production plant to meet the fuel demand of a fleet of heavy duty trucks in the south of Italy. The biomethane is obtained from the upgrading of the biogas produced by means of anaerobic digestion through a plug flow reactor fed by organic fraction of municipal solid waste. The upgrading of the biogas is realized using a three-stage membrane compression process, producing a 96 % pure biomethane. The biomethane liquefaction is realized using a single-mixed refrigerant process and compared to a Linde cycle process. The whole system is assisted by solar energy to reduce the fossil energy consumption of the process and feed-in tariffs are considered as funding policy. The models for the anaerobic digestion, the biogas upgrading, and the biomethane liquefaction are in detail developed in MatLab. The anaerobic digestion model is based on the ADM1 biological model, integrated with a suitable heat transfer model. The biogas upgrading model is based on a simplified Fick model. The liquefaction model is based on an equivalent two heat-exchangers model, taking into account the transient heat transfer. All the components are then integrated in TRNSYS to perform the dynamic simulation for one operating year of the whole system. Results from the thermoeconomic analysis are outstanding in terms of profitability, showing a payback period of less than 2 years and a Net Present Value of the system of 402 M€. The great environmental impact is also confirmed by a Primary Energy Saving of 91 % and a dramatic reduction of 86 % of the CO2 equivalent emissions.

Future Trends: Predicting the Evolution of Rail and Road Transportation in Logistics

The logistics industry represents the vital circulatory system of the global economy, responsible for the efficient movement of goods across sprawling supply chain networks. Historically, rail and road transportation modes have been the workhorses of logistics operations, facilitated by their extensive infrastructure and versatility in cargo handling. However, the convergence of rapid technological advancements, evolving consumer expectations, and mounting environmental pressures is catalyzing a transformative shift in the future evolution of these pivotal transportation sectors. This comprehensive study delves into the emerging trends that are poised to reshape the rail and road transportation landscape within the logistics realm. By synthesizing insights from industry leaders, academic research, and cutting-edge technological developments, the study aims to provide a holistic perspective on the forthcoming changes and their far-reaching implications. The study’s main objective is to integrate semi-autonomous and autonomous cars into fleets of transportation vehicles. The advent of self-driving trucks and trains promises to revolutionize logistics operations by enhancing efficiency, reducing human error, and optimizing route planning. Concurrently, this transition raises critical concerns related to workforce displacement, regulatory frameworks, and cybersecurity vulnerabilities that necessitate proactive mitigation strategies. Moreover, the logistics industry faces mounting pressure to embrace sustainable practices and curtail its environmental footprint. Consequently, the rail sector is anticipated to experience a renaissance fueled by its inherent energy efficiency and lower carbon emissions compared to road transportation. Innovations in electric and hydrogen-powered locomotives, coupled with advancements in rail infrastructure, could position rail as a greener and more cost-effective solution for long-haul freight movement. Concurrently, the road transportation sector is poised for a transformation driven by the proliferation of electric and alternative fuel vehicles. This adoption is projected to accelerate as battery technology improves, charging infrastructure expands, and governments implement stricter emissions regulations. Furthermore, the integration of advanced telematics systems and realtime data analytics could optimize route planning, load management, and vehicle maintenance, further enhancing the operational efficiency of road-based logistics.

Assessing the Additional Benefits of Thailand’s Approaches to Reduce Motor Vehicle Emissions

