Diesel Trucks Research Articles

Comparison of Carbon-Dioxide Emissions of Diesel and LNG Heavy-Duty Trucks in Test Track Environment

Environmental protection and greenhouse gas (GHG) emissions are getting increasingly high priority in the area of mobility. Several regulations, goals and projects have been published in recent years that clearly encourage the reduction of carbon dioxide (CO2) emission, the adoption of green alternatives and the use of renewable energy sources. The study compares CO2 emissions between conventional diesel and liquefied natural gas (LNG) heavy-duty vehicles (HDVs), and furthermore investigates the main influencing factors of GHG emissions. This study was carried out in a test–track environment, which supported the perfect reproducibility of the tests with minimum external influencing factors, allowing different types of measurements. At the results level, our primary objective was to collect and evaluate consumption and emission values using statistical methods, in terms of correlations, relationships and impact assessment. In this research, we recorded CO2 and pollutant emission values indirectly via the fleet management system (FMS) using controller area network (CAN) messages. Correlation, regression and statistical analyses were used to investigate the factors influencing fuel consumption and emissions. Our scientific work is a unique study in the field of HDVs, as the measurements were performed on the test track level, which provide accuracy for emission differences. The results of the project clearly show that gas technology can contribute to reducing GHG emissions of HDVs, and LNG provides a reliable alternative way forward for long-distance transportation, especially in areas of Europe where filling stations are already available.

Optimization for fuel consumption and TCO of a heavy-duty truck with electricity-propelled trailer

As renewable energy grows in the heavy-duty truck sector, exploration of diverse solutions with varied energy types and powertrain configurations becomes a necessity. While most studies focus on powertrain configurations in tractors, this study takes a different approach: propose and evaluate new plug-in hybrid configurations with multiple power sources for heavy-duty trucks. The tractor retains its engine powertrain, while the trailer is equipped with electric axle(s), forming a fuel-electricity hybrid propulsion system. The specifications of the electric propulsion system are optimized, using a multi-objective particle swarm optimization algorithm and dynamic programming control algorithm to evaluate the energy consumption and total cost of ownership (TCO). The results highlight the potential of the configuration with three electric axles and single reduction gear in regard to vehicle energy consumption. Conversely, the configuration with one electric axle and a two-speed transmission exhibits the lowest TCO. Under the China World Transient Vehicle Cycle, the fuel consumption of the diesel truck is reduced by up to 44.59 % with the use of the optimized hybrid configuration. The truck's TCO can be then reduced by up to 832 thousand CNY in one-million-kilometer operation. For an actual road operation, these figures change to 34.79 % and 284 thousand CNY, respectively.

Spatiotemporal Analysis of Complex Emission Dynamics in Port Areas Using High-Density Air Sensor Network.

Cargo terminals, as pivotal hubs of mechanical activities, maritime shipping, and land transportation, are significant sources of air pollutants, exhibiting considerable spatiotemporal heterogeneity due to the complex and irregular nature of emissions. This study employed a high-density air sensor network with 17 sites across four functional zones in two Shanghai cargo terminals to monitor NO and NO2 concentrations with high spatiotemporal resolution post sensor data validation against regulatory monitoring stations. Notably, NO and NO2 concentrations within the terminal surged during the night, peaking at 06:00 h, likely due to local regulations on heavy-duty diesel trucks. Spatial analysis revealed the highest NO concentrations in the core operational areas and adjacent roads, with significantly lower levels in the outer ring, indicating strong emission sources and limited dispersion. Employing the lowest percentile method for baseline extraction from high-resolution data, this study identified local emissions as the primary source of NO, constituting over 80% of total emissions. Elevated background concentrations of NO2 suggested a gradual oxidation of NO into NO2, with local emissions contributing to 32-70% of the total NO2 concentration. These findings provide valuable insights into the NO and NO2 emission characteristics across different terminal areas, aiding decision-makers in developing targeted emission control policies.

