Search Results (20)

Increasing consumer awareness on significant environmental challenges, in addition to forthcoming regulations, is driving domestic appliance manufacturers to adopt an Ecodesign approach to more effectively and significantly reduce the environmental impacts along all of the life cycle phases of their products, minimising energy and material consumption, optimising the life of the product, facilitating recycling, facilitating disassembly, optimising material conservation/renewability, and minimising toxicity. This paper emphasises and discusses the significance of supporting this process by creating a company-specific handbook of guidelines and checklists to design low-environmental-impact products across an entire company’s appliance range. Checklists are design support tools intended to qualitatively assess whether, and to what extent, an Ecodesign guideline has been applied, enabling the evaluation of existing products or newly developed concepts, while also serving to guide and inspire sustainable design decisions. It is argued that these are effective tools in translating eco-efficient design into practice and guiding the whole of product development organisation through a knowledge-based approach. The Handbook of Guidelines to Design Low Environmental Impact Products is the result of a project commissioned by a home appliance company to the LeNSlab (research group on Design and System Innovation for Sustainability) of the Design Department of Politecnico di Milano, elaborated, after preliminary desk research, through a series of activities, interactions, knowledge exchanges, and operative workshops in cooperation with the company team of experts. The handbook contains 7 Ecodesign strategies, 27 sub-strategies, 157 guidelines, and related checklists, to be specific to such a level that they can effectively be applied to all types of company appliances. Full article

Cooperative driving systems can coordinate individual vehicles on the road in a platoon, holding significant promise for enhancing traffic efficiency and lowering the energy consumption of vehicle movements. For an extended period, vehicles on the road will consist of a mix of traditional gasoline and electric vehicles. To explore the economic driving strategies for diverse vehicles on the road, this paper introduces a collaborative eco-driving system that takes into account the energy consumption traits of vehicles. Unlike prior research, this paper puts forward a lane change decision-making approach that integrates energy modeling and speed prediction. This method can effectively capture the speed variations in the vehicle ahead and facilitate lane changes with energy efficiency in mind. The system encompasses three vital functions: vehicle cooperative architecture, ecological trajectory planning, and power system control. Specifically, eco-speed planning is carried out in two stages: the initial stage is executed globally, with cooperative speed optimization performed based on the energy consumption characteristics of different vehicles to determine the economical speed for vehicle platoon driving. The subsequent stage involves local speed adaptation, where the vehicle platoon dynamically adjusts its speed and makes lane change decisions according to local driving conditions. Ultimately, the generated control information is fed into the powertrain control system to regulate the vehicle. To assess the proposed collaborative eco-driving system, the algorithms were tested on highways, and the results substantiated the system’s efficacy in reducing the energy consumption of vehicle driving. Full article

This research examines the impact of digital transformation on green innovation across different regions in China, using data from the Shanghai and Shenzhen stock markets from 2007 to 2022. The study reveals that digital transformation significantly enhances green innovation in enterprises, with notable regional disparities. The effects are most pronounced in the economically advanced eastern coastal areas, followed by central regions, while the western regions lag behind. This spatial pattern underscores the importance of tailored policies and strategies to address specific regional barriers and opportunities. Integrating digital technologies such as AI and big data has empowered companies to enhance their innovation activities, particularly in energy efficiency, pollution mitigation, and eco-friendly manufacturing. However, challenges such as lack of motivation for innovation and inadequate greener technologies persist, necessitating new strategies to revive eco-friendly innovations. This research provides valuable insights for policymakers, highlighting the need for regional cooperation, knowledge sharing, and technology transfer to promote sustainable economic development. By leveraging digital transformation, regions can improve their green innovation capabilities, contributing to the broader goals of China’s “dual carbon” initiative and sustainable development. This study emphasizes the critical role of digital technologies in driving green innovation and calls for comprehensive strategies to enhance digital infrastructure, digital literacy, and environmental consciousness across all regions of China. Full article