Air pollutants and greenhouse gases (GHGs) represent major challenges in our era, contributing to climate change and global health issues. These problems arise from a variety of well-known sources, including motor vehicles. Almost all nations, Thailand included, have formulated and implemented policies to curb greenhouse gas (GHG) emissions in line with the requirements and commitments of the Paris Agreement. The evaluation of specific air pollutants and GHG emissions originating from road vehicles utilises the Thailand database, referencing the year 2019. Data intersections from 2019 to 2022 are grounded in actual data collected from relevant departments in Thailand, while projections for 2023–2030 are forecasted based on the baseline year. The secondary database used in the International Vehicle Emission model is adjusted according to real-world driving data to accurately reflect country-specific emission factors. Dynamic emission factors for specific air pollutants and GHGs are evaluated and integrated with the average Vehicle Kilometres Travelled (VKT) for each vehicle category. The Business-As-Usual (BAU) scenario is then examined, based on existing policies aimed at reducing air pollutants and GHG emissions in Thailand’s transport sector. These policies include strategies for the adoption of electric vehicles and the promotion of public transport to reduce VKT. Under the BAU scenario, the overall number of road vehicles in Thailand, including passenger cars, motorcycles, pickups, vans, trucks, and buses, is expected to increase by approximately 6.58% by 2030, leading to a rise in specific air pollutants and GHG emissions compared to the 2019 baseline. However, by adhering to Thailand’s strategies and transitioning to new electric passenger cars and buses, greenhouse gas emissions and specific air pollutants from the road transport sector will be significantly reduced.

Trends and policy analysis: A case for sustainable transport systems in India

In this article, we analyse India's transport sector policy. The study examines the two important modes of transport, viz., road and rail, and analyses the efficiency of transport infrastructure from 2011 to 2019. Through Data Envelopment Analysis (DEA), we evaluate modes in terms of the capacity of registered road goods vehicles and railway goods wagons, truck km/train km and energy consumption and corresponding freight traffic. The analysis gives valuable insight into the fact that rail infrastructure is more efficient than road infrastructure. Still, current transport sector policies promote energy-intensive carbon-fuel road vehicles rather than energy-efficient alternative transport modes. The study suggests the changes that may be incorporated in inputs to improve the efficiency of the road infrastructure. The Data Envelopment Analysis (DEA)-Malmquist Index analysis reports the need for total factor productivity improvement in rail transport and the introduction of technological innovations in road and rail transport sector management. The study employs a well-to-wheel (WTW) based index to ascertain the energy consumed and pollutants emitted by freight-carrying road and rail modes between two leading business hubs of India, i.e., Ludhiana and Mumbai. The paper identifies policy gaps and suggests a holistic approach for need-based roadway investment and a time-bound development of railway infrastructure in India. Our study generates valuable implications for India's policy planners and government authorities and provides new insights to other countries.

Multicriteria Model to Support the Hiring of Road Freight Transport Services in Brazil

The transportation of goods plays a fundamental role in the global economy. In Brazil, specifically, a significant portion of what is transported goes through highways, and the provision of this service is carried out through the hiring of specialized companies or independent drivers, who end up serving companies from various sectors. This study successfully constructed a decision model to support the hiring of road freight transport services in Brazil. To achieve this, the multicriteria decision analysis (MCDA) approach was used, employing the Measuring Attractiveness By a Categorical-Based Evaluation Technique (MACBETH) method. The development of this model was informed by a comprehensive literature review, interviews with three transportation professionals, and a simulation involving eight anonymous Brazilian companies. This initiative aims to create a practical framework for effectively selecting logistics operators in the road transport sector to meet the needs of companies dependent on these services.

Review of Road Traffic Accident Burdens in Transportation Sector of Ethiopia

The transportation sector has a very immense role in the economic development of a given country. Because human beings' day-to-day activities re highly depends on the transport service. But this sector has its own drawbacks, like road traffic crashes and environmental pollution. In Ethiopia, the road transport sector is poor in terms of quality and service delivery systems. Due to this, the frequent occurrence of road traffic crashes has been recorded in the country continuously. To that end, this paper was mainly intended to review road traffic accident burdens in the transportation sector of Ethiopia. In detail, reviewing the costs of road traffic accidents, the causing factors of road traffic accidents, the types of vehicles highly involved in road traffic accidents, and the victim groups of communities affected by road traffic accidents at the national level were the specific objectives of this paper. Meanwhile, all road traffic accident data found in Ethiopia from the federal police commission report papers, journal articles, and dissertation papers were used for analysis purposes. Besides, the collected data is presented in tables and figures. Furthermore, the data was analyzed and interpreted based on a descriptive research design. Finally, the result of this review shows that trends of road traffic accidents in Ethiopia have been increasing over time by killing, injuring people and damaging resources. Drivers’ bad behaviors, low know-how of road users, poor road infrastructure, old vehicle conditions, and environmental factors are aggravating the occurrence of road traffic accidents in the country. Thus, to tackle this problem, educating people, enforcing traffic laws, enhancing engineering measures, and giving emergency responses were the recommendations given in this paper.