Medium-Duty Road Freight Transport—Investigation of Consumption and Greenhouse Gas Emissions of Battery Electric and Fuel Cell Trucks with Model-Based Predictions Until 2050

The present work intends to make a scientific contribution to future drive technology in medium-duty road freight transportation that is as objective and fact-based as possible. In cooperation with a medium-sized forwarding company, 1-day transports, previously driven with diesel trucks, were examined. Using a physically based model, which was first validated by comparing simulated CNG drive data with real-world diesel data, the findings were transferred to battery electric trucks (BETs) and fuel cell trucks (FCETs) and extrapolated to 2050 based on expected technological developments. The model makes statements based on the results of the investigated application regarding specific consumption, greenhouse gas (GHG) emissions, consumption shares and recuperation. The CNG combustion technology (ICET-CNG) serves as a reference. BETs in this application have the lowest emission and consumption values: BET2050 will consume a third of the energy and emit a fifth of the GHGs of ICET-CNG2024. The weight of the battery leads to higher consumption values. FCETs have higher fuel consumption due to their longer drive trains. This is partially compensated by their lower weight: FCET2050 will consume 40% of the energy and emit a third of the GHGs of ICET2024. In long-distance traffic, aerodynamic drag is the dominant consumption factor, accounting for 40%, which should be addressed in further truck development. Recuperation extends the range by 3–7%.

Comparative Analysis Of Calculation Of Expedition Services Using Full Costing And Variable Costing Methods (Case Study at PT. Pulau Indah Maju Palembang)

This research has purpose to know how the calculation of tariffs for public goods transportation services with the company method and compared with full costing and variable costing approaches at PT. Pulau Indah Maju Palembang. This research was conducted using a comparative descriptive analysis technique that compares 3 methods in calculating freight forwarding rates, namely the company method, the full costing method, and the variable costing method. The data collection method used to obtain data and information that supports and complements each other regarding the calculation of freight forwarding rates is an interview with the main director of PT. Pulau Indah Maju, Observations, and documentation. The results of the research are for colt diesel trucks, the company's method is more profitable than the full costing and variable costing approach, for the ankle truck the company's method is more profitable than the full costing and variable costing approach, and for tronton trucks, the variable costing approach is more profitable than the company's method and the full costing approach. From the data analysis that has been carried out, the following conclusions can be drawn: there is no significant difference in the steps for determining the rate of delivery of goods. The absence of such a difference lies in the basis for determining tariffs.

Optimized demand-based charging networks for long-haul trucking in Europe

Abstract Battery electric trucks (BETs) are the most promising option for fast and large-scale CO2 emission reduction in road freight transport. Yet, the limited range and longer charging times compared to diesel trucks make long-haul BET applications challenging, so a comprehensive fast charging network for BETs is required. However, little is known about optimal truck charging locations for long-haul trucking in Europe. Here we derive optimized truck charging networks consisting of publicly accessible locations across the continent. Based on European truck traffic flow estimates for 2030 and actual truck stop locations we construct a long-term charging network that minimizes the total number of required locations. Our approach introduces an origin-destination pair sampling method and includes local capacity constraints to compute an optimized stepwise network expansion along the highest demand routes in Europe. For an electrification target of 15% BET share in long-haul and without depot charging, our results suggest that about 91% of electric long-haul truck traffic across Europe can be enabled already with a network of 1,000 locations, while 500 locations would suffice for about 50%. We furthermore show how the coverage of origin-destination flows scales with the number of locations and the size of the stations. Ideal locations to cover many truck trips are at highway intersections and along major European road freight corridors (TEN-T core network).

A cost-effectiveness comparison of renewable energy pathways for decarbonizing heavy-duty vehicles in China

Decarbonizing heavy-duty vehicles is becoming increasingly important, yet multiple renewable-based decarbonization pathways have not been compared systematically. To fill this gap, this study develops a techno-economic and environmental model that integrates the fuel cycle and vehicle cycle to assess these pathways for China. The model includes two energy storage technologies: batteries and hydrogen, three energy transmission options, and two vehicle types: fuel cell electric vehicles and battery electric vehicles. Five distinct low-carbon pathways are evaluated on a ton-kilometer basis, including cost, greenhouse gas emissions, and abatement cost relative to conventional diesel trucks. Results indicate that the most cost-effective battery electric vehicle pathway offers a 7 % lower ton-km cost than diesel trucks for a 49-ton gross vehicle weight. Battery electric vehicle charging combined with hydrogen for power generation is more cost-effective than direct use of hydrogen in fuel cell electric vehicles. All studied pathways can achieve over 80 % emission reduction compared to diesel trucks, with fuel cell electric vehicle pathways having the highest abatement costs of 103–117 USD/tonCO2. Analysis of the impact of gross vehicle weight and vehicle range indicates that battery electric vehicle pathways outperform fuel cell electric vehicle pathways across most dimensions. Costs of battery electric vehicle pathways do increase sharply for vehicle ranges beyond about 700 km, and fuel cell electric vehicles become more cost-effective relative to battery electric vehicles for ranges above approximately 1100 km, although all pathways are much more costly than diesel trucks at long ranges. The sensitivity analysis highlights the importance of powertrain efficiency and cost projections show that fuel cell electric heavy-duty vehicles can achieve cost-parity before 2030. These results highlight the desirability of promoting the adoption of heavier battery electric vehicles and providing more targeted subsidies for long-range fuel cell electric vehicles.