The Belt and Road Initiative (BRI) proposed by China in in 2013 prioritizes environmental sustainability and regional economic development from a global perspective. Although the BRI has achieved considerable economic progress in many cities and regions, research on its environmental impacts is still insufficient, with limited attention paid to domestic urban areas in particular. Existing studies have focused primarily on carbon emissions, ignoring the broader environmental impacts of industrial emissions, such as those from smart transportation. To address this gap, this study adopts four major pollutant emissions—carbon dioxide (CO₂), industrial particulate matter, industrial sulfur dioxide (SO₂), and industrial wastewater emissions—as indicators to assess pollution levels in urban environments. Adopting panel data from 281 Chinese cities from 2003 to 2021, this study employs the difference-in-differences (DID) method to estimate the effect of the BRI on urban environmental pollution. This study is based on the following hypotheses: Hypothesis 1. BRI implementation has reduced urban pollution emissions. Hypothesis 2. Advancements in science and technology will drive the implementation of the BRI. Hypothesis 3. A proactive government response can significantly reduce urban environmental pollution. The main findings of this study are as follows. First, BRI implementation significantly reduces urban environmental pollution by 1.05%. Second, the policy effects of the BRI are more pronounced in the eastern and western regions and in larger cities, implying that geopolitical- and market-oriented strategies are important for regional performance. Third, scientific and technological progress positively affects pollution reduction in urban environments. Fourth, the BRI contributes to strengthening government intervention, which subsequently improves sustainable governance, reduces urban environmental pollution, and promotes regional economic cooperation. Our findings will serve as a crucial reference for future policymaking endeavors toward eco-friendly logistics cooperation in the region. Full article

Given the complex powertrain of fuel cell electric vehicles (FCEVs) and diversified vehicle platooning synergy constraints, a control strategy that simultaneously considers inter-vehicle synergy control and energy economy is one of the key technologies to improve transportation efficiency and release the energy-saving potential of platooning vehicles. In this paper, an energy-oriented hybrid cooperative adaptive cruise control (eHCACC) strategy is proposed for an FCEV platoon, aiming to enhance energy-saving potential while ensuring stable car-following performance. The eHCACC employs a hybrid cooperative control architecture, consisting of a top-level centralized controller (TCC) and bottom-level distributed controllers (BDCs). The TCC integrates an eco-driving CACC (eCACC) strategy based on the minimum principle and random forest, which generates optimal reference velocity datasets by aligning the comprehensive control objectives of the platoon and addressing the car-following performance and economic efficiency of the platoon. Concurrently, to further unleash energy-saving potential, the BDCs utilize the equivalent consumption minimization strategy (ECMS) to determine optimal powertrain control inputs by combining the reference datasets with detailed optimization information and system states of the powertrain components. A series of simulation evaluations highlight the improved car-following stability and energy efficiency of the FCEV platoon. Full article

In this paper, a comprehensive deterministic Eco-Driving strategy for Connected and Autonomous Vehicles (CAVs) is presented. In this setup, multiple driving modes calculate speed profiles that are ideal for their own set of constraints simultaneously to save fuel as much as possible, while a High-Level (HL) controller ensures smooth and safe transitions between the driving modes for Eco-Driving. This Eco-Driving deterministic controller for an ego CAV was equipped with Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) algorithms. This comprehensive Eco-Driving strategy and its individual components were tested by using simulations to quantify the fuel economy performance. Simulation results are used to show that the HL controller ensures significant fuel economy improvement as compared to baseline driving modes with no collisions between the ego CAV and traffic vehicles, while the driving mode of the ego CAV was set correctly under changing constraints. For the microscopic traffic simulations, a 6.41% fuel economy improvement was observed for the CAV that was controlled by this comprehensive Eco-Driving strategy. Full article

Conventional energy management strategies (EMSs) of hybrid electric vehicles (HEVs) only utilize in-vehicle information, such as an acceleration pedal, velocity, acceleration, engine RPM, state of charge (SOC), and radar. This paper presents a new EMS using out-vehicle information obtained by vehicle to everything (V2X) communication. The new EMS integrates cooperative eco-driving (CED) guidance and an adaptive equivalent consumption minimum strategy (A-ECMS) based on V2X communication information and road information. CED provides a guide signal and a guide speed to the driver. It guides pedal behavior in terms of coasting driving, acceleration and deceleration, and target speed. A-ECMSs calculate the target SOC based on the simplified road information of the planned route and reflects it in the equivalent factor. An integrated driving hardware-in-the-loop (IDHIL) simulator is also built to prove the new EMS by integrating a V2X communication device, a VANET simulator, and a vehicle simulator. The IDHIL test results demonstrate the validity and performance of the proposed EMS in a V2X communication environment. Full article