DETOURS AND DELAYS: NAVIGATING THE PANDEMIC'S IMPACT ON INDIA'S TRANSPORT SECTOR AND TOURISM

The COVID-19 pandemic has had a profound impact on the Indian transport industry, affecting various sectors such as aviation, railways, road transport, and maritime. The nationwide lockdowns and travel restrictions imposed to curb the spread of the virus led to a significant decline in passenger traffic and freight movement, causing severe financial distress to the industry. This almost standstill in the movement of the people severely affected the Indian tourism industry which provides 7 per cent of GDP and 9 per cent of employment by 2019. The aviation sector witnessed a sharp decline in passenger traffic, leading to financial losses for airlines and airports. Many airlines were forced to suspend operations or reduce their workforce to survive. Similarly, the Indian Railways faced challenges due to the suspension of passenger trains, impacting revenue generation. The road transport sector also suffered due to the lockdowns, with restrictions on inter-state and intra-state movement affecting the movement of goods and passengers. The maritime sector faced challenges due to disruptions in global trade and port operations. To mitigate the impact of the pandemic, the Indian government announced various relief measures, including financial assistance, waivers, and restructuring of loans for the transport industry. The government also launched initiatives such as the Vande Bharat Mission to repatriate stranded Indians and the One Nation, One Card scheme for seamless travel across different modes of transport. By recognising the importance of the revival of tourism in India Indian Government announced many sops and reliefs to the tour operators, travel agents and transport organisations. Despite these measures, the road to recovery for the Indian transport industry remains challenging. The industry will need to adapt to the new normal by implementing safety measures, embracing digital technologies, and diversifying its operations to ensure resilience in future crises. KEYWORDS: Covid -19, Road transport, Railways, Civil aviation, Tourism

Estimation of energy demand and carbon emissions for the road transport sector: A case study of Douala, Cameroon

Road transport is one of the main causes of air pollution around the world. Nowadays, the notion of sustainable development is one of the major pillars for a healthy environment. However, faced with its major challenges, it is more than necessary and important to understand a set of elements which contribute to better understanding the level of planning for sustainable road transport. This study aims to estimate energy demand and greenhouse gas emissions, namely from road CO2 transport, for the city of Douala in Cameroon from 2010 to 2035. In order to achieve our objective, we used the Long range Energy Alternative Planning (LEAP) model. Based on the LEAP model, the estimates were evaluated based on three scenarios Business As Usual (BAU), Energy Optimization and Mitigation (EOM) and Sustainability Mobility (SM). The aim of this work was to identify suitable potential policies with a view to reducing energy consumption and emissions carbon dioxide (CO2) for road transport in Douala. The results tell us that the EOM and SM scenarios have advantages over the BAU scenario with the SM scenario being more optimistic than the other two scenarios. In addition, the SM scenario has a growth rate of 87.408 % in energy demand smaller than the other two scenarios BAU and EOM respectively 151.598 % and 132.073 %. We also note that the SM scenario contributed to a reduction of 60.661 kilo ton emissions of CO2 less than the BAU scenario. At present, with a view to reducing energy consumption and reducing carbon emissions, road vehicles in circulation in the city of Douala should emphasize structural optimization measures through the use of clean energy by promoting the use of biofuels in mass transport, eliminating old cars and finally considering improving energy efficiency through the implementation of technological development in the automobile sector. Policy makers must take this study into consideration in order to better integrate the notion of energy sustainable road transport.