Exploring ultrafine particle emission characteristics from in-use light-duty diesel trucks in China using a portable measurement system

Diesel vehicle exhaust is one of the major contributors to ultrafine particles (UFPs) in urban areas in China. However, there is still a lack of knowledge about UFPs emission characteristics from current in-use diesel vehicles. This study has carried out an on-road test of 10 in-use Light-duty Diesel Trucks (LDDTs) with different emission control standards in China using a self-established portable measurement system based on the Electronic Low-pressure Impactor (ELPI) and characterized the ultrafine particle number (PN) concentration, particle size distribution and metal element contents. The results revealed a significant reduction of 93.37% in the average PN0.1 emission factor of LDDTs from China IV to China VI. Notably, LDDTs compliant with the China VI vehicle emission control standard exhibited the lowest PN0.1 and PM0.1 emission factors, measuring 4.991×1014 #/km and 0.627 g/km, respectively. By taking into account emissions under real driving conditions, we found that the PN emission rates grow with the increase of the Vehicle Specific Power (VSP). The cold-start phase had higher PN emissions than the hot-start phase, with 8590, 1890, 477, and 22 times higher than those of the ambient air (1.18×105 #/cm3), respectively. The installation of Diesel Particulate Filter (DPF) can decrease UFPs by more than 99.8%, while the PN emission factor during the DPF regeneration stage (1.85×1016 #/km) increased by 5 orders of magnitude that of the DPF normal works (7.51×1011 #/km). Metal element contents analysis shows that Fe, Ca, Al and Mg are the dominant elements in UFPs of LDDT exhaust gas, but the element of Ni is slightly increasing in a China VI, possibly due to the new automotive engine exhaust manifolds being made of Ni instead of cast iron for the purpose of having more high-temperature resistance. Our study demonstrates the importance of monitoring and routine maintenance of exhaust after-treatment systems.

Reducing real driving fuel consumption and emissions with a hydraulic hybrid vehicle

We have successfully prototyped and tested the real-driving performance of a hydraulic hybrid heavy commercial vehicle. Hydraulic hybrid driveline technology was fitted to a Euro IV diesel truck equipped with a diesel particulate diffuser/filter and an exhaust gas recirculation system. An AVL portable emissions measurement system was fitted to the test vehicle to quantify gaseous and particle phase emissions species and an on-board diagnostic scan tool was used to obtain data from the trucks electronic control unit. Fuel consumption savings up to 17 % were accomplished in hydraulic hybrid mode when testing on a short urban driving route featuring a high intensity of stop-start activity. Average reductions in solid particle number concentration of 40 % were achieved along with increases in NOx, Hydrocarbons (THCs) and CO. Future work could target improved control system integration of the various driveline components to further reduce fuel consumption and emissions in an improved prototype design.

Emissions of gaseous nitrous acid (HONO) from diesel trucks: Insights from real-driving emission experiments

Nitrous acid (HONO) serves as a substantial contributor in the atmospheric chemistry of hydroxyl radicals (·OH). Despite its significance, the primary sources of atmospheric HONO, particularly diesel truck emissions, have not been thoroughly examined. This study investigated the factors influencing HONO emissions via on-road exhaust emission tests using a self-developed portable measurement system. The findings show that the HONO emissions measured during on-road testing are higher than those measured during chassis dynamometer testing, highlighting the need for on-road tests to capture HONO emissions. Emission standards and truck types greatly influence HONO emission factors (EFs), with stricter regulations leading to lower emissions. The average fuel consumption-based EFs for light-duty diesel trucks ranged from 0.93 g/kg for China III to 0.08 g/kg for China VI. For medium-duty diesel trucks, the EFs decrease from 1.43 g/kg for China III to 0.19 g/kg for China V. Moreover, the vehicle-specific power demonstrated a stronger correlation with HONO emissions. This research showed that HONO emissions were significantly higher without or before the optimal operation of the SCR device, and the device notably reduced HONO emissions. Future research should focus on the impact of various exhaust after-treatment systems and explore HONO conversion mechanisms.