Currently, road transport constitutes a considerable proportion of global fossil fuel consumption, as well as CO₂ and pollutant emissions. To mitigate transportation energy consumption, two primary approaches have emerged: the large-scale adoption of Hybrid Electric Vehicles (HEVs) and Plug-In Electric Vehicles (PHEVs), as well as the implementation of eco-driving strategies, which present an immediate and low-cost solution. In this context, this paper provides a comprehensive review of these two technologies and their integration for connected HEV/PHEVs. We summarize the framework of recent approaches to incorporate fusion road information in single-vehicle and multi-vehicle scenarios, respectively, wherein we compare their advantages, their disadvantages, and their effectiveness in reducing energy consumption. Additionally, we reflect on the future development directions of cooperative optimization in EMS and eco-driving strategies from various perspectives. This comprehensive review underscores the importance and potential impact of these approaches in addressing environmental challenges in transportation systems, thereby offering useful insights for new researchers and practitioners in this area. Full article

Digital platforms are transforming almost every industry today. To gain insight into the innovation mechanism of the industrial Internet platform-based ecosystem, combining its nature of sustainability, this paper investigates strategic factors, such as the intensity of platform governance, the eco-efficiency of cooperation, and the input costs of complementors. A platform ecological system game model comprised of the industrial Internet platform enterprise, industry chain complementors, and innovation chain complementors is then established. The results of game playing and simulation highlight four important facts as revealed by a Chinese COSMOPlat case. First, there are four evolutionary paths for collaborative relations among innovation entities in an ecosystem. Second, platform enterprise may utilize various strategies in the several stages of ecosystem evolution. Third, complementors in the industrial chain and innovation chain have different degrees of dependence on platform enterprise and distinct incentive factors. Finally, investment of platform enterprise in data security drives the construction and upgrading of the ecosystem. In this context, collaborative innovation in platform ecosystems is associated with a self-evolving, self-growing, self-driven, and sustainable cooperation and win–win mechanism. This study provides new ideas for the governance of the industrial Internet platform-based ecosystem. Full article

The ecological efficiency (eco-efficiency) of a regional logistics industry (RLI) is widely regarded as a key factor affecting sustainability of economic development, environmental protection, and resources utilization. This study applied a data-driven method to evaluate and increase the eco-efficiency of an RLI. Based on RLI-related data, which were converted into proper dimensionless indices, data envelopment analysis (DEA), which assumes that the decision-making units (DMUs) are in the situation of variable returns to scale, the Banker, Charnes, and Cooper (BCC) model, and Malmquist index model were used to assess the eco-efficiency of the RLI from both static and dynamic viewpoints. Then, a Tobit regression model was built to explore the factors that influence eco-efficiency. The effectiveness of this approach was verified by its application to an example from Anhui Province. This study has theoretical and practical value for the assessment and promotion of the ecological eco-efficiency of the RLI. We believe that our approach offers a powerful tool to assist logistics enterprises and local governments in coordinating the relationship between the RLI economy and the ecological environment, facilitating the drive to carbon neutrality. Full article

The study of the coupling coordinated relationship between urbanization and the eco-environment is important to promote regional high-quality development. This paper measured the coupling coordination degree between urbanization and the eco-environment from 2008 to 2020, using the coupling coordination model, depicted its spatiotemporal characteristics with ArcGIS, and explored its driving factors and impacts of the interaction between pairwise factors on it with geo-detection methods. The results show that the coupling coordination level becomes increasingly improved, but there exist widening spatial disparities, and in 2020, its spatial distribution presents characteristics of “decreasing from north to south” and “increasing from west to east”. According to their evolutionary characteristics of coupling coordination categories, cities can be classified into four types: “transition from basic misalignment to primary coordination”, “transition from primary coordination to intermediate coordination”, “transition from primary coordination to senior coordination”, “no hierarchical transition”. Currently, driving factors of industrial structure, opening to the outside world and technological innovation significantly affect the coupling coordination degree, and the interaction between pairwise factors is enhanced. Policies should be implemented in categories to improve the coupling coordination level. Regional cooperation, exchanges, and interconnection of resources and factors should be strengthened to jointly build a coordinated regional development pattern. Full article