Carbon emission reduction potential analysis of fuel cell vehicles in China: Based on GRA-BiLSTM prediction model

The development and promotion of fuel cell vehicles is an important way to reduce carbon emissions in transportation. This study predicts the future ownership of fuel cell vehicles in China based on the GRA-BiLSTM combined model, and it is expected that under the low-growth, benchmark, and high-growth scenarios, China's fuel cell vehicle ownership could reach 549,500, 2,351,700, and 8,844,100 vehicles by 2035, respectively. A life cycle assessment of passenger cars and commercial vehicles with different fuel types has shown that the promotion of fuel cell vehicles can significantly reduce greenhouse gas emissions, particularly for commercial vehicles. By 2035, it is expected that China's road transport sector will reduce greenhouse gas emissions by approximately 23.83 Mt CO2,eq. The results of the study provide data support and a decision-making basis for relevant Chinese enterprises and governments to adjust the layout and promotion policies of the fuel cell vehicle industry in the future.

Energy sustainability and carbon dioxide emissions mitigation options for South Africa’s road transport sector

BackgroundThe transport sector in South Africa is responsible for around 11% of the country's carbon dioxide emissions, with road transport contributing an overwhelming 90% of this total, as noted by the South African Green Transport Energy of South Africa. As part of its commitment to global climate pacts, South Africa aims to reduce emissions from its road transport sector. Yet, studies focused on reducing energy consumption and related emissions in this sector have been sparse.ResultsUtilizing a bottom-up accounting modelling framework Low Emissions Analysis Platform (LEAP), this research investigated five low-carbon transition scenarios alongside a business-as-usual (BAU) scenario for road transport. These scenarios comprised Fuel and Technology Switching (FTS), Modal Shift (MS), Logistics Improvement (LI), Energy Efficient (EEF), and a Combined Mitigation (CMT). The BAU scenario was established as a benchmark to demonstrate energy demand and emissions in the absence of changes to current practices or policies. According to our model, under the BAU scenario, there will be a 61% surge in final energy demand, from 769 petajoules (PJ) in 2020 to 1240 PJ by 2050, accompanied by a proportional increase in emissions. The study revealed that the implementation of any of the alternative low-carbon scenarios could yield a reduced energy demand by 2050. LI 21%, MS 33%, FTS 40%, EEF 48%, CMT 77%, Significantly, a combined approach, integrating multiple low-carbon policies, can achieve more substantial reductions in energy demand and Carbon Dioxide (CO2) emissions than applying single policies separately.ConclusionsThis study emphasizes the importance of crafting province-specific solutions, acknowledging that challenges and contexts vary between provinces. Furthermore, lessening energy reliance not only diminishes the nation's fuel import bills but also improves air quality and aids in achieving low emission targets.

A scenario analysis of the energy transition in Japan’s road transportation sector based on the LEAP model

Japan has lagged behind other developed nations in transitioning its transportation sector to sustainable energy sources. This study employs the Low Emissions Analysis Platform model to examine six scenarios, assessing energy consumption and emissions associated with four major energy sources and pollutants. Our findings reveal an overall decline in total energy consumption across all scenarios. Notably, the Combined scenario where multiple policies are integrated demonstrates the most significant reduction, with a 56% decrease compared to the Business as usual scenario by 2050. The analysis also indicates that the electricity and hydrogen demand for electric vehicles and fuel cell vehicles remains economically viable within future strategic plans. Emissions, including CO2, Carbon Monoxide (CO), Methane (CH4), and Nitrous Oxide (N2O), exhibit substantial reductions, particularly under the Active Promotion Scenario, where a high EV adoption rate is achieved. Moreover, the Combined scenario resulting in a comprehensive and integrated approach, leads to a remarkable 66% decrease in emissions. These results serve as valuable reference points for the Japanese government, aiding in the formulation of future targets for widespread EV adoption and emission standards for pollutants.