The health, climate, and equity benefits of freight truck electrification in the United States

Abstract Long-haul freight shipment in the United States relies on diesel trucks and constitutes ∼3% of U.S. greenhouse gas emissions and a significant share of local air pollution. Here, we compare the climate and air pollution-related health damages from electric versus diesel long-haul truck fleets. We use truck commodity flows to estimate tailpipe emissions from diesel trucks and regional grid emissions intensities to estimate charging emissions from electric trucks under various grid scenarios. We use a reduced complexity air quality model combined with valuation of air pollution-related premature deaths (using two hazard ratios (HRs)) and quantify the distributional health impacts in different scenarios. We find that annual health and climate costs of the current diesel fleet are $195–$249/capita compared to $174–$205/capita for a new diesel fleet, and $156–$177/capita for an electric fleet, depending on the HR. We find that freight electrification could avoid $6.2–8.5 billion in health and climate damages annually when compared to a fleet of new diesel vehicles (with even higher benefits when compared to the current diesel fleet). However, the Midwest and parts of the Gulf Coast would experience an increase in health damages due to vehicles charging using electricity from coal power plants. If old coal power plants (operating in 1980 or earlier) are replaced with zero-emission generation, electrification of all U.S. freight would result in $32.3–39.2 billion in avoided damages annually and health benefits throughout the U.S. Electrifying transport of consumer manufacturing goods (including electronics, transport equipment, and precision instruments) and food, beverage, and tobacco products would provide the largest absolute health and climate benefits, whereas mixed freight and manufacturing goods would result in the largest benefits per tonne-km. We find small variations in health damages across race and income. These results will help policymakers prioritize electrification and charging investment strategies for the freight transportation sub-sector.

Characterizing hydrogen-diesel dual-fuel performance and emissions in a commercial heavy-duty diesel truck

This study investigates hydrogen (H2) as a supplementary fuel in heavy-duty diesel engines using pre-manifold injection. A H2-diesel dual-fuel (H2DF) system was implemented on a commercial class-8 heavy-duty diesel truck without modifying the original diesel injection system and engine control unit (ECU). Tests were conducted on a chassis dynamometer at engine speeds between 1000 and 1400 rpm with driver-demanded torques from 10 to 75%. The hydrogen energy fraction (HEF) was strategically controlled in the range between 10 and 30%. Overall, CO2 reduction (comparable to the HEF level) was achieved with similar brake-specific energy consumption (BSEC) at all loads and speeds. To maintain the same shaft torque, the driver-demanded torque was reduced in H2DF operation, which resulted in a lower boost pressure. At higher loads, engine-out BSNOx slightly decreased, while BSCO and black carbon (BC) increased significantly due to lower oxygen concentration resulting from the lower boost pressure. At lower loads, engine-out BSCO and BSBC decreased moderately, while NO2/NO ratio increased substantially in H2DF operation. Deliberate air path and diesel injection control are expected to enable higher HEF and GHG reductions.

Decarbonizing Commercial Vehicles: Life Cycle Assessment of Diesel, Petrol and Electric Trucks

Abstract The electric vehicle (EV) landscape in Malaysia is still trailing behind the more established internal combustion engine industry. However, the promotion of EVs has become an increasing priority for the government, especially after committing to achieving net-zero emissions by 2050 at the earliest, as outlined in the 12th Malaysia Plan. Malaysia has set a target of having 1.5 million EVs by 2040, with a notable portion consisting of commercial EVs like buses and trucks. Developing the EV ecosystem and sustainable trucks in Malaysia faces challenges such as high costs and insufficient supporting infrastructure. This study aims to assess the Well-to-wheel life cycle of CO2 emissions and total cost of ownership (TCO) of diesel trucks (DTs), petrol trucks (PTs), and electric trucks (ETs). The study employs IPCC 2006 guidelines to estimate CO2 emissions and a TCO assessment method. The results indicate that the average CO2 emissions of ET are 38% lower than those of DT, and 33% lower than PT. Furthermore, the TCO of ET is 30% and 15% higher than that of DT and PT, respectively. Despite the higher cost, the study concludes that ETs display superior performance in terms of CO2 emission reduction. These findings contribute significantly to the development of policies and knowledge aimed at promoting sustainable trucks, aligning with the country’s net-zero goals.