The high degree of fragmentation and unsustainable exploitation patterns of forest resources have become prominent obstacles to the realisation of the economic and social value of China’s forest resources. China’s forest eco-bank (FEB) project was set up to achieve centralised utilisation of diffuse forest resources in an underdeveloped area. Analysing FEB projects is of great significance to countries with abundant forest resources aiming to benefit from the economic and ecological functions of such resources and achieve sustainable economic and social development. This study uses the actor-network theory framework to analyse cooperation among various actors in the implementation process of the FEB project in China. Our results indicate the following. First, the government was the principal actor playing a vital role in motivating the other parties and driving the project forward. Second, the diffuse nature of China’s forest resources is a major obstacle to their utilisation. The centralised integration of forest resources is a prerequisite for their effective utilisation. Finally, it is necessary to improve the balance of interests of the various actors to promote a more stable actor network and attract more actors to participate in the FEB project. Full article

In this study, a Green Light Optimal Speed Advisory (GLOSA) system for buses (B-GLOSA) was developed. The proposed B-GLOSA system was implemented on diesel buses, and field tested to validate and quantify the potential real-world benefits. The developed system includes a simple and easy-to-calibrate fuel consumption model that computes instantaneous diesel bus fuel consumption rates. The bus fuel consumption model, a vehicle dynamics model, the traffic signal timings, and the relationship between vehicle speed and distance to the intersection are used to construct an optimization problem. A moving-horizon dynamic programming problem solved using the A-star algorithm is used to compute the energy-optimized vehicle trajectory through signalized intersections. The Virginia Smart Road test facility was used to conduct the field test on 30 participants. Each participant drove three scenarios, including a base case uninformed drive, an informed drive with signal timing information communicated to the driver, and an informed drive with the recommended speed computed by the B-GLOSA system. The field test investigated the performance of using the developed B-GLOSA system considering different impact factors, including road grades and red indication offsets, using a split-split-plot experimental design. The test results demonstrated that the proposed B-GLOSA system can produce smoother bus trajectories through signalized intersections, thus producing fuel consumption and travel time savings. Specifically, compared to the uninformed drive, the B-GLOSA system produces fuel and travel time savings of 22.1% and 6.1%, on average, respectively. Full article

In an effort to reach accident-free milestones or drastically reduce/eliminate road fatalities rates and traffic congestion and to create disruptive, transformational mobility systems and services, different parties (e.g., automakers, universities, governments, and road traffic regulators) have collaborated to research, develop, and test connected vehicle (CV) technologies. CVs create new data-rich environments and are considered key enablers for many applications and services that will make our roads safer, less congested, and more eco-friendly. A deeper understanding of the CV technologies will pave the way to avoid setbacks and will help in developing more innovative applications and breakthroughs. In the CV paradigm, vehicles become smarter by communicating with nearby vehicles, connected infrastructure, and the surroundings. This connectivity will be substantial to support different features and systems, such as adaptive routing, real-time navigation, and slow and near real-time infrastructure. Further examples include environmental sensing, advanced driver-assistance systems, automated driving systems, mobility on demand, and mobility as a service. This article provides a comprehensive review on CV technologies including fundamental challenges, state-of-the-art enabling technologies, innovative applications, and potential opportunities that can benefit automakers, customers, and businesses. The current standardization efforts of the forefront enabling technologies, such as Wi-Fi 6 and 5G-cellular technologies are also reviewed. Different challenges in terms of cooperative computation, privacy/security, and over-the-air updates are discussed. Safety and non-safety applications are described and possible future opportunities that CV technology brings to our life are also highlighted. Full article

Greenhouse gas emissions are the cause of climate change, which in turn has a negative impact on people and the environment. Reducing the fuel consumption of conventional engines reduces climate-damaging emissions and can, thus, contribute to achieving climate protection goals. In addition, fuel costs are a major cost factor for long-haul trucking. Eco-driving helps to reduce fuel costs when driving on inclines and declines. Due to the high mass and, therefore, high kinetic and potential energy of heavy trucks, fuel can be saved by coasting before slopes and before speed limits. However, energy-efficient and non-cooperative driving, i.e., without considering other road users, can lead to increased fuel consumption as vehicles impede each other. To resolve conflicts in road traffic, a variety of methods that enable cooperative driving exist. In general, vehicles communicate with vehicle-to-everything (V2X) and negotiate a joint driving strategy. This paper presents a method that combines cooperative and energy-efficient driving and examines the impact on fuel consumption during uphill driving. The method relies on the exchange of trajectories for cooperative maneuver coordination. By computing a strategic trajectory, energy-efficient driving with long coasting maneuvers is enabled. In the simulative evaluation, travel over hills with two and three trucks is investigated. It is shown that the combination of cooperative and eco-driving reduces the fuel costs for traffic. Full article