Policy scenario analysis of achieving the "dual carbon" goal for the road transportation sector in China

The goal of "dual carbon" has brought the pressure of reducing carbon emissions to the road transportation sector in China. This study aims to identify and analyze possible policy measures that would help to achieve this goal from the perspective of the whole life cycle. We build a bottom-up computing framework based on the LEAP model. Six policy scenarios are designed to quantitatively assess their effects. The results show that promoting pure electric vehicles (PEV) and plug-in hybrid electric vehicles (PHEV) is appropriate for the passenger vehicles (PV), light-duty trucks (LDT), and mini trucks (MT) sub-sectors, while hydrogen fuel cell vehicles (FCV) are more suitable for the promotion of the heavy-duty trucks (HDT), heavy-duty buses (HDB), and medium-duty buses (MDB) sub-sectors. Additionally, the recycling of vehicle materials can effectively reduce the carbon emissions during the life cycle of motor vehicles. Furthermore, reducing the carbon emissions from the vehicle cycle of PV and the fuel cycle of HDT should be taken seriously. The main contribution of this study lies in establishing a comprehensive list of vehicle cycle carbon emission factors, covering various sub-sectors of China's road transportation sector. Besides, this study considers China's strategic planning and "dual carbon" goal, and proposes policy recommendations specifically tailored to the practical issues faced by China.

Exploring the Relationship Between CO2 Emissions and Fuel Consumption in Road Transport: Empirical Evidence from Chad

Over the period 2008-2019, this study examines the linear impact of petroleum product (PP) consumption in Chad, PP prices, the vehicle fleet and urbanisation on CO2 emissions on the one hand, and on the other, it determines the causal links that exist between the various variables studied. This study opts for the augmented Dickey-Fuller and Phillips-Perron tests to verify the stationarity of the variables. The ARDL model is then estimated and diagnostic tests are performed to confirm the validity of the model. To confirm the existence of long-term relationships, the bounds test was applied. Finally, the Toda-Yamamoto causality test was used to capture the influences present between the series under study. The main results show that, in the long term, a 1% increase in gasoline consumption would lead to a 1.03% increase in CO2 emissions and the linear impact of diesel consumption is positive and insignificant on CO2 emissions. In the short term, gasoline and diesel consumption have a positive and insignificant impact on CO2 emissions. In terms of causality, there is a unidirectional causality from gasoline consumption to CO2 emissions and a bidirectional causality between CO2 emissions and diesel consumption. This study is the first to simultaneously link CO2 emissions, PP consumption, PP prices, the vehicle fleet and urbanisation in general, and particularly in the case of Chad. It therefore adds to the literature on the simultaneous relationship between CO2 emissions, PP consumption, the car fleet and urbanisation in a global and restricted context. This study could guide Chadian oil pollution management decision-makers in adopting policies related to the effects of PP consumption in the road transport sector.

Vehicular Fuel Consumption and CO2 Emission Estimation Model Integrating Novel Driving Behavior Data Using Machine Learning

Fossil fuel vehicles significantly contribute to CO2 emissions due to their high consumption of fossil fuels. Accurate estimation of vehicular fuel consumption and the associated CO2 emissions is crucial for mitigating these emissions. Although driving behavior is a vital factor influencing fuel consumption and CO2 emissions, it remains largely unaddressed in current CO2 emission estimation models. This study incorporates novel driving behavior data, specifically counts of occurrences of dangerous driving behaviors, including speeding, sudden accelerating, and sudden braking, as well as driving time and driving distances on expressways, national highways, and local roads, respectively, into monthly fuel consumption estimation models for individual gasoline and hybrid vehicles. The CO2 emissions are then calculated as a secondary parameter based on the estimated fuel consumption, assuming a linear relationship between the two. Using regression algorithms, it has been demonstrated that all the proposed driving behavior data are relevant for monthly CO2 emission estimation. By integrating the driving behavior data of various vehicle categories, a generalizable CO2 estimation model is proposed. When utilizing all the proposed driving behavior data collectively, our random forest regression model achieves the highest prediction accuracy, with R2, RMSE, and MAE values of 0.975, 13.293 kg, and 8.329 kg, respectively, for monthly CO2 emission estimation of individual vehicles. This research offers insights into CO2 emission reduction and energy conservation in the road transportation sector.