Plug-in charging or electric roads? Powering U.S. long-haul heavy-duty trucks in 2050

Abstract Pervasive plug-in fast chargers and/or electrified roadways (eRoads) might address the limited range, long recharging times, and reliance on greenhouse gas (GHG)-intensive, costly, and heavy batteries associated with electrifying long-haul heavy-duty trucks (HDTs). While these large-scale interventions shift environmental and cost burdens onto infrastructure, there is a lack of studies investigating how eRoads affect system-level GHG emissions, costs, material use, and peak electric grid power demands. We compare these aspects for the case of electrifying U.S long-haul HDTs (Class 8) in 2050 powered by combinations of plug-in fast chargers and eRoads. Our model accounts for battery downsizing, energy consumption, and truck operation patterns in quantifying life cycle impacts of batteries, plug-in chargers, eRoads, and hourly truck electricity demand. We find that plug-in fast chargers and eRoads reduce annualized 2050 HDT life cycle GHG emissions by 8% to 14% compared to using long-range batteries, which in turn have at least 50% lower emissions than diesel trucks. Conductive rails, overhead lines, and wireless eRoads (amortized across light- and heavy-duty vehicles) have lower system-wide costs than long-range batteries, plug-in fast chargers, or diesel trucks. Cost savings from smaller batteries, lower energy use and avoided recharging time offset high eRoads capital costs. While eRoads can reduce both system-level GHG and costs compared to diesel trucks, these reductions are sensitive to eRoads capital costs and losses from wireless power transfer and air resistance. eRoads require less lithium (87%) and copper (67%) than long-range batteries but increase regional peak power demands by up to 32%. Efficient wireless power transfer and aerodynamic pantographs enhance eRoads’ GHG and cost advantages, which may diminish if future batteries are more energy-dense, cheaper, or less GHG intensive. If successfully deployed, eRoads present opportunities for tighter integration between the transportation and electricity infrastructure systems, enabling optimized charging strategies to lower GHG emissions and costs.

A Review of the Energy System and Transport Sector in Uzbekistan in View of Future Hydrogen Uptake

This study explores the potential role of hydrogen in decarbonizing the transport sector in Uzbekistan by examining different aspects of the country’s energy system and transport final use. In road transport, Uzbekistan has already gained experience with the use of alternative fuels through the “Compressed Natural Gas—Mobility” initiatives and has achieved a fleet coverage of 59%. These existing frameworks and knowledge can ease the integration of hydrogen into road transport. The rail sector also has the potential for hydrogen uptake, considering that 47% of rail lines are not electrified. The results of this study indicate that powering all CNG vehicles with a 10% hydrogen blend (HCNG) could reduce road transport emissions by 0.62 MtCO2eq per year, while replacing diesel trucks with hydrogen-based vehicles could contribute to an additional reduction of up to 0.32 MtCO2eq per year. In rail transport, hydrogen-powered trains could reduce emissions in non-electrified lines by up to 0.1 kgCO2eq/km of journey. In assessing the potential infrastructure for hydrogen logistics, this study also identifies opportunities for hydrogen export by repurposing the existing natural gas infrastructure. Focusing on Uzbekistan, this study provides a regional perspective on the potential for the integration of hydrogen into the transport sector in Central Asia.

Real-World Emission Characteristics of Diesel Pallet Trucks under Varying Loads: Using the Example of China

Diesel pallet trucks, a type of heavy-duty diesel trucks (HDDTs), have historically been a vital component in logistics and transport due to their high payload capacity. However, they also present significant challenges, particularly in terms of emissions which contribute substantially to urban air pollution. Traditional HDDTs emission measurement methods, such as engine bench tests and those used in laboratory settings, often fail to capture real-world emission behaviors accurately. This study specifically examines the real-world emission characteristics of diesel pallet trucks exceeding 30 t under varying loads (unloaded, half loaded, and fully loaded) and different road conditions (urban, suburban, and high-speed). Considering that data quality is the key to the accuracy of the scheme, this research utilized a portable emission measurement system (PEMS) to capture real-time emissions data of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOX), and total hydrocarbons (THC). Key findings demonstrate a direct correlation between vehicle load and emission factors, with the emission factors for CO2, CO, and NOX increasing by 39.5%, 105.4%, and 22.7%, respectively, from unloaded to fully loaded states under comprehensive operating conditions. Regression analyses further provide an emission factor prediction model for HDDPTs, underscoring the continuous relationship between speed, load, and emission rates. These findings provide a scientific basis for pollution control strategies for diesel trucks.