Assessment of Country-Specific GHG Emissions from Road Transport Sector in India

Assessment of Country-Specific GHG Emissions from Road Transport Sector in India

Hydrogen as Fuel for ICEs: State of Art and Technological Challenges

The climate change, as the main consequence of the polluting emissions due to anthropic activities, is nowadays a well-known threat to human health as well as for the environment safety. Several plans and strategies have been announced by the governments to detach from fossil fuel-based energy and gradually reduce the carbon footprint of their economies. In this scenario, the road transport sector is turning out to be the main “technological gym” to test and improve new powertrain solutions to achieve as soon as possible the goal of the net-zero carbon emissions, at least in the tank-to-wheel (TTW) context. In view of this, the hydrogen as fuel is gaining ever more attention from the scientific community, both as the middle-term solution to achieve the abovementioned goal and as a prominent future energy carrier. In this review, the performance and main characteristics of the hydrogen-internal combustion engines (H2-ICEs) are discussed based on the most recent studies available in literature. A comprehensive overview of various topics is offered, from the production stage to the combustion anomalies, mixture formation strategies, and the challenge of reducing the nitrogen oxides (NOx) emissions under high load conditions.

Discrimination Based on Gender and How It Affects Employee Performance

Gender discrimination in the workplace remains a persistent issue with significant implications for employee well-being and organizational effectiveness. This study investigates the multifaceted impact of gender discrimination on employee performance in the transportation sector, focusing on the experiences of female commercial drivers in Coimbatore, Tamil Nadu, India. Employing a mixed-methods approach, the study integrates qualitative thematic analysis with quantitative survey findings to provide a comprehensive understanding of discrimination dynamics and their implications for organizational productivity. To determine the effects of discrimination on employee performance, data were gathered from 243 front-line female commercial drivers employed in Coimbatore’s road transportation industry. Analysis of the data is done statistically using correlation and regression techniques, and mixed-method analysis was used as comparative analysis using cross-tabulation and chi-square and moderation analysis using AMOS. This study considers three types of gender discrimination: hiring, promotion, and facility discrimination. The level of employee performance is more a result of discrimination against women in hiring and amenities. The paper offers principles for human resource managers to follow to prevent discriminatory behavior that negatively impacts employee performance. Guidelines for human resource management and empirical information from the Coimbatore road transport sector relate to employee performance and how it affects organizational productivity.

Exploring Urban Compactness and Greenhouse Gas Emissions in the Road Transport Sector: A Case Study of Big Cities in South Korea

This study examined the relationship between urban compactness and greenhouse gas (GHG) emissions in the road transport sector in South Korea, focusing on 84 cities, particularly 27 metropolitan areas with populations of approximately 500,000. We developed an urban compactness index (UCI) using Moran’s I, entropy, and the Gini coefficient, integrating city size into the analysis. Cities were categorized into five groups based on their size to analyze GHG emissions and regional variations in compactness comparatively. Our results revealed a significant inverse relationship between UCI and per capita road transport GHG emissions, which was more pronounced in larger cities. Specifically, cities with a population over 1 million displayed reduced per capita road transport GHG emissions in compact urban structures. In conclusion, these findings suggest that larger cities can effectively reduce per capita road transport GHG emissions through urban planning for compact development. Additionally, planners need to consider city size when analyzing the UCI and formulating urban planning strategies aimed at achieving carbon neutrality.