An energy management strategy based on dynamic programming for fuel cell hybrid trucks in ports

The deterioration of environment and the proposal of carbon neutrality are causing the transformation of port freight transportation. Fuel cell hybrid trucks (FCHTs) may be a promising solution for port logistic with the characteristics of low speed, heavy duty and frequent start-stops. How to achieve efficient energy management for FCHTs in ports is a key issue, which is still in the initial stage. The objective of this study is to investigate the effects of dynamic programming (DP) strategy on energy management of FCHTs. With the intention of calculating power demands, the FCHT structure and the models of each component are established. In the DP method, the state of charge (SOC) of the battery, the power supplied by the battery, and hydrogen fuel consumption are regarded as the state variable, the decision variable, and the objective function, respectively. The simulation results under two different typical working conditions in ports show that the proposed DP outperforms existing genetic algorithm (GA) and rule-based strategy for reducing hydrogen fuel consumption by over 10%. Moreover, a set of instances among several FCHTs with different parameters and conditions suggest different influences of key feature parameters on hydrogen fuel consumption and SOC. Nearly 50% cost reduction of the FCHT in the "quay crane-yard " (QCY) cycle compared with diesel trucks at the current price indicates wide application prospect of FCHTs. At last, the results under different conditions reconfirm that DP is an excellent strategy to tackle energy management of FCHTs in ports with frequent start-stops and heavy-load scenarios.

Optimizing container ports’ transportation and Distribution systems toward a low-carbon future: A Shenzhen port case study

Although the large throughput of China’s container ports signals positive progress on trade and economic growth, large Chinese container ports still heavily rely on high-emitting and heavy-polluting diesel trucks for transportation and distribution. The reliance on diesel HDTs is aggravating air pollution in ports’ surrounding areas, worsening traffic congestion, and preventing port cities from establishing ambitious carbon-emission reduction targets.

Zero-Emission Heavy-Duty, Long-Haul Trucking: Obstacles and Opportunities for Logistics in North America

Background: Pressure is growing in North America for heavy-duty, long-haul trucking to reduce greenhouse gas (GHG) emissions, ultimately to zero. With freight volumes rising, improvement depends on zero-emissions technologies, e.g., battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). However, emissions reductions are constrained by technological and commercial realities. BEVs and FCEVs are expensive. Further, BEVs depend on existing electricity grids and FCEVs rely on steam–methane reforming (SMR) or electrolysis using existing grids to produce hydrogen. Methods: This study assembles publicly available data from reputable sources to estimate breakeven vehicle purchase prices under various conditions to match conventional (diesel) truck prices. It also estimates GHG emissions reductions. Results: BEVs face numerous obstacles, including (1) limited range; (2) heavy batteries and reduced cargo capacity; (3) long recharging time; and (4) uncertain hours-of-service (HOS) implications. On the other hand, FCEVs face two primary obstacles: (1) cost and availability of hydrogen and (2) cost of fuel cells. Conclusions: In estimating emissions reductions and economic feasibility of BEVs and FCEVs versus diesel trucks, the primary contributions of this study involve its consideration of vehicle prices, carbon taxes, and electricity grid capacity constraints and demand fees. As electricity grids reduce their emissions intensity, grid congestion and capacity constraints, opportunities arise for BEVs. On the other hand, rising electricity demand fees benefit FCEVs, with SMR-produced hydrogen a logical starting point. Further, carbon taxation appears to be less important than other factors in the transition to zero-emission trucking.

Trilemma of life cycle carbon, employment, and costs of trucking industry's shift toward automation and electrification

AbstractThe transportation sector is undergoing a transformative shift, driven by advancements like autonomous and electric vehicle technologies. In this research, we investigate employment, carbon emissions, and total cost of ownership of autonomy and electrification in the US trucking industry. We utilize life cycle assessment and multi‐regional input‐output modeling to develop a comprehensive life cycle sustainability assessment approach. According to the results, while enhanced fuel economy due to autonomous systems can lead up to a 18% and 41% reduction in emissions and costs, electrification of diesel trucks shows remarkable potential, achieving up to a 40% decline in emissions and a 12% saving in life cycle costs. Autonomy and electrification combined could lead to a 50% decrease in emissions and 46% savings in life cycle costs. On the other hand, autonomy, while enhancing fuel efficiency and reducing costs, causes job losses due to improved efficiency and the elimination of driver positions. Introducing autonomy to diesel trucks results in a 27% decrease in jobs within the US trucking sector, attributed to improved fuel efficiency and subsequent job losses. Transition to autonomy and electrification requires a deliberate balance between environmental, social, and economic aspects. Managerial strategies should consider the use of the proposed composite indicators when setting emission reduction, cost cutting, and managing employment implications. Flexible re‐skilling and training programs should be developed to adapt to the changing skill requirements due to electrification and automation.